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A typology of corporate environemental strategy and its driving factors in jultinational corporations
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A typology of corporate environemental strategy and its driving factors in jultinational corporations
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A TYPOLOGY OF CORPORATE ENVIRONMENTAL STRATEGY AND ITS DRIVING FACTORS IN MULTINATIONAL CORPORATIONS by Dongwon Lee A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BUSINESS) May 2003 Copyright 2003 Dongwon Lee Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. UNIVERSITY OF SOUTHERN CALIFORNIA THE GRADUATE SCHOOL UNIVERSITY PARK LOS ANGELES, CALIFORNIA 90089-1695 This dissertation, written by won L & < Z under the direction o f h < 5 dissertation committee, and approved by all its members, has been presented to and accepted by the D irector o f Graduate and Professional Programs, in pa rtia l fulfillment o f the requirements f o r the degree o f DOCTOR OF PHILOSOPHY D irector Date May 16, 2003 D issertation Committee Chair Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. TABLE OF CONTENTS LIST OF TABLES.................................................................................................................V LIST OF FIGURES............................................................................................................VII ABSTRACT........................................................................................................................VIII CHAPTER 1 INTRODUCTION...........................................................................................1 1.1. M o tivatio n of the St u d y ...................................................................................................................1 1.2. R esea rch Ob je c t iv e s............................................................................................................................5 CHAPTER 2 PREVIOUS STUDIES ON CORPORATE ENVIRONMENTAL STRATEGY.............................................................................................................................6 2.1. D om estic F ir m ’s P er spec tiv e...........................................................................................................6 2.2. M u ltin a tio n a l F ir m ’s Pe r sp e c t iv e............................................................................................. 8 2.3. C o n sid er in g un ifo r m ity a n d pro activity t o g e t h e r .......................................................11 CHAPTER 3 CONCEPTUAL FRAMEWORK FOR CORPORATE ENVIRONMENTAL STRATEGY IN MNCS...................................................................14 3.1. Two D im e n sio n s o f C o r p o r a te E n v ir o n m e n ta l S t r a t e g y in MNCs...................... 14 3.1.1. En v ir o n m e n t a l Pro ac t iv it y ..................................................................................................... 15 3.1.2. En v ir o n m e n t a l U n if o r m it y ...................................................................................................... 17 3.1.3. Fo u r strategic alter n a tiv es u sin g tw o d im e n sio n s...................................................19 3.1.4. A n Em pirical Ev id e n c e of the Pro po sed Ty p o l o g y .....................................................21 3.2. D riv in g F acto rs of C orporate En v ir o n m e n t a l St r a teg y in M N C s : Hypo th eses D evelo pm ent a n d Resea rch M o d e l ......................................................................25 3.2.1. In t e r n a l Ca p a b il it ie s................................................................................................................... 26 3.2.1.1. Environmental T echnology...........................................................................................................26 3.2.1.2. Manufacturing F lexib ility ............................................................................................................. 33 3.2.2. Ex t e r n a l Pr e s s u r e s....................................................................................................................... 37 3.2.2.1. Corporate V isibility..........................................................................................................................37 3.2.2.2. Environmental H eterogeneity......................................................................................................40 ii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3.2.3. R esear ch M o del 44 C H A P T E R 4 R E S E A R C H D E S IG N .....................................................................................................45 4.1. R esear ch Pr o c e s s............................................................................................................................... 45 4.1.1. Fir st Ph a s e : Explo ra tio n through In t e r v ie w s............................................................. 45 4.1.2. Sec o n d Ph a s e : D evelo pm ent of in str u m en ts a n d Initia l Su r v e y ......................46 4.1.3. T hird Ph a s e : s u r v e y .......................................................................................................................48 4.2. Sa m ple a n d D a t a Co l l e c t io n ......................................................................................................49 4.2.1. Sa m p l e ................................................................................................................................................... 49 4.2.2. D a t a C o l l e c t io n ............................................................................................................................. 51 4.3. Oper a tio n a liza tio n a n d M e a su r em en t M o del of V a r ia b l e s.................................. 54 4.3.1. D epe n d e n t V a r ia b l e s ................................................................................................................... 54 4.3.1.1. Operationalization o f Environmental P roactivity................................................................. 54 4.3.1.2. Operationalization o f Environmental U niform ity................................................................. 55 4.3.1.3. M easurement M odel o f Environmental Proactivity and Environmental Uniformity 57 4.3.1.4. Relationship betw een Environmental Proactivity and Environmental Uniform ity... 68 4.3.2. In d e p e n d e n t V a r ia b l e s................................................................................................................70 4.3.2.1. Environmental T echnology Investm ents.................................................................................. 70 4.3.2.2. Manufacturing F lexib ility............................................................................................................. 71 4.3.2.3. Corporate V isibility......................................................................................................................... 72 4.3.2.4. Environmental H eterogeneity......................................................................................................73 4.3.3. Co ntro l V a r ia b l e s........................................................................................................................ 77 4.3.3.1. Country o f O rigin............................................................................................................................. 77 4.3.3.2. Industry................................................................................................................................................77 4.3.3.3. Plant S ize............................................................................................................................................. 78 4.4. A n a l y t ic a l M e t h o d o l o g y ............................................................................................................ 80 4.4.1. T esting of the direct effects of d r iv in g fac to rs o n en v ir o n m e n t a l PRO ACTIVITY AND ENVIRONMENTAL UNIFORMITY...............................................................................81 4.4.2. T esting of the m o d er a tin g effect of en v ir o n m en ta l tec h n o lo g y o n the relationship betw een m a n u fa c t u r in g flexibility a n d e n v ir o n m e n t a l UNIFORMITY....................................................................................................................................................... 82 4.4.3. Split sam ple a n a l y s is ................................................................................................................... 84 C H A P T E R 5 D A T A A N A L Y SIS A N D R E S U L T S .........................................................................86 5.1. H ier arch ic al R eg r essio n A n a l y s is..........................................................................................86 5.1.1. R eg r essio n d ia g n o s t ic s.............................................................................................................. 86 5.1.1.1. N orm ality............................................................................................................................................ 86 5.1.1.2. H eteroscedasticity............................................................................................................................86 5.1.1.3. M ulticollinearity................................................................................................................................88 5.1.1.4. Identifying influential observation..............................................................................................89 5.1.2. H ierarchical Reg r essio n A n a l y sis Re su l t s: Effects of D riving Factors on En v ir o n m e n t a l Pro a c t iv it y ......................................................................................................... 90 iii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5.1.3. H ierarch ical Reg r essio n A n a l y sis R e su l t s: Effects of D riving F actors on En v ir o n m e n t a l U n if o r m it y ...........................................................................................................95 5.2. S p lit S a m p le A n a l y s i s .................................................................................................................100 5.2.1. On e w a y A N O V A A n a l y s is ...................................................................................................... 104 5.2.2. OLS R e g r e s s io n A n a l y s i s ...................................................................................107 5.2.2.1. Effects on Environmental Uniformity within Subgroup 1 (Low Environmental Proactivity)........................................................................................................................107 5.2.2.2. Effects on Environmental Uniformity within Subgroup 3 (High Environmental Proactivity)...................................................................................................................... 110 5.2.2.3. Effects on Environmental Proactivity within Subgroup 4 (Low Environmental Uniformity).......................................................................................................................Ill 5.2.2.4. Effects on Environmental Proactivity within Subgroup 2 (High Environmental Uniformity)...................................................................................................................... 114 CHAPTER 6 CONCLUSIONS..........................................................................................116 6.1. Fin d in g s a n d D isc u ssio n of the Re s u l t s ..............................................................................116 6.1.1. Co n c eptu a l m o d el for corporate e n v ir o n m en ta l st r a t e g y : RELATIONSHIP BETWEEN TWO DIMENSIONS OF ENVIRONMENTAL STRATEGY AND ITS FOUR DRIVING FACTORS........................................................................................................................................116 6.1.2. D ifferential characteristics betw een fo u r types of c orporate ENVIRONMENTAL STRATEGY.....................................................................................................................121 6.2. Im plicatio ns of the R e s u l t s........................................................................................................124 6.2.1. T heoretical Im pl ic a t io n s.........................................................................................................124 6.2.2. M a n a g e r ia l Im p l ic a t io n s.........................................................................................................127 6.3. Lim itations a n d Fu tu r e Resea rch D ir e c t io n s..............................................................129 BIBLIOGRAPHY...............................................................................................................131 APPENDICES.....................................................................................................................138 A. R e spo n d e n t Co m p a n ie s.....................................................................................................................138 B. In ter v iew Qu e st io n s fo r Ph ase 1................................................................................................ 144 B. Su r v e y In st r u m e n t (Eng lish) ....................................................................................................... 146 C. Su r v e y In st r u m e n t (K o r ea n) ........................................................................................................156 iv Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF TABLES Table 1 T-test for the difference of means between local and global standard 24 Table 2 Research Steps 46 Table 3 Number of Surveys Mailed and Responded by Country of Origin 50 Table 4 Surveys Mailed by Country of Operation 50 Table 5 Environmental Practices throughout the life cycle of a product 56 Table 6 Recoding Scheme: 7 point scale to 4 point scale 57 Table 7 Confirmatory factor analysis for environmental proactivity and environmental uniformity model 58 Table 8 Inter-item correlations of environmental proactivity items 60 Table 9 Inter-item correlations of environmental uniformity items 61 Table 10 Items Used in Measuring Environmental Proactivity and Environmental Uniformity 62 Table 11 Individual Item and Composite Reliabilities for Measures of Environmental Proactivity (n=184) 64 Table 12 Individual Item and Composite Reliabilities for Measures of Environmental Uniformity (n=T 84) 65 Table 13 Assessment of Discriminant Validity for Measures of Environmental Proactivity 67 Table 14 Factor Analysis Results of Dependent Variables (Principal Components Extractions and Varimax Rotation) 68 Table 15 Items Used for Environmental Technology Investments Measure 70 Table 16 Items Used for Manufacturing Flexibility Measure 72 Table 17 Items Used for Corporate Visibility Measure 73 Table 18 Items Used for Environmental Heterogeneity Measure 74 v Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 19 Reliabilities for Measures of Independent Variables 74 Table 20 Factor Analysis Results of Independent Variables (Principal Components Extractions and Varimax Rotation) 76 Table 21 Number of Usable Responses by Country of Origin 78 Table 22 Number of Usable Responses by Country of Operation 78 Table 23 Number of Responses by Industry 79 Table 24 Number of Responses by Plant Size (Number of Employees) 79 Table 25 Means, Standard Deviations, and Pearson Product-Moment Correlations among All Variables (n=l 84) 87 Table 26 Hierarchical Regression Results: Dependent Variable: Environmental Proactivity 93 Table 27 Hierarchical Regression Results: Dependent Variable: Environmental Uniformity 97 Table 28 Means, Medians, and Standard Deviations of Environmental Proactivity and Environmental Uniformity 101 Table 29 Four Subgroups Based on a Median Split 102 Table 30 Means and Standard Deviations of Firms in Four Types of Corporate Environmental Strategy 102 Table 31 Driving Factors of Corporate Environmental Strategy in MNCs: Means and Standard deviations 104 Table 32 Post Hoc Analysis - Multiple Comparisons 106 Table 33 OLS Regression Results for Subgroup 1 and 3: Dependent Variable: Environmental Uniformity 108 Table 34 OLS Regression Results for Subgroup 2 and 4: Dependent Variable: Environmental Proactivity 113 Table 35 Summaries: Tests of Hypotheses on Driving Factors of Corporate Environmental Strategy 120 vi Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. LIST OF FIGURES Figure 1 Previous studies on corporate environmental strategy....................................7 Figure 2 Typology of Corporate Environmental Strategy in MNCs........................... 20 Figure 3 Distribution of the level of proactivity (local vs. global standard).............. 23 Figure 4 Research Model for Corporate Environmental Strategy in MNCs.............. 44 Figure 5 Results of Second-order CFA: Environmental Proactivity.......................... 58 Figure 6 Results of Second-order CFA: Environmental Uniformity.......................... 59 Figure 7 Scatter Plot of Environmental Proactivity and Uniformity......................... 69 Figure 8 Four Subgroups and Four Types of Corporate Environmental Strategy in MNCs.................................................................................................................103 Figure 9 Characteristics between four types of corporate environmental strategy in terms of significant driving factors..................................................................125 v ii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ABSTRACT Two streams of research have been done in corporate environmental strategy literature. One stream is studies with a domestic firm’s perspective. It has focused on ‘environmental proactivity’, which is defined as the extent to which companies comply beyond the environmental regulations imposed by the country of operation. The other stream is studies with a multinational firm’s perspective. It has focused on ‘environmental uniformity’, which is defined as the extent to which an MNC standardizes its environmental practices applied to foreign operations compared to its country of origin. The latter, however, has assumed that the level of environmental uniformity is closely related to the level of environmental proactivity. In other words, firms declaring local environmental standards have been considered to pollute the natural environment more than those adopting a global uniform standard across foreign operations. This dissertation started with a question on this assumption, and proposed a new typology of corporate environmental strategy in MNCs. In the new typology, the level of environmental proactivity was combined as a separate dimension together with the level of environmental uniformity. In a 2x2 matrix built on those two dimensions, corporate environmental strategies in MNCs are identified as four viii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. distinctive strategic patterns: reactive/local, proactive/local, reactive/uniform, and proactive/uniform. This dissertation also investigated a subsequent question of what factors drive firms into different environmental strategies. Based on previous studies on corporate environmental strategy, four driving factors were proposed: environmental technology, manufacturing flexibility, corporate visibility, and environmental heterogeneity. Then, a conceptual model for corporate environmental strategy was provided to hypothesize the relationship between two strategic dimensions and four driving factors. The conceptual model and the hypothesized relationships were statistically tested using a dataset collected from 184 MNCs. They are manufacturing plants operating Korea, China, India, and South East Asian countries, headquartered in the U.S., Europe, Japan, and Korea. This dissertation contributes to the environmental management literature by developing a new typology of corporate environmental strategy in MNCs, measuring its two dimensions, and demonstrating its relationship to four driving factors in a conceptual model. The results also provide managers with guidelines for environmental strategic decision making in global operations. ix Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 1 INTRODUCTION 1.1. Motivation of the Study Multinational corporations (MNCs) operate their businesses by crossing geographic borders. As a firm that performs value-added operations in more than one country, an MNC is required to deal with several national governments. In doing so, MNCs face different environmental regulations between the country of foreign operations and the country of origin. Consequently, MNCs should comply with different environmental regulations by the national governments (in both home country and countries of operations) where their facilities and subsidiaries operate. The environmental regulations imposed by a country of their operations would be a set of minimum environmental requirements that MNCs must meet in order to do business in that country. This is termed “regulatory environmental requirements” of each country, in this dissertation. The regulatory environmental requirements, however, are usually different across countries in the level of stringency (e.g., emission limits). Furthermore, in some countries they may not be even enforced or legislated (e.g., German product take-back). Coping with the challenges of different regulatory environmental requirements, MNCs have shown different responses in their strategic patterns. According to the IRRC (Investor Responsibility Research Center)’s Corporate Environmental Profile survey, S&P 500 companies showed inconsistent responses to different 1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental regulations imposed on them across countries in which they are operating. Of the 169 manufacturing companies, 25 percent said they apply U.S. standards except where local laws are more stringent. 56 percent said a uniform corporate policy applies to environmental practices worldwide. 62 percent said that environmental practices vary according to host country environmental regulations and other site-related factors (IRRC 1998). In response to the environmental regulations, firms deal with corporate environmental strategy which is to manage environmental concerns as a strategic issue for the company and to determine the responses in dealing with the natural environment. Many researchers have studied the corporate environmental strategy in MNCs (Christmann 1997; Epstein and Roy 1998; Dowell, Hart et al. 2000). Most research of corporate environmental strategy in MNCs has been conducted in determining the level of uniformity, defined as how much firms standardize their environmental standards applied to host countries, between a global uniform standard and locally different ones. Despite the differences between researchers, their classifications are based on making distinctions along a continuum ranging from a global uniform standard to locally different. On the other hand, corporate environmental strategies in firms within a national boundary have been studied in terms of another dimension - the degree of proactivity (Roome 1992; Coddington 1993; Sadgrove 1993; Greeno and Robinson 2 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1994). Proactivity has been studied as another dimension of environmental strategy. Proactivity can be described as the level of compliance to environmental regulations imposed by the government. If the firm is just complying with regulatory environmental requirements, the firm is considered reactive in one extreme and if they are complying beyond the requirements, proactive in the other extreme. In summary of previous literature of corporate environmental strategy, there have been two streams of research on corporate environmental strategy - (1) research on corporate environmental strategy in firms within a national boundary focusing on proactivity and (2) research on corporate environmental strategy in MNCs across borders focusing on uniformity. This dissertation focuses on corporate environmental strategy in MNCs in terms of both proactivity and uniformity. In the research on corporate environmental strategy in MNCs, there has been an implicit assumption that a local strategy is synonymous with a reactive strategy, while a global strategy is with a proactive strategy, meaning that firms declaring local environmental standards pollute more than those adopting a global uniform standard across host countries of foreign operations. MNCs with uniform strategy are assumed to be proactive in foreign operations, while those with local strategy are considered to be reactive (Investor Responsibility Research Center 1998; Dowell, Hart et al. 2000). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. This dissertation starts with a question of this assumption. Theoretically, this dissertation argues that the different environmental strategies in MNCs, namely a uniformity strategy and a proactivity strategy, need to be considered simultaneously and in relation with each other. For example, two MNCs with uniform strategy may have different levels of environmental technology. Subsequently, this different level of environmental technology may determine the degree of environmental proactivity. Therefore, an MNC with lower level of environmental technology may be less proactive in foreign operations than another MNC with a higher level of environmental technology, although both MNCs have a uniform strategy. Hence, there may be MNCs with uniform strategy but less proactive strategy compared with other MNCs. Since the previous literature has not considered both dimensions, uniformity and proactivity, at the same time in explaining the environmental strategies of MNCs, I argue that it falls short in explaining corporate environmental strategy in MNCs. Operationally, this dissertation aims to make a contribution by measuring uniformity as a continuous variable. Traditionally, local or uniform strategy has been regarded as a dichotomous variable. I argue that by measuring uniformity as a continuous variable, my dissertation captures the rich continuum between local and uniform strategies. After all, all the environmental practices may not be standardized to the same degree across foreign operations. 4 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1.2. Research Objectives This dissertation has two main research objectives. First, considering the level of uniformity and the level of proactivity, the dissertation proposes a new typology of corporate environmental strategy in MNCs. With the two dimensions of a 2x2 matrix, MNCs are classified into four distinctive strategic patterns: reactive/local, proactive/local, reactive/uniform, and proactive/uniform. Next, the dissertation investigates a subsequent question of which factors drive MNCs into a different strategic choice for dealing with environmental regulations. Based on previous studies on corporate environmental strategy, four driving factors are proposed. These are environmental technology investments, manufacturing flexibility, corporate visibility, and environmental heterogeneity in environmental regulations between countries of operations. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 2 PREVIOUS STUDIES ON CORPORATE ENVIRONMENTAL STRATEGY The intent of corporate environmental strategy is to manage environmental concerns as a strategic issue for the company and to determine the responses in dealing with the natural environment. Two streams of research on corporate environmental strategy have been identified in the literature, as shown in Figure 1. The first stream of research focuses on whether a firm pursues a proactive or reactive environmental strategy and concentrates on domestic firms. The second stream focuses on the issue of uniformity, i.e., whether firms pursue uniform environmental strategy across different subunits. This stream looks only at multinational corporations. I will review each perspective in subsequent sections. 2.1. Domestic Firm’s Perspective The issue of proactivity has been studied mainly by researchers of domestic firms. According to these researchers, proactivity can be described as the level of compliance to environmental regulations imposed by the government. If a firm merely complies with regulatory environmental requirements, the firm is considered reactive in one extreme. If a firm exceeds the requirements, it is considered proactive in the other extreme. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 1 Previous studies on corporate environmental strategy Domestic Perspective (Single-site) (Dimension o f Proactiveness) (Roome, 1992; Sadgrove, 1993; Greeno, 1994; Coddington, 1993; Kent Country Council Environmental Assessment Group, 1991) Proactive vs. Reactive Multinational Perspective (Multi-sites) (Dimension o f Uniformity) (Epstein and Roy,1998; Christmann, 1997; Dowell, Hart and Yeung, 2000; Investment Responsibility Research Center, 1998) Uniform vs Local The researchers in this line of work have developed typologies of corporate strategy regarding the natural environment in terms of firms’ degree of proactivity in regard to environmental regulations (Roome 1992; Coddington 1993; Sadgrove 1993; Greeno and Robinson 1994). The classification proposed by Roome (1992) has been the best known and is based on the proactivity as an underlying theme. His framework lays out the following dimensions: - Noncompliance: applying no natural environmental measures of any kind and not even conforming to regulatory requirements Compliance: firms whose postures are determined by prevailing legislation Compliance-plus: firms that not only abide by the law but also have approaches based on their own natural environmental management systems 7 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Commercial and natural environmental excellence: systematically apply preventive methods based on principles of total quality management in their natural environmental and overall managerial practices - Leading edge: firms whose postures point the way for future development by others T h ou gh R o o m e (1 9 9 2 ) d id n ot u se the term p roactivity, h is fram ew ork is b ased essen tia lly o n the d eg ree o f proactivity: n o n co m p lia n ce b e in g th e least proactive strategy and lea d in g ed g e the m o st proactive strategy. F o llo w in g th e lead o f R o o m e, researchers stu d y in g en viron m en tal strategies o f d o m estic firm s m a k e the d istin ction alon g a con tin u u m ran gin g from the m o st reactive p ostu res to the m o st proactive on es. 2.2. Multinational Firm’s Perspective Researchers who study the environmental strategies of multinational corporations, on the other hand are concerned with a strategic decision on the “uniformity” of environmental standards between the headquarters and subsidiaries. Because many MNCs should determine whether to adopt a global uniform standard or to adapt to the locally differentiated requirements, the concept, uniformity, has been a key issue in this stream (Christmann 1997; Epstein and Roy 1998). 8 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Researchers in this steam often treated a uniform strategy as equivalent to aiming to meet a higher environmental standard. Dowell, Hart and Yeung (2000), for example, argued that firms adopting a single, stringent uniform environmental standard have higher market values as measured by Tobin’s q, than firms defaulting to less stringent or poorly enforced host country standards. The researchers’ focus is on answering the contention that MNCs are engaging in flight to “pollution havens” by moving dirty operations to countries where regulatory standards are less stringent (Daly 1994). Through flight to pollution havens, MNCs can avoid expensive pollution controls, cut costs by recapitalizing old equipment, and continue to make products that are no longer considered environmentally acceptable in the more highly regulated markets of the developed world (Vernon 1992). Over time, it is claimed that these practices lead to a “race to the bottom” as nations and localities vie for plants and facilities that seek only to minimize cost and externalize environmental responsibility (Korten 1995). Two likely reasons exist for MNCs pursing less uniform strategies are equated with pursuing less stringent environmental strategies. First, from an managerial perspective, some have argued that for competitive reasons they must be able to establish corporate environmental standards at the lowest legal limit in the countries in which they operate or competitors will continually b e ab le to un d ercost and underprice them on competitive bids (Epstein and Roy 1998). Second, since there are currently no enforced agreements among industrialized nations to insure compliance, 9 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. it is very difficult to enforce highly stringent environmental regulations globally. Despite extensive ongoing interaction on environmental and trade issues, there have been relatively few instances where formal, harmonized regimes have emerged (Munton and Kirton 1996). Therefore, environmentalists often suggest that the absence of strong laws in many developing countries enables giant MNCs - especially in the mining and chemical industries - to play fast and loose with the local environment and the local population’s health (Sims 1995). We can find many examples of this in a popular press. Notwithstanding the difficulties of pursing globally uniform environmental strategies, some have argued that globally uniform standards are important on moral grounds, and that minimal environmental standards should be consistent across the corporation. Some MNCs, such as IBM and Allied Signal, have voluntarily required their foreign operations to apply environmental standards as stringent as they must follow in their home country, the United States (IRRC 1998). Further, MNCs like Hewlett-Packard, Dow Chemical Co. and Du Pont have committed themselves to corporate environmental standard1 , in a global fashion (IRRC 1998). These companies anticipate that regulatory environmental requirements will eventually become more stringent and standardized worldwide. Hence, they wish to exceed the current compliance with local requirements, and incur additional short-term costs to establish an environmental leadership in these locations even where it is not 1 Corporate environmental standard is referred to as the internal measures which foreign operations of MNCs should meet according to the corporate environmental policy established by their headquarters. 10 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. currently required (Epstein and Roy 1998). For example, Hewlett-Packard redesigned packaging for its office machine to meet stringent German requirements and used it to set the standard for the packaging of its products worldwide (Rondinelli and Vastag 1996). To support the MNCs with a global standard, researchers have begun to study corporate environmental strategy in MNCs. Recently, Dowell, Hart and Yeung (2000) found that adopting a single stringent globally uniform environmental standard has much higher market values, as measured by Tobin’s q, than firms defaulting to less stringent, or poorly enforced host country standards. Also, Christmann (1997) indicates that MNCs benefit from global standardization of environmental strategies, even though setting a high level of worldwide internal environmental standards increases costs. 2.3. Considering uniformity and proactivity together As described above, there have been two strategic alternatives in corporate environmental strategy according to which strategic dimensions (uniformity and proactivity) are used. That is, in a domestic company’s view, the company moves between proactive and reactive. And in a multinational firm’s point of view, they have a choice between global and local in terms of environmental standards applied to host countries. In this dissertation, the question of whether they can be combined to create a richer typology of environmental strategies for MNCs is addressed. I 11 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. argue that two dimensions are different and that they could be fruitfully combined to yield a typology. In the previous studies on corporate environmental strategy of MNCs, researchers have mainly considered the dichotomous decision-making between uniform and local standards (Epstein and Roy 1998; Dowell, Hart et al. 2000) or one-dimensional decision on the level of uniformity in environmental standards across countries of foreign operations (Christmann 1997). In doing so, they have implicitly assumed that there is no difference between proactivity and uniformity. In many cases, they regarded the uniform standards as proactive and local standards as reactive. For example, if an MNC applies a global uniform standard across foreign operations, it implies that the company is proactive. Likewise, if an MNC adapts to the environmental standards of host countries, it implies that the company is reactive. Therefore, MNCs with a global uniform standard are more proactive than those with locally adapted standards. It also implies that environmental performance measured by the level of proactivity is higher in MNCs with a global uniform standard than those with local standards (Dowell, Hart et al. 2000). The current dissertation argues that uniformity is different from proactivity. In other words, MNCs can implement different levels of proactivity even though their level 12 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. of uniformity is the same. So far in the studies of corporate environmental strategy in MNCs, no consideration of the level of proactivity has been done along with the level of uniformity. But firms adopting a uniform standard may meet a different degree of stringency in their environmental standards across foreign operations. To overcome the deficiency, both proactivity and uniformity dimensions should be simultaneously considered to identify alternatives of corporate environmental strategy in MNCs. The two dimensions described above have been studied separately so far. Hence, no study has been done combining these two dimensions. Instead, uniformity and proactivity have been used interchangeably in the literature of corporate environmental strategy as if they are highly correlated or identical. For example, companies with local standards usually adapt to the requirements of host countries as a minimum standard. But it is also observed that companies such as Praxair and Ecolab apply more stringent environmental standards than the requirements imposed by host countries than those with a global uniform standard (IRRC 1998). Therefore, in this dissertation, I combined uniformity and proactivity to build a new typology of corporate environmental strategy in multinational corporations. It was also proposed that there exist two distinctive strategic alternatives in each category of previous strategy classifications of MNCs. 13 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 3 CONCEPTUAL FRAMEWORK FOR CORPORATE ENVIRONMENTAL STRATEGY IN MNCS 3.1. Two Dimensions of Corporate Environmental Strategy in MNCs The main goal of developing a new typology of corporate environmental strategy in MNCs is to identify potential strategic choices of managers. Previously managers as well as researchers have thought of their corporate environmental strategy in the single dimension of the local-global framework (Christmann 1997; Epstein and Roy 1998). They have used an integration-responsiveness framework in international studies. Dowell, Hart and Yeung (2000) categorize strategic choices of environmental standards into three: corporate standard, US standard, local standards. Later, Dowell, Hart and Yeung (2000) added one more strategic option for MNCs to the previous work. Still all studies have presumed that firms with local standards are less proactive than those that follow a global standard. It will be argued here, that a firm’s corporate environmental strategy can be discriminated from just the local/global dimension. I argue that the level of proactivity is another strategic choice of corporate environmental strategy. Figure 2 shows the proposed typology. 14 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3.1.1. Environmental Proactivity In my framework, the first dimension of corporate environmental strategy is the level of proactivity. Environmental Proactivity is defined as an MNC’s level of stringency in environmental practices (standards) applied to a foreign operation relative to environmental regulations of the country of foreign operation. Several terms that have been used simultaneously to describe a firm’s proactivity including voluntary overcompliance, environmental responsiveness, environmental responsibility, and environmental consciousness. Many researchers have attempted to establish the dimensions of environmental practices to distinguish between reactive and proactive firms and look for the consistency of environmental practices across the dimensions that are relevant to a firm’s range of operations. For example, the generic strategy categories of “reactive” and “proactive” responses have been frequently used in the corporate social performance literature (Post 1978; Sethi 1979). When a company acts on environmental problems as they occur and in response to internal or more likely, external pressures, the company has a reactive strategy. On the other hand, a firm may decide that it will integrate environmental concerns at the very beginning of the product’s life cycle, namely at the development phase, thus trying to anticipate and correct any negative environmental impacts which could occur over the entire life cycle (Caimcross 1992). Such a company’s strategy would be termed proactive. (Sharma and Vrendenburg 1998) consider companies “proactive” only if they exhibit 15 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. a consistent pattern of environmental practices across all dimensions relevant to their activities, not required to undertake in fulfillment of environmental regulations or in response to isomorphic pressures within the industry as standard business practices. Therefore, even though a company is very active in one or some of the dimensions, the company is not considered proactive if the company undertakes very limited environmental practices in the other dimensions. Below are some examples of proactive environmental strategy (Berry and Rondinelli 1998). • Waste minimization and pollution prevention Scott Paper adopted an integrated approach to source reduction, recycling, and reuse and to materials substitution. General Dynamics eliminated almost 40 million pounds of hazardous waste discharge from its production processes between 1984 and 1988. Chevron reduced hazardous wastes by 60% between 1987 and 1990, saving more than $10 million in disposal costs. General Electric adopted a program to decrease toxic emissions by 90% between 1988 and 1993. - Xerox reduced hazardous waste generation by 50% between 1990 and 1995. Earthshell Container Corporation is working with the McDonald’s fast- food chain to test an alternative food container using low-cost materials 16 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (potato starch, water, calcium carbonate, and cellulose fiber) that are both stronger than conventional paper and polystyrene packaging and that are, after use, fully dissolvable in water. • Demand-side management • Design for environment • Product stewardship • Full cost environmental accounting 3.1.2. Environmental Uniformity The second dimension of the proposed framework is environmental uniformity, defined as a level of similarity in environmental practices applied to a foreign operation relative to environmental practices applied to the firm’s country of origin. Previous studies have examined corporate environmental strategies of MNCs by considering either of the two strategic options. One is to adopt a global uniform corporate standard worldwide. It is referred to as “global/uniform standard” in this dissertation. The other is to adapt to national differences of regulatory environmental standards across countries of foreign operations. It is referred to as “local standards” in this dissertation. However, in the real world managers of MNCs in general would not simply choose one of these two environmental strategic alternatives between global and local. 17 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Instead, they may go between the two extremes. Thus, it is referred to as “the level of uniformity” in this dissertation. Further, managers may use a mix of environmental operations strategies by adopting different degrees of standardization for different types of environmental regulations, respectively. For example, environmental standards related to air emissions may be globally standardized by adopting the same corporate compliance measures across subsidiaries. They may adapt to local environmental standards by applying different environmental standards to different countries. Otherwise, they may adopt a uniform corporate standard for recycling except some subsidiaries. To simplify the situation for improved analysis, in this dissertation, I will restrict the study to the two extremes of the level of uniformity: local and uniform. (1) Local strategy A strategy is defined as a local strategy if MNCs allow their different business units or facilities to determine the level of environmental performance they wish to attain to respond to local environmental standards. At a minimum, they may choose to comply with relevant local regulations and other requirements. Local environmental strategy allows more operational flexibility to cope with fast changing and widely different environmental regulations and social attitudes. Competitive issues are particularly important as some companies must compete with companies with lower 18 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental standards (Epstein and Roy 1998). For competitive reasons, they may be able to establish corporate environmental standards at the lowest legal limit in the countries in which they operate so that competitors can not continually undercost and underprice them on competitive bids. (2) Uniform strategy Business units and facilities may also need to comply with corporate environmental standards. For business units operating in locations with lax environmental regulations, to adopt a global environmental standard often means overcompliance with local regulations. But in this dissertation, I put more emphasis on the fact that they adopt a “uniform” standard, because the typology of our corporate environmental strategy distinguishes between proactivity and uniformity in the dissertation. 3.1.3. Four strategic alternatives using two dimensions The “environmental regulations of the country of operation” versus “environmental practices (or standards) of the country of origin” distinction suggests that firms can be characterized along two dimensions: environmental proactivity and environmental uniformity. The environmental proactivity can be defined as a firm’s level of stringency in environmental practices (or standards) applied to a foreign operation compared to environmental regulations of the country of foreign operation. Environmental uniformity can be defined as a firm’s level of similarity in 19 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental practices (or standards) applied to a foreign operation compared to those applied to the firm’s country of origin. Figure 2 summarizes the resulting typology of corporate environmental strategy in MNCs, with, on one dimension, the degree of environmental proactivity that goes beyond the environmental regulations imposed by the country of operation and, on the other dimension, the degree of environmental uniformity that goes with environmental practices (or standards) applied in the country of origin. I have simplified the representation by dichotomizing both dimensions. In reality, of course, both the degree of environmental proactivity and the degree of environmental uniformity are continuous variables. Figure 2 Typology of Corporate Environmental Strategy in MNCs Multinational Perspective (Uniform vs. Local) R eactive Uniform Proactive Uniform c 0 ) E c e R eactive Local Proactive Local ■ 5 c m Low Low E n v iro n m e n ta l Domestic Perspective (Proactive vs. Reactive) 20 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Using the two dimensions described above, corporate environmental strategy is defined as simultaneous decision making on both the level of uniformity and the level of proactivity in response to different environmental regulations imposed by host countries of foreign operations. This dissertation proposes that there exist four distinctive corporate environmental strategies in MNCs. These are: (1) Reactive / Local Strategy (2) Reactive / Uniform Strategy (3) Proactive / Uniform Strategy (4) Proactive / Local Strategy The characteristics of each strategy will be explained in detail later in chapter 4. 3.1.4. An Empirical Evidence of the Proposed Typology Before proceeding further, I examined whether there is any empirical basis for dividing corporate environmental strategies in terms of the suggested 2x2 matrix. To do this, I used the IRRC survey results. The IRRC survey results contain a record of each corporation’s declared stance regarding its international environmental standards. 21 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Proactivity is measured by the level of environmental standards applied to foreign operations compared with environmental regulations of the foreign country of operation. But in applying my model with the IRRC survey results, one difficulty is that consistent and reliable pollution data at the plant level on a global scale do not exist, especially in developing countries. In operationalizing the level of proactivity, Dowell, Hart and Yeung (2000) used each firm’s U.S. TRI (Toxic Release Inventory) data to measure the firm’s environmental performance, because the level of proactivity would be reflected in the level of environmental performance achieved. The IRRC tracked US plants’ toxic releases (by weight) from 1993 to 1995 and reported for each company its ratio of toxic releases to sales and industry average (IRRC 1998). Dowell, Hart and Yeung (2000) created a variable, “relative emissions”, which is the difference between a firm’s IRRC emission efficiency index and industry average. The IRRC emission efficiency index is the ratio of reported toxic chemical emissions in pounds to the company’s domestic revenues (i.e., US toxic release/sales). A high index value may indicate that a company operates in an industry with relatively high pollutant emissions. A high index value in comparison to other firms in the same industry may be an indication that a company has more toxic chemical-intensive operations or has been less efficient than its competitors in reducing the use or emission of certain toxics in its production process (IRRC 1998). Consistent with their 22 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. operationalization, here I use the variable, “relative emissions,” as a surrogate measure of the level of proactivity Uniformity is measured by the level of environmental standards applied to foreign operations compared with those applied to their country of origin. IRRC survey of Corporate Environmental Profile surveyed a company’s declared class of environmental standard (IRRC 1998). Firms can be classified into two categories: local standard vs. uniform standard. I used this declared class of environmental standard as the level of uniformity. Using the two measures of proactivity and uniformity, as shown in Figure 3 and Table 1, the variation of the level of proactivity within each group (local and global) is so high that the null hypothesis of equal means between groups cannot be rejected. Figure 3 Distribution of the level of proactivity (local vs. global standard) w -7.44 -4.98 .06 2.40 - 2.52 -6.21 - 3.75 - 1.29 1.17 3.63 T he level of pro activ en ess (Global uniform standard) 40 (A ‘ S < u -Q E 3 z •7.44 -6.21 - 4.98 - 3.75 -2.52 - 1.29 -.06 1.17 2.40 3.63 -5.60 -4.37 -3.14 - 1.91 .55 1.78 3.01 4,24 T he level of p ro activ en ess (Local stan d ard s) 23 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Therefore, there is no statistical evidence that MNCs with local standards are less proactive than that follow a global standard. Further, the results suggest the possibility that there exists another dimension along with a proactivity strategy. Table 1 T-test for the difference of means between local and global standard Proactivity N Mean Std Dev Std Error Mean Reactive 44 -0.0270 1.4925 0.2250 Proactive 94 0.0005 1.5169 0.1565 Independent Sam ples Test L evene's T est for Equality of V ariances t-test for Equality of M eans Sig. M ean Std. Error 95% Confidence Interval of the M ean F Sig. t df (2-tailed) Difference Difference Lower U pper Proactivity Equal variances .012 .915 -.101 136 .920 -2.78E-02 .2757 -.5730 .5174 assu m ed Equal variances not assu m ed -.101 85.403 .919 -2.78E-02 .2741 -.5727 .5171 Traditionally, the classification of corporate environmental strategy in the previous studies is one-dimensional scheme. I believe that another dimension of the corporate environmental strategy is left out of the literature on MNCs. In other words, two MNCs, both of which follow a global uniform standard, could be proactive or reactive in terms of their environmental strategic patterns. This would be reflected in their environmental performance. Likewise, MNCs with local standards could also be proactive and their environmental performance could outrun that of MNCs that adhere to a uniform standard. 24 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In the next chapter, I will identify the characteristics of each corporate environmental strategy and examine the differences in the strategic choices in terms of factors affecting proactivity and uniformity. 3.2. Driving Factors of Corporate Environmental Strategy in MNCs: Hypotheses Development and Research Model In the previous section, a typology of corporate environmental strategy in MNCs was identified using two dimensions: environmental proactivity and environmental uniformity. These two dimensions classify corporate environmental strategies in MNCs into four types of corporate environmental strategy. In this section, four factors driving the two dimensions of corporate environmental strategy will be discussed. These four driving factors differentiate proactive strategies from reactive ones and uniform strategies and local ones. Multinational firms face the challenge of selecting the appropriate degree of environmental uniformity for each of their environmental practices. In selecting the degree of environmental proactivity, firms must consider environmental regulations of the country of operation. In addition, in selecting the degree of environmental uniformity, companies must consider environmental practices applied to the country of origin. Further, environmental practices are particularly interesting because they encompass a variety of the firm such as R&D, production, marketing, and public relations. This makes it more challenging for firms to adopt the level of 25 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental practices or standards consistent with the internal capabilities of the firms and the external pressures that firms face. Why are firms different in their corporate environmental strategy? First, they can deploy the resources and capability in accordance with their proactive strategy. Second, consumers want firms to be environmentally proactive. The first motive is internally originated and the second is an external pressure of a firm’s making a proactive strategic choice. In this section, I developed seven hypotheses regarding the effects of external pressures and internal capabilities of the firms on the degree of environmental proactivity and environmental uniformity. 3.2.1. Internal Capabilities As the internal capabilities of firms related to environmental practices, environmental technology, defined as the intensity of environmental technology investments and manufacturing flexibility, defined as adaptability to changes in environmental issues and changes in products and processes, were used. 3.2.1.1. Environmental Technology Environmental technology is defined as technology that limits or reduces negative impacts of products or services on the natural environment (Shrivastava 1995). 2 6 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Shrivastava (1995) called for the inclusion of environmental technology in frameworks of strategy. The potential of these technologies to offer competitive advantage has been noted (Hart 1995; Porter and Linde 1995; Shrivastava 1995). (Klassen and Whybark 1999b) found the pattern of its investment in environmental technologies in manufacturing overtime significantly affects both manufacturing and environmental performance. Shrivastava (1995) proposed classifying environmental technologies into five themes based on their general management orientation: design for disassembly, manufacturing for the environment, total quality environmental management, industrial ecosystems, and technology assessment. However, these themes are difficult to measure over time, cannot be easily overlaid onto existing manufacturing strategy research, and include aspects of both strategy development and implementation. Other research supports a more straightforward typology for characterizing environmental technologies as belonging to three general categories: pollution prevention (Caimcross 1992; Freeman, Harten et al. 1992; Schmidheiny 1992), management systems (Marguglio 1991; Dillon and Fischer 1992), and pollution control (Hart 1995; Russo and Fouts 1997). Using these categories, Klassen and Whybark (1999b) classified the allocation of resources across environmental technologies. 27 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In this dissertation, two categories of environmental technologies classification were used, because these two categories are more closely related to environmental regulations of the countries of operation. Also, especially in Third World countries, management systems are not as easy to transfer to the country of operation as the two categories. (1) Pollution prevention technologies This category is defined as structural investments in operations that involve fundamental changes to a basic product or primary process. These technologies reduce or eliminate pollutants by using cleaner alternatives than those currently in place (Freeman, Harten et al. 1992). Pollution prevention technologies can be further characterized as product or process adaptation, although the two are related. Product adaptation encompasses all investments that significantly modify an existing product's design to reduce any negative impact on the environment during any stage of the product's manufacture, use, disposal, or reuse. Process adaptation refers to fundamental changes to the manufacturing process that reduce any negative impact on the environment during material acquisition, production, or delivery. Pollution prevention technologies can provide net benefits because of their potential to improve environmental performance up-front, rather than as an afterthought (Schmidheiny 1992; Porter and Linde 1995). Because the implementation of pollution prevention technologies depends on organizational and knowledge-based resources, greater competitive advantage is expected during periods of uncertainty 28 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. due to rapid industry growth (Russo and Fouts 1997), new environmental regulation (Dean and Brown 1995), declining availability of natural resources, or increased external stakeholder pressure (Hart 1995). Pollution prevention technologies are expected to significantly reduce the total quantity of harmful pollutants released into the environment and disposed of (Royston 1979; Freeman, Harten et al. 1992; Schmidheiny 1992). Pollutants are not merely transferred from one medium to another (for instance, from the air to solid waste); instead, their generation is avoided. (2) Pollution control technologies In contrast to prevention technologies, pollution control technologies treat or dispose of pollutants or harmful by-products at the end of a manufacturing process, either immediately or later. To accomplish this, a plant must add operations or equipment to the end of an existing manufacturing process, thereby leaving the original product and process virtually unaltered. Pollution control technologies can be further characterized as either remediation or end-of-pipe controls. Remediation refers to cleaning up environmental damage caused by crises or past practices, and it is often driven by regulations or by improvements in the scientific understanding of environmental damage. End-of-pipe controls refer to using equipment that is added as a final process step to capture pollutants and wastes prior to their discharge. In contrast to pollution prevention, pollution control does not usually reduce the total quantity of harmful pollutants either released into the environment or disposed of, 29 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. thus also posing future liabilities (Royston 1979; Freeman, Harten et al. 1992; Schmidheiny 1992). Any environmental benefit offered by pollution control technologies is limited to reducing the risk associated with a specific pollutant, either transferring it from a less secure medium to a more secure one (for instance, from air emissions to solid wastes) or converting it to a more benign substance. Thus, no significant change in the quantity of pollutants is expected The MNC will consider the environmental costs related to compliance with the environmental regulations in the countries of their foreign operations. Environmental costs have two categories: cost of compliance and cost of intangibles. Costs of compliance, which are mostly tangible, include the following: capital expenditures (fixed costs) and operating costs (variable costs). Capital expenditures vary according to the type of environmental technology used. These may be either the pollution control technology or pollution prevention technology. The choice of technology depends upon the environmental proactivity of the company and the stringency of environmental regulations of host countries compared to the home country. The specific characterization of each type of posture may be based on firms' use of either traditional or modem approaches to improving their natural environmental performance (Evan, 1988). (Buchholz 1993) pointed out that normal regulations have usually required the use of traditional methods. Modem procedures are normally adopted on a firm's own initiative, as a result of a growing awareness of problems and perceptions of advantages. Traditional methods, also known as end-of- pipe solutions, are attempts to solve problems when they arise through procedures 30 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. such as refuse destruction and chimney filters (Caimcross 1992; North 1992). Modem methods, on the other hand, are mainly designed to prevent the occurrence of problems by dealing with their sources (Schmidheiny 1992). A reactive company tends to merely comply with environmental regulations by minimizing their costs related to the environment. Therefore, they prefer to use the end-of-pipe technology to reduce or remove pollutants or wastes after those have already been generated throughout the production processes. On the contrary, a proactive company tends to comply beyond the current environmental regulations by anticipating the changes of environmental regulations. Further, they create an opportunity from the environmental issues by either changing their production processes or product design. Their interests are not only to minimize costs but also to pursue the competitive advantages related to the environment. Therefore, they prefer to use the pollution prevention technology which reduces or eliminates pollution at the source. Regarding the countries of foreign operations, the end-of-pipe technology may be enough to meet the requirements without incurring additional costs of using more expensive pollution prevention (P2) technology for some countries with less stringent regulations than those of their home country. But for other countries with more stringent environmental regulations than those of their home country, P2 technology will be needed. Therefore, the selection of environmental technology is highly related to the location selection of their foreign operations. But the location of foreign operations is not the issue of this dissertation. 31 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The selection and intensity of investments in environmental technologies will affect the environmental proactivity of the company and the uniformity of environmental practices between the country of operation and the country of origin. Therefore, MNCs with a high level of environmental technology may be more proactive because they can achieve a higher level of environmental performance in reducing pollutants or preventing pollution at the source by redesigning products and production processes. These same proactive MNCs, however, could conceivably invest and innovate in different operations to come up with better environmental practices, thus being local rather than uniform. Over time, these best practices would be shared amongst all its operations. Therefore, more environmental technology need not force MNCs to become more uniform. This could be the reason that firms dynamically move from proactive/uniform to proactive/local and vice versa. Therefore, I hypothesized that: HI: Environmental technology is positively related to environmental proactivity. H2: Environmental uniformity is highest at a moderate level of environmental technology. 32 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3.2.1.2. Manufacturing Flexibility Multinational corporations adapt design and production for international markets, while maintaining manufacturing flexibility to adapt quickly to local market tastes, evolving technical standards, and changing governmental regulations (McGraith and Hoole 1992). Manufacturing firms worldwide are investing in flexibility to efficiently and effectively adapt to external change. Manufacturing flexibility enables firms to rapidly deploy new technologies, respond to new consumer demands, and handle legislative, political, and social climates that differ around the world. The natural environment is one issue that affects consumer demand, technology, and socio-political climate. A firm’s management of issues related to the natural environment might potentially benefit from increased flexibility. Manufacturing flexibility has been studied by many researchers with various definitions. Manufacturing flexibility provides options for developing new products or entering new geographic markets and adapting to demand (Kogut and Kulatilaka 1994). Manufacturing flexibility refers to the quickness and ease with which plants can respond to changes in market conditions (Cox Jr 1989). Manufacturing flexibility includes both volume and product-mix flexibility (Skinner 1974; Schonberger 1986). Volume flexibility refers to the capacity to quickly expand the quantities of a given product mix produced, while mix flexibility addresses the ability to quickly change the types of products produced in the plant. The latter includes both changes to existing products and the addition of new ones. (Slack 33 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1983) suggests that the incentives to seek flexibility are founded in the instability and unpredictability of the manufacturers’ operational environment. (Gerwin 1987) attempted to associate types of uncertainty with types of flexibility. (Cox Jr 1989) defines manufacturing flexibility as the quickness and ease with which plants can respond to changes in market conditions. Nagarur (1992) defines flexibility as the ability of the system to quickly adjust to any change in relevant factors like product, process, loads and machine failure. In this dissertation, manufacturing flexibility with implications of environmental strategy is defined as adaptability to changes in environmental issues and changes in products and processes. Some MNCs operate only in countries with less stringent environmental standards than their countries of origin. Others go to countries both with less stringent environmental standards and more stringent environmental standards than their countries of origin. Therefore, if foreign operations of an MNC are arranged by the stringency of environmental standards imposed by the countries of operation, the distribution of the countries of operation would be different across MNCs. Differences in regulatory systems between countries and in the pace of regulatory change can be expected to foster different corporate environmental standards partly based on manufacuting flexibility. The general regulatory approach, either command-and-control of manufacturing (US) or final poduct disposition (Europe), can prompt different responses from manufacturing. For example, in a command- 34 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. and-control regulatory system, firms with low mix and low new product flexibility are more likely to resist changes, and ultimately resort to end-of-pipe controls (e.g., water treatment plant or air scrubber at the end of a process), which add to overall cost. Firms with high flexibility can move into new markets or alter the product design to minimize the cost impact of these regulations. Alternatively, in a system that emphasizes final poduct disposition, firms can more quickly respond to the availability of recycled materials as flexibility increases. Finally, in the face of regulatory change, particualrly if the future direction of such change is unclear, flexibility enables improved responsiveness without requiring costly process retro-fit or product redesign (Klassen and Angell 1998). For example, Vulcan Chemicals, an Alabama-based producer of chlor-alkalies, faced significant uncertainty of demand after reports of affects on the human and the natural environment (Ainsworth 1994). As public debate heated up, new environmental regulations targeted Vulcan’s chlorinated products. The company was forced to invest in manufacturing and marketing flexibility in order to adapt to wildly fluctuating demand and changing markets. Increased flexibility in the production process also enabled Vulcan to diversify into less environmentally sensitive product lines. Thus, manufacturing flexibility helped to support a strong competitive response to environmental pressures. Vulcan Chemicals was able to alter its earlier business strategy toward more environmentally friendly products and markets as a direct result of its investment in production flexibility. (Klassen and Angell 1998) explored the relationship between manufacturing flexibility and environmental proactivity. 35 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Generally a major benefit of standardization strategy is to reduce cost. Therefore, we need to check whether standardization (i.e., uniform corporate environmental standard) is accompanied by cost reduction. If so, the company can afford standardization. In operations management, flexibility is a competitive weapon to achieve cost minimization (Klassen and Angell 1998). One possible strategy in response to different environmental regulations for manufacturing firms is to leverage their manufacturing flexibility to respond to changing regulatory systems both within and among countries (Klassen and Angell 1998). Thus, high manufacturing flexibility is a firm’s capability to quickly respond to those environmental pressures by redesigning product and processes. Therefore, MNCs with local strategy may tend to choose different environmental practices across foreign operations than MNCs with uniform strategy. But MNCs with uniform strategy have less intention to choose different environmental practices across foreign operations than MNCs with local strategy. Therefore, MNCs with local strategy may become more proactive in any foreign operations if they have high manufacturing flexibility. Therefore, I hypothesized that: H3: Manufacturing flexibility is positively related to environmental proactivity. H4: Manufacturing flexibility is negatively related to environmental uniformity. 36 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. H5: The negative effect of manufacturing flexibility on environmental uniformity is enhanced as environmental technology increases. 3.2.2. External Pressures As the external pressures of firms related to environmental practices, corporate visibility and environmental heterogeneity were used. 3.2.2.1. Corporate Visibility Corporate visibility is defined as both the observability of a business activity and an improvement in the firm’s ability gained by recognition from internal and external stakeholders. Corporate visibility is a multidimensional construct including the level of recognition, transparency, legitimacy, media exposure, corporate image, reputation, firm size, etc. Today’s operations managers manipulate global networks of resources. They integrate foreign suppliers into the supply chain, and they must make and deliver products that satisfy both local and foreign customers. Large corporations increasingly rely on global expansion to increase profits and improve shareholder value. However, the environmental regulations outside of the United States, particularly in developing countries, are not always as strict as U.S. regulations. Therefore, it is of particular importance that consumers and investors have access to 37 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. information not only about a company’s U.S. environmental track record, but also about its overseas environmental practices (Cassady, 1995). To explain the importance of proactive strategy, (Macauley 1993) notes that there are two concepts regarding external credibility that will have a positive impact on internal credibility as well: objective indicators and independent verification. When firms lose value in the public perception, they seek more rapid means than law and regulation to verify the appropriateness of their strategy. The rapid revitalization of Union Carbide’s audit system, its internal code, and its use of A. D. Little consulting were all shaped, changed, and refocused by the avalanche set in motion by the tragedy in Bhopal. In this way, customers can evaluate a firm based on its corporate visibility and the environmental impact of its product, processes and activities of a company released to customers would be leveraging effects both from positive and negative environmental information. Because of the leverage effect, leading companies could take advantage of environmental issues as their competitive advantage for barriers to followers. In any industry, especially the chemical industry, any incident anywhere in the world affects everyone, regardless of whether or not it happened in the company itself. It means that they are sharing the burden of risk, and the risk of being harmed by 38 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. others’ actions. (Rondinelli and Vastag 1996) describe environmental policy alternatives arising from a company’s exogenous and endogenous risks. Their framework can help international corporations with plants or sites in different countries to prepare tailored environmental policies. The US EPA initiated the 33/50 program in 1991 to encourage firms to voluntarily reduce releases ands transfers of 17 toxic chemicals by 33% at the end of 1992 and by 50% at the end of 1995. In February 1991, the EPA invited 555 companies with substantial chemical releases to participate in the program. In July 1991, it extended the invitation to an additional 5000 companies. Participation in the program is purely voluntary, and EPA claims that it will not give preferential treatment of any kind to the participants in the form of relaxed regulatory oversight or enforcement of other EPA regulations. (Arora and Cason 1995) evaluate the factors leading to participation in the program. The results indicate that public information and awareness plays an important role. This results also indicate that large firms with substantial chemical releases are the most likely to participate and that participation is greatest in unconcentrated industries. Publicly available information on environmental performance of firms enables consumers to identify clean firms. This implies that consumers’ perception of environmental responsibility of a firm is mainly determined by the visibility of the firm. 39 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Finally, consumers are increasingly reacting to corporate mismanagement in foreign countries. For example, potential German Shell consumers reacted to the decision of the British Shell subsidiary to sink the Brent Spar oil platform in the Atlantic by boycotting the German Shell gas stations. This action contributed to a drop in sales by about 11 percent in June 1995. The consumer rating of the company in Germany crashed to the bottom (The Financial Times 1995). Because of broadcast media and environmental organizations, such as Green Peace, people in different countries are converging a similar values regarding environmental impact of MNCs. According to previous studies, MNCs that are more vulnerable due to their size and visibility have responded to this sensitivity by pushing their environmental practices to be proactive to mitigate the risk of environmental disasters. Therefore, I hypothesized that: H6: Corporate visibility is positively related to environmental proactivity. 3.2.2.2. Environmental Heterogeneity Environmental heterogeneity is defined as differences in the stringency of environmental regulations and environmental infrastructure between a country of operation and country of origin. The location of a foreign operation determines the level of regulatory environmental standards to comply with. Some MNCs operate in countries with less stringent 40 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental standards than their country of origin. Others go to countries with both less and more stringent environmental standards than their country of origin. Therefore, the distribution of the countries of origin will be different among MNCs. Epstein and Roy (1998) suggest the homogeneous or heterogeneous environmental regulations of host countries as a factor affecting corporate environmental strategies between uniformity and localization. They report that high heterogeneity of environmental regulations across countries of operation is associated with local standard. The pressures for adapting to national differences of environmental regulations result from different environmental standards in the countries of operation. The differences stem mostly from the differences in the level of environmental standards as well as in types of environmental regulations imposed. Even between countries of similar wealth, environmental regulations differ frequently. For example, in contrast to other industrial countries, Britain was very reluctant to curb sulfur dioxide from power stations. Germany, for instance, has more stringent laws than other industrialized nations regulating the take-back of packaging and other materials to reduce the amount of solid waste. Environmental goals, priorities, and regulations differ even more between countries of different levels of economic development (World Bank 1992). MNCs also face pressures from different consumer preferences for environmental quality across countries. Consumers in lower income countries are generally more concerned about the product price than about the environmental responsibility of the 41 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. company manufacturing the product or the environmental characteristics of products than customers in higher income countries. As a result of this, the potential for achieving differentiation advantages from a responsible environmental strategy differs across countries. These national differences suggest that MNCs might be best able to adapt to local regulations and conditions within each country where they operate by formulating and implementing their environmental strategies on a country-by-country basis. In addition, although uniformity is beneficial and important, it is sometimes necessary to adopt some degree of local adaptation when MNCs implement their environmental practices (Selig 1994). First, some Third countries lack sufficient infrastructure for accommodating the same kind of pollution control facility that an MNC may have in their country of origin. It would be pointless, for example, to build a pretreatment plant for a waste stream that is supposed to be conveyed through sewers to a central treatment plant if no such system is in place. It is also senseless to have a highly complex piece of pollution prevention technology where the expertise required maintaining it is not available. Cultural differences also require local adaptation It is hard enough to get US workers to wear respirators and other protective equipment when exposed to hazardous substances. If a company 42 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. operates joint ventures with a foreign government, differing priorities for economic development and environmental protection may have to be compromised. Instead of maintaining rigid uniformity, the company would be wise to review the product life cycle of what it produces overseas in order to define appropriate technology that is sensitive to the culture in which the company operates. Therefore, as the gap of environmental regulations between the country of foreign operation and the country of origin widens, MNCs are pushed to be local, since the investment needed to be uniform could be considered far greater than its benefits in operational and maintenance costs. If environmental regulations grow closer and closer between the two countries, MNCs would rather standardize their technology to reduce operations and maintenance costs and obtain economic gains, especially in mature industries. This could be the reason for firms to move from reactive/local strategy to reactive/uniform strategy dynamically. Therefore, I hypothesized that: H7: Environmental heterogeneity is negatively related to environmental uniformity. 43 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3.2.3. Research Model The overall research model of my hypotheses is presented in Figure 4. Figure 4 Research Model for Corporate Environmental Strategy in MNCs environmental Technolog’ Environmental Proactivity Manufacturing Flexibility, H4i H6 Environmental Uniformity Corporate Visibility Environmental Heterogeneity Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 4 RESEARCH DESIGN The hypotheses developed in Chapter 3 have been tested using multiple regression analysis of data. The data was collected through a mail questionnaire survey of multinational firms operating in Korea, China, South-East Asia, and India. In this section, I first describe the sample, discuss the rationale for selecting the sample, and explain the data collection process. Second, I describe the construction of the measures. Third, I discuss the analytical methodology. 4.1. Research Process The research process for this study had three phases: the interviews, the development of questionnaire instruments and distribution of pilot survey, and execution of the full-scale survey. The first phase was exploratory in nature. The process was to better understand the subjects under study. The second phase is related to developing instruments, including the pilot survey. In the third phase, the final survey was conducted. In this stage, relationships among variables were tested using the research model (Table 2). 4.1.1. First Phase: Exploration through Interviews During the first stage, initial data collection was performed using interviews. The main purpose of the phase was to a) Understand the phenomena under study b) Refine the conceptual model 45 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. c) Facilitate the development of the questionnaire instrument while refining and validating the measures. Table 2 Research Steps Research Phase Step Description 1. First Phase Interview 16 subjects, semi-structured interviews 2. Second Phase (Instrument Development) a) Initial development From existing measures, theories and interviews b) Refinement Panel of experts (in academy and industry) c) translation From existing Korean literature d) pilot test A feedback session with 5 subjects 3. Third Phase Survey 257 subjects In the first phase, sixteen managers at various positions in ten multinational companies, half of them are headquartered in Korea, were interviewed. Each interview lasted from one to one and half hours. The format of the interviews was semi-structured; prepared questions were asked and answered in an open-ended way (Appendix A). These interviews provided a basic understanding of the environmental strategies employed by managers at various responsible positions as well as factors that impact those environmental strategies. 4.1.2. Second Phase: Development of instruments and Initial Survey The instrument development process was guided by (Churchill 1979) framework: a) Initial development of the instruments b) Refinement through a panel of experts 46 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. c) Translation d) Pilot test a) Initial development of instruments Based on preliminary interviews, a pilot questionnaire was developed. Initial concepts were conceived, and as the interviews progressed, key concepts such as environmental proactivity and environmental uniformity were identified. While full- fledged concepts were not developed, initial measurements of these concepts were developed. b) Refinement through a panel of experts After the initial development of constructs, measurements were refined with the support of a panel of experts. The panel included five university professors with doctoral degrees in Operations Management, Environmental Strategy, or Environmental Economics. The members thoroughly reviewed the completed instrument for clarity and completeness, determined whether the items in the survey made sense, and helped develop more objective measures for measuring independent variables. c) Translation A problem in survey development for international research is that of translation. While measures were all written in English, the questionnaire for the Korean firms needed to be administered in Korean. In choosing the corresponding Korean terms, I used Korean terms found in existing Korean literature on environmental issues. After 47 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. translation, an initial review was conducted with a Korean doctoral student and a Korean university professor who were proficient in both good in English and Korean. This process helped refine some of the complex constructs that were difficult to translate. To minimize problems associated with translation, the measures of many constructs rest on relatively objective data, which are less susceptible to translation problems than subjective data, d) Pilot test A preliminary version of the questionnaire was pilot-tested with five managers in three Korean firms and two foreign firms. Each of the five respondents completed the questionnaire in the presence of the researcher and, while completing the questionnaire, asked questions regarding the wording of items. After completing the questionnaire, the five respondents were interviewed. They provided feedback about the general context of the questionnaire, commenting on clarity, the organization and their opinions about the research. 4.1.3. Third Phase: survey The process of designing the questionnaire, selecting a site and sample, and administering the survey were discussed in the development of instrument (Section 4.3) and data collection section (Section 4.2.2). 48 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.2. Sample and Data Collection 4.2.1. Sample The research population consisted of multinational companies operating in multiple countries. The company names were assembled from a directory published by the Ministry of Commerce, Industry and Energy in Korea (“Foreign Companies Invested in Korea”, 2000). From the directory, 728 foreign companies were chosen. They were headquartered in the United States, European countries and, Japan and operated manufacturing plants in Korea. Surveys were mailed to those companies. Similarly, from a database maintained by KOTRA (Korea Trade Promotion Corporation), called “Korean Companies Invested in Foreign Countries,” a list of Korean firms operating overseas was obtained. A survey was sent to each of 828 Korean companies with manufacturing plants in South-East Asia, India and China. The survey distribution procedure followed the three-step process suggested by (Dillman 1978). Each survey instrument along with a cover letter explaining the study and a return envelope was mailed directly to the CEO of the company. The cover letter was written on the letter head from the College of Business Administration at Seoul National University in Korea. The following week, instead of a postcard, a reminder fax was sent to those who had not responded. Finally, two weeks later, I followed up on the initial mailing of the survey with telephone calls and personal visits to increase the response rate. 49 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Finally, 133 non-Korean and 124 Korean companies returned the surveys for a total of 257 surveys (Table 3, Table 4). Table 3 Number of Surveys Mailed and Responded by Country of Origin Country of Origin US Europe Japan Subtotal (Non- Korea) Korea Total Mailed 235 253 240 728 828 1556 Responded 48 45 40 133 124 257 Response rate 36.1% 33.8% 30.1% 18.3% 15.0% 16.5% Table 4 Surveys Mailed by Country of Operation Country of Operation Mailed Percent China 593 38.1% India 13 0.8% Indonesia 30 1.9% Sri Lanka 32 2.1% Philippines 42 2.7% Thailand 20 1.3% Vietnam 98 6.3% Korea 728 46.8% Total 1556 100% The manufacturing sector was selected because environmental issues are more salient to the sector than others, like service. In addition, previous research in environmental studies has used the manufacturing industry to study environmental issues. The unit of analysis for empirical validation was the individual plant. Consistent with Klassen’s reasoning (Klassen 1995), this plant level, rather than the corporate or subsidiary level, was chosen for three reasons. First, many options for investments in 50 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. particular environmental technologies are identified at the plant level, either by operating personnel, external consultants or corporate specialists. Thus, environmental investment is implemented at the plant level. Second, the environmental investment varies among plants even within the same firm, indicating that a more aggregate unit of analysis, such as can be developed at the firm-level, is likely to obscure important differences. The third major impetus for selecting the plant level is that the formulation of environmental management strategy appears to vary among plants. It is reasonable to assume that the strategy of plants from the same firm may be correlated. To minimize potential bias, the number of plants from any individual company was limited. In addition, the average level of environmental practices is chosen as the level of analysis for the corporate environmental strategy in MNCs. Environmental practices ranged over the stages of product’s life cycle from R&D, product design, production process, product distribution and use, to product disposal (Table 5). 4.2.2. Data Collection Ideally, information should be gathered from multiple respondents at each site to minimize the potential for bias from a single informant (Miller and Roth 1994). Asking a single respondent to make complex judgments about organizational or competitive characteristics may increase this propensity to make their response consistent and increase random measurement error. Random measurement error can 51 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. conceivably result from some combination of the reporting process, knowledge deficiencies or inadequate measures. These potential sources of error limit the assessment of convergent and discriminant validity. However, the cost associated with gaining access to individuals from large numbers of large sized plants, needed for control purpose, is very high. Thus, only the single respondent was targeted in this dissertation, though measures were taken to increase the reliability of this sample. Earlier research suggests that careful selection of respondents can help minimize any bias (Phillips 1981). Following similar key informant research, my goal was to identify a person who would be highly knowledgeable about environmental practices (Cini, Moreland et al. 1993). In this dissertation, this person was a manager responsible for company-level environmental management of its foreign operations. The respondents were top and middle managers such as presidents, vice presidents, general managers, plant managers, and environmental managers. It is hoped that in this way, a single highly qualified respondent can and does provide valid and reliable data. Identifying such qualified respondents was a significant challenge for this type of research, and placed practical constraints on the multiple respondents from each company (Tatikonda and Montoya-Weiss 2001). Common method bias can pose problems for survey research that relies on self- reported data, especially if the data are provided by the same person at the same time 52 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (Campbell and Fiske 1959). One important concern in such cases is that common bias may artificially inflate observed relationships between variables. To estimate the extent of bias, Harman’s single-factor test (Harman 1967; Podsakoff and Organ 1986) was performed. The basic assumption of this technique is that if a substantial amount of common method variance existed in the data, either a single factor would emerge from a factor analysis of all questionnaire measurement items, or one general factor that accounted for most of the variance would result. The factor analysis revealed eight factors with eigenvalues greater than 1.0 that accounted for 78 percent of the total variance. The first factor only accounted for 26 percent of the variance. These results suggest that common method variance was not a serious problem in this study. Finally, as (Wagner and Crampton 1993) observed in their review of numerous studies, the problem of common methods variance is often overstated. 53 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.3. Operationalization and Measurement Model of Variables 4.3.1. Dependent Variables 4.3.1.1. Operationalization of Environmental Proactivity ‘Environmental proactivity’, in this dissertation, is defined as a firm’s level of stringency in environmental practices or standards applied to a foreign operation compared to environmental regulations of the country of foreign operation. The variable was constructed from survey items asking the respondents to rate the extent to which their environmental practices comply with environmental regulations of the host country. All of these items were rated on a scale from 1 to 7 from “the plant complies with the environmental laws and regulations” to “the plant applies much higher environmental standards than the environmental laws and regulations.” These items include questions regarding the managers’ perceptions of the local plant’s compliance with local environmental regulations on such practices as dealing with raw materials input, product design, manufacturing, information distribution, packaging, and recycling / final disposition. (SETAC 1993; Lefebvre, Lefebvre et al. 1995; Klassen and Angell 1998) These practices are identified from a literature search of environmental regulations and related environmental management practices, and include 25 environmental practices throughout the entire life cycle of a product (Table 5). 54 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.3.1.2. Operationalization of Environmental Uniformity ‘Environmental uniformity’ is defined as a firm’s level of similarity of environmental practices (or standards) between its foreign operation and its country of origin. The same practices identified to measure environmental proactivity were used to measure the degree of environmental uniformity between environmental practices applied at a plant in a country of foreign operations and those applied to other plants in the country of origin. To my knowledge, little previous literature regarding environmental uniformity measures existed. While I developed the measure of environmental uniformity, two alternatives existed. One was a seven point scale ranging from ‘very different’ to ‘very similar’. The other was also a seven point scale with 1 indicating ‘much less stringent’, 4 ‘same’, and 7 ‘much more stringent’. I chose the latter because it contains more information. That is, in addition to the information which the former scale provides, the latter also explains whether a firm applied upper or lower level of environmental practices or standards compared to the plants in the country of origin. 55 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 5 Environmental Practices throughout the life cycle of a product* Raw material input 01 Use o f recycled materials 02 Reduction in the amount o f raw materials 03 Selection o f environmentally friendly raw materials 04 Reduction in the amount o f energy in using the product 05 Extension o f the product’s useful life Product Design 06 Product design for multiple future uses 07 Product design for easy repair 08 Product design for disassembly 09 Product design for recycling Manufacturing 10 Choice o f suppliers whose operations pollute less 11 Minimization o f air emissions 12 Minimization o f water effluents 13 Minimization o f solid wastes (reduce, reuse and recycle) 14 Limitation on pollutants that enter soil at industrial sites 15 Reduction o f the amount o f energy required for the manufacturing and assembly o f the product Information 16 Building data available to the public about the environmental aspects o f product (e.g. the inventory and emissions o f hazardous substances used in manufacturing) 17 Informing customers o f the environmental aspects o f the product (e.g. any known environmental risks etc.) Packaging 18 Minimization o f product packaging 19 Easily recyclable packaging Disposition and Recycling 20 Establishment o f recycling procedures (e.g. packaging materials, scraps, wastes etc.) 21 Ensuring recuperation infrastructure (e.g. collection system etc.) 22 Assessment o f liability for the clean-up o f sites containing hazardous substances 23 Disposition o f hazardous wastes, including treatment and incineration 24 Prohibition o f mixing waste solvents and other wastes to enable reprocessing 25 Taking responsibility for the disposal o f products * The numbers (01 - 25) are the item numbers used in coding process. The above items were used as measures o f environmental proactivity (code: QIC) and environmental uniformity (code: Q2C). 56 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Since environmental uniformity, by definition, measures how different (or similar) environmental practices are between plants in foreign operations and those in the country of origin, it was necessary to recode the 7 point scale into the 4 point scale. Table 6 Recoding Scheme: 7 point scale to 4 point scale Original 7 point scale Recoding Recoded 4 point scale 1 Much less stringent -» 1 Very different 2 2 3 -> 3 4 Same or similar 4 Same or similar 5 -> • 3 6 -> 2 7 Much more stringent -» 1 Very different As shown in Table 5, 1 indicating ‘much less stringent’ and 7 indicating ‘much more stringent’ are classified into the same category, which is ‘very different’ in terms of environmental uniformity. 4 indicating ‘same or similar’ is classified into the category, which is ‘same or similar’. 4.3.1.3. Measurement Model of Environmental Proactivity and Environmental Uniformity Among the 25 items identified, 4 items in the product design stage were omitted because they are related to DfE (Design for Environment), which is not directly controlled by environmental regulations. Second-order CFAs (confirmatory factor analyses) were conducted to assess whether the remaining 21 items in five stages constitute the overall construct of environmental proactivity and environmental uniformity. According to (Marsh and Hocevar 1985), the higher order CFA allows 57 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. the researcher to specify the measurement model and to directly test its convergent and discriminant validities. Using the result of modification index, 7 items were deleted because they were multiple indicators for other stages (dimensions). The modification index presents the incremental chi-square improvement on a single change in a model. The model fit was tested and resulted in an acceptable data fit. Table 7 Confirmatory factor analysis for environmental proactivity and environmental uniformity model Fit indices Chi-square (df) p-value GFI AGFI RMR Suggested cut-off values >.05 V ii to © o o o if A <.05 Environmental proactivity 76.071 (61) .093 .946 .907 .109 Environmental uniformity 69.959 (65) .315 .951 .922 .026 Figure 5 Results of Second-order CFA: Environmental Proactivity E n v iro n m e n ta l P ro activ ity Y P =.7£ Ypy y p=-9 i R a w M a te ria ls In p u t M a n u fa c tu rin g P r o c e s s Info rm atio n D is c lo s u re R e c y c le / D isp o sitio n P a c k a g in g '.93 =.86 =.95 q1c16 q1c17 q1c19 q1c24 q1c25 q 1 c 0 3 q 1 c 1 1 q 1 c 1 2 q 1 c 1 3 q1 c1 4 q1c01 q 1 c 0 2 * t-values for all X and y are significant at p<0.001. 58 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Second-order CFAs showed that the 14 items constituted the overall construct of environmental proactivity (Figure 5) and environmental uniformity (Figure 6). Figure 6 Results of Second-order CFA: Environmental Uniformity Environm ental Uniformity R ecycle/ D isposition R aw M aterials Input M anufacturing P ro c e s s Inform ation D isclosure P ack a g in g =.84 ■ .9 4 11 =.90 =.93 =.92 =.80 q2c17r q2c19r q2c23r q2c24r q2c25r q2c02r q2c03r q2c12r q2c13r q2c14r q2c16r q2c01r * t-values for all X and y are significant at p<0.001. The inter-item correlations are also given in Table 8 (environmental proactivity) and Table 9 (environmental uniformity). The item-to-sample ratio became 1:13 (14 items and 184 cases). The remaining 14 items to measure environmental proactivity and environmental uniformity are listed in Table 10. 59 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 8 Inter-item correlations of environmental proactivity items N Mean s.d. Q1C01 Q1C02 Q1C03 Q1B11 Q1B12 Q1B13 Q1B14 Q1C01 184 3.38 1.86 1.00 Q1C02 184 3.63 1.86 0.77 1.00 Q1C03 184 3.59 1.92 0.66 0.66 1.00 Q1B11 184 4.66 1.55 0.35 0.35 0.38 1.00 Q1B12 184 3.12 1.71 0.05 0.07 0.15 0.48 1.00 Q1B13 184 4.69 1.89 0.25 0.17 0.28 0.47 0.46 1.00 Q1B14 184 4.64 1.82 0.26 0.25 0.33 0.57 0.50 0.62 1.00 Q1C16 184 3.86 2.08 0.53 0.50 0.62 0.38 0.23 0.34 0.38 Q1C17 184 4.00 2.02 0.57 0.57 0.55 0.39 0.24 0.28 0.33 Q1C18 184 3.59 1.80 0.60 0.59 0.54 0.29 0.18 0.22 0.29 Q1C19 184 3.56 1.71 0.58 0.56 0.60 0.31 0.15 0.21 0.25 Q1C23 184 3.73 1.98 0.57 0.54 0.53 0.33 0.20 0.34 0.35 Q1C24 184 3.70 1.99 0.58 0.54 0.57 0.33 0.16 0.34 0.32 Q1C25 184 3.65 2.01 0.55 0.51 0.57 0.37 0.23 0.37 0.37 Q1C16 Q1C17 Q1C18 Q1C19 Q1C23 Q1C24 Q1C01 Q1C02 Q1C03 Q1B11 Q1B12 Q1B13 Q1B14 Q1C16 1.00 Q1C17 0.84 1.00 Q1C18 0.67 0.76 1.00 Q1C19 0.67 0.74 0.81 1.00 Q1C23 0.72 0.75 0.74 0.65 1.00 Q1C24 0.71 0.73 0.70 0.71 0.86 1.00 Q1C25 0.71 0.77 0.72 0.69 0.88 0.90 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 9 Inter-item correlations of environmental uniformity items N M ean s.d. Q 2C 01N Q 2C 02N Q 2C 03N Q 2C 11N Q 2C 12N Q 2C 13N Q 2C 14N Q 2C 01N 184 3.13 1.00 1.00 Q 2C02N 184 3.27 0.96 0.63 1.00 Q 2C03N 184 3.14 1.05 0.73 0.72 1.00 Q 2C11N 184 3.04 1.05 0.45 0.51 0.52 1.00 Q 2C12N 184 3.00 1.08 0.44 0.49 0.53 0.87 1.00 Q 2C 13N 184 2.98 1.07 0.49 0.58 0.61 0.77 0.80 1.00 Q 2C 14N 184 3.04 1.04 0.49 0.48 0.59 0.77 0.74 0.80 1.00 Q 2C 16N 184 3.08 1.00 0.49 0.56 0.57 0.61 0.65 0.75 0.67 Q 2C17N 184 3.04 1.00 0.46 0.51 0.50 0.54 0.57 0.62 0.66 Q 2C 18N 184 3.11 1.01 0.63 0.59 0.62 0.52 0.55 0.61 0.63 Q 2C 19N 184 3.17 0.94 0.65 0.61 0.68 0.52 0.52 0.63 0.63 Q 2C 23N 184 3.03 1.09 0.47 0.53 0.55 0.62 0.63 0.69 0.66 Q 2C 24N 184 2.96 1.08 0.45 0.52 0.58 0.63 0.62 0.69 0.65 Q 2C 25N 184 3.02 1.08 0.42 0.53 0.58 0.65 0.66 0.72 0.68 Q 2C 16N Q 2C 17N Q 2C 18N Q 2C 19N Q 2C 23N Q 2C 24N Q 2C 01N Q 2C 02N Q 2C 03N Q 2C 11N Q 2C 12N Q 2C 13N Q 2C 14N Q 2C 16N 1.00 Q 2C 17N 0.78 1.00 Q 2C 18N 0.60 0.70 1.00 Q 2C 19N 0.63 0.63 0.82 1.00 Q 2C 23N 0.68 0.60 0.62 0.64 1.00 Q 2C 24N 0.69 0.62 0.59 0.64 0.88 1.00 Q 2C 25N 0.70 0.63 0.61 0.65 0.79 0.84 61 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 10 Items Used in Measuring Environmental Proactivity and Environmental Uniformity Raw material input * U se o f recycled materials ■ Reduction in the amount o f raw materials ■ Selection o f environmentally friendly raw materials Manufacturing ■ Minimization o f air emissions ■ Minimization o f water effluents ■ Minimization o f solid wastes (reduce, reuse and recycle) * Limitation on pollutants that enter soil at industrial sites Information ■ Building data available to the public about the environmental aspects o f product (e.g. the inventory and emissions o f hazardous substances used in manufacturing) ■ Informing customers o f the environmental aspects o f the product (e.g. any known environmental risks etc.) Packaging ■ Minimization o f product packaging ■ Easily recyclable packaging Disposition and Recycling ■ Disposition o f hazardous wastes, including treatment and incineration ■ Prohibition o f mixing waste solvents and other wastes to enable reprocessing ■ Taking responsibility for the disposal o f products Assuming that each item from the survey instrument is dependent on only one factor as modeled in the second order CFA, the reliability of individual items can be computed as follows (Bagozzi 1981), /if * var A _ Pi = -7T2----- TTuT (Equation 1) Ai * var A + 4L where p t is the reliability of the item, i, Ai is the factor loading relating item i to its respective environmental proactivity factor (i.e., raw material input, manufacturing process, information disclosure, packaging, or disposition/recycling), and V FI - is the 62 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. error varian ce o f item i. I f A. is standardized (i.e ., A* is the correlation o f item i on factor A), then Equation 1 simplifies to A = W (Equation 2) Similarly, the composite reliability of m items for factor A can be calculated as (Bagozzi 1981), f m \ 2 P c = S ' . v i= i y var A c / \ 2 ( -m l _ w EA - var^ + E ^ , V i=l ) (Equation 3) i= i A similar simplification can be made by standardizing the loadings, to give P c ( m y V i=i f m \ 1 (Equation 4) + E d - r t ) J) V i=i y 1=1 All individual item reliabilities for measures of environmental proactivity were statistically significant (p<=0.01) and the composite reliabilities were sufficiently large, ranging from 0.876 to 0.961 (Table 11) All individual item reliabilities for measures of environmental uniformity were statistically significant (p<=0.01) and the composite reliabilities were sufficiently large, ranging from 0.876 to 0.926 (Table 12) 63 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 11 Individual Item and Composite Reliabilities for Measures of Environmental Proactivity (n=184) Scale items Standardized factor loading (correlation) Individual reliability Composite reliability raw material input 0.876 qlcOl 0.88 0.774 qlc02 0.86 0.740 qlc03 0.77 0.593 manufacturing process 0.961 qlcll 0.91 0.828 qlcl2 0.91 0.828 qlcl 3 0.96 0.922 qlcl4 0.93 0.865 information disclosure 0.917 qlcl6 0.89 0.792 qlcl7 0.95 0.903 packaging 0.901 qlcl8 0.93 0.865 qlcl9 0.88 0.774 disposition/recycling 0.951 qlc23 0.96 0.922 qlc24 0.91 0.828 qlc25 0.92 0.846 Thus the reliability of the five individual scales was high for both measures of environmental proactivity and environmental uniformity. Finally, composite scores of environmental proactivity and environmental uniformity were obtained by averaging the scores for 14 items (Spreitzer 1995). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 12 Individual Item and Composite Reliabilities for Measures of Environmental Uniformity (n=184) Scale items Standardized factor loading (correlation) Individual reliability Composite reliability raw material input 0.876 q2c01n 0.81 0.656 q2c02n 0.8 0.640 q2c03n 0.9 0.810 manufacturing process 0.926 q2clln 0.83 0.689 q2cl2n 0.85 0.723 q2cl3n 0.93 0.865 q2cl4n 0.87 0.757 information disclosure 0.879 q2cl6n 0.93 0.865 q2cl7n 0.84 0.706 packaging 0.895 q2cl8n 0.88 0.774 q2cl9n 0.92 0.846 disposition/recycling 0.948 q2c23n 0.94 0.884 q2c24n 0.92 0.846 q2c25n 0.92 0.846 In confirming the validity of the environmental proactivity and environmental uniformity measure, guidelines suggested by (Anderson and Gerbing 1988) were followed. All individual parameters were significantly different from zero, as indicated by t-values (Figure 5 and Figure 6). Significant y coefficients of the environmental proactivity and environmental uniformity model indicated convergent validity of the five dimensions of the two dependent variables. Next a formal test of discriminant validity was performed. Discriminant validity was assessed by 65 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. sequentially testing the effect of constraining each of the inter-factor correlation parameters of the final measurement model to one (Bagozzi 1981; Sethi and King 1994). The constrained model is termed a “nested” model. The nested model was estimated to determine whether the “fit” of the nested model was significantly worse than that of the unconstrained measurement model for the observed data covariance matrix. The difference between % 2 statistics of the two models can be tested for significance to determine if one model “fit” the observed data covariance matrix significantly 2 • • better. This difference also has a % distribution, with degree of freedom equal to the difference in the degree of freedom between the two models (Hayduk 1987). The x2 statistic was statistically significant in each case, indicating that five related, but not identical, factors were being measured. Thus, analysis of both convergent and discriminant validity indicate that five related, but distinct factors were being measured with multi-item scales (Table 13). In addition, a formal test of discriminant validity for environmental uniformity measure was performed in the same way as the environmental proactivity measure. The x2 statistic difference between the constrained model and the unconstrained model also showed that discriminant validity was achieved. 66 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 13 Assessment of Discriminant Validity for Measures of Environmental Proactivity Description Correlation Covariance (p-value) y2 statistic Constrained Model (df) Unconstrained Model (df) Difference (p-value) Raw material input with Manufacturing .712 2.248 41.943 15.587 26.356 process (<0.01) (11) (10) (<0.001) Information .690 1.999 19.211 3.322 15.889 disclosure (<0.01) (4) (3) (<0.001) Packaging .746 2.008 21.981 0.782 21.009 (<0.01) (4) (3) (<0.001) Disposition / .694 2.101 34.892 13.717 21.175 recycling (<0.01) (8) (7) (<0.001) Manufacturing process with Information .822 2.96 68.577 11.346 57.231 disclosure (<0.01) (6) (5) (<0.001) Packaging .805 2.590 53.661 6.705 46.956 (<0.01) (7) (6) (<0.001) Disposition / .861 3.059 85.324 10.497 74.827) recycling (<0.01) (10) (9) (<0.001) Information disc osure with Packaging .857 2.552 43.468 0.192 43.276 (<0.01) (2) (1) (<0.001) Disposition / .851 2.976 64.514 0.145 64.369 recycling (<0.01) (3) (2) (<0.001) Packaging with Disposition / .844 2.617 53.159 0.080 53.079 recycling (<0.01) (2) (1) (<0.001) In sum, a total of 14 items were loaded into the five dimensions of the environmental proactivity and environmental uniformity measure, demonstrating strong support for convergent and discriminant validity of the measures. The values of the final items were averaged to generate a measurement scale for raw materials input, manufacturing processes, information disclosure, packaging, and disposition / recycling. Finally, an overall measure of environmental proactivity and environmental uniformity was computed from a simple average of the items. 67 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.3.1.4. Relationship between Environmental Proactivity and Environmental Uniformity The factor analysis showed that all loadings are over 0.6, having eigenvalues greater than 9 for the two factors (Table 14). Table 14 Factor Analysis Results of Dependent Variables (Principal Components Extractions and Varimax Rotation) Item Code Factor Environmental Proactivity Environmental Uniformity Q1C14 0.89 0.00 Q1C23 0.89 -0.02 Q1C11 0.88 0.06 Q1C13 0.88 0.06 Q1C25 0.88 -0.03 Q1C24 0.87 -0.02 Q1C12 0.87 0.04 Q1C17 0.87 0.02 Q1C18 0.86 0.05 Q1C16 0.84 -0.01 Q1C19 0.81 0.05 Q1C01 0.74 -0.06 Q1C03 0.71 -0.02 Q1C02 0.71 -0.07 Q2C13N 0.05 0.87 Q2C25N -0.05 0.84 Q2C14N 0.08 0.84 Q2C24N -0.05 0.84 Q2C16N -0.02 0.84 Q2C23N -0.03 0.84 Q2C19N -0.02 0.82 Q2C12N -0.01 0.81 Q2C18N -0.01 0.80 Q2C11N 0.01 0.80 Q2C17N -0.06 0.78 Q2C03N 0.06 0.77 Q2C02N 0.06 0.72 Q2C01N 0.02 0.68 The first fourteen items have a clear loading on the first factor (named “environmental proactivity”) with an average loading of .84, and the next fourteen Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. items on the second factor (named “environmental uniformity”), an average loading of .80. All other cross-loadings are less than 0.1, showing clear discriminant validity for the two constructs. These two factors explained 67.7 % of total variance. The scatter plot shows that the samples are dispersed without any correlation between the two dimensions. The correlation between environmental proactivity and environmental uniformity is 0.06 (p = 0.932). Null hypothesis that the correlation between environmental proactivity and environmental uniformity is zero cannot be rejected. It indicates that the two dimensions are statistically independent and orthogonal. Therefore, in Chapter 5 Data Analysis and Results, I separately analyzed the effects of driving factors on environmental proactivity and environmental uniformity. Figure 7 Scatter Plot of Environmental Proactivity and Uniformity 4 .0 - o □ a eg o d d G P c rc o m cd as a a o o □ □ o an □ □ | 2.5 a a LU 1 .5 - a a a 2 3 5 6 Environm ental Proactivity 69 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.3.2. Independent Variables 4.3.2.1. Environmental Technology Investments In measuring the environmental technology investment, a classification of environmental technologies suggested by (Klassen 1995) was used. As the items are derived from existing scales developed and validated in studies like (Klassen and Whybark 1999a) and (Klassen and Whybark 1999b), it has construct validity. Reliability is reasonably confirmed as the Cronbach’s alpha reaches 0.9082. Items assessing the degree of environmental technology investments over the last five years were asked of each respondent. Then the items were averaged to assess the level of environmental technology investments for each company. All of these items were rated on a scale from 1 “not invested at all in the area”, through 4 “invested at a moderate level in the area” to 7 “invested to a great extent in the area” Table 15 Items Used for Environmental Technology Investments Measure ■ Reformulating of a product to reduce the use of hazardous materials ■ Greater use of recycled materials in products ■ Energy conservation ■ Redesigning of manufacturing equipment to reduce waste " Covering of open process lines or tanks ■ Recycling of former wastes 70 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 43 .2.2. Manufacturing Flexibility Flexibility is recognized as a multidimensional construct. However, researchers do not appear to have reached the level of agreement on its dimensions (White 1996). (Sethi and Sethi 1990) identified eleven different dimensions of flexibility used by other researchers. But most have studied far fewer. For example, Cox (1989) discusses the two dimensions of product (also called product mix) flexibility and volume flexibility. Volume flexibility refers to the capacity to quickly expand the quantities of a given product mix produced, while mix flexibility addresses the ability to quickly change the types of products produced in the plant. The latter includes both changes to existing products and the addition of new ones. (Hill 1994) lists demand increases (volume flexibility) and product range (product flexibility) as the only two flexibility related order winners and qualifiers that are specific to manufacturing. The great majority of existing research that measures flexibility as a manufacturing capability has examined either one or both of these dimensions (White 1996). The manufacturing flexibility has been assessed using self-reported perceptual scales (Swamidass and Newell 1987; Vickery, Droge et al. 1993; Whybark and Vastag 1993; Miller and Roth 1994). To date, the impact of manufacturing flexibility on environmental management has not been explicitly considered in the literature except (Klassen and Angell 1998). Based on the four types of flexibility, they propose areas where manufacturing flexibility supports and facilitates a more proactive environmental management posture. 71 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. This dissertation derived the items in measuring the manufacturing flexibility from existing scales developed and validated in a study of (Narasimhan and Das 1999). The reliability is reasonably confirmed as the Cronbach’s alpha reaches 0.8865. Questions addressing the degree of manufacturing flexibility compared with competitors’ levels were asked of each respondent. Then the items were averaged to assess the level of manufacturing flexibility for each company. All of these items were rated on a scale from 1 “far worse than the competitors”, through 4 “about the same” to 7 “far better than the competitors”. Table 16 Items Used for Manufacturing Flexibility Measure ■ raw matrial variation ■ range of parameters (size, difficulty, etc.) ■ number of markets served ■ change product mix rapidly ■ vary production volume ■ adapt to changes in demand ■ change delivery schedule 4.3.2.3. Corporate Visibility (Bowen 2000) derived a typology of environmental visibility from the qualitative interview data, operationalizing four types of visibility. In this dissertation, to measure corporate visibility, items of organizational visibility at corporate level from existing scales developed and validated in a study of Bowen (2000) were used. The reliability is reasonably confirmed as the Cronbach’s alpha reaches 0.7731. 72 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Items assessing the degree of corporate visibility of the parent company were asked of each respondent. Then the items were averaged to assess the level of corporate visibility of the parent company for each plant in a foreign operation. All of these items were rated on a scale from 1 “strongly disagree” to 7 “strongly agree”. Table 17 Items Used for Corporate Visibility Measure ■ Our parent company’s name is widely recognized outside our customers and suppliers. ■ The activities of our parent company are closely monitored by the media. ■ Our parent company place a greater marketing emphasis on environmental issues than our competitors do. 4.3.2.4. Environmental Heterogeneity Because of previous studies’ lack of an empirical instrument of environmental heterogeneity (Selig 1994; Epstein and Roy 1998), it was essential to develop an instrument to measure the environmental heterogeneity for each company. The items are adapted from the reasons for some degree of variability when companies implement their environmental policies (Selig 1994; Epstein and Roy 1998). The reliability is reasonably confirmed as the Cronbach’s alpha reaches 0.7405. Questions addressing the degree of environmental heterogeneity between the country of operation and the country of origin were asked of each respondent. Then the items were averaged to assess the level of environmental heterogeneity for each plant of 73 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. foreign operation. All of these items were rated on a scale from 1 “strongly disagree” to 7 “strongly agree”. Table 18 Items Used for Environmental Heterogeneity Measure ■ There is a lack of infrastructure for accommodating the same pollution control equipment in the foreign plant ■ The expertise to maintain the complex pollution control equipment is not available in the foreign plant ■ Cultural difference of workers between the country of foreign operation and the country of origin headquartered by your parent company ■ What is produced by the plant in the country of foreign operation is different from those produced by the plant headquartered in the country of origin with regard to production technologies. Table 19 Reliabilities for Measures of Independent Variables Variables Number of scale items Mean s.d. 1 2 3 4 1. Environmental Technology 6 4.11 1.35 (0.9082) 2. Manufacturing Flexibility 7 4.98 1.02 0.34** (0.8865) 3. Corporate Visibility 3 4.40 1.45 0.36" 0.34*’ (0.7731) 4. Environmental Heterogeneity 4 3.49 1.40 -0.14 -0.23*' -0.16* (0.7405) N = 184, tests of significance are two-tailed, *p < 0.05, **p < 0.01 Reliabilities (alpha coefficients) are on diagonal. Reliability of these constructs was summarized based on Cronbach’s alpha (Table 19). The reliability measures for the independent variables demonstrated reasonable 74 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. reliability of measures as measures greater than 0.6 are thought to reach the usual acceptable range (Nunnally 1978; Van de Ven and Ferry 1980). Finally, a factor analysis was conducted to test the discriminant validity of the independent variables developed so far (Table 20). The factor analysis based on orthogonal varimax transformation has all loading over 0.6 except two on these factors, having eigenvalues greater than 1 for all four factors. The first seven items have a clear loading on the first factor with an average loading of .75, and the next six items on the second factor with an average loading of .81. Four items are on the third factor with the average loading of .79. The final three items loaded on the last factor, an average was .81. All other cross-loadings are less than 0.4, showing clear discriminant validity for the constructs. These four factors explained 64.99 % of total variance. 75 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 20 Factor Analysis Results of Independent Variables (Principal Components Extractions and Varimax Rotation) Manufacturing l'lcxibililv Environmental Technology Environmental Heterogeneity Corporate Visibility Vary production volume 0.877 0.065 -0.107 0.028 change delivery schedule 0.857 0.155 -0.129 -0.030 adapt to changes in demand 0.849 0.132 -0.111 0.001 change product mix rapidly 0.740 0.060 -0.077 0.158 range of parameters (size, difficulty, etc.) 0.716 0.080 -0.068 0.194 Raw matrial variation 0.624 0.230 -0.006 0.135 number of markets served 0.577 0.161 -0.050 0.274 Redesigning manufacturing equipment 0.093 0.889 -0.011 0.131 Recycling of former wastes 0.141 0.820 -0.094 0.064 Use of recycled materials 0.008 0.800 0.021 0.025 Reformulating product 0.157 0.795 -0.094 0.226 Covering open process lines or tanks 0.198 0.788 ■ -0.085 0.094 Energy conservation 0.235 0.741 0.033 0.146 Expertise availability -0.039 -0.152 0.838 -0.040 Lack of Infrastructure -0.126 -0.090 0.801 -0.037 Cultural difference of workers -0.011 0.018 0.728 -0.011 Difference in production technologies -0.181 0.047 0.585 -0.087 Recognition of parent company’s name 0.172 0.046 -0.056 0.813 Media monitor 0.104 0.276 -0.103 0.812 Marketing emphasis on environmental issues 0.176 0.182 -0.031 0.797 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.3.3. Control Variables Together with the main independent variables, three control variables expected to explain the degree of environmental proactivity and environmental uniformity were used. The correlations among independent variables and control variables are shown in Table 25. 4.3.3.1. Country of Origin The sample is divided into four groups of countries based on the firms’ country of origin: the United States, European countries, Japan, and Korea. Table 21 shows the composition of the sample by country of origin. Among the 184 total respondent firms, 19.02 percent of firms are based in Europe. 21.74 percent of firms are based in the United States. 16.3 percent of firms are based in Japan. And 42.93 percent of firms are based in Korea. 4.3.3.2. Industry The sample is further divided into three groups of industry based on pollution intensity (Mani and Wheeler 1999): high pollution-intensive industries, medium pollution-intensive industries, low pollution-intensive industries. (Table 23) 77 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 21 Number of Usable Responses by Country of Origin Country of Origin Frequency Percent Europe 35 19.02% Belgium Denmark France Germany Ireland Italy Luxembourg Netherlands Sweden Swiss UK 1 0.54% 1 0.54% 7 3.80% 3 1.63% 1 0.54% 2 1.09% 1 0.54% 6 3.26% 2 1.09% 4 2.17% 7 3.80% USA 40 21.74% Japan 30 16.30% Korea 79 42.93% Total 184 100.00% Table 22 Number of Usable Responses by Country of Operation Country of Operation Frequency Percent China 64 34.8% India 3 1 .6 % Indonesia 4 2 .2 % Korea 105 57.1% Philippines 1 .5% Sri Lanka 1 .5% Thailand 2 1 .1% Vietnam 4 2 .2 % Total 184 100.0% 4.3.3.3. Plant Size The size of the company is a continuous variable representing the number of employees in the plant at which an MNC is operating in a foreign country. Since studies in environmental management literature have indicated that the firm size is a factor explaining different environmental responsiveness of companies, this variable Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. needs to be controlled in the analysis (Klassen 1995; Christmann 1997; Bowen 2000). The distribution of the number of employees in the surveys used in this dissertation is shown in Table 24. Also the plant size is transformed by using the natural logarithm in the analysis to avoid the violation of normality assumption. Table 23 Number of Responses by Industry Industry Frequency Percent High Pollution Intensive Industries 62 33.70% Pulp, paper products and publications Chemical products Non-metallic mineral products Coke and petroleum products Rubber and plastic products 8 4.35% 36 19.57% 3 1.63% 3 1.63% 12 6.52% Medium Pollution Intensive Industries 54 29.35% Processed foods and tobacco Leather products and footwear Fabricated metal products Furniture & other manufacturing products Basic metal products 9 4.89% 14 7.61% 24 13.04% 2 1.09% 5 2.72% Low Pollution Intensive Industries 68 36.96% Electronic machinery and apparatus Precision instruments Textile products and apparel Wood and wood products General machinery and equipment Radio, TV & communication equipment Transportation equipment 20 10.87% 5 2.72% 16 8.70% 2 1.09% 7 3.80% 16 8.70% 2 1.09% Total 184 100.00% Table 24 Number of Responses by Plant Size (Number of Employees) Number of employees Frequency Percent <= 50 34 18.48% 51 - 100 28 15.22% 1 0 1 - 2 0 0 36 19.57% 210-500 41 22.28% 501 - 1000 18 9.78% >= 10 0 1 27 14.67% Total 184 100.00% 79 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.4. Analytical Methodology In order to test the hypotheses developed in this dissertation, an ordinary least square hierarchical multiple regression analysis was used. This methodology allowed for the testing of direct effects as well as more complex relationship such as moderation effect. Since the conceptual model in this dissertation dealt with two dependent variables such as environmental proactivity and environmental uniformity, simultaneous equation models based on structural equations were considered. These models, however, were abandoned for two reasons. First, testing of the moderating effect of the variable of environmental technology is an important part of the hypotheses testing in environmental uniformity model. Techniques to test moderating effects using structural equation models are still in the development process (Chin, Marcolin et al. 1996) and typically require a large sample size. Second, regression models of environmental proactivity and environmental uniformity can be separately and independently tested because environmental proactivity and environmental uniformity are not correlated with each other. Further, the relationship between the two is not hypothesized in the conceptual model of this dissertation. 80 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.4.1. Testing of the direct effects of driving factors on environmental proactivity and environmental uniformity In testing the direct effects on environmental proactivity (or uniformity) of driving factors (environmental technology, manufacturing flexibility, and corporate visibility, environmental heterogeneity), the following two regressions equations are used. Model 1: Environmental proactivity (or uniformity) = Control Variables Model 2: Environmental proactivity (or uniformity) = Control Variables + Driving Factors While it is sometimes sufficient to see the coefficients of driving factors in Model 2 to test the direct effects of driving factors on environmental proactivity (or uniformity), hierarchical multiple regression analysis (HRA) was used to confirm that driving factors further explains environmental proactivity (or uniformity) even after control variables explained the variance. This method is especially effective when high correlations are expected between main variables and control variables. The direct effects of driving factors on Environmental Strategies are demonstrated when an increase of F-value from Model 1 to Model 2 is statistically significant and the coefficients of driving factors in Model 2 are significant. 81 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 4.4.2. Testing of the moderating effect of environmental technology on the relationship between manufacturing flexibility and environmental uniformity In order to investigate the moderating effect of environmental technology on the relationship between manufacturing flexibility and environmental uniformity, both HRA and split sample analysis were used. In certain statistical methods, it is very important to understand the characteristics, the underlying assumptions, advantages, disadvantages and supplements of the methods. HRA has generally been recognized as the most appropriate statistical test for examining moderators that produce differences in the form of the relationship between a predictor and a criterion variable (Cohen and Cohen 1983). However, HRA is often criticized for providing downward biased estimates under the condition of (a) measurement errors (Jaccard, Wan et al. 1990) and (b) relative different size of groups (Stone-Romero, Alliger et al. 1994). (Chin, Marcolin et al. 1996) provided a convincing example in which the effect of moderating effect is significantly underestimated under measurement error conditions: When the reliability of both independent and moderating variables is 0.7 and their correlation is 0 , the reliability of the product term (i.e. independent * moderating variables) becomes 0.49. In this situation, the estimate of the proportion of the dependent variable explained by the interaction effect will be half of the true effect. 82 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (Stone-Romero, Alliger et al. 1994) also warned of possible erroneous conclusions if one accepts the null hypotheses in the face of a different proportion of cases in each group. In their Monte Carlo simulations, they demonstrated that the proportion of cases in two groups contribute extensively to statistical power. When the sample size was 90, for instance, the statistical power of detecting a 0.6 difference between two groups reached 0.925 when there were equal size samples distributed between two groups. But the statistical power became 0.341 when the proportion became 0.1 vs. 0.9. Along with problems of downward biases due to measurement errors and the unequal group proportion distributions indicated earlier, multicollinearity problems related to moderated multiple regression should be carefully addressed, too. The problems of multicollinearity in product terms in regression analysis have been issues for a long time (Blalock 1979). Although it did change the properties of ordinary least square model (Cronbach 1989), high correlation between predictors caused computational errors, given that the algorithms are typically used for regression (Jaccard, Wan et al. 1990). The results of HRA should be cautiously interpreted and supplemented by other methods. 83 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In HRA, entering the individual predictor variables followed by the product terms for their interaction performs a test of moderation. Three models have been suggested by (Cohen and Cohen 1983) to test the moderating effects. Model 1: DV = IV + CV, Model 2: DV = IV + MV + CV and Model 3: DV = IV + MV + (IV*MV) + CV where DV = Dependent Variables, IV = Independent Variables, CV = Control Variables, MV = Moderating Variables. 4.4.3. Split sample analysis According to (Aiken and West 1991), moderation effect has been traditionally tested with median splits of interested variables. This practice allows data to be subjected to the familiar procedures of the 2 X 2 factorial ANOVA by breaking continuous variables into categories (cut points being median point). Though (Aiken and West 1991) cautioned of some major shortcomings of this approach, they also pointed out the wide usage of this technique in major psychological journals. I also found a number of articles utilizing this approach (Arnold 1982; Eisenhardt and Tabrizi 1995; Rajagopalan and Datta 1996; Sharma and Vrendenburg 1998). The advantage of using this analysis for this study is that it clearly shows the four different types of environmental strategies and the driving factors for each one of them. 84 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In order to analyze the differences among the four types of corporate environmental strategy in MNCs proposed in this dissertation, I divided the pooled sample into two subgroups based on a median split on the composite score of environmental proactivity: reactive strategy and proactive strategy. Also, I divided the pooled sample into two subgroups based on a median split on the composite score of environmental uniformity: uniform strategy and local strategy. Then I estimated the same OLS regression model with direct effects for each subgroup (Rajagopalan and Datta 1996). This OLS regression model for each subgroup provided the differences between two types of corporate environmental strategy within each subgroup in terms of the independent variables used in this dissertation. 85 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 5 DATA ANALYSIS AND RESULTS 5.1. Hierarchical Regression Analysis 5.1.1. Regression Diagnostics Since regression analysis requires certain conditions, regression diagnostics were conducted first. 5.1.1.1. Normality Normality is the assumption that each variable is normally distributed. Each variable was carefully checked with univariate procedures to verify the normality. Among variables, plant size seemed to be significantly skewed, and it is log transformed. Finally, the Q-Q and Kolmogorov-Smimov tests showed that normality was assured for all variables. 5.1.1.2. Heteroscedasticity Heteroscedasticity refers to the differences in the variance of the regression residuals related to one of the independent variables. To detect heteroscedasticity, I inspected plots of the residuals against all independent variables. Visual inspection of the plots of residuals against the independent variables revealed no heteroscedasticity for all independent variables. 86 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. Table 25 Means, Standard Deviations, and Pearson Product-Moment Correlations among All Variables (n=184) Variable Mean s.d. 1 2 3 4 5 6 7 8 9 10 11 12 13 1 . Environmental 3.75 1.63 1.00 Proactivity 2. Environmental 3.07 0.83 0.01 1.00 Uniformity 3. Environmental 0.00 1.35 0.04 1.00 0.44 Technology 4. Manufacturing 0.00 1.36 0.34** 0.01 0.34** 1.00 Flexibility 5. Corporate 0.00 1.45 0.35“ 0.12 0.36“ 0.34“ 1.00 Visibility 6. Environmental 0.00 1.40 -0.20“ -0.12 -0.14 -0.23” -0.16* 1.00 Heterogeneity 7. Environmental Technology (squared 1.82 2.50 -0.05 -0.21“ -0.16* 0.08 -0.11 -0.09 1.00 term) 8. Technology*Flexibility 0.47 1.51 0.02 -0.25** 0.11 0.06 -0.05 -0.02 0.29** 1.00 9. Japan 0.16 0.37 -0.03 -0.01 -0.04 -0.06 -0.02 -0.11 -0.03 -0.13 1.00 10. US 0.22 0.41 0.16* 0.11 0.12 0.17* 0.15* -0.27“ -0.02 -0.03 -0.23“ 1.00 11. Europe 0.19 0.39 0.13 0.00 0.08 0.14 0.06 -0.12 0.04 0.08 -0.21“ -0.26" 1.00 12. High Pollution Intensive Industry 0.34 0.47 0.19" 0.04 0.27“ 0.25" 0.18* -0.16* 0.06 0.04 -0.03 0.29“ 0.21“ 1.00 13. Medium Pollution Intensive Industry 0.29 0.46 -0.17* -0.10 -0.13 -0.12 -0.15* 0.03 -0.01 -0.04 0.04 -0.08 -0.13 -0.46** 1.00 14. Plant Size 5.29 1.37 0.09 -0.04 0.22** 0.04 0.17* -0.01 -0.09 0.01 -0.12 -0.12 -0.14 -0.18* 0.04 a. Logarithm o f the number o f employees in plant o f foreign operation * significant at p<=0.05 (2-tailed) ** significant at p<=0.01 (2-tailed) 5.1.1.3. Multicollinearity The presence of multicollinearity in the data can lead to large standard errors of the estimated regression coefficients resulting in insignificant t-ratios. To evaluate multicollinearity, pair-wise correlation data were inspected first. The correlations among the independent variables shown in Table 25 were reviewed for multicollinearity. These correlations are generally low (below 0.3), with three exceptions. The environmental technology investment was correlated with the corporate visibility of parent company, indicating that more visible firms invested more in environmental technology in there foreign operations. The environmental technology investment was correlated with manufacturing flexibility, indicating that firms with high manufacturing flexibility also invest in pollution prevention technology. Manufacturing flexibility was also correlated with the corporate visibility of parent company, meaning that more visible companies have more recognition and reputation through their manufacturing flexibility such as adaptability to change in demand, change in delivery schedule, change in product mix, and so on. Following this step, the extent of multicollinearity among the independent variables was assessed. Indices such as the variance inflation factors (VIF) and condition indices recommended by (Belsley, Kuh et al. 1980) were used. VIF measure the inflation in the variances of the parameter estimates due to the collinearities that exist 88 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. among independent variables. A high VIF indicates that the multiple correlation coefficient of the explanatory variable Xj regressed on the remaining explanatory variables is nearly unity, and thus points to collinearity. Condition indices refer to the square root of the ratio of the largest to the smallest characteristic root of X’X. An index of 5 or 10 points has weak dependencies, while moderate to strong relationships have indices over 30. Examinations of condition indices and of variance inflation factors indicated that multicollinearity was not a problem. In Model 1 and Model 2 in Table 25., both VIF and condition indices indicated that multicollinearity is not a problem. In Model 3 and Model 4 in Table 26, both VIF and condition indices indicated that multicollinearity is not a problem either. When the moderating variable was added on Model 5, multicollinearity still does not become a serious problem when the independent variables were mean centered in order to reduce the collinearity between the predictors and their product terms as recommended by (Cronbach 1989). 5.1.1.4. Identifying influential observation A small set of the data can have a disproportionate influence on the estimated parameters in a regression equation. Two basic diagnostic tools are the diagonal elements of the least-square project matrix h,, and the studentized residuals. It is suggested that when hj is more than twice its average value, p/n, the ith observation is a leveraging point and may be an influential observation (Belsley, Kuh et al. 1980). 89 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The studentized residuals are used to identify data points that have an extreme effect on the regression results. Observations in which the studentized residuals exceed a value of two are potential outliers (Belsley, Kuh et al. 1980). The analysis revealed that twelve observations are potentially influential in the regression. In order to examine the influence of these variables, a series of regression analyses were conducted by eliminating these observations, but R2 was not significantly increased in all the Models when observations are eliminated. Therefore, the cases were kept in the data set and the subsequent results for regression equations were based on 184 data points without eliminating those potential outliers. 5.1.2. Hierarchical Regression Analysis Results: Effects of Driving Factors on Environmental Proactivity HRA Model 1 and Model 2 were used to test the hypotheses HI, H3, and H6 . Model 1: Control Variables Environmental Proactivity = Parent Company (Japan, US, Europe) + Industry (High pollution intensive industries, medium pollution intensive industries) + Plant size Where, variable: Japan = 1 if country of origin = Japan 0 if country of origin = Elsewhere 90 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. US = 1 if country of origin = the United States 0 if country of origin = Elsewhere Europe = 1 if country of origin = European countries 0 if country of origin = Elsewhere (Since there are four levels in the country of origin, three dummy variables were used in the regression equations) variable: Hi Dirty = 1 if industry belong to high pollution intensive industries 0 other Me Dirty = 1 if industry belong to medium pollution intensive industries 0 other (Since there are three levels in the type of industry, two dummy variables are used in the regression equations) Model 2: Control Variables + Direct Effects of Three Driving Factors Environmental Proactivity = Parent Company (Japan, US, Europe) + Industry (High pollution intensive industries, medium pollution intensive industries) + Plant size + Three driving factors (environmental technology, environmental flexibility, and corporate visibility) Table 26 presents the results of HRA for the environmental proactivity. If we closely look at Model 1 in Table 26, plants headquartered in the United States and European countries are positively related to environmental proactivity. Plants with larger sizes 91 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. in terms of the number of employees have adopted more environmentally proactive practices or standards than those with smaller sizes. But high pollution intensive or medium pollution intensive industries are not to be shown more significantly environmentally proactive than cleaner industries. Model 2 shows that environmental technology has a significant effect on environmental proactivity: standardized regression coefficient was 0.309, and it was significant at the 0.1% alpha level. Manufacturing flexibility has a significant effect on environmental proactivity: standardized regression coefficient was 0.143, significant at the 5% alpha level. Corporate visibility has a significant effect on environmental proactivity: standardized regression coefficient was 0.160, significant at the 5% alpha level. Environmental technology turned out to be the strongest driver for the environmental proactivity among all three driving factors. Compared with manufacturing flexibility and corporate visibility in which the standardized regression beta are 0.143 and 0.160, respectively, the coefficient of environmental technology is 0.309 and t = 4.152 (pO.OOl). Hypothesis 1, 3, and 6 predicts the relationship of three driving factors with environmental proactivity. ■ H I: Environmental technology is positively related to environmental proactivity. 92 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ■ H3: Manufacturing flexibility is positively related to environmental proactivity. ■ H6 : Corporate visibility is positively related to environmental proactivity. Table 26 Hierarchical Regression Results: Dependent Variable: Environmental Proactivity Standardized coefficients Beta (t-value) Model 1 Model 2 Japan .097 (1.235) .058 (.805) US .229** (2.678) .130 (1.648) Europe .208* (2.496) .125 (1.634) High pollution-intensive industry .070 (.791) -.052 (-.640) Medium pollution-intensive industry -.103 (-1.285) -.089 (-1.219) Plant size .174* (2.326) .0 2 1 (.289) Environmental technology 309*** (4.152) Manufacturing flexibility .143* (1.980) Corporate visibility .160* (2.213) R2 .108 .283 F change 3.559** 14.183*** * p < .05, ** p < .01, ***p < .001 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. As can be observed from Model 1 and Model 2 in Table 26, the R-squared was increased 0.175 (162% increase) when three driving factors were added as independent variables. Thus, an F test for the significance of increase of explained variance yields the following equations: F = R: -R] 1 - R e J N - K - l V k e ~ k o J where Re: the multiple R for the expanded equations Ro: the multiple R for the original equation ke: the number of predictors in the expanded equation ko: the number of predictors in the original equation N: the total sample size (Equation 5) Using the Equation 5, F = ^0.283-0.108^ r 1-0.283 184 - 9 - 1 9 - 6 , - 14.18 This F, with (3, 174) degrees of freedom, is statistically significant at the 0.1% level @ 7 3 ,1 7 4 at 0.1% = 5.667), indicating that by adding three driving factors (i.e., environmental technology, manufacturing flexibility, and corporate visibility), on control variables such as country of origin, industry type, and size of plant, the variance explained on environmental proactivity has been significantly increased. 94 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In this way, Model 2 indicated that environmental technology, manufacturing flexibility and corporate visibility are important variables in explaining the variance of environmental proactivity. HI, H3, and H6 were supported. 5.1.3. Hierarchical Regression Analysis Results: Effects of Driving Factors on Environmental Uniformity HRA Model 3,4, and 5 were used to test the hypotheses H2, H4, H5 and H7. Model 3: Control Variables Environmental Uniformity = Parent Company (Japan, US, Europe) + Industry (High pollution intensive industries, medium pollution intensive industries) + Plant size where, dummy variables are the same as in Model 1. Model 4: Control Variables + Direct Effects of Three Driving Factors Environmental Uniformity = Parent Company (Japan, US, Europe) + Industry (High pollution intensive industries, medium pollution intensive industries) + Plant size + Three driving factors (environmental technology, environmental flexibility, and environmental heterogeneity, environmental technology squared) Model 5: Control Variables + Direct Effects of Three Driving Factors + Moderating Effect 95 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Environmental Uniformity = Parent Company (Japan, US, Europe) + Industry (High pollution intensive industries, medium pollution intensive industries) + Plant size + Three driving factors (environmental technology, environmental flexibility, and environmental heterogeneity, environmental technology squared) + Interaction variable between environmental technology and manufacturing flexibility (environmental technology * manufacturing flexibility) Table 27 presents the results of HRA for environmental uniformity. Unlike environmental proactivity, Model 3 showed that all control variables are not significantly related to environmental uniformity. In Model 4 and Model 5 ,1 tested the hypotheses H2 and H5 using high-order regression analysis and moderated regression analysis suggested by (Aiken and West 1991) and (Jaccard, Wan et al. 1990). To minimize multicollinearity both between (1) a squared term and its constituent term and (2 ) an interaction term and its constituent terms in the regression model, I mean-centered2 all independent variables (Jaccard, Wan et al. 1990; Aiken and West 1991). 2 It is important to note that because I have mean-centered the variables in the model, the interpretation o f main effects changes slightly. In a main effects-only model, the main effects are interpreted as constant effects. For example, in a main effects model, the coefficient o f an independent variable represents the effect o f the variable on dependent variable, holding all other independent variables in the model constant. In a mean-centered interaction effects model, the coefficient o f an independent variable is instead interpreted as the regression o f dependent variable on an independent variable when the other independent variables are at their mean values (Aiken and W est 1991; Jaccard, Wan, and Turrisi, 1990). 96 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 27 Hierarchical Regression Results: Dependent Variable: Environmental Uniformity Standardized coefficients Beta (t-value) Model 3 Model 4 Model 5 Japan .028 (.344) -.025 (-.296) -.052 (-.626) US .137 (1.538) .066 (.693) .051 (.548) Europe .036 (.411) -.007 (-.082) -.005 (-.054) High pollution-intensive industry -.064 (-.696) -.042 (-.455) -.047 (-.517) Medium pollution-intensive industry -.116 (-1.383) -.116 (-1.407) - .1 2 2 (-1.506) Plant size -.019 (-.237) -.054 (-.663) -.060 (-.755) Environmental technology -.016 (-.186) .0 2 2 (.267) Manufacturing flexibility -.0 1 1 (-.133) -.017 (-.207) Environmental heterogeneity -.133 (-1.609) -,135T (-1.664) Environmental technology (squared) -.228** (-3.018) -.159* (-2.035) Environmental technology*manufacturing flexibility . 216** (-2.814) R2 .025 .083 .124 F change .765 2.74* 7.918** + p < .1, *p<.05, **p<.01 Environmental technology was predicted to have a non-linear (inverted-U) relationship with environmental uniformity. In Model 4, the squared term had a significantly negative relationship with environmental uniformity, though the linear term is not significant. The standardized coefficient of the linear term was -0.016, t value was -0.186, and p<.90. However, the standardized regression coefficient of the 97 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. squared term was -0.228, and it was significant at the 0.1% alpha level. H2 is supported. In Model 4, manufacturing flexibility and environmental heterogeneity were predicted to have a negative relationship with environmental uniformity (H4, and H7). These predictions were not supported. The coefficient of manufacturing flexibility is not significant (standardized beta = -0.011, t = -0.133, and p<.90). However, the direction of the relationship was shown as predicted, indicating that there could be a negative relationship between manufacturing flexibility and environmental uniformity. This will be discussed more in Model 5 (moderating effect) as well as in subgroup analysis in the next section 5.3. Nor was the coefficient of environmental heterogeneity significant (standardized beta = -0.133, t = -1.609, and p<.20).The direction of the relationship, however, was shown as predicted, indicating that there could be a negative relationship between environmental heterogeneity and environmental uniformity. This negative relationship was reinforced in Model 5. In Model 5, consistent with my expectation, the environmental heterogeneity was negatively related to environmental uniformity (standardized beta = -0.135, t = -1.664, and p<.10). Thus, H7 was weakly supported at 1 0 % alpha level. 98 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Hypothesis 2 predicts that environmental technology is non-linearly (inverted-U) related to environmental uniformity. Also Hypotheses 4 and 7 predict that manufacturing flexibility and environmental heterogeneity will be negatively related to environmental uniformity. ■ H2: Environmental uniformity is highest at a moderate level of environmental technology. ■ H4: Manufacturing flexibility is negatively related to environmental uniformity. ■ H7: Environmental heterogeneity is negatively related to environmental uniformity. With the added effects of these driving factors added in Model 3 ,1 observed from Model 4 that the R-squared was increased by 0.058 (43.1% increase) when three linear terms and one squared term were added as independent variables. Using the Equation 5, /'0 .0 8 3 -0 .0 2 5 V fl8 4 -1 0 -lN F = v 1-0.083 ) \ 10-6 = 2.74 This F, with (4, 173) degrees of freedom, is statistically significant at the 5% level (F4;i73 at 5% = 2.42), indicating that by adding three linear terms and one squared term on control variables, the variance explained on environmental uniformity has been significantly increased. Thus, Model 4 is statistically significant. 99 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A test for moderating effect of environmental technology in the hypothesis 5 was strongly supported in Model 5. Hypothesis 5 predicts that the negative effect of manufacturing flexibility on environmental uniformity is enhanced as environmental technology increases. The interaction between environmental technology and manufacturing flexibility is significant in the expected direction (standardized coefficient beta = -.216, t - -2.814, and p<0.01). Thus, H5 was supported. With an additional effect of the moderating variable added to Model 4 ,1 observed from Model 5 that the R-squared was increased by 0.040 (48.2 % increase). Using the Equation 5, ^ 0.124-0.083 V f 184-11-1'' F = v 1-0.124 j 11-10 7.92 This F, with (1,172) degrees of freedom, is statistically significant at the 1% level (Fi,i72 at 1% = 6.784), indicating that by adding a moderating term on control variables and independent variables in Model 4, the variance explained on environmental uniformity has been significantly increased. Thus, Model 5 is statistically significant. 5.2. Split Sample Analysis In the previous section, I tested the hypothesized effects of driving factors on two dimensions of corporate environmental strategy in MNCs (i.e., environmental proactivity and environmental uniformity) using hierarchical regression analysis. In 100 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. this section, I explored the characteristics of the four types of corporate environmental strategy in MNCS in order to investigate the results of hierarchical regression analysis further to identify what driving factors are significant between two different environmental strategies. To do so, the sample was first divided into four subgroups based on a median split on two dimensions of corporate environmental strategy (i.e., environmental proactivity and environmental uniformity). Table 28 Means, Medians, and Standard Deviations of Environmental Proactivity and Environmental Uniformity Environmental Proactivity Environmental Uniformity Mean 3.75 3.07 Median 4 3.21 Std. Deviation 1.63 0.83 N 184 184 A firm is referred to as “reactive” relative to other firms when the degree of environmental proactivity of the firm is less than the median (4). A firm is referred to as “proactive” relative to other firms when the degree of environmental proactivity of the firm is greater than the median (4). A firm is referred to as “local” relative to other firms when the degree of environmental uniformity of the firm is less than the median (3.21). A firm is referred to as “uniform” relative to other firms when the degree of environmental uniformity of the firm is higher than the median (3.21). From this, four subgroups are 101 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. identified and two types of corporate environmental strategy in each subgroup can be named after the typology I proposed in this dissertation. Table 29 Four Subgroups Based on a Median Split Subgroup Description Strategy Within a Subgroup Subgroup 1 (Reactive Strategy) Firms whose environmental proactivity is less than median ■ Reactive/Local ■ Reactive/Uniform Subgroup 2 (Uniform Strategy) Firms whose their environmental uniformity is greater than median ■ Reactive/Uniform ■ Proactive/Uniform Subgroup 3 (Proactive strategy) Firms whose environmental proactivity is greater than median ■ Proactive/Uniform ■ Proactive/Local Subgroup 4 (Local Strategy) Firms whose their environmental uniformity is less than median ■ Proactive/Local ■ Reactive/Local Means and standard deviations of environmental proactivity and environmental uniformity of firms that belong to each type of corporate environmental strategy are shown in Table 30. Table 30 Means and Standard Deviations of Firms in Four Types of Corporate Environmental Strategy Strategy Dimension Strategy N Mean Standard Deviation Environmental Proactivity Reactive/Local 46 2.14 0.94 Reactive/Uniform 43 2.56 0.99 Proactive/Uniform 49 4.79 0.64 Proactive/Local 46 5.36 0.88 Total 184 3.75 1.63 Environmental Uniformity Reactive/Local 46 2.36 0.70 Reactive/Uniform 43 3.72 0.30 Proactive/Uniform 49 3.72 0.27 Proactive/Local 46 2.48 0.65 Total 184 3.07 0.83 102 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. After classifying the sample into four subgroups, two analytical methods were employed: one way ANOVA and ordinary least square regression analysis for each subgroup. A graphical representation of the subgroups and types of environmental strategy is shown on Figure 8 . Figure 8 Four Subgroups and Four Types of Corporate Environmental Strategy in MNCs § ' High £ c Z) " t o ■ 4 - » c C D c 2 > c L L I Low Subgroup2 (Ur ( d Reactive 3 5 Uniform .2 « £ 2 O C P S iform Strategy) H •& Proactive < o Uniform 3 5 .2 '£ 5 O C O T - § ■ Reactive §, Local ■ q C O Subgroup4 (L £ 0 0 Proactive § ■ Local | ■ § C O .ocal Strategy) Low High Environmental Proactivity 103 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5.2.1. One way ANOVA Analysis In this section, one way ANOVA was conducted to examine the differences in means among the four types of corporate environmental strategy in MNCs. I examined whether the four driving factors are different among four types of corporate environmental strategies. To do this, one way ANOVA and post hoc analysis were conducted. Because one way ANOVA is an alternative explanation in an exploratory fashion, it characterizes the four strategies and assesses whether there are any significant differences across strategies in terms of each of those driving factors. However, there is also a limitation of one way ANOVA. It tests the mean differences among the four types of corporate environmental strategy using one variable at a time without controlling the effects of other variables. Table 31 Driving Factors of Corporate Environmental Strategy in MNCs - Means and Standard deviations Characterization Reactive Reactive Proactive Proactive F-statistic Variable Local Uniform Uniform Local (n) Strategy Strategy Strategy Strategy Environmental 3.45 3.95 4.37 4.66 7 7 7 4 *** Technology (1.37) (1.07) (1.37) (1.26) (184) Manufacturing 4.61 4.82 4.99 5.48 6.599*** Flexibility (1.03) (1.03) (.92) (.92) (184) Corporate 3.82 4.10 5.04 4.57 7.048*** Visibility (1 .6 ) (1.1) (1 .2 ) (1.4) (184) Environmental 3.99 3.49 3.27 3.20 3.063* Heterogeneity (1.3) (1 .1) (1.3) ( 1 .6 ) (184) Group size 46 43 49 46 184 F-test: *p<0.05, ***<0.001 104 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Firms with “reactive/local strategy” have lowest environmental technology, lowest manufacturing flexibility, and lowest corporate visibility. But they have highest environmental heterogeneity. Firms with “proactive/local strategy” have the highest environmental technology, highest manufacturing flexibility and lowest environmental heterogeneity. Firms with “proactive/uniform strategy” have the highest corporate visibility among all strategy types. Overall, F statistics demonstrate significant differences between the four types of corporate environmental strategy on environmental technology (at a 0.001 level), manufacturing flexibility (at a 0.001 level), corporate visibility (at a 0.001 level), and environmental heterogeneity (at a 0.05 level). If the null hypotheses of equal means are rejected, the question is raised: “which groups have different means?” Procedures for the comparison of cell means are called multiple comparison procedures. In this post hoc analysis, the LSD (least significant difference) procedure was employed if the a level F-test for the equality of means hypothesis is rejected recommended by Fisher (Jobson, 1991). The results are summarized in Table 32. 105 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 32 Post Hoc Analysis - Multiple Comparisons Driving Factor Strategy (0 Strategy (J) Mean Difference (l-J) Std. Error Sig. Environmental Technology Reactive/Local Reactive/Uniform Proactive/Uniform Proactive/Local -0.5065f -0.9202*** -1.2138*** 0.2724 0.2637 0.2678 0.0647 0.0006 0.0000 Reactive/Uniform Reactive/Local Proactive/Uniform Proactive/Local 0.5 065 f -0.4138 -0.7073* 0.2724 0.2684 0.2724 0.0647 0.1248 0.0102 Proactive/Uniform Reactive/Local Reactive/Uniform Proactive/Local 0.9202*** 0.4138 -0.2935 0.2637 0.2684 0.2637 0.0006 0.1248 0.2671 Proactive/Local Reactive/Local Reactive/Uniform Proactive/Uniform 1.2138*** 0.7073* 0.2935 0.2678 0.2724 0.2637 0.0000 0.0102 0.2671 Manufacturing Flexibility Reactive/Local Reactive/Uniform Proactive/Uniform Proactive/Local -0.2116 -0.3764f -0.8717*** 0.2076 0.2009 0.2040 0.3094 0.0626 0.0000 Reactive/Uniform Reactive/Local Proactive/Uniform Proactive/Local 0.2116 -0.1648 -0.6601** 0.2076 0.2045 0.2076 0.3094 0.4212 0.0017 Proactive/Uniform Reactive/Local Reactive/Uniform Proactive/Local 0.3764f 0.1648 -0.4953* 0.2009 0.2045 0.2009 0.0626 0.4212 0.0146 Proactive/Local Reactive/Local Reactive/Uniform Proactive/Uniform 0.8717*** 0.6601** 0.4953* 0.2040 0.2076 0.2009 0.0000 0.0017 0.0146 Corporate Visibility Reactive/Local Reactive/Uniform Proactive/Uniform Proactive/Local -0.2744 -1.2184*** -0.7428* 0.2942 0.2847 0.2892 0.3521 0.0000 0.0110 Reactive/Uniform Reactive/Local Proactive/Uniform Proactive/Local 0.2744 -0.9439** -0.4683 0.2942 0.2898 0.2942 0.3521 0.0013 0.1131 Proactive/Uniform Reactive/Local Reactive/Uniform Proactive/Local 1.2184*** 0.9439** 0 .4 756 f 0.2847 0.2898 0.2847 0.0000 0.0013 0.0966 Proactive/Local Reactive/Local Reactive/Uniform Proactive/Uniform 0.7428* 0.4683 -0.47 56 f 0.2892 0.2942 0.2847 0.0110 0.1131 0.0966 Environmental Heterogeneity Reactive/Local Reactive/Uniform Proactive/Uniform Proactive/Local 0.49311 0.7135* 0.7862** 0.2928 0.2834 0.2878 0.0939 0.0127 0.0069 Reactive/Uniform Reactive/Local Proactive/Uniform Proactive/Local -0.4931 f 0.2204 0.2931 0.2928 0.2884 0.2928 0.0939 0.4458 0.3181 Proactive/Uniform Reactive/Local Reactive/Uniform Proactive/Local -0.7135* -0.2204 0.0727 0.2834 0.2884 0.2834 0.0127 0.4458 0.7978 Proactive/Local Reactive/Local Reactive/Uniform Proactive/Uniform -0.7862** -0.2931 -0.0727 0.2878 0.2928 0.2834 0.0069 0.3181 0.7978 LSD test ( f p<0.1, * p<0.05, ** p<0.01, *** p<0.001) 106 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5.2.2. OLS Regression Analysis In this section, I conducted four OLS regression models to explore the effects of four driving factors on environmental proactivity and environmental uniformity. Unlike one way ANOVA, OLS regression model can consider the effects of control variables. By examining each regression model, I explained which independent variables drive firms to adopt different corporate environmental strategies. To do this, I estimated an OLS regression model for each subgroup with independent variables including only first-order terms and control variables. Also, these OLS regression models are not independent of the hierarchical regression models which analyzed in the previous sections. On the contrary, these OLS regression analyses validated and complemented the results of the hypothesized relationships in the conceptual model proposed in this dissertation. 5.2.2.I. Effects on Environmental Uniformity within Subgroup 1 (Low Environmental Proactivity) I investigated the effects of the driving factors on environmental uniformity based on the two subgroups - one group with low environmental proactivity and the other with high environmental proactivity. Two subgroups were divided based on a median split on the environmental proactivity (median = 4.0). Table 33 presents results of the subgroup regressions. Model 6 shows the relationships between the 107 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. driving factors and environmental uniformity within the subgroup with low environmental proactivity. Table 33 OLS Regression Results for Subgroup 1 and 3: Dependent Variable: Environmental Uniformity Dependent Variable Environmental Uniformity Subgroup Low Proactivity (Reactive Strategy) High Proactivity (Proactive Strategy) Standardized coefficients beta (t value) Model 6 Model 7 R2 .242 .153 F 2.804** 1.712f Japan .127 (1.166) -.120 (-959) US .132 .053 (1.101) (.379) Europe .094 (.766) -.023 (-.181) High pollution-intensive industry -.148 (-1.186) .128 (.961) Medium pollution-intensive industry -.170 (-1.525) -.030 (-.257) Plant size -.181 (-1.587) .088 (.792) Environmental technology .259* (2.454) -.284* (-2.390) Manufacturing flexibility .131 (1.220) -.233* (-2.040) Environmental heterogeneity -.225* (-2.105) -.034 (-.291) fp<0.1, * p<0.05, **p<0.01 Within the subgroup with low environmental proactivity, environmental technology and environmental heterogeneity were the driving factors on environmental uniformity. Environmental technology was positively related to environmental 108 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. uniformity (p < .05), while environmental heterogeneity was negatively related to environmental uniformity (p < .05). Manufacturing flexibility was not significant. This result is similar to those of the hierarchical regression model (Model 5), which indicates that environmental technology has an inverted U-shaped relationship with environmental uniformity. The inverted U-shaped relationship between environmental technology and environmental uniformity implies that as environmental technology increases from low to moderate levels, environmental uniformity becomes high. That is, firms choose more uniform strategy. In Model 6, the degree of environmental proactivity ranges from low to moderate. Since the hypothesis (HI) that environmental technology is positively related to environmental proactivity is supported, environmental technology ranges from low to moderate among the group with low to moderate environmental proactivity. Therefore, the result in Model 6, indicating that environmental technology is positively related to environmental uniformity, is consistent with the hypothesis (H2) that environmental technology has an inverted U-shaped relationship with environmental uniformity. The result in Model 6, indicating that environmental heterogeneity has a negative relationship with environmental uniformity, is consistent with that of the full model (Model 5). However, while in the full model the environmental heterogeneity is 109 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. marginally significant (p < .10), environmental heterogeneity is significant at level of 0.05 in the Model 6. The hypothesis (H7) that environmental heterogeneity is negatively related to environmental uniformity fits better with the data when the environmental proactivity is low. 5.2.2.2. Effects on Environmental Uniformity within Subgroup 3 (High Environmental Proactivity) Model 7 shows the relationships within the subgroup with high environmental proactivity. As indicated in the Model 7 of Table 33, environmental technology and manufacturing flexibility were the driving factors on environmental uniformity within the group with high environmental proactivity. Environmental technology was negatively related to environmental uniformity (p < .05) and manufacturing flexibility was negatively related to environmental uniformity (p < .05). Environmental heterogeneity was not significant. This result supports the inverted U-shaped relationship between environmental technology and environmental uniformity, which was also supported in the full model (Model 5). The inverted U-shaped relationship between environmental technology and environmental uniformity implies that as environmental technology increases from moderate to high levels, environmental uniformity becomes low, that is, firms choose local strategy. The subgroup with high environmental proactivity has moderate to high levels of environmental technology, since the hypothesis (HI) that environmental technology is positively related to environmental proactivity in the 110 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. full model was supported. Therefore, the result in Model 7, indicating environmental technology is negatively related to environmental uniformity, is consistent with the hypothesis (H2) that environmental technology has an inverted U-shaped relationship with environmental uniformity. Noticeably, the result in Model 7 supported the hypothesis (H4) that manufacturing flexibility is negatively related to environmental uniformity (p < .05) in the subgroup with high environmental proactivity. H4, however, was not supported in the full model (Model 5). H4 fits better with the data when the environmental proactivity is high. Firms with moderate and high level of environmental proactivity would become “local” as their environmental flexibility becomes higher. Environmental heterogeneity was not significant. It is inconsistent result with Model 6. But the following can be a possible reason of this result. By the very strategy of being proactive, MNCs establish environmental practices far ahead of governmental regulations in every country that they are present in. Therefore, heterogeneity of environmental regulations should not affect the strategies of proactive companies. 5.2.2.3. Effects on Environmental Proactivity within Subgroup 4 (Low Environmental Uniformity) Relationships between the driving factors and environmental proactivity based on the two subgroups - one with low uniformity and the other with high uniformity - were 111 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. also investigated. Two subgroups were divided based on a median split on the environmental uniformity (median = 3.21). Table 34 presents results of the subgroup regressions. Model 8 shows the relationships between the driving factors and environmental proactivity within the subgroup 4 with low environmental uniformity. Consistent with Model 2 in hierarchical regression model, within the subgroup 4 with low environmental uniformity, environmental technology and manufacturing flexibility were the driving factors on environmental proactivity. Environmental technology was positively related to environmental proactivity (p < .001), and manufacturing flexibility was positively related to environmental proactivity (p < .01). HI and H3 are supported. But corporate visibility was not significant in the subgroup 4. H6 is not supported. Even though the hypothesis was not supported in the subgroup 4, the direction of the relationship between corporate visibility and environmental proactivity is the same as that of the full model. This indicates that corporate visibility is not a significant environmental driving factor that moves firms with a low level of environmental uniformity to be more environmentally proactive. 112 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 34 OLS Regression Results for Subgroup 2 and 4: Dependent Variable: Environmental Proactivity Dependant Variable Environmental Proactivity Subgroup Local Strategy Uniform Strategy (Low Uniformity) (High Uniformity) Standardized coefficients beta Model 8 Model 9 (t value) R2 .473 .190 F 8.188*** 2.139** Japan ,149t -.042 (1..677) (-.363) US .152 .103 (1.533) (.835) Europe .084 .132 (.879) (1.106) High pollution-intensive industry -.002 .041 (-.021) (.298) Medium pollution-intensive -.039 -.133 industry (.398) (-1.169) Plant size .004 .161 (.04) (1.259) Environmental technology .396*** .058 (4.277) (.456) Manufacturing flexibility .287** -.123 (3.119) (-1.055) Corporate Visibility .108 .313** (1.212) (2.681) **p<0.01, ***p<0.001 The following is a probable reason for this result. Even though MNCs become more visible, those with reactive/local strategy are hard to be more proactive compared to other MNCs who have already obtained environmental technology and manufacturing flexibility because these capabilities are path dependent. Therefore, Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. unless environmental technology and manufacturing flexibility are accommodated, firms are not encouraged to become more proactive by their corporate visibility. 5.2.2.4. Effects on Environmental Proactivity within Subgroup 2 (High Environmental Uniformity) Model 9 shows the relationships within subgroup 2 with high environmental uniformity. Only corporate visibility was a driving factor on environmental proactivity within subgroup 2 with high environmental uniformity. Corporate visibility was positively related to environmental proactivity (p < .01). H6 was supported. This is consistent with the explanation of the result in Model 8. Since firms in subgroup 2 are considered to have high environmental technology and manufacturing flexibility compared with firms with reactive/local strategy in subgroup 4, corporate visibility would be a significant factor driving firms to be more proactive. Environmental technology and manufacturing flexibility, on the other hand, were not significant. This result is different from that of the full model, which hypothesized that environmental technology and manufacturing flexibility is positively related to environmental proactivity. This result may imply that the firms within subgroup 2 with high environmental uniformity have similar level of environmental technology and manufacturing flexibility, but significantly different level of corporate visibility. 114 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. This result would be interesting since it shows the factors driving the firms within subgroup 2 (with high environmental uniformity) to be proactive. Based on the previous literature, the firms with uniform strategy are regarded as environmentally proactive. This dissertation, however, shows that there is a difference in the level of environmental proactivity even among the firms with uniform strategy. Further, corporate visibility is a driving factor in the move from uniform/reactive strategy to uniform/proactive strategy. This result implies that, as the firms in the subgroup with high uniformity become visible, the firms become to seek more proactive strategy. 115 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. CHAPTER 6 CONCLUSIONS 6.1. Findings and Discussion of the Results 6.1.1. Conceptual model for corporate environmental strategy: relationship between two dimensions of environmental strategy and its four driving factors This dissertation began by questioning the implicit assumption in research on corporate environmental strategy in MNCs that a local strategy is synonymous with a reactive strategy and that a uniform strategy is with a proactive one. Having discussed the assumption, I tried to make the following contributions. First, the dissertation proposed a new typology of corporate environmental strategy in MNCs. Corporate environmental strategy was operationalized along two dimensions: the degree of environmental uniformity and the degree of environmental proactivity. The environmental uniformity was defined as the similarity of environmental practices between the country of operation and the country of origin. The environmental proactivity was defined as the stringency of environmental practices relative to environmental regulations of the country of operation. With a 2x2 matrix built on the degrees of those two dimensions, environmental strategies of MNCs were classified into four distinctive strategic patterns: reactive/local, reactive/uniform, proactive/uniform, and proactive/local. 116 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Next, the dissertation investigated a subsequent question of what factors drive firms into one of the four strategic patterns. Four driving factors were proposed: environmental technology, manufacturing flexibility, corporate visibility, and environmental heterogeneity. A conceptual model for corporate environmental strategy and the hypothesized relationships between two strategic dimensions and four driving factors were tested empirically. As dependent variables, composite indices of environmental proactivity and environmental uniformity constructs, each of which consists of five sub-dimensions, were developed using second-order confirmatory factor analysis. As independent variables, four constructs of driving factors such as environmental technology, manufacturing flexibility, corporate visibility, and environmental heterogeneity were developed using factor analysis with principal component extraction and varimax rotation. To investigate the effects of driving factors on the degree of environmental proactivity and environmental uniformity, I conducted a series of hierarchical regression analyses using three control variables (country of origin, industry type, and plant size) and four independent variables (environmental technology, manufacturing flexibility, corporate visibility, and environmental heterogeneity). Overall, the results of empirical investigation supported the conceptual framework presented in the research model. 117 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. With respect to environmental proactivity, plant size and country of origin were positively related to environmental proactivity. That is, larger firms were more proactive. Plants based in the U.S. and European countries were more proactive than those based in Korea. But industry type did not have any significant effect on environmental proactivity. On adding three driving factors in the HRA model, environmental technology, manufacturing flexibility, and corporate visibility were significantly and positively related to environmental proactivity. Environmental technology showed the strongest effect on the environmental proactivity among all three driving factors. Therefore, it was shown that companies with high environmental technological capability are more environmentally proactive. The more companies become visible, the more proactive they become. With respect to environmental uniformity, all of the control variables were not significantly related to environmental uniformity. After adding three driving factors, high-order regression analysis and moderated regression analysis were conducted. Environmental technology had a non-linear (inverted-U) relationship with environmental uniformity. This indicated that, as the level of environmental technology increases, environmental uniformity rather decreases beyond the moderate level. In other words, as the companies develop their environmental 118 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. technology capability from the low to the moderate level, they increase the adoption of uniform strategy. However, as the companies evolve from the moderate to the high level of environmental capabilities, they abandon the uniform strategy and start to localize. Though the direction of the relationship was shown as predicted, manufacturing flexibility was not negatively related to environmental uniformity. Interestingly, it was hypothesized that there is an interaction effect of environmental technology on the relationship between manufacturing flexibility and environmental uniformity. The test for moderating effect was supported: the negative effect of manufacturing flexibility on environmental uniformity was enhanced as environmental technology increased. Therefore, as companies’ manufacturing flexibility increases, they tend to become more environmentally proactive and more local. Environmental heterogeneity was negatively related to environmental uniformity. That is, higher environmental heterogeneity between countries leads to more localization in their environmental practices. The results of the tested hypotheses are summarized in Table 35. 119 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission o f the copyright owner. Further reproduction prohibited without perm ission. Table 35 Summaries: Tests of Hypotheses on Driving Factors of Corporate Environmental Strategy Hypothesis Independent Variable Dependent Variable Hypothesized Relationship Hypothesis Supported Sig. Level Related Regression Model HI Environmental Technology Environmental Proactivity Positive YES a<0.001 Model 2 H2 Environmental Technology Environmental uniformity Inverted-U YES a<0.01 Model 4 H3 Manufacturing flexibility Environmental Proactivity Positive YES a<0.05 Model 2 H4 Manufacturing flexibility Environmental uniformity Negative NO - Model 4 and Model 5 H5 Environmental Technology * Manufacturing flexibility Environmental uniformity Negative YES a<0.01 Model 5 H6 Corporate visibility Environmental Proactivity Positive YES a<0.05 Model 2 H7 Environmental heterogeneity Environmental uniformity Negative YES a<0.1 Model 5 to o 6.1.2. Differential characteristics between four types of corporate environmental strategy To explore the characteristics of the four types of corporate environmental strategy in MNCs and identify what driving factors are significant for different environmental strategies, the sample was divided into four subgroups based on a median split of the two dimensions of corporate environmental strategy (proactivity and uniformity). Within the subgroup with low environmental proactivity, reactive/local strategy and reactive/uniform strategy were compared in order to explain what factors differentiate the degree of environmental uniformity between the two. OLS regression results showed that environmental technology and environmental heterogeneity were the main driving factors on environmental uniformity. Manufacturing flexibility was not significant in determining the degree of environmental uniformity. Noticeably, this result was consistent with the results from the hierarchical regression model of the full sample. Because the subgroup only includes firms with the below median score of environmental proactivity, the positive relationship between environmental technology and environmental uniformity is maintained with this subgroup, as predicted by the inverted U shaped relationship between the two. Among firms with the low environmental proactivity, firms with high environmental technology chose more uniform strategy. 121 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Within the subgroup with high environmental proactivity, proactive/local strategy and proactive/uniform strategy were compared in order to explain what factors differentiate the degree of environmental uniformity between the two. Environmental uniformity was also used as a dependent variable in an OLS regression. Environmental technology and manufacturing flexibility were the main driving factors on environmental uniformity. Contrary to the results in the subgroup analysis of low environmental proactivity, environmental technology was negatively related to environmental uniformity. Interestingly, this result was consistent with the results from the hierarchical regression model of the full sample. Because the subgroup only includes firms with the above median score of environmental proactivity, the negative relationship between environmental technology and environmental uniformity is maintained with this subgroup, as predicted by the inverted U shaped relationship between the two. In addition, manufacturing flexibility was negatively related to environmental uniformity. This hypothesis, however, was not supported in the full sample regression model. This implies that firms with high environmental technology chose more local strategy as manufacturing flexibility increases. Environmental heterogeneity was not a significant driving factor between proactive/local strategy and proactive/uniform strategy. It seemed that this result was inconsistent with the full sample regression model. But firms with high environmental technology and manufacturing flexibility would be much less influenced by the environmental heterogeneity. 122 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Within the subgroup with high environmental uniformity, reactive/uniform strategy and proactive/uniform strategy were compared in order to explain what factors differentiate the degree of environmental proactivity between the two environmental strategies. Only corporate visibility was a main driving factor on environmental proactivity within this subgroup. Corporate visibility was positively related to environmental proactivity, indicating within high uniformity firms, corporate visibility would be a significant factor encouraging firms to be more proactive. Environmental technology and manufacturing flexibility, on the other hand, were not significant. This result appeared to be different from that of the full model. But it could be understood that, because firms with high environmental uniformity had already similar level of environmental technology and manufacturing flexibility, corporate visibility could be a major differentiating factor between the two strategies. Therefore, as firms with high uniformity become visible, they would come to seek more proactive strategy. Within the subgroup with low environmental uniformity, reactive/local strategy and proactive/local strategy were compared in order to explain what factors differentiate the degree of environmental proactivity between the two environmental strategies. Consistent with the full sample regression model, environmental technology and manufacturing flexibility were the main driving factors on environmental proactivity. Both environmental technology and manufacturing flexibility were positively related to environmental proactivity. But corporate visibility was not significant. This 123 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. indicated that corporate visibility might not be a significant environmental driving factor for firms with low environmental uniformity to be more environmentally proactive. Hence, firms with reactive/local strategy would have the lowest score of environmental technology and manufacturing flexibility among all the firms in the sample, while firms within the proactive/local strategy would have the highest score in term of both internal capabilities. Therefore, until firms reach a certain level of environmental technology and manufacturing flexibility, firms could not become more proactive just because of their high corporate visibility. Because this research is cross sectional, we can only speculate what factors motivate firms to move across different types of environmental strategies. Based on my research findings, I can suggest that the four driving factors examined so far may also allow firms to move across the four types of corporate environmental strategy, as shown in Figure 9. 6.2. Implications of the Results The findings of this dissertation have several implications for researchers and managers. 6.2.1. Theoretical Implications This study developed a framework that has two dimensions in environmental strategy: environmental proactivity and environmental uniformity. In the past 124 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. studies, on the one hand, corporate environmental strategy with a domestic firms’ perspective was often seen to be linear on the continuum of reactive and proactive. Figure 9 Characteristics between four types of corporate environmental strategy in terms of significant driving factors Reactive/Uniform Proactive/Uniform Proactive/Local Reactive/Local Environmental Proactivity C o rp o rate visibility E nvironm ental technology M anufacturing flexibility E nvironm ental technology M anufacturing flexibility Environm ental technology E nvironm ental hetero g en eity On the other hand, corporate environmental strategy with a multinational firms’ perspective was often seen to be dichotomous between local and uniform. Also the past studies assumed that proactive companies are uniform in their environmental strategies and that reactive ones are adopting locally different environmental practices or standards. However, from related studies, this dissertation developed a conceptual framework that provides a richer perspective on a typology of corporate environmental strategy in MNCs. It is argued that environmental proactivity and 125 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental uniformity are two separate and orthogonal dimensions which MNCs should take into account in their formulating and implementing their environmental strategy in their foreign operations. This framework can be a starting point of many follow-up studies in environmental management literature. This study identified and proposed additional variables that affect corporate environmental strategies. In the past studies, environmental strategy was considered as something that is determined by manager’s decision or corporate strategy. From the survey of related areas including operations management, strategic management and organizational theory, this dissertation developed four factors that would affect companies’ environmental strategy: environmental technology, manufacturing flexibility, corporate visibility, and environmental heterogeneity. The directions of effect (i.e., the sign of correlation) were also predicted based on the literature. The empirical results confirmed that these factors significantly affect environmental strategies. This dissertation took an initial step toward developing and validating multidimensional measures of environmental proactivity and environmental uniformity in an operational context: raw material input, manufacturing processes, information disclosure, product packaging, and product disposition/recycling. The measurement model suggested that each of the five dimensions contributed to an overall construct of environmental proactivity and environmental uniformity in a 126 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. series of second-order factor analyses and that the dimensions are not construct- equivalent. Results also showed evidence of the internal consistency. Clearly, the empirical study of corporate environmental strategy in MNCs is in its infancy. This dissertation contributed to the literature by developing a typology of corporate environmental strategy in MNCs, measuring its two dimensions, and demonstrating its relationship to a number of driving factors in a conceptual model. 6.2.2. Managerial Implications This dissertation also informs senior managers that certain popular notions about their corporate environmental strategy facing different environmental regulations across countries of foreign operations may not be correct. For example, it is generally believed that environmental uniformity goes with environmental proactivity. However, the results of this dissertation showed that those two dimensions are not dependent. Managers need to consider how much uniform, as well as how proactive their companies should be. Companies do not necessarily have to be uniform to become proactive. Companies can be very proactive but localize at the same time. The finding that the effects of driving factors differ across environmental strategies also has important implications for implementing environmental practices of foreign operations. Firms should not blindly follow the recommendations of some 127 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. environmental management literature and try to implement the uniform standards or best environmental practices with the expectation that these practices or standards help them to automatically become environmentally conscious and environmentally responsible. The results of this dissertation actually imply that it might be more difficult for some firms to become proactive and uniform than much of the literature suggests without consideration of their internal capabilities and external pressures. In other words, this dissertation reinforces the importance of internal capabilities and external pressures that drive corporate environmental strategy in MNCs. The relationships between the driving factors and environmental proactivity and uniformity provided implications for the environmental practices of MNCs. If firms indeed want one of the four environmental strategies, they need to carefully examine whether their internal capabilities and external conditions do not discourage either proactive or uniform stance. Therefore, when managers need to make decisions on their environmental strategy, this study can provide their guidelines. For examples, if a company has high manufacturing flexibility, the result implies that the will increase proactivity and decrease uniformity. If a company has high visibility, it would be more proactive, especially when it has adopted uniform strategy. If a company faces high heterogeneity in a foreign operation, it would be local/reactive strategy when it has lower capabilities. However, its capabilities become higher, environmental heterogeneity would not be a significant driving factor in its environmental strategic 128 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. decision making. Noticeably, environmental technology plays an influential role in corporate environmental strategy in MNCs. If a company wants to be proactive, it should first have invested in environmental technology. This improved environmental technology could be transferred into foreign operations to make narrow the gap of environmental practices between foreign operations and the country of origin of the company. This would encourage the company to adopt a uniform strategy. But if the company invested further in environmental technology, it could be local while maintaining its proactivity. Manufacturing flexibility would reinforce this localizing movement. 6.3. Limitations and Future Research Directions A limitation of this dissertation is its focus on one foreign plant of each MNC, which affect the generalizability of the findings to extend to corporate environmental strategy in MNCs at parent company level. Thus, further research which examine multiple plants of MNCs is needed to examine whether the relationships found here still hold. The findings of this dissertation were derived from survey data which asked managers of their perception on their environmental practices. To further strengthen the findings presented here, it may be necessary to collect other objective data such as the amount of environmental technology investment, various measures of 129 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. en viron m en tal perform an ce, and environm ental co st a sso cia ted w ith en viron m en tal issues. The cross-sectional design of this dissertation does not allow the direct examination of causal relationships. Longitudinal research that measures environmental practices at different times could overcome this causality problem. Longitudinal research would also allow researchers to examine dynamic effects on environmental proactivity and environmental uniformity of the changes in driving factors. I measured driving factors and environmental practices at the same point in time and this did not consider the difference between short-run and long-run strategic behavior of firms. A follow-up survey in a few years can allow us to examine how the firms studied in this research evolve in their approach to environmental strategies. 130 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. BIBLIOGRAPHY Aiken, L. S. and S. G. West (1991). Multiple Regression: Testing and Interpreting Interactions. Newbury Park: CA, Sage Publications. Ainsworth, S. J. (1994). “Vulcan Chemicals Builds Specialties Portfolio around Chlor-alkali Core.” Chemical Engineering News 72(36): 12-14. Anderson, J. C. and D. W. Gerbing (1988). “Structural equation modeling in practice: A Review and Recommended Two-step Approach.” Psychological Bulletin 103(3): 411-423. Arnold, H. J. (1982). “Moderator Variables: A Clarification of Conceptual Analytic and Psychometric Issues.” Organizational Behavior and Human Performance 29: 143-174. Arora, S. and T. N. Cason (1995). “An Experiment in Voluntary Environmental Regulation: Participation in EPA's 33/50 Program.” Journal of Environmental Economics and Management 28: 271-286. Bagozzi, R. P. (1981). “An Examination of the Validity of Two Models of Attitude.” Multivariate Behavioral Research 16(3): 323-359. Belsley, D. A., E. Kuh, et al. (1980). Regression Diagnostics. New York: NY, John Wiley & Sons, Inc. Berry, M. A. and D. Rondinelli (1998). “Proactive Corporate Environmental Management: A New Industrial Revolution.” Academy of Management Executive 12(2): 38-50. Blalock, H. (1979). Social Statistics. New York, McGraw-Hill. Bowen, F. E. (2000). Does Size Matter? Organizational Slack and Visibility as Alternative Explanations for Environmental Responsiveness, the University of Bath. Buchholz, R. A. (1993). Principles of Environmental Management. Englewood Cliffs: NJ, Prentice Hall. Caimcross, F. (1992). Costing the earth : the challenge for governments, the opportunities for business. Boston, Mass., Harvard Business School Press. 131 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Campbell, D. T. and D. W. Fiske (1959). “Convergent and Discriminant Validation by the Multitrait-multimethod Matrix.” Psychological Bulletin 56: 81-105. Chin, W., B. Marcolin, et al. (1996). A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and Voice Mail Emotion/ Adoption Study. International Conference on Information Systems, Cleveland, Ohio. Christmann, P. (1997). Environmental Strategies of Multinational Companies: Determinants and Effects on competitive Advantage. Management. Los Angeles, University of California, Los Angeles. Churchill, G. A. (1979). “A Paradigm for Developing Better Measures of Marketing Constructs.” Journal of Marketing Research 16(2): 64-73. Cini, M. A., R. L. Moreland, et al. (1993). “Group Staffing Levels and Response to Prospective and New Group Members.” Journal of Personality and Social Psychology 65(4): 723-734. Coddington, W. (1993). Environmental marketing : positive strategies for reaching the green consumer. New York, McGraw-Hill. Cohen, J. and P. Cohen (1983). Applied Multiple Regression / Correlation Analysis for the Behavioral Sciences. Hillsdale, NJ, Erlbaum. CoxJr, T. (1989). “Toward the Measurement of Manufacturing Flexibility.” Production and Inventory Management Journal 30(1): 68-72. Cronbach, L. J. (1989). “Statistical Tests for Moderator Variables: Flaws in Analyses Recently Proposed.” Psychological Bulletin 102: 414- 417. Daly, H. (1994). “Forecasting Environmentally Sustainable Development: Four Parting Suggestions for the World Bank.” Ecological Economics 10: 183-187. Dean, T. J. and R. L. Brown (1995). “Pollution Regulation as a Barrier to New Firm Entry: Initial Evidence and Implication for Future Research.” Academy of Management Journal 38(1): 288-303. Dillman, D. (1978). Mail and Telephone Surveys. New York, John Wiley & Sons. Dillon, P. S. and K. Fischer (1992). Environmental Management in Corporations: Methods and Motivations. Medford, MA, Tufts Center for Environmental Management. 132 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Dowell, G., S. Hart, et al. (2000). “Do Corporate Environmental Standards Create Or Destroy Market Value?” Management Science 46(8): 1059-1074. Eisenhardt, K. M. and B. N. Tabrizi (1995). “Accelerating Adaptive Processes: Product Innovation in the Global Computer Industry.” Administrative Science Quarterly 40: 84-110. Epstein, M. and M. Roy (1998). “Managing Corporate Environmental Performance: A Multinational Perspective.” European Management Journal 16(3): 284-296. Freeman, H., T. Harten, et al. (1992). “Industrial Pollution Prevention: A Critical Review.” Journal of the Air and Waste Management Association 42(5): 617- 656. Gerwin, D. (1987). “An Agenda for Research on the Flexibility of Manufacturing Processes.” International Journal of Operations and Production Management 7: 38-49. Greeno, J. L. and S. N. Robinson (1994). “Rethinking Corporate Environmental Management.” The Columbia Journal of World BusinesstFall & Winter): 222-232. Harman, H. H. (1967). Modem Factor Analysis. Chicago, University of Chicago Press. Hart, S. L. (1995). “A Natural-resource-based view of the firm.” Academy of Management Review 20(4): 986-1014. Hayduk, L. A. (1987). Structural Equation Modeling with LISREL. Baltimore: MD, Johns Hopkins University Press. Hill, T. (1994). Manufacturing Strategy: Text and Cases. Burr Ridge, IL, Irwin. Investor Responsibility Research Center (1998). Corporate Environmental Profiles Directory 1998: Executive Summary. Washington, DC. IRRC, T. I. R. R. C. (1998). The Corporate Environmental Profiles Directory 1998. Washington, D.C. Jaccard, J., C. K. Wan, et al. (1990). “The Detection and Interpretation of Interaction Effects Between Continuous Variables in Multiple Regression.” Multivariate Behavioral Research 25(October): 467-478. 133 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Klassen, R. D. (1995). The Implications of Environmental Management Strategy for Manufacturing Performance, University of North Carolina at Chapel Hill: 206. Klassen, R. D. and L. C. Angell (1998). “An International Comparison of Environmental Management in Operations: The Impact of Manufacturing flexibility in The U.S. and Germany.” Journal of Operations Management 16: 177-194. Klassen, R. D. and D. C. Whybark (1999a). “Environmental Management in Operations: The Selection of Environmental Technologies.” Decision Sciences 30(3): 601-631. Klassen, R. D. and D. C. Whybark (1999b). “The Impact of Environmental Technologies on Manufacturing Performance.” Academy of Management Journal 42(6): 599-615. Kogut, B. and N. Kulatilaka (1994). “Options thinking and Platform Investments: Investing in Opportunity.” California Management Review 36(2): 52-71. Korten, D. (1995). When Corporations Rule the World. San Francisco, Berrett- Koehler Publishers. Lefebvre, L. A., E. Lefebvre, et al. (1995). Integrating Environmental Issues Into Corporate Strategy: A Catalyst for Radical Organizational Innovation, CIRANO. Macauley, D. (1993). “Responding to a New Social Charter: Voluntary Environmental Strategies.” Corporate Environmental Strategy 1(3). Mani, M. and D. Wheeler (1999). In Search of Pollution Havens? Dirty Industry in the World Economy, 1960-1995. The OECD Conference on FDI and the Environment, The Hague. Marguglio, B. W. (1991). Environmental Management Systems. New York, M. Dekker. Marsh, H. W. and D. Hocevar (1985). “Applications of Confirmatory Factor Analysis to the Study of Self-concept: First- and High-order Factor Models and Their Invariance across Groups.” Psychological Bulletin 97(3): 562-582. McGraith, M. E. and R. W. Hoole (1992). “Manufacturing's New Economies of Scales.” Harvard Business Review 70(3): 94-102. 134 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Miller, J. G. and A. V. Roth (1994). “A Taxonomy of Manufacturing Strategies.” Management Science 4013): 285-304. Munton, D. and J. Kirton (1996). Beyond and Beneath the Nation-State: Province/State Interactions and NAFTA. The International Studies Association Annual Meeting, San Diego, CA. Narasimhan, R. and A. Das (1999). “An Empirical Investigation of the Contribution of Strategic Sourcing to Manufacturing Flexibilities and Performance.” Decision Sciences 30(3): 683-718. North, K. (1992). Environmental Business Management: An Introduction. Geneva, International Labor Organization. Nunnally, J. (1978). Psychometric Theory. New York, McGraw Hill. Phillips, L. W. (1981). “Assessing Measurement Error in Key Informant Reports: A Methodological Note on Organizational Analysis in Marketing.” Journal of Marketing Research 18(November): 395-415. Podsakoff, P. M. and D. W. Organ (1986). “Self-Reports in Organizational Research: Problems and Prospects.” Journal of Management 12(4): 531-544. Porter, M. E. and C. v. d. Linde (1995). “Green and Competitive: Ending the Stalemate.” Harvard Business Review(September-October): 120-134. Post, J. E. (1978). Corporate Behavior and Social Change. Reston, VA, Reston Publishing. Rajagopalan, N. and D. K. Datta (1996). “CEO Characteristics: Does Industry Matter?” Academy of Management Journal 3911): 197-215. Rondinelli, D. A. and G. Vastag (1996). “International Environmental Standards and Corporate Policies: An Integrative Framework.” California Management Review 39(1): 106-122. Roome, N. (1992). “Developing Environmental Management Strategies.” Business Strategy and the Environment 1: 11-24. Royston, M. E. (1979). Pollution Prevention Pays. New York, Pergamon Press. Russo, M. V. and P. A. Fouts (1997). “A Resource-Based Perspective on Corporate Environmental Performance and Profitability.” Academy of Management Journal 40(3): 534-539. 135 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Sadgrove, K. (1993). “The Green Grid.” Director(May): 68-69. Schmidheiny, S. (1992). Changing course : a global business perspective on development and the environment. Cambridge, Mass., MIT Press. Schonberger, R. J. (1986). World Class Manufacturing: the Lessons of Simplicity Applied. New York, The Free Press. Selig, E. (1994). Global Policies: Strive for Consistency, Allow for Flexibility. Achieving Environmental Excellence: A Conference Report. S. J. Garone. New York, The Conference Board. Report Number 1066-94-CH: 13-14. SETAC (1993). Guidelines for Life-Cycle Assessment: A 'Code for Practice1 . Workshop, Sesimbra, Portugal. Sethi, A. K. and S. P. Sethi (1990). “Flexibility in Manufacturing: A Survey.” International Journal of Flexible Manufacturing Systems 2(4): 289-328. Sethi, S. P. (1979). “A Conceptual Framework for Environmental Analysis of Social Issues and Evaluation of Business Response Patterns.” Academy of Management Review 4: 63-74. Sethi, V. and W. R. King (1994). “Development of Measures to Assess the Extent to Which an Information Technology Application Provides Competitive Advantage.” Management Science 40(12): 1601-1627. Sharma, S. and H. Vrendenburg (1998). “Proactive Corporate Environmental Strategy and the Development of Competitively Valuable Organizational Capabilities.” Strategic Management Journal 19: 729-753. Shrivastava, P. (1995). “ENVIRONMENTAL TECHNOLOGIES AND COMPETITIVE ADVANTAGE.” STRATEGIC MANAGEMENT JOURNAL 16(Special Issue, Summer): 183-200. Sims, C. (1995). In Peru, a Fight for Fresh Air: U.S.-Owned Smelter Makes Residents 1 1 1 and Angry. The New York Times: Cl, C3. Skinner, W. (1974). “The Focused Factory.” Harvard Business Review May-June: 113-121. Slack, N. (1983). “Flexibility as a Manufacturing Objective.” International Journal of Operations and Production Management 3(3): 4-13. 136 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Spreitzer, G. M. (1995). “Psychological Empowerment in the Workplace: Dimensions, Measurement, and Validation.” Academy of Management Journal 38(5): 1442-1465. Stone-Romero, E., G. M. Alliger, et al. (1994). “Type II Error Problems in the Use of Moderated Multiple Regression for the Detection of Moderating Effects of Dichotomous Variables.” Journal of Management 20(1): 167-178. Swamidass, P. M. and W. T. Newell (1987). “Manufacturing Strategy, Environmental Uncertainty and Performance: A Path Analytic Model.” Management Science 33(4): 509-524. Tatikonda, M. V. and M. M. Montoya-Weiss (2001). “Integrating Operations and Marketing Perspectives of Product Innovation: The Influence of Organizational Process Factors and Capabilities on Development Performance.” Management Science 47(1): 151-172. The Financial Times (1995). Shell shocked but recovering (Public Relations Impact on Shell UK of Brent Spar U-tum): 7(1). Van de Ven, A. H. and D. L. Ferry (1980). Measuring and Assessing Organizations. New York: NY, Wiley. Vemon, R. (1992). “Transnational Corporations: Where Are They Coming From, Where Are They Headed?” Transnational Corporations 1(2): 7-35. Vickery, S. K., C. Droge, et al. (1993). “Markland, Production Competence and Business Strategy: Do They Affect Business Performance?” Decision Sciences 24(2): 435-455. Wagner, J. A. and S. M. Crampton (1993). Percept-percept inflation in micro organizational research: An investigation of prevalence and effect. Academy of Management Best Papers Proceedings. White, G. P. (1996). “A Meta-analysis Model of Manufacturing Capabilities.” Journal of Operations Management 14: 315-331. Whybark, D. C. and G. Vastag, Eds. (1993). Global Manufacturing Practices: A Worldwide Survey of Practices in Production Planning and Control. Elsevier. Amsterdam. World Bank (1992). World Development Report 1992: Development and the Environment. New York, NY, Oxford University Press. 137 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. APPENDICES A. Respondent Companies Country o f Origin COMPANY NAM E Belgium UCB S.A. Denmark DENMARK DAIRY DEVELOPMENT CORP. France AVENTIS PHARMMMA S.A. France COMPAGNIE PLASTIC OMNIUM France DEVANLAY S.A. France LE CARBONE-LORRAINE France PROTEX INTERNATIONAL France S AFT-PARTICIPATION S France VALEO BAYEN Germany HOECHST SCHERING AGREVO GMBH. Germany INDUSTRIEAUFBAUGESELLSCHAFT SCLAEFFLER KG Germany PROCTER&GAMBLE SERVICE GMBH Ireland PFIZER PHARMACEUTICALS Italy ERGOM MATERIE Italy SAES GETTERS S.P.A. Japan ALPS ELECTRIC CO., LTD. Japan ARRK CORPORATION Japan CLEAN TECHNOLOGY CO LTD Japan DAINIPPON INK & CHEMICALS Japan DISCO CORP Japan ENPLAS CORP Japan FANUCLTD Japan HIROSE ELECTRIC CO LTD Japan HOKURIKU ELECTRIC INDUSTRY CO Japan IMAYOSHIELECTRNICS CO. LTD. Japan JAPAN VILENE CO. Japan JSP CORP Japan KOSO SERVICE CO LTD Japan NIKKO COPPER SMELTING Japan NISSAN SCREW CO LTD 138 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Country o f Origin COMPANY NAME Japan OTSUKA PHARMACEUTICAL CO Japan SAM NAM ELECTRONICS Japan SINTO KOGYO LTD Japan SUMITOMO CHEMICAL CO., LTD. Japan TAIYO INK MANUFACTURING CO.LTD Japan TAIYO YUDEN CO.LTD. Japan TDK CORPORATION Japan TECHNOLOGY AND KINDNESS TOKA.LTD Japan TOKYO SANYO ELECTRIC CO.,LTD Japan TORAY INDUSTRIES, INC. Japan TOREY PRECISION CO. LTD. Japan YAM AICH IBUSSAN CO.LTD Japan YAMAICHI INDUSTRY CO LTD Japan YAM AYA COMMUNICATIONS IN Korea A PLUS CREATION LTD Korea AUK Korea BIROBART Korea BOOJU Korea BOOKANG SEMS Korea BU SAN DIPPING RUBBER CO LTD Korea COMAC CO LTD Korea DAE YANG RUBBER CO LTD Korea DAEM YUNG CO LTD Korea DAESANG CORP Korea DASTEK Korea DATON GLOBAL Korea DG TECH CO LTRD Korea DONGA TIRE Korea DONGLIM CO LTD Korea DONGW ON FISHERIES CO LTD Korea DONGYANG Korea DSM CO LTD Korea EKON Korea ESTEC CORP 139 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Country o f Origin COMPANY NAME Korea ETRONICS CORPORATION Korea FYD CORP Korea HALLA CLIMATE CONTROL CO.,LTD Korea HANBI Korea HANBO PRECISION Korea HANIL LEATHER Korea HANSHIN Korea HANSOL ELECTRONICS Korea HANSOL PAPER CO LTD Korea HUM AN ELECTRONICS Korea HWAWOO CO LTD Korea HYUNDAI HEAVY INDUSTRIES Korea HYUPDONG Korea I&H ELECTRONICS CO LTD Korea IC TECH INC Korea IKON Korea ILWOLSANG Korea JINSUNGTOPIA Korea JOONGWON Korea KORYO LEPORTS Korea KYUNGHI FISHING NET MFG CO LTD Korea LEOSCO Korea LG CABLE LTD Korea LG CHEMICAL Korea LG ELECTRONICS Korea LG ELECTRONICS Korea M AKYUNG INDUSTRIAL CO LTD Korea MOTEX CO LTD Korea MYOUNGMOON Korea NAM CHUN INTERNATIONAL CO LTD Korea OHSUNGSA CO LTD Korea OLYMPIA Korea PHILCO ELECTRONICS Korea PHILCO INC 140 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Country o f Origin COMPANY NAME Korea PT. KOHAP Korea PYEONGHWA AUTOMOTIVE CO LTD Korea SAMHAN Korea SAMHO Korea SAMHONG Korea SAMWHA CAPACITATOR Korea SHINKWANG Korea SONG TOWEL CO LTD Korea SOOSAN HEAVY INDUSTRIES CO Korea SUN STAR ELECTRIC CO Korea SUNG JIN FISHERIES CO LTD Korea SUNOP CO Korea TAEKYUNG Korea TAEYANG ELECTRONICS CO LTD Korea TEXTOPIA CO LTD Korea TRIGEM COMPUTER INC. Korea WONEEL MERCANTILE CO LTD Korea WOOSEOK ESTECH CORP Korea WOOYON Korea YONKYUNG ELECTRONICS Korea YOUNG CHANG Korea YOUNGAN HAT CO LTD Korea YOUNGHW A CO Luxembourg CARRARO INT'L S.A. Netherlands FOSROC Netherlands ICIOMICRON B.V Netherlands ICI THERA B.V. Netherlands MARMOIN HOLDING B.V. Netherlands RENAULT GROUP BV Netherlands SHELL PETROLEUM N.V Sweden CARDO RAILWAY Sweden VOLVO Swiss ABB(ASEA BROWN BOVERI) A.G. Swiss CIBA SPECIALITY CHEMICALS INT'L INC. 141 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Country o f Origin COMPANY NAME Swiss CLARIANT A.G. Swiss SIKA FINANZ AG UK ALLIED DOMECQ UK BOC GAS UK FOSECO UK GLAXO SMITH KLINE UK POTNITTS & SPENCER LTD UK THE MORGAN CRUCIBLE CO LTD UK TOOTAL TREAD LTD USA 3M USA ALLIED SIGNAL USA ALPHA METALS USA AMERICAN CYANAMID CO. USA AMERICAN STANDARD INTERNATIONAL INC. U SA AMKOR TECHNOLOGY INC. USA AMOCO CHEMICAL CO. USA APPLIED POWER INC. U SA ASCK INC. USA ASHLAND ACT U SA BANDO CHEMICAL INDUSTRIES LTD USA BORG-WARNER AUTOMOTIVE INC. USA BOWATER NUW AY INC USA CALTEX(OVERSEAS)LTD USA CLOROX INTERNATIONAL CO USA CORNING INTERNATIONAL CORP. USA E.I. DU PONT DE NEMOURS & CO. USA EMPAK INC. USA ENGELLHARD ASIA PACIFIC INC. USA FAIRCHILD SEMICONDUCTOR CORP. OF CALIFORNIA USA FEDERAL-MOGUL CORPORATION USA GE BETZ USA GE POLYMERLAND USA GE THERMOMETRICS USA GENERAL MOTORS CORPORATION 142 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Country o f Origin COMPANY NAME USA H.J.HEINZ COMPANY. USA HONEYWELL CO LTD USA HONEYWELL ELECTRIC MATERIALS USA INTERNATIONAL PAPER COMPANY USA INT'L PAPER MASONITE USA KIMBERLY-CLARK CORP. USA LIQUID CARBONIC CORPORATION USA MOLEX INTERNATIONAL INC USA NASH ENGINEERING CO USA PREMIERE PRODUCTS INC. U SA PROD AIR CORPORATION USA S.C.JOHNSON&SON INC. USA TEXAS INSTRUMENTS INCORPORATED USA TRW INC. USA VALEX CORP Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. B. Interview Questions for Phase 1 Question about General Environmental issues 1. What type of environmental issues do you see affecting your industry now? 2. What forces are driving these changes (public, government, customers)? 3. What type of environmental issues do you consider in building a new plant in foreign countries? ■ in developed countries (US, Europe) ■ in developing countries (China, Vietnam, Philippine) 4. What type of environmental issues do you consider in operating the plant in foreign countries? ■ in developed countries (US, Europe) ■ in developing countries (China, Vietnam, Philippine) 5. What type of decision making do you make in foreign countries with regard to environmental issues? ■ What environmental and other investment choices are made by different plants? ■ What are the implications of these choices for your business (performance)? Questions about plant operations 1. What is the major product lines produced in this plant? 2. How large is the plant (people and sales)? 3. What is the average age of equipment in the plant? 4. What are the most critical environmental issues specifically for your plant? 5. Will environmental issues affect the way your plant can manufacture your product? 6 . How broadly define management efforts to change your impact on the environment? 7. How are you organized to care of these issues (people, support) 144 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Questions about international operations 1. How different are environmental regulations in different countries compared with your home country? 2. How different are environmental practices/standards implemented between home and host countries? ■ Our company has an universal environmental policy for any country and any branch ■ When building a new foreign plant, we apply our own standards even if ours are more stringent than local regulations ■ Our company applies more stringent environmental standards to domestic (host country) plants/branches in operating the facility ■ Flexible in terms of adapting local environmental standards depending on local regulations 3. How do you define uniformity (or standardization)? ■ Policy level ■ Implementation level 4. What do you apply uniformly among environmental practices? Put them in order by importance. ■ Environmental policy ■ Environmental program ■ Environmental management system ■ Environmental standards 5. What drives you to adopt a uniform standard? ■ Cost: Using a same standard across countries is more cost-efficient than applying different local standards. ■ Reputation and image: The main reason that companies use same standards across countries is to become environmentally friendly company rather than to save costs. 145 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. B. Survey Instrument (English) A Study on Corporate Environmental Strategies in Global Operations This survey is part of an international study to understand the corporate environmental strategies in global operations with multi-plant firms coping with different environmental regulations across countries. It is jointly conducted by professor Soo II Kwak at the College of Business Administration, Seoul National University, Korea and professor K. Ravi Kumar at the Marshall School of Business, University of Southern California, USA. All individual responses will be kept strictly confidential, and only statistical summary results will be reported. Your attention in carefully completing all the questions will provide a comprehensive picture of the actual environmental practices implemented by global companies and help them develop corporate environmental strategies in global operations. For any kind of query, please do not hesitate to contact the office of professor Kwak1 or the office of professor Kumar2 . Thank you for your time. September 2002 Principal Researcher: Soo II Kwak* and K. Ravi Kumar** Research Assistant: Dongwon Lee * Soo II Kwak, Professor Operations Management College of Business Administration Seoul National University Seoul, Korea Tel. (02) 880-9856 Email, skwak@snu.ac.kr________ * * K. Ravi Kumar, Professor Information and Operations Management Marshall School of Business University of Southern California Los Angeles, CA, USA Tel. (213) 740-4826 Email. rkumar@marshall.use.edu______ 1. Jong Beom Moon: Ph.D. Candidate, Seoul National University, College o f Business Administration Tel. (02) 880-6931, Email. jmoon@snu.ac.kr 2. Dongwon Lee: Ph.D. Candidate, University o f Southern California, Marshall School o f Business Tel. (Korea) 011-227-1813, Email, dongwon@marshall.usc.edu 146 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 1 Environmental practices of parent company and plant in Korea 1.1 Please circle the number that you think represents the environmental policy o f vour parent com pany best. ■ If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. strongly strongly __________________________________________________________________________disagree______________________ agree a. Our parent company always goes beyond compliance with environmental regulations on any environmental issues 1 2 3 4 5 6 7 b. The top managers in our parent company give a high priority to environmental issues. 1 2 3 4 5 6 7 c. Our parent company is an industry leader on environmental issues. 1 2 3 4 5 6 7 d. Our parent company effectively manages the environmental risks which affect our business. 1 2 3 4 5 6 7 1.2 Please circle the number that you think represents the environmental management orientation of vour plant in K orea best. ■ If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. strongly strongly ___________________________________________________________________________ disagree_____________________agree a. Our plant’s business plan includes an extensive, detailed section that 1 9 ■ j A c f. 7 describes our objectives for environmental performance 1 4 0 D b. Our plant has a formal, well defined, written environmental policy 1 2 3 4 5 6 7 c. New environmental issues are continually identified and evaluated for 1 9 A < f. 7 their long term (5 years or more) impact on this plant. j d. We provide our suppliers with detailed, written environmental requirements. 1 2 3 4 5 6 7 e. An environmental life cycle assessment (LCA) has been conducted on major products manufactured in this plant. 1 2 3 4 5 6 7 f. First-level plant supervisors work on environmental issues jointly with marketing personnel, related to product performance. 1 2 3 4 5 6 7 g. Environmental performance is the responsibility of everyone in this plant. 1 2 3 4 5 6 7 h. Employee suggestions have proven to be an excellent source of ideas to improve environmental performance for this plant 1 2 3 4 5 6 7 i. Formal teams are used in the plant to identify environmental problems and opportunities and to develop solutions 1 2 3 4 5 6 7 j. First-level plant supervisors work on environmental issues jointly with design engineers, related to product or process design. 1 2 3 4 5 6 7 k. First-level plant supervisors work on environmental issues jointly with production engineers, related to process changes. 1 2 3 4 5 6 7 1 . All production personnel are evaluated against environmental performance objectives in their annual salary or compensation reviews 1 2 3 4 5 6 7 m. Operating practices are formally reviewed at least annually for their impact on the environment 1 2 3 4 5 6 7 n. Formal procedures are in place to review environmental concerns for all 1 9 9 A e 7 new capital investments for this plant o. An audit of waste reduction programs and their results is performed annually for their production areas 1 2 3 4 5 6 7 p. An audit of environmental risks for the existing production equipment is performed annually for all production areas. 1 2 3 4 5 6 7 147 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1.3 For the following environmental practices, what level o f environmental standards has been implemented in vour plant in Korea, compared to the environmental laws and regulations imposed by the Korean government? ■ If you think “the plant complies with the environmental laws and regulations,” then circle the number 1, ■ If you think “the plant applies moderately higher environmental standards than the environmental laws and regulations,” then circle the number 4, * If you think “the plant applies much higher environmental standards than the environmental laws and regulations,” then circle the number 7, ■ If you think “the plant in Korea does not consider the area as an environmental practice due to the lack o f environmental laws or regulations on that issue,” then circle n/a (not applied). complies moderately very with it higher much ________________________ higher a. Use of recycled materials n/a 1 2 3 4 5 6 7 b. Reduction in the amount of raw materials n/a 1 2 3 4 5 6 7 c. Selection of environmentally friendly raw materials n/a 1 2 3 4 5 6 7 d. Reduction in the amount of energy in using the product n/a 1 2 3 4 5 6 7 e. Extension of the product’s useful life n/a 1 2 3 4 5 6 7 f. Product design for multiple future uses n/a 1 2 3 4 5 6 7 g. Product design for easy repair n/a 1 2 3 4 5 6 7 h. Product design for disassembly n/a 1 2 3 4 5 6 7 i. Product design for recycling n/a 1 2 3 4 5 6 7 j. Choice of suppliers whose operations pollute less n/a 1 2 3 4 5 6 7 k. Minimization of air emissions n/a 1 2 3 4 5 6 7 1 . Minimization of water effluents n/a 1 2 3 4 5 6 7 m. Minimization of solid wastes (reduce, reuse and recycle) n/a 1 2 3 4 5 6 7 n. Limitation on pollutants that enter soil at industrial sites n/a 1 2 3 4 5 6 7 o. Reduction of the amount of energy required for the manufacturing and assembly of the product n/a 1 2 3 4 5 6 7 p. Building data available to the public about the environmental aspects of product (e.g. the inventory and emissions of hazardous substances used in manufacturing) n/a 1 2 3 4 5 6 7 q. Informing customers of the environmental aspects of the product (e.g. any known environmental risks etc.) n/a 1 2 3 4 5 6 7 r. Minimization of product packaging n/a 1 2 3 4 5 6 7 s. Easily recyclable packaging n/a 1 2 3 4 5 6 7 t. Establishment of recycling procedures (e.g. packaging materials, scraps, wastes etc.) n/a 1 2 3 4 5 6 7 u. Ensuring recuperation infrastructure (e.g. collection system etc.) n/a 1 2 3 4 5 6 7 v. Assessment of liability for the clean-up of sites containing hazardous n/a 1 0 3 4 5 6 7 substances w. Disposition of hazardous wastes, including treatment and incineration n/a 1 2 3 4 5 6 7 x. Prohibition of mixing waste solvents and other wastes to enable n/a 1 T 1 1 5 6 7 reprocessing y. Taking responsibility for the disposal of products n/a 1 2 3 4 5 6 7 148 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 2 Environmental practices of parent company and plant in Korea (continued) 2.1 Please circle the number that you think represents your parent com pany best. * If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. Strongly Strongly __________________________________________________________________________Disagree______________________Agree a. Our parent company has the same environmental policy as applied to any 1 2 3 4 5 6 7 country and any branch b. When building a new plant, our parent company applies our own 1 2 3 4 5 6 7 standards even if ours are more stringent than local regulations c. When operating plants overseas, our company adapts to local 1 2 3 4 5 6 7 requirements of environmental regulations. 2.2. Has vour plant in K orea implemented a standardized version o f the following procedures and programmes throughout the plants across countries? ■ If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. ■ If you think “the plant in Korea does not have a procedure or program,” then circle n/a (not applied). Strongly Strongly Disagree________________________ Agree a. Pollution monitoring techniques n/a 1 2 3 4 5 6 7 b. Environmental audit procedures n/a 1 2 3 4 5 6 7 c. Environmental impact assessment procedures n/a 1 2 3 4 5 6 7 d. Waste handling procedures n/a 1 2 3 4 5 6 7 e. Safety audit procedures n/a 1 2 3 4 5 6 7 f. Hazardous assessment procedures n/a 1 2 3 4 5 6 7 g. Accident prevention plans n/a 1 2 3 4 5 6 7 h. Emergency response systems n/a 1 2 3 4 5 6 7 i. Worker safety training programmes n/a 1 2 3 4 5 6 7 j. Management safety training programmes n/a 1 2 3 4 5 6 7 k. Contents of material safety data sheets (MSDS) n/a 1 2 3 4 5 6 7 1 . Contents of product safety and labeling instructions n/a 1 2 3 4 5 6 7 149 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 2.3 To what level o f environmental standards does the plant in Korea apply, compared to the plants in the home country of the parent company? ■ If you think “the plant in Korea applies much less stringent standards,” then circle the number 1, ■ If you think “the plant in Korea applies the same or similar standards,” then circle the number 4, ■ If you think “the plant in Korea applies much more stringent standards,” then circle the number 7, ■ If you think “the plant in Korea does not categorize the area as an environmental issue,” then circle n/a (not applied). much less same or much more stringent similar stringent a. Use of recycled materials n/a 1 2 3 4 5 6 7 b. Reduction in the amount of raw materials n/a 1 2 3 4 5 6 7 c. Selection of environmentally friendly raw materials n/a 1 2 3 4 5 6 7 d. Reduction in the amount of energy in using the product n/a 1 2 3 4 5 6 7 e. Extension of the product’s useful life n/a 1 2 3 4 5 6 7 f. Product design for multiple future uses n/a 1 2 3 4 5 6 7 g. Product design for easy repair n/a 1 2 3 4 5 6 7 h. Product design for disassembly n/a 1 2 3 4 5 6 7 i. Product design for recycling n/a 1 2 3 4 5 6 7 j. Choice of suppliers whose operations pollute less n/a 1 2 3 4 5 6 7 k. Minimization of air emissions n/a 1 2 3 4 5 6 7 1 . Minimization of water effluents n/a 1 2 3 4 5 6 7 m. Minimization of solid wastes (reduce, reuse and recycle) n/a 1 2 3 4 5 6 7 n. Limitation on pollutants that enter soil at industrial sites n/a 1 2 3 4 5 6 7 o. Reduction of the amount of energy required for the manufacturing and assembly of the product n/a 1 2 3 4 5 6 7 p. Building data available to the public about the environmental aspects of product (e.g. the inventory and emissions of hazardous substances used in manufacturing) n/a 1 2 3 4 5 6 7 q. Informing customers of the environmental aspects of the product (e.g. any known environmental risks etc.) n/a 1 2 3 4 5 6 7 r. Minimization of product packaging n/a 1 2 3 4 5 6 7 s. Easily recyclable packaging n/a 1 2 3 4 5 6 7 t. Establishment of recycling procedures (e.g. packaging materials, scraps, wastes etc.) n/a 1 2 3 4 5 6 7 u. Ensuring recuperation infrastructure (e.g. collection system etc.) n/a 1 2 3 4 5 6 7 v. Assessment of liability for the clean-up of sites containing hazardous substances n/a 1 2 3 4 5 6 7 w. Disposition of hazardous wastes, including treatment and incineration n/a 1 2 3 4 5 6 7 x. Prohibition of mixing waste solvents and other wastes to enable n/a 1 2 t\ 5 A 7 reprocessing d y. Taking responsibility for the disposal of products n/a 1 2 3 4 5 6 7 150 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 3 V isibility o f the parent com pany and the plant in Korea 3.1 Please circle the number that you think represents vour parent company best. ■ If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. Strongly Strongly ____________________________________________________________________________ Disagree___________________ Agree a. Our parent company’s name is widely recognized outside our customers j and suppliers. 2 3 4 5 6 7 b. The activities of our parent company are closely monitored by the j media. 2 3 4 5 6 7 c. Our parent company place a greater marketing emphasis on j environmental issues than our competitors do. 2 3 4 5 6 7 d. Does vour parent coniDanv have the following? ■ If your parent company has it, circle yes, and ■ If your does not have it, then circle no. ® a formal published environmental policy or program Yes No (D a separate environmental report, or a section in the annual report on the environment Yes No (3) a separately identified annual statement on environmental affairs for the corporate board Yes No © an environmental bulletin or newsletter for managers throughout the company Yes No 3.2 Please circle the number that you think represents your Plant in Korea best. * If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. Strongly Strongly ____________________________________________________________________________ Disagree___________________ Agree a. Our plant is easily recognized by outside our customers and suppliers in Korea as part of the parent company’s name. 2 3 4 5 6 7 b. Our plant has a good local reputation on social and environmental issues in Korea. 2 3 4 5 6 7 c. The activities of our plant closely monitored by the media in Korea. 2 3 4 5 6 7 d. Our plant is a major local employer in Korea. 2 3 4 5 6 7 e. Our plant gets involved in local and community issues in the environmental area in Korea 2 3 4 5 6 7 f. Korean community representatives and local groups visit our site often. 2 3 4 5 6 7 g- The environmental impacts of our plant are obviously visible in the local area (smell, sight, sound, touch...) in Korea. 2 3 4 5 6 7 h. Our plant reports any environmental weakness as well as strength to interested groups in Korea. 2 3 4 5 6 7 151 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 4 Heterogeneity between Korea and home country of the parent company 4.1 Please circle the number that vou think renresents vour Diant in Korea best. ■ If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. strongly disagree strongly agree a. There is the lack of infrastructure for accommodating the same pollution control j ^ equipment in Korea 3 4 5 6 7 b. The expertise to maintain the complex pollution control equipment is not available j ^ in Korea 3 4 5 6 7 c. Cultural difference of workers between Korea and the home country of your parent ^ company 3 4 5 6 7 d. What is produced by the plant in Korea is different from that of plants in the home j ^ country with regard to production technologies. 3 4 5 6 7 4.2 To what extent are the environmental regulations imposed by the government of Korea different from those imposed by the government of the home country of vour parent company? very very sim ilar different a. Use of recycled materials n/a 1 2 3 4 5 6 7 b. Reduction in the amount of raw materials n/a 1 2 3 4 5 6 7 c. Selection of environmentally friendly raw materials n/a 1 2 3 4 5 6 7 d. Reduction in the amount of energy in using the product n/a 1 2 3 4 5 6 7 e. Extension of the product’s useful life n/a 1 2 3 4 5 6 7 f. Product design for multiple future uses n/a 1 2 3 4 5 6 7 g. Product design for easy repair n/a 1 2 3 4 5 6 7 h. Product design for disassembly n/a 1 2 3 4 5 6 7 i. Product design for recycling n/a 1 2 3 4 5 6 7 j. Choice of suppliers whose operations pollute less n/a 1 2 3 4 5 6 7 k. Minimization of air emissions n/a 1 2 3 4 5 6 7 1 . Minimization of water effluents n/a 1 2 3 4 5 6 7 m. Minimization of solid wastes (reduce, reuse and recycle) n/a 1 2 3 4 5 6 7 n. Limitation on pollutants that enter soil at industrial sites n/a 1 2 3 4 5 6 7 o. Reduction of the amount of energy required for the manufacturing and assembly of the product n/a 1 2 3 4 5 6 7 p. Building data available to the public about the environmental aspects of product (e.g. the inventory and emissions of hazardous substances used in manufacturing) n/a 1 2 3 4 5 6 7 q. Informing customers of the environmental aspects of the product (e.g. any known environmental risks etc.) n/a 1 2 3 4 5 6 7 r. Minimization of product packaging n/a 1 2 3 4 5 6 7 s. Easily recyclable packaging n/a 1 2 3 4 5 6 7 t. Establishment of recycling procedures (e.g. packaging materials, scraps, wastes etc.) n/a 1 2 3 4 5 6 7 u. Ensuring recuperation infrastructure (e.g. collection system etc.) n/a 1 2 3 4 5 6 7 v. Assessment of liability for the clean-up of sites containing hazardous substances n/a 1 2 3 4 5 6 7 w. Disposition of hazardous wastes, including treatment and incineration n/a 1 2 3 4 5 6 7 x. Prohibition of mixing waste solvents and other wastes to enable n/a 1 o /\ 6 7 reprocessing J y. Taking responsibility for the disposal of products n/a 1 2 3 4 5 6 7 152 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 5 Environmental technologies of the plant in Korea 5.1 What do you see as the main reasons for investing in environmental technologies over the last 5 years in the plant in K orea? Please tick as appropriate: ■ If you think “it is not a very important reason for investing in, ” then circle the number 1, ■ If you think “it is a moderately important reason for investing in, ” then circle the number 4, and ■ If you think “it is a very important reason for investing in, ” then circle the number 7. not very m oderately very im portant_____ im portant____ m p ortant a. Compliance with regulations 1 2 3 4 5 6 7 b. Anticipating future regulations 1 2 3 4 5 6 7 c. Response to action by competitors 1 2 3 4 5 6 7 d. Pressure from stakeholders (shareholders, public, financiers) 1 2 3 4 5 6 7 e. Pressure from customers 1 2 3 4 5 6 7 f. Corporate commitment to social and environmental responsibility 1 2 3 4 5 6 7 g- Cost savings / greater efficiency 1 2 3 4 5 6 7 h. Increased competitiveness 1 2 3 4 5 6 7 i. Other. Please specify. 1 2 3 4 5 6 7 5.2 Please think about the all the projects or investments over the last 5 years, to what extent has your plant in K orea invested in the following area. ■ If you think “you plant did not invest at all in the area,” then circle the number 1, ■ If you think “you plant invested at a moderate level in the area,” then circle the number 4, and ■ If you think “you plant invested to a great extent level in the area,” then circle the number 7. Not m oderate to a great At all level extent a. Removal of underground storage tanks or contaminated soil 1 2 3 4 5 6 7 b. Cleanup of a spill or environmentally damaged area 1 2 3 4 5 6 7 c. Installing a new dust collector or other pollution control equipment on exhaust stacks 1 2 3 4 5 6 7 d. Upgrading capture on an existing end-of-pipe technology 1 2 3 4 5 6 7 e. Installing new water treatment equipment 1 2 3 4 5 6 7 f. Any collection system that captures wastes/emissions for disposal or transfers emissions to another media (water to air, water to solid, etc.) 1 2 3 4 5 6 7 g- Developing waste reporting and tracking systems 1 2 3 4 5 6 7 h. Training employees to minimize spills and unplanned emissions 1 2 3 4 5 6 7 i. Better housekeeping 1 2 3 4 5 6 7 j- Reformulating a product to reduce the use of hazardous materials 1 2 3 4 5 6 7 k. Greater use of recycles materials in products 1 2 3 4 5 6 7 1 . Energy conservation 1 2 3 4 5 6 7 m . Redesigning manufacturing equipment to reduce waste 1 2 3 4 5 6 7 n. Covering open process lines or tanks 1 2 3 4 5 6 7 0 . Recycling of former wastes 1 2 3 4 5 6 7 153 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 6 Flexibility of the plant in Korea 6.1 For each o f the characteristics listed below, how does your plant in Korea compare with vour competitors? ■ If you think “our plant in Korea is far worse than the competitors,” then circle the number 1, ■ If you think “our plant in Korea is about the same or similar to the competitors,” then circle the number 4, * If you think “our plant in Korea is far better than the competitors,” then circle the number 7. far about fa r worse the sam e b etter a. We adapt to changes in product or process regulation 1 2 3 4 5 6 7 b. We use recycled materials and components 1 2 3 4 5 6 7 c. We serve new green markets and consumers 1 2 3 4 5 6 7 d. We include existing green markets and consumers 1 2 3 4 5 6 7 e. We adapt to varying quality of recycled raw materials used as inputs (e.g., purity) 1 2 3 4 5 6 7 f. We adapt to availability of recycled materials or components 1 2 3 4 5 6 7 g- We generate less waste (e.g., obsolescence) because of reduced inventory levels 1 2 3 4 5 6 7 h. We deliver less frequently, but on a timely basis, to reduce environmental harm (e.g., air pollution) 1 2 3 4 5 6 7 6.2 For each o f the characteristics listed below, how does your plant in Korea compare with vour competitors? ■ If you think “our plant in Korea is far worse than the competitors,” then circle the number 1, * If you think “our plant in Korea is about the same or similar to the competitors,” then circle the number 4, ■ If you think “our plant in Korea is far better than the competitors,” then circle the number 7. far about far worse the sam e b etter a . number of products manufctured at a point in time 1 2 3 4 5 6 7 b. raw matrial variation 1 2 3 4 5 6 7 c. range of parameters (size, difficulty, etc.) 1 2 3 4 5 6 7 d. number of markets served 1 2 3 4 5 6 7 e. change product mix rapidly 1 2 3 4 5 6 7 f. vary production volume 1 2 3 4 5 6 7 g- adapt to changes in demand 1 2 3 4 5 6 7 h. change delivery schedule 1 2 3 4 5 6 7 i. time from earliest stage of design or prototyping to full production 1 2 3 4 5 6 7 j- time to modify existing products 1 2 3 4 5 6 7 k. time to implement engineering change order 1 2 3 4 5 6 7 154 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Section 7 Benefits gained from environmental management activities The following statements address vour plant’s position in Korea with regard to benefits associated with environmental management activities. Please circle the extent to which you agree or disagree that the statement describes your plant. * If you strongly disagree the statement, then circle the number 1, and ■ If you strongly agree the statement, then circle the number 7. strongly strongly disagree____________________________agree a . Increased sales volume 1 2 3 4 5 6 7 b. Cost savings (through better energy management and waste management etc) 1 2 3 4 5 6 7 c. Enhanced profitability 1 2 3 4 5 6 7 d. Improved corporate image 1 2 3 4 5 6 7 e. Improved product quality 1 2 3 4 5 6 7 f. Increased market share 1 2 3 4 5 6 7 g- Preempted market 1 2 3 4 5 6 7 h. Increased customer satisfaction 1 2 3 4 5 6 7 i. Diversification with new products 1 2 3 4 5 6 7 j- Improved process efficiency 1 2 3 4 5 6 7 k. New expertise gained in-house 1 2 3 4 5 6 7 Section 8 G eneral questions about your plant 1) Type o f industry (Choose one o f the following) Processed foods and tobacco ( Leather products and footwear ( Pulp, paper products and publications ( Chemical products ( Non-metallic mineral products ( Fabricated metal products ( Electronical machinery and apparatus ( Precision instruments ( Furniture & other manufacturing . products Textile products and apparel Wood and wood products Coke and petroleum products Rubber and plastic products Basic metal products General machinery and equipment Radio, TV & communication equipment Transportation equipment 2) Main products: ____________________________ 3) Age o f company: Established in the year___________ 4) Sales (million dollars): 2000 ( ) 2001 ( ) 5) Number o f employees: 2000 ( ) 2001 ( ) 6) Does your plant have any dedicated “environmental” staffs or a department? Yes( ) N o( ) I f not, please give the job title o f the person responsible for environmental management? Job title ( ) Department name: ( ) 7) Ownership: W holly owned ( ) Joint Venture ( )% 155 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. C. Survey Instrument (Korean) o[^§|.Aju|7;|-? M 0R uR o i r S i t ^ s y p R o | AHS m 0|& t a a f l a t q i§ s fe s r a s s b h er a s = a e j# ? m s | -^SSSgoJi £ § 0 | £ | t a|aR # £ # § F t t £ ^ * | ° m S R SItM ch ■£ S i t t Ai#DH®!-5l S S m s t a i ^ t i l n i t 21 o R fePltcH SK Sl K. Ravi Kumar H i t ? ! § § £ 1 t « R t 7 R £ | S ^ W I £ t* f ° 1 t c |. s is s i s ) 2 i 2 i a e * a i r ° ^ s r e r o r® - s i t A|-§H ^ O j* q):^H ^ju|c|-. ^ O H O II H^A|2J(A|DJ. Ai£|#o| o ^ 0 || A R S . &0H8H t i i R S i , 7|<go| g g o ii f l o R H t t l c H S - a ^ R e i l l f f * o |s H s u S R ^ g £ R § t l R ^ I B te £ § o | - i s R u R . 7 R M 04^1011 c ||# o| = A ^ 0 | S i° A |S , A -i-gqR Iil 5 | t i l H i t S i t ^ T S E t O R f e R t c l R n i Kumar H i t £ i t ^ 2M t £ | § R t AP | yHJ-Mc|-. quy ^ ° R a R 7 I S I R D K £ R t R |c |- . 2002 'S 9 H S i t ^ i R : ^ t & T / K. Ravi Kumar** S it^ l : 0 |#§l A -R P R m * * University of Southern California S c ! P R Marshall School of B usiness I t ^ t i l Professor K. Ravi Kumar £ fs |. (02) 8 8 0 -8 5 9 5 Tel. (213) 7 4 0 -4826 Email. skw ak@ snu.ac.kr Email, rkum ar@ m arshall.usc.edu 1 S I S : Ai-g-cy aj-jB. H § R | ° h £ 1 s h (02) 8 8 0 -6 9 3 1 / e -m a il: jm o o n @ sn u .a c .k r 2 0 |-§•§!: y-7 |-^i:||S J-jn g ° t m * h T !s k (61^-) (011) 2 2 7 -1 8 1 3 / e -m a il: d o n g w o n @ m a rsh a ll.u s c .e d u 156 Reproduced with permission of the copyright owner. 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Asset Metadata
Creator
Lee, Dongwon
(author)
Core Title
A typology of corporate environemental strategy and its driving factors in jultinational corporations
School
Graduate School
Degree
Doctor of Philosophy
Degree Program
Business
Degree Conferral Date
2003-05
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
business administration, management,OAI-PMH Harvest
Language
English
Contributor
Digitized by ProQuest
(provenance)
Advisor
[illegible] (
committee chair
), [illegible] (
committee member
), Devinny, Joseph (
committee member
), Rajagopalan, Nandini (
committee member
)
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c16-371489
Unique identifier
UC11339410
Identifier
3103929.pdf (filename),usctheses-c16-371489 (legacy record id)
Legacy Identifier
3103929.pdf
Dmrecord
371489
Document Type
Dissertation
Rights
Lee, Dongwon
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA
Tags
business administration, management