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Essays on Online Advertising Markets
by
Shijie Lu
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BUSINESS ADMINISTRATION)
May 2015
Dissertation Committee:
Sha Yang (Chair)
Anthony Dukes
Matthew Shum
Botao Yang
Object Description
| Title | Essays on online advertising markets |
| Author | Lu, Shijie |
| Author email | shijielu@usc.edu;cj.shijielu@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Business Administration |
| School | Marshal School of Business |
| Date defended/completed | 2015-03-13 |
| Date submitted | 2015-04-15 |
| Date approved | 2015-04-15 |
| Restricted until | 2015-04-15 |
| Date published | 2015-04-15 |
| Advisor (committee chair) | Yang, Sha |
| Advisor (committee member) |
Dukes, Anthony Shum, Matthew Yang, Botao |
| Abstract | My dissertation examines novel interactions between consumers and advertisers enabled by Internet platforms with new targeting technologies in online advertising markets. As paid‐search and display become two most prevalent forms of online advertising, this dissertation empirically investigates the consumer and advertiser interactions in these two online advertising markets. ❧ In my first essay, I examine the determinant of competition and its impact on click‐volume and cost‐per‐clicks in paid‐search advertising. I regard each keyword as a market and measure the competition by the number of ads on the paid‐search listings. I build an integrative model of the number entrant advertisers, the realized click‐volume and cost‐per‐clicks of each entrant. The proposed model is applied to data of keywords associated with digital camera/video and accessories. Results indicate that the number of competing ads has a significant impact on baseline click‐volume, decay factor, and value‐per‐click. These findings help search advertisers assess the impact of competition on their entry decisions and advertising profitability. The proposed framework can also provide profit implications to the search host regarding two polices: raising the decay factor by encouraging consumers to engage in more in‐depth search/click‐through, and providing coupons to advertisers. ❧ As Internet advertising infomediaries now provide rich competition‐related information, search advertisers are becoming more strategic in their keyword decisions. In the second essay, I explore whether positive or negative spillover effects occur in advertisers’ keyword entry decisions, which lead to assimilation or differentiation in their keyword choices. I develop a model of advertisers’ keyword decisions based on the incomplete‐information and simultaneous‐move game with two novel extensions: (i) I allow the strategic interactions to vary with advertisement positions to reflect consumers’ top‐down search pattern; and (ii) I infer potential entrants of a keyword by modeling the advertisers’ keyword consideration process to capture their limited capacity in analyzing all existing keywords. Using a panel dataset of laptop‐related keywords mainly used by 28 manufacturers, retailers, and comparison websites that advertise on Google, I find both assimilation and differentiation tendencies, which vary across firm types and the expected ranking of competing firms. A counterfactual simulation suggests that the more accurate competition information provided by infomediaries leads to a market‐expansion effect. ❧ Behavioral targeting, displaying personalized advertisements based on consumers’ past online behaviors, has become a popular practice in the online advertising industry. Yet, empirical research on behavioral targeting remains relatively nascent. The final essay studies the impact of targeting level on three key players (users, advertisers, and the advertising host) in behaviorally targeted display advertising. The targeting level is defined as an inverse scale of the number of a consumer’s recently activated interests used in the user‐ad match. Intuitively, a high targeting level can increase the relevance of the served ads and consequently the users’ click‐through rate, but it might also evoke users’ negative reactions by triggering privacy concerns and/or information satiation, lowering the click‐through rate. Besides the mixed reaction from users, advertisers may also respond to a high targeting level by either raising bids in an anticipation of a higher value‐per‐click, or lowering bids due to the reduced competition as the result of a high targeting level. To understand the impact of the targeting level, I develop a model to simultaneously capture users’ reactions to behaviorally targeted ads, the advertising host’s decision on ad serving, and advertisers’ bid decisions. I apply the model to a novel dataset obtained from a leading Internet advertising platform. Results suggest that although the advertisers’ profits increase with the targeting level, both the consumers’ click‐through rate and the advertising host’s revenue has an inverted‐U relationship with the targeting level. |
| Keyword | online advertising; Internet marketing; paid search; competition; generalized second-price auction; entry; incomplete-information game; infomediary; behavioral targeting; Bayesian estimation |
| Language | English |
| Format (imt) | application/pdf |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Lu, Shijie |
| Physical access | 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 author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-LuShijie-3300.pdf |
| Archival file | Volume1/etd-LuShijie-3300.pdf |
Description
| Title | Page 1 |
| Repository email | cisadmin@lib.usc.edu |
| Full text | Essays on Online Advertising Markets by Shijie Lu A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BUSINESS ADMINISTRATION) May 2015 Dissertation Committee: Sha Yang (Chair) Anthony Dukes Matthew Shum Botao Yang |
