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97
1. Preferential probabilities in Time Interval 0 (Time 12:00) are excluded because
they are given by equal likelihood.
2. For the Filter Selection Problem, preferential probabilities in Interval 1 are
excluded because the team did not discuss filters until Time Interval 2.
3. Data for one alternative in each component selection problem are excluded
because the preferential probability of the third alternative can be calculated from
those of the other two. In this study, only the data from Glass Carafe, Stainless-Steel
Carafe, Gold Tone Filter, and Paper Filter are used for comparison.
5.5.1 Correlations between Survey Ratings and Preferential Probabilities from
Transcripts
The conjecture on the first evaluation is that the preferential probabilities
extracted from the transcript be positively correlated with the survey ratings.
Two major measures of statistical significance, Pearson product-moment
correlation coefficient and Spearman's rho, were applied to study the possible
correlation between the extracted preferential probabilities and the group ratings.
Correlation values range from +1 to -1. A correlation of +1/-1 means that there is a
perfect positive/negative linear relationship between variables. The closer the
correlation coefficient is to the +1/-1, the better two variables are correlated
positively/negatively. The results of correlation are shown in Table 5.16.
Object Description
| Title | Extraction of preferential probabilities from early stage engineering design team discussion |
| Author | Ji, Haifeng |
| Author email | haifengj@usc.edu; haifeng.ji@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Industrial & Systems Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-08-19 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-07 |
| Advisor (committee chair) | Yang, Maria C. |
| Advisor (committee member) |
Lu, Stephen Jin, Yan |
| Abstract | Activities in the early stage of engineering design typically include the generation of design choices and selection among these design choices. A key notion in design alternative selection is that of preference in which a designer or design team assigns priorities to a set of design choices. However, preferences become more challenging to assign on both a practical and theoretical level when done by a group of individuals. Preferences may also be explicitly obtained via surveys or questionnaires in which designers are asked to rank the choices, rate choice with values, or select a "most-preferred" choice. However, these methods are typically employed at a single point of time; therefore, it may not be practical to use surveys to elicit a team’s preference change and evolution throughout the process.; This research explores the text analysis on the design discussion transcripts and presents a probabilistic approach for implicitly extracting a projection of aggregated preference-related information from the transcripts. The approach in this research graphically represents how likely a choice is to be "most preferred" by a design team over time. For evaluation purpose, two approaches are established for approximating a team's "most preferred" choice in a probabilistic way from surveys of individual team members. A design selection experiment was conducted to determine possible correlations between the preferential probabilities estimated from the team's discussion and survey ratings explicitly stated by team members. Results suggest that there are strong correlations between extracted preferential probabilities and team intents that are stated explicitly, and that the proposed methods can provide a quantitative way to understand and represent qualitative design information using a low overhead information extraction method. |
| Keyword | preferences; probabilities; concept selection; design process; design decision-making |
| Language | English |
| 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-m1635 |
| Contributing entity | University of Southern California |
| Rights | Ji, Haifeng |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Ji-2413 |
| Archival file | uscthesesreloadpub_Volume14/etd-Ji-2413.pdf |
Description
| Title | Page 109 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 97 1. Preferential probabilities in Time Interval 0 (Time 12:00) are excluded because they are given by equal likelihood. 2. For the Filter Selection Problem, preferential probabilities in Interval 1 are excluded because the team did not discuss filters until Time Interval 2. 3. Data for one alternative in each component selection problem are excluded because the preferential probability of the third alternative can be calculated from those of the other two. In this study, only the data from Glass Carafe, Stainless-Steel Carafe, Gold Tone Filter, and Paper Filter are used for comparison. 5.5.1 Correlations between Survey Ratings and Preferential Probabilities from Transcripts The conjecture on the first evaluation is that the preferential probabilities extracted from the transcript be positively correlated with the survey ratings. Two major measures of statistical significance, Pearson product-moment correlation coefficient and Spearman's rho, were applied to study the possible correlation between the extracted preferential probabilities and the group ratings. Correlation values range from +1 to -1. A correlation of +1/-1 means that there is a perfect positive/negative linear relationship between variables. The closer the correlation coefficient is to the +1/-1, the better two variables are correlated positively/negatively. The results of correlation are shown in Table 5.16. |
