臺灣博碩士論文加值系統

過去個體選擇模式考慮知覺與態度等不可觀測變數的方法，會有參數估計值不具一致性與有效性、指標無法直接影響決策、以及指標不適用於預測等問題，且不可觀測的潛在變數無法隨個體不同而有所改變，以致不利於政策分析與應用。此外現今模式校估技術大多利用模擬最大概似法，來克服模式中多維度參數積分的困難，而模擬次數不足時參數校估結果將出現不穩定情況，但卻鮮少研究探討模擬次數對模式校估之影響，故適當的模擬次數相當重要。
本研究主要目的乃利用聯立方程模式觀念，整合潛在變數與個體選擇模式，決定較佳的隨機亂數抽取次數，使得參數估計值具有一致性、有效性、及穩定性，並考慮服務品質知覺變數之異質性、相關性、及層級式因果關係，增加模式解釋能力以掌握旅客的乘車行為，使易於應用於政策分析，及瞭解各政策變數對選擇行為之直接或間接影響效果，以解決過去相關研究所發生之問題。研究範圍為國道客運高雄至台北路線。
在處理潛在變數選擇模式的部份，實證結果顯示，加入了服務品質滿意度之後，皆已提昇選擇模式的解釋能力，顯示此研究方法之有效性。而隨機亂數抽取次數的部份，各種潛在變數選擇模式之模擬對數概似函數值，將隨著模擬抽取次數的增加而增加，且以Halton亂數模擬次數增加為4000次時，皆顯示模擬對數概似函數值之改善情況漸趨緩和，故本研究以模擬次數為4000次作為各種潛在變數選擇模式之適宜的隨機數列抽取次數。
潛在變數假設為外生變數時，以整合潛在變數異質性與相關性之一般化潛在變數選擇模式的解釋能力較佳，且證實便利性、舒適娛樂性、乘客互動度等滿意度潛在變數，具有個體異質與相關之情況，且此三個服務品質滿意度變數正向影響旅客對國道客運公司的選擇行為。若考慮潛在變數間層級式因果關係時，則旅客對各客運公司之便利滿意度與舒適娛樂滿意度會直接正向影響選擇行為，且以便利滿意度之影響程度較舒適娛樂滿意度影響強；旅客的互動滿意度則透過便利滿意度與舒適娛樂滿意度間接正向影響對各客運公司的選擇行為。

In the past, the way that the discrete choice models treated the unobservable variables such as perceived and attitude variables caused some problems. For example, the estimated parameters were not consistent and efficient, the index could not be used directly to affect the policies, and the index may not be suitable in the prediction, and the unobservable variables are unchangeable as individuals vary. It results in some disadvantages for policies analysis and applications. Now the most widely used models is Maximum Simulated Likelihood to overcome the model with multi dimension parameter integration problems. There exists unstable situation in parameter calibrating as the number of simulated draws is not enough. The earlier reference seldom explored the influence of the model calibrating by simulating the number of draws. The number of draws is quite important.
The purpose of this research is to use the simultaneous equations concepts for integrating latent variables and individual choice models, and decide the best number of the random draws. The parameters estimation will be more consistent, efficient, and stable. In addition, this study also discusses the heterogeneity, correlation, and hierarchy cause-and-effect of service quality perceived variables to increase the explanatory power in the models and to know the travelers’ riding behaviors. It will be implementing to policy analysis, to understand every policy variables on direct and indirect effect of choice behaviors, and to solve the problem which came about in the previous researches. The scope of this research was the intercity bus travelers of Taipei-Kaohsiung route in Taiwan.
For the part of dealing with the latent variable choice models, the evidence shows that as the service satisfaction factors add in the model, the explanatory power will be improved. It also presented the methodology is efficient. For the part of the number of random draws, simulating the log-likelihood function of different latent variable choice models will boost as the simulating number increase. While the Halton random number reached to 4000, the improvement of the simulation to simulating the log-likelihood function was getting smooth. So this research picks 4,000 as the number of random draws.
In this paper, if the latent variables are assumed as exogenous variables, the I II - -
integrating latent variables heterogeneity and correlation of the choice model has better explanatory power. It presents that there are individual heterogeneity and correlation among the three service quality variables-convenience, commoditization and entertainment, the passengers’ interaction. In addition, there is positive influence on the travelers’ choices to the intercity bus companies by these three service quality satisfaction variables. The convenience and commoditization and entertainment satisfaction of the travelers to the bus companies will influence positively on travelers’ choice behaviors, and the convenience satisfaction is stronger than commoditization and entertainment satisfaction. Moreover, the travelers’ interaction satisfaction influence indirectly on the travelers’ choice behaviors to the bus companies through the convenience and commoditization and entertainment satisfaction of the travelers.

摘 要..................................................................................................................I
Abstract................................................................................................................II
誌 謝...............................................................................................................IV
目 錄..............................................................................................................V
表 目 錄..........................................................................................................VII
圖 目 錄...........................................................................................................IX
圖 目 錄...........................................................................................................IX
第一章 緒論.....................................................................................................1
1.1 研究背景與動機.....................................................................................................1
1.2 研究目的.................................................................................................................4
1.3 研究範圍與限制.....................................................................................................5
1.4 研究內容.................................................................................................................5
第二章 文獻回顧.............................................................................................7
2.1 個體選擇模式(Disaggregate Choice Model, DCM)..............................................7
2.2 結構方程模式(SEM)............................................................................................14
2.3 考慮潛在變數之選擇模式...................................................................................18
2.4 公路客運旅客乘車行為之相關研究...................................................................24
2.5 綜合評析...............................................................................................................34
第三章 模式構建...........................................................................................37
3.1 基礎模式(MNL)...................................................................................................38
3.2 基準潛在變數選擇模式(BLVCM)......................................................................39
3.3 異質潛在變數選擇模式(HLVCM)......................................................................42
3.4 一般化潛在變數選擇模式(GLVCM)..................................................................44
3.5 內生潛在變數選擇模式(ELVCM).......................................................................47
3.6 一般化內生潛在變數選擇模式(GELVCM)........................................................50
3.7 模式校估方法.......................................................................................................53 V I - -
3.8 研究方法...............................................................................................................58
第四章 實證結果...........................................................................................63
4.1 基本資料與旅次特性分析...................................................................................63
4.2 個體選擇模式(MNL)結果分析...........................................................................68
4.3 BLVCM結果分析.................................................................................................71
4.4 HLVCM結果分析.................................................................................................76
4.5 GLVCM結果分析.................................................................................................80
4.6 ELVCM結果分析.................................................................................................86
4.7 敏感性分析...........................................................................................................99
第五章 結論與建議.....................................................................................105
5.1 結論.....................................................................................................................105
5.2 建議.....................................................................................................................109
參考文獻..........................................................................................................111
附錄：問卷.....................................................................................................119

一、中文部分
王志剛、謝文雀，消費者行為，台北：華泰，1995年。
方世榮譯，行銷管理學，第4版，台北：東華，2000年。譯自Kotler, P., Marketing Management, 10th ed., N.J.: Prentice Hall, 2000.
任維廉、呂堂榮，「國道客運知覺之服務品質，滿意度與移轉障礙對其行為意向之影響」，運輸計劃季刊，第33卷，第2期，頁421-448，2004年。
任維廉、董士偉、呂堂榮，「服務場景與等候經驗對國道客運乘客行為意向與選擇行為之影響」，運輸計劃季刊，第34卷，第3期，頁413-442，2005年。
邱皓政，結構方程模式，台北：雙葉，2003年。
胡凱傑，「應用服務品質量表與知覺價值模式探討旅客再消費意願之影響因素：以汽車客運業為例」，國立交通大學運輸科技與管理學系博士論文，2003年。
施鴻志、段良雄、凌瑞賢，都市交通計劃—理論與實務，台北：茂昌，1984年。
陳順宇，多變量分析(二版)，台北：華泰，2007年。
陳順宇，結構方程模式，台北：心理出版社，2007年。
陳宥欽，「離散選擇模式方案異質與相似的誤差項問題」，國立成功大學交通管理科學系博士論文，2005年。
張紹勳、張紹評、林秀娟，多變量統計分析，台北：松崗，2000年。
葉日武譯，消費者行為，第8版，台北：前程，2001年。譯自Hawkins, Best ＆Coney, Consumer Behavior: Building Marketing Strategy, 8th ed., 2001.
楊志文，「考慮選擇集合、市場定位及個體異質性之城際客運選擇模式」，國立成功大學交通管理科學系博士論文，2003年。
楊志文、段良雄，「考慮選擇集合與異質性之個體城際客運選擇模式」，運輸計劃季刊，第33卷，第2期，頁391-420，2004年。
楊志文、曾維琦、宋彥青，「應用成對比較與選擇圖像法探討國道客運服務品質之定位效果」，運輸計劃季刊，第36卷，第1期，頁83-114，2007年。
楊必立、陳定國、黃俊英、劉水深、何雍慶，行銷學，台北：華泰，1999年。
謝雨生，「潛在結構模式在社會科學之應用」，中國統計通訊，第8卷，第9期，頁2-16，1997年。
二、英文部分
Abelson, R.P. and A. Levy, “Decision Making and Decision Theory, Handbook of Social Psychology 1, G. Lindzey and E. Aronsom, Eds., Ransom House, New York, 1985.
Ailawadi, K. L., D. R. Lehmann, and S. A. Neslin, “Market Response to A Major Policy Change in The Marketing Mix: Learning form Procter ＆ Gamble’s Value Pricing Strategy, Journal of Marketing, 65, pp. 44-61, 2001.
Arbucke, J. L. and W. Wothke, Amos 4.0 User’s Guide, Small Waters Corporation, 1999.
Ashok, K., W. R. Dillon, and S. Yuan, “Extending Discrete Choice Models to Incorporate Attitudinal and Other Latent Variables, Journal of Marketing Research, 39(1), pp. 31-46, 2002.
Ben-Akiva, M. and B. Boccara, “Integrated Framework for Travel Behavior Analysis, presented at the International Association of Travel Behavior Research (IATBR) Conference, Aix-en-Provence, France, 1987.
Bearden, W. D. and M. J. Etzel, “Reference Group Influence on Product and Brand Purchase Decisinon, Journal of Consumer Research, pp. 185, 1982.
Ben-Akiva, M. and S. R. Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, 1985.
Ben-Akiva, M.et al., “Extended Framework for Modeling Choice Behavior, Marketing Letters, 10(3), pp. 187-203, 1999.
Ben-Akiva, M., D. Bolduc, and J. L. Walker, Specification Identification ＆ Estimation of the Logit Kernel (or Continuous Mixed Logit) Model, Working paper, MIT Press, 2002.
Bernardino, A.T., Telecommuting Modeling the Employer’s and the Employee’s Decision-Making Process, Garland Publishing, New York, 1996.
Berry, S. T., J. Levinsohn, and A. Pakes, “Automobile prices in market equilibrium, Econometrica, 63, pp. 841-890, 1995.
Besanko, D., S. Gupta, and D. Jain, “Logit Demand Estimation under Competitive Pricing Behavior：An Equilibrium Framework, Management Science, 44(11), pp. 1533-1547, 1998.
Beynolds, F. D. and W. D. Wells, Consumer Behavior, N. Y.: McGraw Hill, 1977.
Bhat, C. R., “An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel, Transportation Science, 31(1), pp. 34-48, 1997.
Bhat, C. R., “Covariance Heterogeneity in Nested Logit Models: Econometric Structure and Application to Intercity Travel, Transportation Research B, 31(1), pp. 11-21, 1997.
Bhat, C. R., “Accommodating Variations in Responsiveness to Level-of-Service Measures in Travel Mode Choice Modeling, Transportation Research Part A, 32, pp. 495-507, 1998.
Bhat, C. R., “Incorporating Observed and Unobserved Heterogeneity in Urban Work Travel Mode Choice Modeling, Transportation Science, 34, pp. 228-238, 2000.
Bhat, C. R., “Quasi-random Maximum Simulated Likelihood Estimation of the Mixed Multinomial Logit Model, Transportation Research B, 35, pp. 677-693, 2001.
Blackwell, D. R., P. W. Miniard, and J. F. Eendel, Consumer Behavior, 9th ed., Harcourt, 2001.
Blundell, R. W. and J. L. Powell, “Endogeneity in Semiparametric Binary Response Models, The Review of Economic Studies, 71, pp. 655-679, 2004.
Bollen, K. A., Structural Equations with Latent Variables, New York: John Wiley ＆ Sons, 1989.
Bollen, K. A., “Latent Variables in Psychology and the Social Sciences, Annual Review of Psychology, 53, pp. 605-634, 2002.
Browstone, D. and K. Train, Forecasting new product penetration with flexible substitution patterns, Working paper, Dept. of Economics, University of California, Irvine, 1996.
Chintagunta, P. K., “Endogeneity and Heterogeneity in a Probit Demand Model：Estimation Using Aggregate Data, Management Science, 20(4), pp. 442-456, 2001.
Christ, C. F., Econometric Models and Methods, Wiley, New York, 1966.
Elrod, T. and M. P. Keane, “A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data, Journal of Marketing Research, 32(1), pp. 1-16, 1995.
Engel, J. F. et al., Comsumer Behavior, 7th ed., Chicago: Dryden, 1993.
Everitt, B. S., an Introduction to Latent Variable Models, Chapman and Hall, 1984.
Fischer, G.W. and D. Nagin, “Random vs. fixed coefficient quantal choice models: An empirical comparison, A Structural Analysis of Discrete Data with Econometric Applications, MIT Press, Cambridge, pp. 273-304, 1981.
Fornell, C. and D. Larcker, “Evaluating Structural Equation Models with Unobservable Variables and Measurement Errors, Journal of Marketing Research, 18(1), pp. 39-50, 1981.
Fujii, S., and R. Kitamura, “Evaluation of Trip-Inducing Effects of New Freeways Using A Structural Equations Model System of Commuters’ Time Use and travel, Transportation Research Part B, 34, pp. 339-354, 2000.
Green, P., “Hybrid Models for Conjoint Analysis: An Expository Review, Journal of Marketing Research, 21, pp. 155-169, 1984.
Golob, T. F., “Structural Equation Modeling for Travel Behavior Research, Transportation Research Part B, 37, pp. 1-25, 2003.
Gopinath, D. A., Model Heterogeneity in Discrete Choice Processes: Application to Travel Demand, Ph.D. Dissertation, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 1995.
Harris, K. M. and M. P. Keane, “A Model of Health Plan Choice: Inferring Preferences and Perceptions from a Combination of Revealed Preference and Attitudinal Data, Journal of Econometrics, 89, pp. 131-157, 1998.
Howard, J. A. and J. N. Sheth, the Theory of Buyer Behavior, pp. 30, 1969.
Hong, H. and E. Tamer, “Endogenous Binary Choice Model with Median Restrictions, Economics Letters, 80, pp. 219–225, 2003.
Hsiao, C., Analysis of Panel Data, Cambridge, UK: Cambridge University Press, 1986.
Jen, W. and K. C. Hu, “Application of Perceived Value Model to Identify Factor Affecting Passengers’ Repurchase Intentions on City Bus: A Case Study of the Taipei Metropolitan Area, Transportation, 30(3), pp.307-327, 2003.
Johnson, R. A. and Dean W. Wichern, Applied Multivariate Statistical Analysis, Prentice Hall, 1998.
Jreskog, K. G. and D. Sorbom, LISREL 8.14: Structural Equation Modeling with the SIMPLIS command language, Chicago: Scientific Software International, 1993.
Keane, M. P., “Modeling Heterogeneity and State Dependence in Consumer Choice Behavior, Journal of Business and Economic Statistics, 15(3), pp. 310-327, 1997.
Kettinger, W. J. and C. C. Lee, “Perceived Service Quality and User Satisfaction with the Information Service Function, Decision Sciences, 25, pp. 737-766, 1994.
Koppelman, F. and J. Hauser, “Destination Choice for Non-Grocery-Shopping Trips, Transportation Record, 673, pp. 157-165, 1979.
Kotler, P., Marketing Management: Analysis, Planning, Implementation and Control, 9th ed., Prentice-Hall, 1998.
Kotler, P., Marketing Management - The Millennium Edition, 10th ed., Upper Saddle River, NJ: Prentice-Hall International Editions, Prentice Hall, 2000.
Kuppam, A. R. and R. M. Pendyala, “A Structural Equations Analysis of Commuters’ Activity and Travel Pattern, Transportation, 28(1), pp. 33-54, 2001.
Madanat, S. M., C. Y. Yang, and Y-M Yen, “Analysis of Stated Route Diversion Intentions under Advanced Traveler Information Systems Using Latent Variable Modeling, Transportation Research Record, 1485, pp. 10-17, 1995.
McFadden, D., Rationality for Economists, Presented at the NSF Symposium on Eliciting Preferences, Berkeley, California, 1997.
McFadden, D., “Disaggregate Behavioral Travel Demand’s RUM Side: A 30-Year Retrospective, presented at the International Association of Travel Behavior Research (IATBR) Conference, Gold Coast, Queensland, Australia, 2000.
McFadden, D. and K. Train, “Mixed MNL models for discrete response, Journal of Applied Econometrics, 15(5), pp. 447-470, 2000.
Morikawa, T., M. Ben-Akiva, and D. McFadden, Incorporating Psychomeric Data in Econometric Choice Models, Working paper, Massachusetts Institute of Technology Press, 1996
Morikawa, T., M. Ben-Akiva, and D. McFadden, “Discrete Choice Models Incorporating Revealed Preferences and Psychometric Data, Econometric Models in Marketing, 16, pp. 29-55, 2002.
Nicosia, M., and Francesco, Marketing and Advertising Implication, Prentice-Hall Inc, pp. 29, 1968.
Olson, J. M. and M. P. Zanna, “Attitudes and Attitude Change, Annual Review of Psychology, 44, pp. 117-154, 1993.
Peter, J. P. and J. C. Olson, Consumer Behavior and Marketing Strategy, 5th ed., Irwin, CA: McGraw-Hill companies, Inc., 1999.
Petrin, A., and K. Train, “Omitted Product Attributes in Discrete Choice Models, Working paper NBER, 2003.
Polydoropoulou, A., Modeling User Response to Advanced Traveler Information Systems (ATIS), Ph.D. Dissertation, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 1997.
Prashker, J. A., “Mode Choice Models with Perceived Reliability Measures, Transportation Engineering Journal, 105 TE3, pp. 251-262, 1979.
Prashker, J. A., “Scaling Perceptions of Reliability of Urban Travel Modes Using Indscal and Factor Analysis Methods, Transportation Research A, 13, pp. 203-212, 1979.
Proni, P., and D. A. Hensher, “Measuring Service Quality in Scheduled Bus Service, Journal of Public Transportation, 3(2), pp. 51-74, 2002.
Raykov, T. and G. A. Marcoulides, a First Course in Structural Equation Modeling, Mahwah, NJ: Lawrence Erlbaum Associates, Inc., 2000.
Raykov, T. and G. A. Marcoulides, “Can There Be Infinitely Many models Equivalent to a Given Covariance Structure Models?, Structural Equation Modeling, 8, pp.142-149, 2001.
Simma, A. and K. W. Axhausen, “Structures of Commitment in Mode Use: A Comparison of Switzerland, Germany and Great Britain, Transport Policy, 8, pp.279-288, 2001.
Sgroi, D., “The Right Choice at the Right Time: A Herding Experiment in Endogenous Time, Experimental Economics, 6, pp. 159-180, 2003.
Taylor, S., “Waiting for Service: The Relationship between Delays and Evaluations of Service, Journal of Marketing, 58(2), pp. 55-69, 1994.
Train, K. E., Discrete Choice Method with Simulation, Forthcoming, Cambridge University Press, 2003.
Tripp, C. and T. D. John, “Selecting and Promoting Service Encounter Elements in Passerenger Rail Transportation, The Journal of Services Marketing, 16(5), pp. 432-476, 2002.
Villas-Boas, J. M., and R. S. Winer, “Endogeneity in Brand Choice Models, Management Science, 45(10), pp. 1324-1338, 1999.
Vovsha, P., “The cross-nested logit model: Application to mode choice the Tel-Aviv metropolitan area, Transportation Research Record, 1607, pp. 6-15, 1997.
Walker, J. L., Extended Discrete Choice Model: Integrated Framework, Flexible Error Structures, and Latent Variables, Ph.D. Dissertation, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 2001.
Walker, J. L. and M. Ben-Akiva, “Generalized Random Utility Model, Mathematical Social Sciences, 43 (1), pp. 303-343, 2002.
Wen, C. H. and F. S Koppelman, “The Generalized Nested Logit Model, Transportation Research B, 35, pp. 627-641, 2001