臺灣博碩士論文加值系統

隨著網路的興起，購物的方式也逐漸改變。多數消費者從實體店面購買，逐漸轉為網路購物。不過，網路購物雖然方便，卻仍有風險。線上瀏覽商品無法觸摸到商品本質，也無法進行體驗，只能從商品敘述、圖像或是他人的評論來評估是否購買。因此，如果收到的產品不符合原先期待，或是有運送錯誤等的問題存在時，退貨的情形就會發生。隨著購物型態的改變，退貨的情形也日趨嚴重，如何面對高退貨率的問題，必須進一步了解退貨者的退貨原因、購買動機，以及購物與退貨之間的關係。
然而，過去的網路購物文獻主要多探討退貨政策、購買評論與衝動購買的主題，或是針對服飾產業進行分析。亞太地區線上購物者最常購買的產品類別中，家用電器和電子產品占39%。本研究瀏覽過去文獻後發現，家用電器較少被研究提及並深入討論的產品類別，因此針對家電產業進行研究。本研究透過文獻探討提出三項假設，並建構購買動機量表與退貨原因量表，以問卷的形式進行資料蒐集，運用變異數分析來驗證三個假說。
研究的結果發現，較少在網路上購買家用電器的人退貨率越高，較常在網路上購買家用電器者的人退貨率卻越低。另外，研究證明不同退貨率的人，他們購買家用電器的動機不同，退貨的原因也不相同。因此，網路購物業者可以透過本研究提出的購物動機與退貨原因，針對不同退貨率的人設計網路購物與退貨政策，藉此解決高退貨率的問題。

With the growth of the Internet, the way of shopping has changed gradually. Most consumption is changing to online shopping rather than physical store. Online shopping is convenient but still risky. Online browsing cannot touch the product, nor can be experienced. It can only be evaluated from the web description of the product, the image or other people’s comments. Therefore, if the received product does not meet the original expectations, or a shipping errors, etc., the return will occur. With the change of shopping style, the return situation will become more and more serious. To deal with the problem of high return rate, we must understand the return reason, purchase motivation, and the relationship between shopping and return.
In the past, online shopping literature focused on return policies, purchase reviews, and impulse purchases, as well as the apparel industry. Household appliances and electronics account for 39%, which is one of the most purchased product category for online shoppers in the Asia Pacific region. After reviewing the past literature, this study found that household appliances are rarely mentioned and discussed. Therefore, this study uses the home appliance industry to conduct online return behavior analysis.This study explores three hypotheses, constructs purchase motivation and return reason scale, collects data by questionnaire, and uses variance analysis to verify the three hypotheses.
The results found that the less home appliances the people buy, the more they return, the more home appliances the people buy, the less they return. In addition, the study shows that people with different return rates have different shopping motives and the reasons for return. Therefore, online shopping stores can solve the problem of high return rate by designing shopping and return policies for people with different return rates.

摘要 i
Abstract ii
目次 iii
表目次 iv
圖目次 v
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究方法 4
第四節 研究流程 5
第二章 文獻探討 7
第一節 影響退貨之因素 7
第二節 影響網路購物之動機 12
第三節 分析方法 16
第三章 理論背景與假說發展 23
第四章 研究設計 26
第一節 問卷設計 26
第二節 前測 30
第三節 抽樣設計與資料收集 31
第五章 資料分析 32
第一節 樣本結構分析 32
第二節 假說檢定 34
第六章 結論與建議 59
第一節 研究結果與討論 59
第二節 管理層面影響 67
第三節 研究限制與後續研究建議 68
參考書目 69
附錄 77

一、中文部分
王玉佩（2011）。電視購物頻道服務品質量表建構之研究。正修學報，24，193-212.
王瑞之（1996）。電子商務大未來，資訊與電腦，66-72。
吳明隆（2005）。SPSS統計應用學習實務：問卷分析與應用統計。台北市：知城。
吳明隆（2010）。論文寫作與量化研究。臺北市：五南。
吳明隆、涂金堂（2005）。SPSS 與統計應用分析。台北市：五南。
李城忠（2018）。應用統計學：SPSS & AMOS範例分析完全手冊。新北市：新文京。
周品均（2015）。2015退貨率多少才正常？5大因素評估退貨原因。取自https://www.smartm.com.tw/Article/31313234cea3
林佩蓁（2008）。服務品質、知覺風險、顧客滿意度與顧客忠誠度關係之研究─以台灣網路書店為例（碩士論文）。取自華藝線上圖書館。（系統編號10.6846/TKU.2008.00931）
林傑斌、林川雄、馮兆康（2011）。SPSS統計分析與實務。新北市：博碩文化。
林震岩（1997）。產品型態與訊息呈現方式對網路購物行為影響之研究。第九屆資訊管理學術研討會。
林震岩（2018）。多變量分析：SPSS的操作與應用。台北市：智勝文化。
邱浩政（2000）。量化研究與統計分析。臺北市：五南。
邱浩政（譯）（2010）。量表編制理論與應用。（原作者：Robert F. DeVellis）。台北市：五南。
洪沚君（2013）。服務創新對顧客購買動機與顧客滿意度影響之研究—以Yahoo!奇摩購物中心為例（碩士論文）。取自台灣碩博士論文系統。
消費者保護法（1994年1月11日）。
張芳全（2008）。問卷就是要這樣編。台北市：心理。
陳正昌、程炳林、陳新豐、劉子鍵（2009）。多變量分析方法—統計軟體應用，第五版。台北市：五南。
蘇柏全、蔡宇智（2015）。網購退貨：顧客服務構面、產品構面、安全構面、退貨機率。電子商務研究，13（2），141-166。
二、西文部分
Ainscough, T. L., 1996. The Internet for the rest of us: marketing on the World Wide Web. Journal of consumer marketing, 13（2）, 36-47.
Alba J., John L., Barton W., Chris J., Richard L., Alan S. and Stacy W., 1997. Interactive home shopping : Consumer , Retailer, and manufacturer incentives to participate in electronic marketplaces , Journal of Marketing, 61, July, 38-53
Alba, J.W., & Hutchinson, J.W., 1987. Dimensions of consumer expertise. Journal of Consumer Research, 13（1）, 411-54.
Anastasi, A., 1988. Psychological Testing.（6th ed）. New York: Macmillan Publishing.
Anderson, E. T., Hansen, K., & Simester, D., 2009. The option value of returns: Theory and empirical evidence. Marketing Science, 28（3）, 405-423.
Appriss Retail, 2017. Consumer Returns in the Retail Industry. Retrieved fromhttps://appriss.com/retail/wp-content/uploads/sites/4/2017/12/2017_Consumer-Returns-in-the-Retail-Industry-Report.pdf
Asdecker, B., Karl, D., & Sucky, E., 2017. Examining Drivers of Consumer Returns in E-Tailing with Real Shop Data. In Proceedings of the 50th Hawaii International Conference on System Sciences.
Bahn, K. D., & Boyd, E., 2014. Information and its impact on consumers' reactions to restrictive return policies. Journal of Retailing and Consumer Services, 21（4）, 415-423.
Banjo, S., 2013. Rampant Returns Plague E-Retailers. The Wall Street Journal. Retrieved from https://www.wsj.com/articles/rampant-returns-plague-eretailers-1387752786
Barr, A., 2013. E-tailers embrace same-day delivery, but U.S. shoppers shrug – survey. Retrieved from https://www.reuters.com/article/etailers-delivery/e-tailers-embrace-same-day-delivery-but-u-s-shoppers-shrug-survey-idUSL1N0BWD3C20130305
Bechwati, N. N., & Siegal, W. S., 2005. The impact of the prechoice process on product returns. Journal of Marketing Research, 42（3）, 358-367.
Bellman, S., Lohse, G., & Johnson, E. J., 1999. Predictors of online buying behavior. Communications of the ACM, 42（12）, 32-38.
Bernon, M., Cullen, J., & Gorst, J., 2015. Online retail returns management: Integration within an omni-channel distribution context. International Journal of Physical Distribution & Logistics Management. 46（6/7）, 584-605.
Blanchard, D., 2005. Moving forward in reverse Logistics. Material Handling & Logistics. Retrieved from https://www.mhlnews.com/transportation-amp-distribution/moving-forward-reverse.
Blanchard, D., 2007. Supply chains also work in reverse. Industry Week/IW, 256（5）, 48-49.
Bonifield, C., Cole, C., & Schultz, R. L., 2010. Product returns on the internet: a case of mixed signals? Journal of Business Research, 63（9-10）, 1058-1065.
Bonifield, Carolyn, Catherine Cole, and Randall L. Schultz., 2002. Product Returns on the Internet: A Case of Mixed Signals? Working paper, Market Department, University of Vermont.
Brohan, M., 2005. Online retailers learn to live with that persistent problem of returns. Digital commerce 360. Retrieved from https://www.digitalcommerce360.com/2005/09/01/online-retailers-learn-to-live-with-that-persistent-problem-of-r/
Brusch, M., & Stüber, E., 2014. Developments and Classifications of Online Shopping Behavior in Germany. International Journal of Cyber Society and Education, 7（2）, 147-156.
Cao, X., & Mokhtarian, P. L., 2005. How do individuals adapt their personal travel? A conceptual exploration of the consideration of travel-related strategies. Transport Policy, 12（3）, 199-206.
Cattell, R. B., 1966. The scree test for the number of factors. Multivariate behavioral research, 1（2）, 245-276.
Charlton, G., 2018. Ecommerce Returns: 2018 Stats and Trends. Retrieved from: https://blog.salecycle.com/featured/ecommerce-returns-2018-stats-trends/
Chiang, K. P., & Dholakia, R. R., 2003. Factors driving consumer intention to shop online: an empirical investigation. Journal of Consumer psychology, 13（1-2）, 98-105.
Cho, H. and Fiorito, S.S., 2009. Acceptance of online customisation for apparel shopping. International Journal of Retail & Distribution Management, 37（5）, 389-407.
Chu, S. C., & Sung, Y., 2015. Using a consumer socialization framework to understand electronic word-of-mouth (eWOM) group membership among brand followers on Twitter. Electronic Commerce Research and Applications, 14（4）, 251-260.
Davis, S., Hagerty, M., & Gerstner, E., 1998. Return policies and the optimal level of “hassle”. Journal of Economics and Business, 50（5）, 445-460.
De, P., Hu, Y., & Rahman, M. S., 2013. Product-oriented web technologies and product returns: An exploratory study. Information Systems Research, 24（4）, 998-1010.
DeVellis R. F., 1991. Scale Development: Theory and Applications, Applied Social Research Method Series, 26, Newbury Park, California: Sage Publications.
Dholakia, R., Zhao, M., Dholakia, N., 2005. Multi-channel retailing: A case study of early experiences. Journal of Interactive Marketing, 19（2）, 64-74.
Dillon, T. D., and Reif, H. L., 2004. Factors influencing consumer‟s e-commerce commodity purchases. Information Technology, Journal of Learning and Performance, 22（2）, 1-12.
Dimoka, A., Hong, Y., & Pavlou, P. A., 2012. On product uncertainty in online markets: Theory and evidence. MIS quarterly, 36（2）, 395-426
Ding, Y., Xu, H., & Tan, B. C., 2016. Predicting Product Return rate with" Tweets". In PACIS（p. 345）.
Dodds, W. B., Monroe, K. B., & Grewal, D., 1991. Effects of price, brand and store information on buyers’ product evaluations. Journal of Marketing Research, 28, 307-319.
Eastlick, M. A., & Feinberg, R. A., 1999. Shopping motives for mail catalog shopping. Journal of Business Research, 45（3）, 281-290.
Foscht, T., Ernstreiter, K., Maloles, C., Sinha, I., & Swoboda, B., 2013. Retaining or returning? Some insights for a better understanding of return behaviour. International Journal of Retail & Distribution Management, 41（2）, 113-134.
Fu, Y., Liu, G., Papadimitriou, S., Xiong, H., Li, X., & Chen, G., 2016. Fused latent models for assessing product return propensity in online commerce. Decision Support Systems, 91, 77-88.
Gillett, P.L., 1970. A profile of urban in-home shoppers. Journal of Marketing, 34（3）, 40-5.
Girard, T., Silverblatt, R., & Korgaonkar, P., 2002. Influence of product class on preference for shopping on the internet. Journal of Computer-Mediated Communication, 8（1）, JCMC815.
Goldsmith, R. E., & Horowitz, D., 2006. Measuring motivations for online opinion seeking. Journal of interactive advertising, 6（2）, 2-14.
Grewal, D., Iyer, G. R., Krishnan, R., & Sharma, A., 2003. The Internet and the price–value–loyalty chain. Journal of Business Research, 56（5）, 391-398.
Grewal, D., Iyer, G.R., Levy, M., 2004. Internet retailing: Enablers, limiters, and market consequences. Journal of Business Research, 57（7）, 703-713.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L., 2006. Multivariate Data Analysis, 6. Upper Saddle River, NJ: Pearson Prentice Hall.
Hess, J. D., & Mayhew, G. E., 1997. Modeling merchandise returns in direct marketing. Journal of Direct Marketing, 11（2）, 20-35.
Hoffman, D. L., & Novak, T. P., 1996. Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing,（July）, 50-68.
Hong, Y., & Pavlou, P. A., 2014. Product fit uncertainty in online markets: Nature, effects, and antecedents. Information Systems Research, 25（2）, 328-344.
Ibrahim, S., & Suki, M. N., & Harun, A., 2014. Structural relationships between perceived risk and consumers unwillingness to buy home appliances online with moderation of online consumer reviews. Asian Academy of Management Journal,19（1）, 73-92.
Jasper, C.R. & Lan, P.-N.R., 1992. Apparel catalog patronage: demographic, lifestyle and motivational factors. Psychology & Marketing, 9（4）, 275-96.
JDA and Centiro, 2015. Customer pulse report 2015: voice of the online customer, Centiro & JDA Software Group. Retrieved from http://now.jda.com/JDA-Customer-Pulse-Report-2015-EN.html.
Jha, M., Kemper, J., & Brettel, M., 2019. Product Uncertainty in Online Markets: The Influence of Situational Factors and Individual Characteristics on Purchase Decision Reversal. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
Jiménez, F. R., & Mendoza, N. A., 2013. Too popular to ignore : The influence of online reviews on purchase intentions of search and experience products. Journal of Interactive Marketing, 27, 226-235.
Kaiser, H. F., 1974. An index of factorial simplicity. Psychometrics, 39, 31-36.
Kalakota, R. and Whinston, A.B., 1996. Frontier of Electronic Commerce. Addison-Wesley, New York.
Kang, M., & Johnson, K., 2009. Identifying characteristics of consumers who frequently return apparel. Journal of Fashion Marketing and Management: An International Journal, 13（1）, 37-48.
Kerlinger, Fred N., 1973. Foundations of Behavioral Research. CBS International Editions.
Klein, Lisa R., 1998. Evaluating the Potential of Interactive Media through a New Lens: Search versus Experience Goods, Journal of Business Research, 41（March）: 195-203.
Kopalle, P.K., & D.R. Lehmann., 1995. The effects of advertised and observed quality on expectations about new product quality. Journal of Marketing Research, 32（3）, 280-290.
Levin, A. M., Levin, I. P., & Weller, J. A., 2005. A multi-attribute analysis of preferences for online and offline shopping: Differences across products, consumers, and shopping stages. Journal of Electronic Commerce Research, 6（4）.
Levin, A. M., Levin, I. R., & Heath, C. E., 2003. Product category dependent consumer preferences for online and offline shopping features and their influence on multi-channel retail alliances. Journal of Electronic Commerce Research, 4（3）, 85-93.
Liang, Ting-Pen and Jin-Shiang Huang, 1998. An Empirical Study on Consumer Acceptance of Products in Electronic Markets: A Transaction Cost Model. Decision Support System, 24, 29-43.
Lohse, G. L., & Spiller, P., 1998. Electronic shopping: how do customer interfaces produce sales on the Internet? Communications of the ACM, 41, 81-87.
Lynch, P. D., Kent, R. J., & Srinivasan, S. S., 2001. The global internet shopper: evidence from shopping tasks in twelve countries. Journal of advertising research, 41（3）, 15-23.
Mathwick, C., Malhotra, N., & Rigdon, E., 2001. Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment. Journal of retailing, 77（1）, 39-56.
Matthews, C., 2015. Top 10 Reasons for a Product Return. Retrieved from: https://chargeback.com/top-10-reasons-for-a-product-return/
Minnema, A., Bijmolt, T. H., Gensler, S., & Wiesel, T., 2016. To keep or not to keep : effects of online customer reviews on product returns. Journal of retailing, 92（3）, 253-267.
Morning consult, 2018. The state of retail 2018. Retrieved from https://static1.squarespace.com/static/52ca9f04e4b083e90ec41c17/t/5a5604b0e2c483133c606b74/1515586774360/white+paper+ENG.pdf
Noble, S. M., Griffith, D. A., & Adjei, M. T., 2006. Drivers of local merchant loyalty: Understanding the influence of gender and shopping motives. Journal of retailing, 82（3）, 177-188.
Nord, W.R. and Peter, P.J., 1980. A behavior modification perspective on marketing. Journal of Marketing, 44（2）, 36-47.
Parasuraman, A., Zeithaml, V. A., & Malhotra, A., 2005. ES-QUAL: a multiple-item scale for assessing electronic service quality. Journal of service research, 7（3）, 213-233.
Park, J. and Stoel, L., 2005. Effect of brand familiarity, experience and information on online apparel purchase. International Journal of Retail & Distribution Management, 33（2）, 148-60.
Peck, J., Childers, T.L., 2003. To have and to hold: The influence of haptic information on product judgments. Journal of Marketing, 67（2）, 35-48.
Pei, Z., Paswan, A., & Yan, R., 2014. E-tailer’ s return policy, consumer's perception of return policy fairness and purchase intention. Journal of Retailing and Consumer Services, 21（3）, 249-257.
Petersen, J.A. & Kumar, V., 2009. Are product returns a necessary evil? Antecedents and consequences. Journal of Marketing, 73（3）, 35-51.
Peterson, R. A., Balasubramanian, S., & Bronnenberg, B. J., 1997. Exploring the implications of the Internet for consumer marketing. Journal of the Academy of Marketing science, 25（4）, 329.
Punj, G. N., & Staelin, R., 1983. A model of consumer information search behavior for new automobiles. Journal of Consumer Research , 9（Mar）, 366-380.
Ramanathan, R., 2011. An empirical analysis on the influence of risk on relationships between handling of product returns and customer loyalty in E-commerce. International Journal of Production Economics, 130（2）, 255-261.
Ryder, 2010. Reverse logistics: From black hole to untapped revenue stream. Logistics Management. Retrieved from https://www.logisticsmgmt.com/article/reverse_logistics_from_black_hole_to_untapped_revenue_stream
Sahoo, N., Srinivasan, S., & Dellarocas, C., 2018. The impact of online product reviews on product returns and net sales. The information systems Research, 29（3）, 525-777.
Scansaroli, J. A., & Eng, V., 1997. Interactive retailing: Consumers online. Chain Store Age, 73（1）, 5A-8A
Scansaroli, J. A., 1997. Interactive retailing ,the threat, the opportunity: Imagine this; Wired Kingdom, Chain Store Age, Jan. 2A-4A.
Scitovszky, T., 1945. Some consequences of the habit of judging quality by price. Review of Economic Studies, 12（Winter）, 100-105.
Sharma, S., 2008. Online shopping in Asia/Pacific-Patterns, trends and future growth. Master Card Worldwide Insights. Retrieved from http://www.mastercard.com/us/company/en/insights/pdfs/2008/Asia_Pacific_Online_Shop.pdf
Sheth, J.N., 1983. An integrative theory of patronage preference and behavior, in Darden, W.R. and Lusch, R.F.（Eds）. Patronage Behavior and Retail Management, North-Holland, New York, NY, pp. 9-28.
Shulman, J. D., Coughlan, A. T., & Savaskan, R. C., 2009. Optimal restocking fees and information provision in an integrated demand-supply model of product returns. Manufacturing & Service Operations Management, 11（4）, 577-594.
Shulman, J. D., Cunha Jr, M., & Saint Clair, J. K., 2015. Consumer uncertainty and purchase decision reversals: Theory and evidence. Marketing Science, 34（4）, 590-605.
Spar, D., & Bussgang, J., 1996. Ruling commerce in the networld. Journal of Computer-Mediated Communication, 2（1）, JCMC215.
Swinyard, W. R., & Smith, S. M., 2003. Why people（don't）shop online: A lifestyle study of the internet consumer. Psychology & marketing, 20（7）, 567-597.
Teo, T. S., 2002. Attitudes toward online shopping and the Internet. Behaviour & Information Technology, 21（4）, 259-271.
Utter, D.A., 2013. Shop.org asks if business should rush to same-day delivery. EcommerceBytes. Retrieved from http://www.ecommercebytes.com/cab/cab/abn/y13/m04/i15/s04.
Wee, K. N., & Ramesh, R., 1999. Cyber buying in China, Hong Kong and Singapore: tracking the profile of online buyers. Paper presented at the Conference on the Measurement of Electronic Commerce. p. 6-8.
Wood, S. L., 2001. Remote purchase environments: the influence of return policy leniency on two-stage decision processes, Journal of Marketing Research, 38（2）, 157-169.