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研究生: 但漢唐
Han-Tang Dan
論文名稱: 線上商品評論對消費者商品態度的影響- 以商品類別、主觀知識與商品涉入為干擾變項
How online product reviews influence consumers’ product attitude – the moderating role of product type, subjective knowledge, and product involvement
指導教授: 陳炫碩
Shiuann-Shuoh Chen
陳德釗
Der-Chao Chen
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 企業管理學系
Department of Business Administration
論文出版年: 2016
畢業學年度: 105
語文別: 中文
論文頁數: 93
中文關鍵詞: 線上商品評論負面偏誤商品類別主觀知識商品涉入
外文關鍵詞: Online product reviews, negativity bias, product type, subjective knowledge, product involvement
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  •   隨著網路日益發達,使消費者在做購買決策時所需要參考的商品資訊來源更多樣。同時為了降低對於商品的品質不確定性,人們傾向在網路上尋找其他已購買此商品的消費者所撰寫之線上商品評論。根據文獻探討,消費者在瀏覽線上商品評論時,其評論的影響力會因為其評論方向而有所不同而產生偏誤。本研究主張線上商品評論的負面偏誤並非皆存在於各種情況,其負面偏誤關係會因為眾多因素而產生變化。
      本研究根據Nelson(1970; 1974)對商品分類的方式,將商品分為搜尋性商品與經驗性商品,探討在不同商品類別之下,評論方向對消費者商品態度影響的負面偏誤關係之差異;並且主張線上商品評論之負面偏誤關係會由於消費者之商品涉入程度與主觀商品知識程度不同而有差異。
      透過實驗設計各種情境並發放實體問卷,有效問卷共計296份。模型驗證部分,本研究使用SPSS 22、Amos 22與SmartPLS(v3.2.4)統計軟體分析各路徑之影響關係,結果顯示:(1)整體而言,線上商品評論對消費者商品態度的影響之負面偏誤確實存在。(2)在同樣程度的商品涉入之下,搜尋性商品的負面偏誤比經驗性商品更為顯著。(3)主觀商品知識程度並無顯著的干擾作用存在。(4)在經驗性商品之下,商品涉入程度對負面偏誤有顯著的負向干擾效果,即商品涉入越高,負面偏誤越小;搜尋性商品下,商品涉入程度對負面偏誤的干擾作用並不顯著。


     As internet and technology advance rapidly, the diversity of product information source that consumers require when making purchase decision is much more than be-fore. For reducing the uncertainty of the product’s quality, people tend to seek online product reviews that written by consumers who had purchased the product. From pre-vious studies, the effect of reviews would vary due to the review valence. This article argues that the negativity bias of online product reviews cannot be universally applied, the relationship would vary due to lots of factors instead.
     According to Nelson (1970; 1974), products can be classified into search goods and experience goods, this paper examines and compares the negativity bias of online product reviews of different product types. We also suggest that the negativity bias would vary because of different product involvement and subjective knowledge.
     By designing different senarios of our experiment, data was then collected through entity questionnaire and 296 effective responses were collected. Statistical softwares such as SPSS 22, Amos 22 and SmartPLS(v3.2.4) were used for analyzing purposes. Results from our experiments imply that (1) the negativity bias of online product re-views on consumers’ product attitude does exist significantly overall. (2) Specifically, given the degree of product involvement, the negativity bias of search goods is signifi-cantly higher than that of experience goods. (3) Subjective knowledge has no signifi-cant moderating effect on negativity bias. (4) For experience goods, product involve-ment has a significant negative moderating effect on negativity bias, but there’s no moderating effect on negativity bias for search goods.

    中文摘要 …………………………………………………………... ii 英文摘要 …………………………………………………………... iii 目錄 …………………………………………………………... iv 表目錄 …………………………………………………………... vi 圖目錄 …………………………………………………………... viii 第壹章 緒論……………………………………………………... 1   第一節  研究背景與動機……………………………………….... 1   第二節  研究目的與問題………………………………………… 3   第三節  研究範圍與限制………………………………………… 4   第四節  研究流程……………………………..………………… 5 第貳章 文獻探討………………………………………………... 6   第一節  評論方向與消費者的商品態度…………………………... 6   第二節  商品類別……………………..………………………… 7   第三節  商品知識……………..………………………………… 9   第四節  商品涉入……………………………..………………… 10 第參章 研究方法………………………………………………... 12   第一節  研究架構…………………………..…………………… 12   第二節  研究假說…………………………..…………………… 13   第三節  變數定義與操作………………….……………………... 13   第五節  問卷設計………………………...……………………... 18   第六節  資料蒐集……………………………………...………... 21   第七節  資料分析方式…………………………………………... 22 第肆章 資料分析………………………………………………... 24   第一節  前測之分析結果……………………………………….... 24   第二節  問卷回收………………………………..……………… 26   第三節  樣本基本資料分析……………………………………… 27   第四節  信度與效度分析………………………………………… 28   第五節  模型與假說驗證分析結果………...……………………... 31 第伍章 結論與建議……………………………………………... 45   第一節  研究結果與貢獻…………….…………………………... 45   第二節  管理意涵……………………………………………….. 48   第三節  研究限制與未來研究建議………..……………….……... 49 參考文獻 …………………………………………………………... 50 附錄一 …………………………………………………………... 60 附錄二 …………………………………………………………... 61 附錄三 …………………………………………………………... 65

    中文文獻
    1. 方世榮、張嘉雯 (2004)。顧客涉入程度對服務品質與關係品質之干擾效果-以電腦賣場與內部商店為例。中山管理評論,12(4),755-794。
    2. 吳明隆 (2009)。SPSS 操作與應用-問卷統計分析實務。五南圖書出版,台北。
    3. 李青峰 (1999)。產品涉入、品牌權益與市場特性對品牌評估與選擇的影響。國立成功大學企業管理研究所碩士論文。
    4. 汪志堅、黃營杉 (2001)。消費者產品知識對網際網路上商品資訊搜尋量之影響。企業管理學報 (51),109-138。
    5. 林南宏、王文正、邱聖媛、鍾怡君 (2007)。產品知識及品牌形象對購買意願的影響-產品類別的干擾效果。行銷評論,4(4),481-504。
    6. 張文琪 (2005)。線上購物資訊需求研究:產品類型與消費者產品知識議題。國立交通大學傳播研究所碩士論文。
    7. 張杏翎、林妙姿 (2015)。女性嬰兒潮世代保養品涉入程度對顧客價值影響之研究。美容科技學刊,12(1),35-65。
    8. 張珮芬 (2005)。iPod態度與忠誠度對Apple電腦其他商品之態度影響。國立政治大學國際經營與貿易學系研究所碩士論文。
    9. 陳正男、林素吟、丁學勤、詹琇蓉 (2004)。產品涉入、消費者特性與情境對網路購物的影響:風險的觀點。中華管理評論國際學報,7(1),106-125。
    10. 陳思吟 (2005)。網路負面經驗留言對消費者態度形成之影響。國立政治大學國際經營與貿易學系研究所碩士論文。
    11. 陳美芳 (2004)。檢視構念間關係之外顯調節效果的有效方法。國立交通大學經營管理研究所博士論文。
    12. 陳慧珊、黃汝華 (2010)。消費者的網路口碑選擇行為之研究。國立中正大學電訊傳播研究所碩士論文。
    13. 三星寫手門事件 (2015/12/13)。維基百科。造訪日期:2016年5月31日,取自:https://zh.wikipedia.org/wiki/三星寫手門事件

    英文文獻
    1. Arbuckle, J. L. (2010). IBM SPSS Amos 19 user’s guide. Crawfordville, FL: Amos Development Corporation.
    2. Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of marketing Research, 4(3), 291-295.
    3. Bae, S., & Lee, T. (2011). Product type and consumers’ perception of online con-sumer reviews. Electronic Markets, 21(4), 255-266.
    4. Baek, H., Ahn, J., & Choi, Y. (2012). Helpfulness of online consumer reviews: Readers' objectives and review cues. International Journal of Electronic Com-merce, 17(2), 99-126.
    5. Basuroy, S., Chatterjee, S., & Ravid, S. A. (2003). How critical are critical re-views? The box office effects of film critics, star power, and budgets. Journal of marketing, 67(4), 103-117.
    6. Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing letters, 2(2), 159-170.
    7. Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of general psychology, 5(4), 323-370.
    8. Beatty, S. E., & Smith, S. M. (1987). External search effort: An investigation across several product categories. Journal of consumer research, 14(1), 83-95.
    9. Bettman, J. R., & Park, C. W. (1980). Effects of prior knowledge and experience and phase of the choice process on consumer decision processes: A protocol anal-ysis. Journal of consumer research, 7(3), 234-248.
    10. Bone, P. F. (1995). Word-of-mouth effects on short-term and long-term product judgments. Journal of business research, 32(3), 213-223.
    11. Brinol, P., Petty, R. E., & Tormala, Z. L. (2004). Self-validation of cognitive re-sponses to advertisements. Journal of consumer research, 30(4), 559-573.
    12. Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral be-havior. Journal of Consumer research, 14(3), 350-362.
    13. Brucks, M. (1985). The effects of product class knowledge on information search behavior. Journal of consumer research, 12(1), 1-16.
    14. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, 43(3), 345-354.
    15. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
    16. Cho, J. (2006). The mechanism of trust and distrust formation and their relational outcomes. Journal of retailing, 82(1), 25-35.
    17. Connors, L., Mudambi, S. M., & Schuff, D. (2011). Is it the review or the review-er? A multi-method approach to determine the antecedents of online review help-fulness. In System Sciences (HICSS), 2011 44th Hawaii International Conference on System Sciences. IEEE Computer Society, 1-10.
    18. Dawson, S., & Kim, M. (2009). External and internal trigger cues of impulse buy-ing online. Direct Marketing: An International Journal, 3(1), 20-34.
    19. Dimoka, A., Hong, Y., & Pavlou, P. A. (2012). On product uncertainty in online markets: Theory and evidence. MIS Quarterly, 36(2), 395-426.
    20. Donthu, N., & Garcia, A. (1999). The internet shopper. Journal of Advertising Re-search, 39(3), 52-58.
    21. Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1-26.
    22. Ekelund, R. B., Mixon, F. G., & Ressler, R. W. (1995). Advertising and infor-mation: an empirical study of search, experience and credence goods.Journal of Economic Studies, 22(2), 33-43.
    23. Ellison, G., & Fudenberg, D. (1995). Word-of-mouth communication and social learning. The Quarterly Journal of Economics, 110(1), 93-125.
    24. Engel, J. F., & Blackwell, R. D. (1982). Consumer Behavior. New York: Holt.
    25. Engel, J.F., Blackwell,R.D., & Miniard,P.W.(1993), Consumer Behavior, 7th ed., New York: Dryden Press.
    26. Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications. Springer Verlag, New York.
    27. Feldman, S. (1966). Motivational aspects of attitudinal elements and their place in cognitive interaction. Cognitive consistency: Motivational antecedents and be-havioral consequences, 75-108. New York: Academic.
    28. Festinger, L. (1957). A Theory of Cognitive Dissonance. Stanford: Stanford Uni-versity Press.
    29. Fiske, S. T. (1980). Attention and weight in person perception: The impact of negative and extreme behavior. Journal of personality and Social Psychology, 38(6), 889-906.
    30. Floh, A., Koller, M., & Zauner, A. (2009). The impact of perceived valence, per-ceived information credibility and valence intensity of online reviews on purchase intentions. In 9th International Conference on Electronic Business, Macau, 257-264
    31. Floh, A., Koller, M., & Zauner, A. (2013). Taking a deeper look at online reviews: The asymmetric effect of valence intensity on shopping behaviour. Journal of Marketing Management, 29(5-6), 646-670.
    32. Flynn, L. R., & Goldsmith, R. E. (1999). A short, reliable measure of subjective knowledge. Journal of business research, 46(1), 57-66.
    33. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
    34. Fornell, C., & Larcker, D. F. (1987). A second generation of multivariate analysis: Classification of methods and implications for marketing research. Review of mar-keting, 51(1), 407-450.
    35. Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the associa-tion for information systems, 4(7) 1-70.
    36. Gelman, A., Carlin, J. B., Rubin, D. B., & Stern, H. S. (2004). Bayesian data analysis, 2nd ed. Boca Raton, FL : Chapman and Hall.
    37. Gilly, M. C., Graham, J. L., Wolfinbarger, M. F., & Yale, L. J. (1998). A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science, 26(2), 83-100.
    38. Hair J.F., Anderson R.E., Tatham R.L., Black, W.C. (1992). Multivariate Data Analysis with Readings, 3rd edn. Macmillan, New York.
    39. Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2013). A primer on par-tial least squares structural equation modeling (PLS-SEM). Sage Publications.
    40. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bul-let. Journal of Marketing theory and Practice, 19(2), 139-152.
    41. Hair, J.F. Jr., Anderson, R.E., Tatham, R.L., Black, W.C. (1998). Multivariate Da-ta Analysis (5th ed.). Englewood Cliffs, NJ:Prentice-Hall.
    42. Hempel, D.J. (1969). Search Behavior and Information Utilization in the Home Buying Process, Marketing Involvement in Society and the Economy, ed. P. R. McDonald, Chicago: American Marketing Association, 241-249.
    43. Homer, P. M., & Yoon, S. G. (1992). Message framing and the interrelationships among ad-based feelings, affect, and cognition. Journal of Advertising, 21(1), 19-33.
    44. Hu, N., Liu, L., & Zhang, J. J. (2008). Do online reviews affect product sales? The role of reviewer characteristics and temporal effects. Information Technology and Management, 9(3), 201-214.
    45. Ito, T. A., Larsen, J. T., Smith, N. K., & Cacioppo, J. T. (1998). Negative infor-mation weighs more heavily on the brain: the negativity bias in evaluative catego-rizations. Journal of personality and social psychology, 75(4), 887-900.
    46. Jiang, B., & Srinivasan, K. (2015). Pricing and persuasive advertising in a differ-entiated market. Marketing Letters. Advance online publication. doi: 10.1007/s11002-015-9370-1
    47. Johnson, E. J., & Russo, J. E. (1984). Product familiarity and learning new infor-mation. Journal of consumer research, 11(1), 542-550.
    48. Jones, E. E. (1972). Attribution: Perceiving the causes of behavior. Morristown, NJ: General Learning Press.
    49. Katz, E., & Lazarsfeld, P. (1955). Personal Influence: The Part Played by People in the Flow of Mass Communications. New York: The Free Press.
    50. Klein, L. R. (1998). Evaluating the potential of interactive media through a new lens: Search versus experience goods. Journal of business research, 41(3), 195-203.
    51. Krugman, H. E. (1965). The impact of television advertising: Learning without involvement. Public opinion quarterly, 29(3), 349-356.
    52. LaRose, R. (2001). On the negative effects of e‐commerce: A sociocognitive ex-ploration of unregulated on‐line buying. Journal of Computer‐Mediated Commu-nication, 6(3), 1-26.
    53. LaRose, R., & Eastin, M. S. (2002). Is online buying out of control? Electronic commerce and consumer self-regulation. Journal of Broadcasting & Electronic Media, 46(4), 549-564.
    54. Lee, M., Rodgers, S., & Kim, M. (2009). Effects of valence and extremity of eWOM on attitude toward the brand and website. Journal of Current Issues & Research in Advertising, 31(2), 1-11.
    55. Levin, A. M., Levin, I. P., & Weller, J. A. (2005). A multi-attribute analysis of preferences for online and offline shopping: Differences across products, consum-ers, and shopping stages. Journal of Electronic Commerce Research, 6(4), 281-290.
    56. Lewicki, R. J., McAllister, D. J., & Bies, R. J. (1998). Trust and distrust: New re-lationships and realities. Academy of management Review, 23(3), 438-458.
    57. Li, X., & Hitt, L. M. (2008). Self-selection and information role of online product reviews. Information Systems Research, 19(4), 456-474.
    58. Lynch Jr, J. G., & Ariely, D. (2000). Wine online: Search costs affect competition on price, quality, and distribution. Marketing Science, 19(1), 83-103.
    59. McClelland, G. H., & Judd, C. M. (1993). Statistical difficulties of detecting in-teractions and moderator effects. Psychological bulletin, 114(2), 376-389.
    60. McWilliams, A., & Siegel, D. (2001). Corporate social responsibility: A theory of the firm perspective. Academy of management review, 26(1), 117-127.
    61. Moon, J., Chadee, D., & Tikoo, S. (2008). Culture, product type, and price influ-ences on consumer purchase intention to buy personalized products online. Jour-nal of Business Research, 61(1), 31-39.
    62. Mudambi, S. M., & Schuff, D. (2010). What makes a helpful review? A study of customer reviews on Amazon. com. MIS Quarterly, 34(1), 185-200.
    63. Nelson, P. (1970). Information and consumer behavior. Journal of political econ-omy, 78(2), 311-329.
    64. Nelson, P. (1974). Advertising as information. Journal of political economy, 82(4), 729-754.
    65. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
    66. Ou, C. X., & Sia, C. L. (2010). Consumer trust and distrust: An issue of website design. International Journal of Human-Computer Studies, 68(12), 913-934.
    67. Park, C. W., & Lessig, V. P. (1981). Familiarity and its impact on consumer deci-sion biases and heuristics. Journal of consumer research, 8(2), 223-231.
    68. Park, C. W., Feick, L., & Mothersbaugh, D. L. (1992). Consumer Knowledge As-sessment: How Product Experience and Knowledge of Brands, Attributes, and Features Affects What We Think We Know. Advances in Consumer Research, 19(1), 193-198.
    69. Park, C., & Lee, T. M. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business research, 62(1), 61-67.
    70. Petty, R. E., & Cacioppo, J. T. (1979). Issue involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of person-ality and social psychology, 37(10), 1915-1926.
    71. Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of consumer research, 10(2), 135-146.
    72. Punj, G. N., & Staelin, R. (1983). A model of consumer information search behav-ior for new automobiles. Journal of consumer research, 13(4), 366-380.
    73. Raju, P. S., Lonial, S. C., & Mangold, W. G. (1995). Differential effects of sub-jective knowledge, objective knowledge, and usage experience on decision mak-ing: An exploratory investigation. Journal of consumer psychology, 4(2), 153-180.
    74. Ratchford, B. T., Lee, M. S., & Talukdar, D. (2003). The impact of the Internet on information search for automobiles. Journal of Marketing research, 40(2), 193-209.
    75. Ratneshwar, S., & Chaiken, S. (1991). Comprehension's role in persuasion: The case of its moderating effect on the persuasive impact of source cues. Journal of Consumer Research, 18(1), 52-62.
    76. Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and social psychology review, 5(4), 296-320.
    77. Sarstedt, M., Henseler, J., Ringle, C.M. (2011). Multi-group analysis in partial least squares (PLS) path modeling: alternative methods and empirical results. Ad-vances in International Marketing, 22(1), 195-218.
    78. Selnes, F., & Troye, S. V. (1989). Buying expertise, information search, and prob-lem solving. Journal of Economic Psychology, 10(3), 411-428.
    79. Sen, S., & Lerman, D. (2007). Why are you telling me this? An examination into negative consumer reviews on the web. Journal of interactive marketing, 21(4), 76-94.
    80. Sheffet, M. J. (1983). An experimental investigation of the documentation of ad-vertising claims. Journal of Advertising, 12(1), 19-29.
    81. Sherif, M., & Hovland, C. I. (1961). Social judgment: Assimilation and contrast effects in communication and attitude change. New Haven, CT: Yale University Press.
    82. Skowronski, J. J., & Carlston, D. E. (1989). Negativity and extremity biases in impression formation: A review of explanations. Psychological bulletin, 105(1), 131-142.
    83. Smith, D. C., & Park, C. W. (1992). The effects of brand extensions on market share and advertising efficiency. Journal of Marketing Research, 29(3), 296-313.
    84. Spiegelhalter D., Thomas A., Best N. & Lunn D. (2003) WinBUGS user manual V1.4. Retrieved June 2, 2016, from http://www.mrc-bsu.cam.ac.uk/software/bugs.
    85. Spool, J. M. (2009). The magic behind amazon’s 2.7 billion dollar question. Re-trieved April 2, 2016, from http://www.uie.com/articles/magicbehindamazon/ .
    86. Swinyard, W. R. (1993). The effects of mood, involvement, and quality of store experience on shopping intentions. Journal of Consumer Research, 20(1), 271-280.
    87. Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth ver-sus traditional marketing: findings from an internet social networking site. Journal of marketing, 73(5), 90-102.
    88. Willemsen, L. M., Neijens, P. C., Bronner, F., & de Ridder, J. A. (2011). “Highly Recommended!” The content characteristics and perceived usefulness of online consumer reviews. Journal of Computer‐Mediated Communication, 17(1), 19-38.
    89. Williams, L. M., Gatt, J. M., Grieve, S. M., Dobson-Stone, C., Paul, R. H., Gor-don, E., & Schofield, P. R. (2010). COMT Val 108/158 Met polymorphism ef-fects on emotional brain function and negativity bias. Neuroimage, 53(3), 918-925.
    90. Yin, D., Bond, S., & Zhang, H. (2014). Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Quarterly, 38(2), 539-560.
    91. Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of con-sumer research, 12(3), 341-352.
    92. Zaichkowsky, J. L. (1986). Conceptualizing involvement. Journal of advertising, 15(2), 4-34.
    93. Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revi-sion, and application to advertising. Journal of advertising, 23(4), 59-70.
    94. Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of personality and social psychology, 9 (2, part 2), 1-27.
    95. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of marketing, 52(1), 2-22.
    96. Zhang, J. Q., Craciun, G., & Shin, D. (2010). When does electronic word-of-mouth matter? A study of consumer product reviews. Journal of Business Re-search, 63(12), 1336-1341.

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