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    题名: 探討個人評論、綜合評分與評論數量如何影響線上消費者評論說服性與採用意圖—簡則系統式模型的應用
    Examining the Effects of Individual Review, Aggregated Rating, and Review Quantity on Perceived Persuasiveness and Intention to Adopt Online Consumer Reviews: An Application of the Heuristic-Systematic Model
    作者: 李家安
    Lee, Chia-An
    贡献者: 林芝璇
    Lin, Jhih-Syuan
    李家安
    Lee, Chia-An
    关键词: 雙重路徑資訊處理模式
    簡則系統式模型
    線上消費者評論
    個人評論
    綜合評分
    效價
    評論數量
    說服性
    採用意圖
    Dual-process theory
    Intention to adopt
    Aggregated rating
    Valance
    Perceived persuasiveness
    Review quantity
    HSM
    Individual review
    Online consumer reviews
    日期: 2021
    上传时间: 2021-11-01 12:21:24 (UTC+8)
    摘要: 近年人們已習慣在各種消費決策前，試著以網路查詢其他消費者的經驗與評價，除了早期人們所依賴的論壇、討論區、部落格等資訊管道，近年提供各類商品或服務評論的第三方評論平台出現，人們可以因應不同需求到特定資訊管道查找相關的線上消費者評論。線上消費者評論作為電子口碑的一種形式，十分常見提供個人評論與綜合評分兩種資訊給消費者作參考，兩者資訊之間的交互影響也是近年學界常見的討論主題。
    為了更進一步比較兩者所提供訊息線索的影響力，本研究以雙重路徑資訊處理模式的簡則系統式模型作為理論背景，釐清兩種資訊面的說服性如何受到個人評論效價、綜合評分效價與評論數量等三個線索所交互影響，形成整體線上消費者評論的說服性，並影響到採用意圖。本研究採用實驗法，以2(個人評論正/負)x2(綜合評分高/低)x 2(評論數量多/寡)的三因子實驗，分別於私立世新大學以及國立政治大學共計14堂課程中進行受試者招募與研究流程，共計取得247份有效問卷。
    本研究結果顯示，正面評價的影響力會透過系統式線索的個人評論效價以及簡則式線 索的綜合評分效價，直接影響個人評論說服性，而簡則式線索的評論數量則會直接影響綜合評分說服性。此外，個人評論效價與綜合評分效價的交互作用分別會對個人評論說服性與綜合評分說服性產生影響力，本研究亦討論效價一致與不一致的情況所產生的加乘效果、稀釋效果以及偏誤效果。論個人評論說服性與綜合評分說服性的比較，綜合評分說服性對線上消費者評論說服性的影響力更大，並且能夠預測線上消費者評論的採用意圖。本研究結果對學術與實務上，理解台灣消費者閱讀線上消費者評論的資訊處理過程具有重要參考價值。
    In recent years, people have relied on online consumer reviews when making purchase decisions. As a form of electronic word-of-mouth, online consumer reviews provide two kinds of information, individual reviews and aggregated ratings. However, the understanding of the persuasiveness of these information effects on consumer purchase decisions is still vague. This study applies the heuristic-systematic model to clarify the information process through individual reviews and aggregated ratings, focusing on the effects of individual reviews, aggregated rating, and review quantity on perceived persuasiveness and intention to adopt online consumer reviews. A three-factor experiment, combined with 2 (positive/negative individual reviews) x 2 (high/low aggregated rating) x 2 (large/few reviews quantity), was conducted in this research. The experiment recruitment and process were conducted during 14 classes from Shih Hsin University and National Chengchi University. A total of 247 valid responses were included for data analysis. The findings show that positive cues will directly affect the persuasiveness of individual reviews through both positive individual reviews and high aggregated ratings. However, only the quantity of reviews will directly affect the persuasiveness of aggregated ratings. On the other hands, the interaction of valence between individual reviews and aggregated ratings will directly influence the persuasiveness of both individual reviews and aggregated ratings. In this case, three kinds of hypothesis were discussed, additivity hypothesis , attenuation hypothesis, and bias hypothesis. Furthermore, compared to the persuasiveness of individual reviews and aggregated ratings, the latter has a greater impact on the persuasiveness of online consumer reviews, which is proven to predict the adoption intention of online consumer reviews. The results of this study could be discussed with theoretical and practical implications.
    參考文獻: 中文文獻
    吳統雄，1985。態度與行為研究的信度與效度：理論, 應用, 反省。民意學術專刊，夏季號，29-53。
    徐淑如、董和昇、柳雅婷，2011。網路論壇口碑強度、雙面訊息與口碑順序對說服效果之影響－產品涉入之干擾效應。電子商務學報，13(1)，135-167。
    黃俊堯、柳秉佑，2016。消費者線上口碑與評論研究：國內外相關文獻回顧與討論。臺大管理論叢，第二十六卷第三期，215-256。
    黃郁珊，2015。線上口碑網站成功個案之策略行銷分析：以TripAdvisor、Yelp、愛評網為例。政治大學國際經營與貿易研究所學位論文，臺北市。
    蕭至惠、蔡進發、許雅涵，2012。自我建構與調節焦點對衝動性購買行為之影響。臺大管理論叢，第二十三卷第一期，119-150。

    英文文獻
    Akpinar, E., & Berger, J. (2017). Valuable virality. Journal of Marketing Research, 54(2), 318–330.
    Akram, U., Hui, P., Khan, M. K., Yan, C., & Akram, Z. (2018). Factors affecting online impulse buying: evidence from Chinese social commerce environment. Sustainability, 10(2), 352.
    Amblee, N., & Bui, T. (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International journal of electronic commerce, 16(2), 91-114.
    Archak, N., Ghose, A., & Ipeirotis, P. G. (2011). Deriving the pricing power of product features by mining consumer reviews. Management science, 57(8), 1485-1509.
    Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of marketing Research, 4(3), 291-295.
    Babbie, E. R. (2012). The practice of social research. Belmont, CA: Wadsworth.
    Baek, H., Ahn, J., & Choi, Y. (2012). Helpfulness of online consumer reviews: Readers' objectives and review cues. International Journal of Electronic Commerce, 17(2), 99-126.
    Bailey, A. A. (2005). Consumer awareness and use of product review websites. Journal of Interactive Advertising, 6(1), 68–81.
    Baker, W. E. (1999). When can affective conditioning and mere exposure directly influence brand choice?. Journal of advertising, 28(4), 31-46.
    Basuroy, S., Chatterjee, S., & Ravid, S. A. (2003). How critical are critical reviews? The box office effects of film critics, star power, and budgets. Journal of marketing, 67(4), 103-117.
    Berger, J. (2016). Contagious: Why things catch on. Simon and Schuster.
    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 analysis. Journal of consumer research, 7(3), 234-248.
    Blazevic, V., Hammedi, W., Garnefeld, I., Rust, R. T., Keiningham, T., Andreassen, T. W., ... & Carl, W. (2013). Beyond traditional word‐of‐mouth: An expanded model of customer‐driven influence. Journal of Service Management.
    Bohner, G., Frank, E., & Erb, H. P. (1998). Heuristic processing of distinctiveness information in minority and majority influence. European Journal of Social Psychology, 28(5), 855-860.
    Borgida, E., & Nisbett, R. E. (1977). The differential impact of abstract vs. concrete information on decisions 1. Journal of Applied Social Psychology, 7(3), 258-271.
    Broniarczyk, S. M., & Griffin, J. G. (2014). Decision difficulty in the age of consumer empowerment. Journal of Consumer Psychology, 24(4), 608–625.
    Bronner, F., & De Hoog, R. (2010). Consumer-generated versus marketer-generated websites in consumer decision making. International Journal of Market Research, 52(2), 231-248.
    Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer research, 14(3), 350-362.
    Cao Q, Duan W, & Gan Q. (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach. Decision Support Systems 50(2):511–521.
    Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of personality and social psychology, 39(5), 752.
    Chaiken, S., & Ledgerwood, A. (2011). A theory of heuristic and systematic information processing. Handbook of theories of social psychology: Volume one, 246-166.
    Chaiken, Shelly, Liberman, A. & Eagly, A. H. (1989). Heuristic and systematic processing within and beyond the persuasion context. In Uleman James S. & Bargh John A. (eds.), Unintended Thought, 212-252. New York: Guilford Press.
    Chakravarty, A., Liu, Y., & Mazumdar, T. (2008). Online user comments versus professional reviews: Differential influences on pre-release movie evaluation. Marketing Science Institute.
    Chen, P., Wu, S., & Yoon, J. (2004), The Impact of Online Recommendations and Consumer Feedback on Sales, Association for Information Systems, Seattle, Washington, DC, 711-724.
    Chen, S., & Chaiken, S. (1999). The heuristic-systematic model in its broader context. In S. Chaiken & Y. Trope (Eds.), Dual-process theories in social psychology (pp. 73–96). The Guilford Press.
    Chen, Y., Wang, Q., & Xie, J. (2011). Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of marketing research, 48(2), 238-254.
    Chen, Z., & Berger, J. (2016). How content acquisition method affects word of mouth. Journal of Consumer Research, 43(1), 86-102.
    Cheng, Y. H., & Ho, H. Y. (2015). Social influence's impact on reader perceptions of online reviews. Journal of Business Research, 68(4), 883-887.
    Cheung, C. M. K., & Lee, M. K. O. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision Support Systems, 53(1), 218–225.
    Cheung, C. M. Y., Sia, C. L., & Kuan, K. K. (2012). Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. Journal of the Association for Information Systems, 13(8), 2.
    Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470.
    Cheung, C. M., Lee, M. K., & Rabjohn, N. (2008). The impact of electronic word‐of‐mouth: The adoption of online opinions in online customer communities. Internet research.
    Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International journal of electronic commerce, 13(4), 9-38.
    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.
    Chu, S. C., & Kim, Y. J. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47–75.
    Clemons, E. K., Gao, G. G., & Hitt, L. M. (2006). When online reviews meet hyperdifferentiation: A study of the craft beer industry. Journal of management information systems, 23(2), 149-171.
    Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. New York, NY: Routledge Academic.
    Cui, G., Lui, H. K., & Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), 39-58.
    Daugherty, T., Eastin, M. S., & Bright, L. (2008). Exploring consumer motivations for creating user-generated content. Journal of interactive advertising, 8(2), 16-25.
    Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
    Day, G. S. (1971). Attitude change, media and word of mouth. Journal of advertising research, 11, 6, 31–40.
    De Matos, C.A., & Rossi, C.A.V. (2008). Word-of-mouth communications in marketing: a meta- analytic review of the antecedents and moderators. Journal of the Academy of Marketing Science, Vol. 36 No. 4, 578-596.
    De Pelsmacker, P., N. Dens, & A. Kolomiiets. (2018). The impact of text valence, star rating and rated usefulness in online reviews. International Journal of Advertising 37, no.3: 1–2
    Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, 49(10), 1407–1424.
    Dellarocas, C., Zhang, X.,& Awad, N.F. (2007). Exploring the value of online product reviews in forecasting sales: the case of motion pictures. Journal of Interactive Marketing, Vol. 21 No. 4, 23-45.
    Dhar, V., & Chang, E. A. (2009). Does chatter matter? The impact of user-generated content on music sales. Journal of Interactive Marketing, 23(4), 300-307.
    Duan, W., Gu, B., & Whinston, A. B. (2008). The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry. Journal of retailing, 84(2), 233-242.
    Duan, W., Gu, B., & Whinston, A. B. (2008)a. Do online reviews matter? An empirical investigation of panel data. Decision Support Systems, 45 (4): 1007-1016.
    Dwyer, P. (2007). Measuring the value of electronic word of mouth and its impact in consumer communities. Journal of Interactive marketing, 21(2), 63-79.
    Eisinga, R., Te Grotenhuis, M., & Pelzer, B. (2013). The reliability of a two-item scale: Pearson, Cronbach, or Spearman-Brown?. International journal of public health, 58(4), 637-642.
    Ellison, G., & Fudenberg, D. (1995). Word-of-mouth communication and social learning. The Quarterly Journal of Economics, 110(1), 93-125.
    Feng, J., & Papatla, P. (2011). Advertising: stimulant or suppressant of online word of mouth?. Journal of Interactive Marketing, 25(2), 75-84.
    Feng, J., & Papatla, P. (2012). Is online word of mouth higher for new models or redesigns? An investigation of the automobile industry. Journal of Interactive Marketing, 26(2), 92-101.
    Filieri, R., Hofacker, C. F., & Alguezaui, S. (2018). What makes information in online consumer reviews diagnostic over time? The role of review relevancy, factuality, currency, source credibility and ranking score. Computers in Human Behavior, 80, 122-131.
    Floyd, K., Freling, F., Alhogail, S., Cho, H. Y., & Freling, T. (2014). How online product reviews affect retail sales: A meta-analysis. Journal of Retailing, 90(2), 217–232.
    Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information systems research, 19(3), 291-313.
    Ganjalyan, S. (2018). Star rating remains the most important part of a review. TutorCruncher. https://tutorcruncher.com/blog/star-rating-remains-the-most-important-part-of-a-review/
    George, C. E., & Scerri, J. (2007). Web 2.0 and User-Generated Content: legal challenges in the new frontier. Journal of Information, Law and Technology, 2.
    Go, E., Jung, E. H., & Wu, M. (2014). The effects of source cues on online news perception. Computers in Human Behavior, 38, 358-367.
    Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketing science, 23(4), 545-560.
    Goldsmith, R.E., & Horovitz, D. (2006), Measuring motivations for online opinion seeking, Marketing Science, Vol. 23 No. 4, 545-560.
    Gong, W., & Li, X. (2017). Engaging fans on microblog: the synthetic influence of parasocial interaction and source characteristics on ce- lebrity endorsement. Psychology & Marketing, 34(7), 720–732.
    Greenwald, A. G. (1968). Cognitive learning, cognitive response to persuasion, and attitude change. Psychological foundations of attitudes, 1968, 147-170.
    Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business research, 59(4), 449-456.
    Gu, B., Park, J., & Konana, P. (2012). The impact of external word-of-mouth sources on retailer sales of high-involvement products. Information Systems Research, 23 (1): 182-196.
    Haas A, Brosius H-B. (2011). Interpersonal-Public Communication in Discussion Forums: A Valid Indicator for Everyday Conver- sation and Public Opinion?, Paper presented at the 64th World Association for Public Opinion Research Annual Conference, 21–23 September 2011.
    Haines, George H. (1974). Process Models of Consumer Decision Making. Buyer/Consumer Information Processing, G. David Hughes and Michael L. Ray ed. Chapel Hill, NC: University of North Carolina Press, 89-107.
    Hennig-Thurau, T., Gwinner, K.P., Walsh, G. and Gremler, D.D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet?. Journal of Interactive Marketing, Vol. 18 No. 1, 38-52.
    Hennig-Thurau, T., Walsh, G., & Walsh, G. (2003). Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the Internet. International journal of electronic commerce, 8(2), 51-74.
    Higgins, E. T., Shah, J., & Friedman, R. (1997). Emotional responses to goal attainment: strength of regulatory focus as moderator. Journal of personality and social psychology, 72(3), 515.
    Hildebrand, C., & Schlager, T. (2019). Focusing on others before you shop: Exposure to Facebook promotes conventional product config- urations. Journal of the Academy of Marketing Science, 47(2), 291– 307.
    Hlee, S., Lee, H., & Koo, C. (2018). Hospitality and tourism online review research: A systematic analysis and heuristic-systematic model. Sustainability, 10(4), 1141.Hong, S., & Park, H. S. (2012). Computer-mediated persuasion in online reviews: Statistical versus narrative evidence. Computers in human behavior, 28(3), 906-919.
    Hong, S., & Pittman, M. (2020). eWOM anatomy of online product reviews: interaction effects of review number, valence, and star ratings on perceived credibility. International Journal of Advertising, 39(7), 892-920.
    Hong, W., Yu, Z., Wu, L., & Pu, X. (2020). Influencing factors of the persuasiveness of online reviews considering persuasion methods. Electronic Commerce Research and Applications, 39, 100912.
    Hu N, Pavlou PA,& Zhang J.(2006). Can Online Reviews Reveal a Product’s True Quality? Empirical Findings and Analytical Modeling of Online Word of Mouth Communication. Proceedings of the 7th ACM conference on Electronic commerce, 324–330.
    Hu, H. F., & Krishen, A. S. (2019). When is enough, enough? Investigating product reviews and information overload from a consumer empowerment perspective. Journal of Business Research, 100, 27-37.
    Huang, M., Cai, F., Tsang, A. S. L., & Zhou, N. (2011). Making your voice loud: The critical role of WOM information. European Journal of Marketing, 45(7), 1277–1297.
    Ismagilova, E., Slade, E., & Williams, M. (2016). Persuasiveness of eWOM communications: literature review and suggestions for future research. In Conference on e-Business, e-Services and e-Society(pp. 354-359). Springer, Cham.
    Jabr, W., & Zheng, Z. E. (2014). Know yourself and know your enemy: An analysis of firm recommendations and consumer reviews in a competitive environment. MIS Quarterly, 38 (3), 635-654.
    Jeong, E., & Jang, S.S. (2011). Restaurant experiences triggering positive electronic word-of-mouth (eWOM) motivations. International Journal of Hospitality Management, Vol. 30 No. 2, 356-366.
    Jeong, H. J., & Koo, D. M. (2015). Combined effects of valence and attributes of e-WOM on consumer judgment for message and product: The moderating effect of brand community type. Internet Research.
    Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological review, 80(4), 237.
    Kanouse, D. E., & Hanson, L. R., Jr. (1987). Negativity in evaluations. In E. E. Jones, D. E. Kanouse, H. H. Kelley, R. E. Nisbett, S. Valins, & B. Weiner(Eds.), Attribution: Perceiving the causes of behavior (p. 47–62). Lawrence Erlbaum Associates, Inc.
    Katz, Elihu ,& Paul F. Lazarsfeld (1955), Personal Influence; The Part Played by People in the Flow of Mass Communications. Glencoe, IL: Free Press.
    Keller, Ed (2007). Unleashing the Power of Word of Mouth: Creating Brand Advocacy to Drive Growth. Journal of Advertising Research, 47, 4, 448–52.
    Keller, K. L. (2003). Building, Measuring, and Managing Brand Equity, 2nd edition, NJ: Prentice-Hall.
    Keller, K. L., Heckler, S. E., & Houston, M. J. (1998). The effects of brand name suggestiveness on advertising recall. Journal of marketing, 62(1), 48-57.
    Kim, E. E. K., Mattila, A. S., & Baloglu, S. (2011). Effects of gender and expertise on consumers’ motivation to read online hotel reviews. Cornell Hospitality Quarterly, 52(4), 399-406.
    Kim, J., & Gambino, A. (2016). Do we trust the crowd or information system? Effects of personalization and bandwagon cues on users' attitudes and behavioral intentions toward a restaurant recommendation website. Computers in Human Behavior, 65, 369-379.
    Kim, J., & Gupta, P. (2012). Emotional expressions in online user reviews: How they influence consumers' product evaluations. Journal of Business Research, 65(7), 985-992.
    Kim, Y., & Slotegraaf, R. J. (2015). Brand-embedded interaction: A dynamic and personalized interaction for co-creation. Marketing Letters, 27(1), 183–193.
    King, R. A., Racherla, P., & Bush, V. D. (2014). What we know and don't know about online word-of-mouth: A review and synthesis of the literature. Journal of interactive marketing, 28(3), 167-183.
    Klein, L. R. (1998). Evaluating the potential of interactive media through a new lens: Search versus experience goods. Journal of business research, 41, 196-203.
    Kotler, P. (2002). Marketing management: Analysis, planning, implementation and control, 11th edition, NJ: Prentice-Hall.
    Kupfer, A.-K., Pähler vor der Holte, N., Kübler, R. V., & Hennig-Thurau, T. (2018). The role of the partner brand’s social media power in brand alliances. Journal of Marketing, 82(3), 25–44.
    Lee, J. Y., & Bell, D. R. (2013). Neighborhood social capital and social learning for experience attributes of products. Marketing Science, 32(6), 960–976.
    Lee, J. Y., & Sundar, S. S. (2013). To tweet or to retweet? That is the question for health professionals on Twitter. Health Communication, 28(5), 509-524.
    Lee, J., Park, D. H., & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic commerce research and applications, 7(3), 341-352.
    Lee, M., & Youn, S. (2009). Electronic word of mouth (eWOM) How eWOM platforms influence consumer product judgement. International Journal of Advertising, 28(3), 473-499.
    Leitner, P., & Grechenig, T. (2008). Collaborative shopping networks: Sharing the wisdom of crowds in E-commerce environments. BLED 2008 Proceedings, 21.
    Li, X., C. Wu.,& F. Mai. (2019). The effect of online reviews on product sales: A joint sentiment- topic analysis. Information & Management 56, no. 2: 172–84.
    Lin, T. M., Lu, K. Y., & Wu, J. J. (2012). The effects of visual information in eWOM communication. Journal of research in interactive marketing.
    Litvin, S. W., Goldsmith, R. E., & Pan, B. (2007). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458–468.
    Liu, H., Jayawardhena, C., Osburg, V.,& Mohiuddin Babu, M. (2019), Do online reviews still matter post-purchase?, Internet Research
    Liu, X., He, M., Gao, F., & Xie, P. (2008). An empirical study of online shopping customer satisfaction in China: a holistic perspective. International Journal of Retail & Distribution Management.
    Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of marketing, 70(3), 74-89
    Liu, Z., & Park, S. (2015). What makes a useful online review? Implication for travel product websites. Tourism management, 47, 140-151.
    Lo, A. S., & Yao, S. S. (2019). What makes hotel online reviews credible?. International Journal of Contemporary Hospitality Management.
    Luca, M. (2011). Reviews, Reputation, and Revenue: The Case of Yelp.com. Working Paper No. 12-016, Harvard Business School, Boston, MA.
    Luo, C., Wu, J., Shi, Y., & Xu, Y. (2014). The effects of individualism–collectivism cultural orientation on eWOM information. International Journal of Information Management, 34(4), 446-456.
    Lutz, R.J., S.B. MacKenzie & G.E. Belch (1983). Attitude toward the ad as a mediator of advertising effectiveness: Determinants and consequences. Advances in Consumer Research, 10(1), 532-539.
    Ma, X., Khansa, L., Deng, Y., & Kim, S. S. (2013). Impact of prior reviews on the subsequent review process in reputation systems. Journal of Management Information Systems, 30(3), 279-310.
    MacInnis, D. J., Moorman, C., & Jaworski, B. J. (1991). Enhancing and measuring consumers’ motivation, opportunity, and ability to process brand information from ads. Journal of Marketing, 55(4), 32–53.
    Maheswaran, D., & Chaiken, S. (1991). Promoting systematic processing in low-motivation settings: Effect of incongruent information on processing and judgment. Journal of personality and social psychology, 61(1), 13.
    McNeal, J. U., & Zeren, L. M. (1981). Brand name selection for consumer products. MSU Business Topics, 29(2), 35-39.
    Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010). Social and heuristic approaches to credibility evaluation online. Journal of communication, 60(3), 413-439.
    Metzger, M.J.,& A.J. Flanagin. (2013). Credibility and trust of information in online environ- ments: The use of cognitive heuristics, Journal of Pragmatics 59, 210–220.
    Moe, W. W., & Trusov, M. (2011). The value of social dynamics in online product ratings forums. Journal of Marketing Research, 48(3), 444– 456.
    Moorman, C. (2014). CMO survey report: Highlights and insights. Retrieved June 26, https://cmosurvey.org/wpcontent/uploads/sites/15/2017/04/The_CMO_Survey-Highlights_ and_Insights-Feb-2015_Compressed.pdf].
    Moran, G., Muzellec, L., & Nolan, E. (2014). Consumer moments of truth in the digital context: How “search” and “e-word of mouth” can fuel consumer decision making. Journal of Advertising Research, 54(2), 200–204.
    Mudambi, Susan M.,& David Schuff .(2010). What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon. Com. MIS Quarterly, 34, 1, 185–200.
    Nam, H., & Kannan, P. K. (2014). The informational value of social tagging networks. Journal of Marketing, 78(4), 21–40.
    Pan, Y., & Zhang, J. Q. (2011). Born unequal: A study of the helpfulness of user-generated product Reviews. Journal of Retailing, 87(4), 598–612.
    Park, C. W., & MacInnis, D. J. (2006). What's in and what's out: Questions on the boundaries of the attitude construct. Journal of consumer Research, 33(1), 16-18.
    Park, C., & Lee, T. (2009). Information direction, website reputation and eWOM effect: A moder- ating role of product type. Journal of Business Research, 62(1), 61–67
    Park, D. H., & Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic commerce research and applications, 7(4), 399-410.
    Park, D. H., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International journal of electronic commerce, 11(4), 125-148.
    Park, J., Gu, B.,& Lee, H. (2012). The relationship between retailer-hosted and third-party hosted WOM sources and their influence on retailer sales. Electronic Commerce Research and Applications, 11 (3): 253-261
    Petty, Richard E. & Cacioppo, John T. (1981). Attitudes and Persuasion: Classic and Contemporary Approaches. Dubuque, IA: Wm. C. Brown.
    Petty, Richard E. & Cacioppo, John T. (1983). Issue Involvement as a Moderator of the Effects of Attitude Advertising Content and Context. In Advances in Consumer Research, Edited by: Munroe, K. B. Vol. 8, Ann Arbor, MI: Association for Consumer Research.
    Petty, Richard E. & Cacioppo, John T. (1986a). Communication and persuasion: Central and peripheral route to attitude change. New York: Springer-Verlag.
    Petty, Richard E. & Cacioppo, John T. (1986b). The elaboration likelihood model of persuasion. In L. Berkowitz (ed.), Advances in Experimental Social Psychology (Vol.19 pp. 123-205). New York: Academic Press.
    Petty, Richard E., Cacioppo, John T., & Schumann, David (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10 (Sep.), 135-146.
    Petty, Richard E., Cacioppo, John T., Kasmer, Jeff A., & Haugtvedt, Curt P. (1987). A reply to Stiff and Boster. Communication Monographs, 54 (3), 257-263.
    Petty, Richard E., Unnava, Rao, & Strathman, Alan J. (1991). Theories of attitude change. Handbook of Consumer Behavior, 4th Ed. Thomas S. Robertson & Harold H. Kassarjian eds. 241-278.
    Petty, Richard E. & Wegener, Duane T. (1999). The elaboration likelihood model: Current status and controversies. in Dual-Process Theories in Social Psychology, ed. Shelley Chaiken and Yaacov Trope, New York: Guilford. 41-72.
    Phelps, J.E. & Hoy, M.G. (1996). The Aad-Ab-PI relationship in children: The impact of brand familiarity and measurement timing. Psychology & Marketing, Vol.13, (1), 77- 101.
    Qahri-Saremi, H., & Montazemi, A. R. (2019). Factors affecting the adoption of an electronic word of mouth message: A meta-analysis. Journal of Management Information Systems, 36(3), 969-1001.
    Qiu, L., Pang, J., & Lim, K. H. (2012). Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: The moderating role of review valence. Decision Support Systems, 54(1), 631-643.
    Racherla, P., & Friske, W. (2012). Perceived ‘usefulness’ of online consumer reviews: An exploratory investigation across three services categories. Electronic Commerce Research and Applications, 11(6), 548-559.
    Reichheld, F. F. (2003). The one number you need to grow. Harvard business review, 81(12), 46-55.
    Robertson, K. (1989). Strategically desirable brand name characteristics. Journal of Consumer Marketing.
    Rosario, A. B., de Valck, K., & Sotgiu, F. (2020). Conceptualizing the electronic word-of-mouth process: What we know and need to know about eWOM creation, exposure, and evaluation. Journal of the Academy of Marketing Science, 48(3), 422-448.
    Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and social psychology review, 5(4), 296-320.
    Salehan, M., & Kim, D. J. (2016). Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics. Decision Support Systems, 81, 30-40.
    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.
    Senecal, S., & Nantel, J. (2004). The influence of online product recommendations on consumers’ online choices. Journal of retailing, 80(2), 159-169.
    Shen, Y., Shan, W., & Luan, J. (2018). Influence of aggregated ratings on purchase decisions: an event-related potential study. European Journal of Marketing.
    Sher, P. J., & Lee, S. H. (2009). Consumer skepticism and online reviews: An elaboration likelihood model perspective. Social Behavior and Personality: an international journal, 37(1), 137-143.
    Shin, S. Y., Van Der Heide, B., Beyea, D., Dai, Y. N., & Prchal, B. (2017). Investigating moderating roles of goals, reviewer similarity, and self-disclosure on the effect of argument quality of online consumer reviews on attitude formation. Computers in Human Behavior, 76, 218-226.
    Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 102–113.
    Sohaib, M., Akram, U., Hui, P., Rasool, H., Razzaq, Z., & Khan, M. K. (2019). Electronic word-of-mouth generation and regulatory focus. Asia Pacific Journal of Marketing and Logistics.
    Sparks, B. A., Perkins, H. E., & Buckley, R. (2013). Online travel reviews as persuasive communication: The effects of content type, source, and certification logos on consumer behavior. Tourism Management, 39, 1-9.
    Sun, M. (2012). How does the variance of product ratings matter?. Management Science, 58(4), 696-707.
    Sun, T., Youn, S., Wu, G.,& Kuntaraporn, M. (2006). Online word-of-mouth (or mouse): an exploration of its antecedents and consequences. Journal of Computer-Mediated Communication, Vol. 11 No. 4, 1104-1127.
    Sun, Y., Dong, X., & McIntyre, S. (2017). Motivation of user-generated content: Social connectedness moderates the effects of monetary rewards. Marketing Science, 36, 3, 329–337.
    Sundar, S. S., Xu, Q., & Oeldorf-Hirsch, A. (2013). How deeply do we process online recommendations? Heuristic vs. systematic processing of authority and bandwagon cues. In 63rd Annual Conference of the International Communication Association London, UK.
    Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information systems research, 14(1), 47-65.
    Sweeney, J. C., Soutar, G. N., & Mazzarol, T. (2008). Factors influencing word of mouth effectiveness: receiver perspectives. European journal of marketing.
    Tellis, G. J., MacInnis, D. J., Tirunillai, S., & Zhang, Y. (2019). What drives virality (sharing) of online digital content? The critical role of information, emotion, and brand prominence. Journal of Marketing, 83(4), 1–20.
    Teng, S., Khong, K. W., Goh, W. W., & Chong, A. Y. L. (2014). Examining the antecedents of persuasive eWOM messages in social media. Online Information Review.
    Thomas, R. J., Masthoff, J., & Oren, N. (2019). Can i influence you? development of a scale to measure perceived persuasiveness and two studies showing the use of the scale. Frontiers in Artificial Intelligence, 2, 24.
    Tirunillai, S., & Tellis, G. J. (2012). Does chatter really matter? Dynamics of user-generated content and stock performance. Marketing Science, 31(2), 198-215.
    Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: findings from an internet social networking site. Journal of marketing, 73(5), 90-102.
    Tsao, W. C., Hsieh, M. T., Shih, L. W., & Lin, T. M. (2015). Compliance with eWOM: The influence of hotel reviews on booking intention from the perspective of consumer conformity. International Journal of Hospitality Management, 46, 99-111.
    Tsao, W.C.,& Hsieh, M.T. (2015). eWOM persuasiveness: do eWOM platforms and product type matter?. Electronic Commerce Research, Vol. 15 No. 4, 509-541.
    Vargo, C., Gangadharbatla, H., & Hopp, T. (2019). eWOM across channels: comparing the impact of self-enhancement, positivity bias and vengeance on Facebook and Twitter. International Journal of Advertising, 38(8), 1153-1172.
    Walther, J. B., & Jang, J. W. (2012). Communication processes in participatory websites. Journal of Computer-Mediated Communication, 18(1), 2-15.
    Wathieu, L., Brenner, L., Carmon, Z., Chattopadhyay, A., Wertenbroch, K., Drolet, A., ... & Wu, G. (2002). Consumer control and empowerment: a primer. Marketing Letters, 13(3), 297-305.
    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.
    Wojnicki, A. C., & Godes, D. (2008). Word-of-mouth as self-enhancement. HBS marketing research paper, (06-01).
    Wright, S.,& Zdinak, J. (2008), New Communication Behaviours in a Web 2.0 World – Changes, challenges and Opportunities in the Era of the Information Revolution, Alcatel-Lucent, Boulogne- Billancourt.
    Wu, P. F. (2013). In search of negativity bias: An empirical study of perceived helpfulness of online reviews. Psychology & Marketing, 30(11), 971-984.
    Wu, P. F., Van der Heijden, H., & Korfiatis, N. (2011). The influences of negativity and review quality on the helpfulness of online reviews. In International conference on information systems.
    Xie H, Miao L, Kuo P-J, Lee B-Y. (2011). Consumers’ responses to ambivalent online hotel reviews The role of perceived source credibility and pre-decisional disposition. International Journal of Hospitality Management 30: 178–183.
    Yang, S. B., Shin, S. H., Joun, Y., & Koo, C. (2017). Exploring the comparative importance of online hotel reviews’ heuristic attributes in review helpfulness: a conjoint analysis approach. Journal of Travel & Tourism Marketing, 34(7), 963-985.
    Yang, X. (2019). Consumers’ decisions in social commerce: the role of guanxi elements. Asia Pacific Journal of Marketing and Logistics.
    Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human behavior, 27(2), 634-639.
    Yoon, Y., Kim, A. J., Kim, J., & Choi, J. (2019). The effects of eWOM characteristics on consumer ratings: evidence from TripAdvisor. com. International Journal of Advertising, 38(5), 684-703.
    Zhang, J. Q., Craciun, G., & Shin, D. (2010). When does electronic word-of-mouth matter? A study of consumer product reviews. Journal of Business Research, 63(12), 1336-1341.
    Zhang, K. Z., Zhao, S. J., Cheung, C. M., & Lee, M. K. (2014). Examining the influence of online reviews on consumers' decision-making: A heuristic–systematic model. Decision Support Systems, 67, 78-89.
    Zhang, Z., Zhang, Z., & Yang, Y. (2016). The power of expert identity: How website-recognized expert reviews influence travelers' online rating behavior. Tourism Management, 55, 15-24.
    Zhao, X., Strasser, A., Cappella, J. N., Lerman, C.,& Fishbein, M. (2011). A measure of perceived argument strength: aeliability and validity. Commun. Methods Meas. 5, 48–75.
    Zhou, S., & Guo, B. (2017). The order effect on online review helpfulness: A social influence perspective. Decision Support Systems, 93, 77-87.
    Zhuang, L., Jing, F., & Zhu, X. Y. (2006). Movie review mining and summarization. In Proceedings of the 15th ACM international conference on Information and knowledge management, 43-50.
    Ziegele, M,& Weber, M .(2015). Example, please! Comparing the effects of single customer reviews and aggregate review scores on online shoppers’ product evaluations. Journal of Consumer Behavior 14(2), 103–114.
    Zou, P., Yu, B., & Hao, Y. (2011). Does the valence of online consumer reviews matter for consumer decision making? The moderating role of consumer expertise. Journal of computers, 6(3), 484-488.






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    意藍資訊（2019）。「大數據開講Bar」 解析網路口碑與社群聆聽 – 會後整理，2019年6月13日，取自：https://www.opview.com.tw/activity-highlights/20190617/10519
    資策會產業情報研究所（2014）。台灣有81%消費者在購物前搜尋口碑訊息，2014年8月5日，取自：https://mic.iii.org.tw/news.aspx?id=366。
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