Ürün ve hizmetler hakkında çevrimiçi (online) yorum okuyanların, bu yorumların doğruluğu ve tarafsızlığına dair şüpheleri her geçen gün artmaktadır. Bu sebeple, tüketicilerin bu yorumlara inanmasını ve faydalı bulmasını sağlamak amacıyla firmalar, çevrimiçi yorum yazanlardan yorumun gerçekçi olduğuna dair ipuçları sunmalarını istemektedir. Bu ipuçlarından biri olan ürün kullanım süresinin çevrimiçi yorumda belirtilmesi mevcut araştırmada ele alınmıştır. Bu kapsamda, çevrimiçi yorumda ürün kullanım süresinin yer almasının, okuyucunun yorumdan algıladığı fayda üzerindeki etkileri, bu etkinin olumlu ve olumsuz yorumlar için nasıl farklılaştığı ve yorumun inandırıcılığının bu etkideki aracılık rolü incelenmiştir. Bu amaçla, üç ön-araştırma ile çevrimiçi yorumun manipülasyonu sağlanmış; sonrasında ise dört farklı senaryonun yer aldığı denekler arası faktöriyel tasarım modeli uygulanmıştır. Yapılan analizler sonucunda ürün kullanım süresinin çevrimiçi yorumda yer almasının yorumdan algılanan faydayı önemli ölçüde arttırdığı görülmüştür. Olumsuz çevrimiçi yorumlarda ürün kullanım süresinin belirtilmesi algılanan faydayı olumlu yorumlarda belirtilmesine göre daha az etkilemektedir. Ayrıca, ürün kullanım süresinin çevrimiçi yorumda belirtilmesi algılanan faydayı yorumun inandırıcılığı aracılıyla etkilemektedir.
Bu çalışma, 2017 yılında Raife Meltem YETKİN ÖZBÜK tarafından yazılan "Online Yorumda Ürün Kullanım Süresinin Algılanan Fayda Üzerindeki Etkileri" başlıklı doktora tezinden türetilmiştir.
Kaynakça
Agnihotri, A. ve Bhattacharya, S. (2016). Online review helpfulness: Role of qualitative factors. Psychology and Marketing. https://doi.org/10.1002/mar.20934
Ansari, A., Essegaier, S. ve Kohli, R. (2000). Internet Recommendation Systems. Journal of Marketing Research, 37(3), 363–375. https://doi.org/10.1509/jmkr.37.3.363.18779
Baron, R. M. ve Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
Benedicktus, R. L., Brady, M. K., Darke, P. R. ve Voorhees, C. M. (2010). Conveying trustworthiness to online consumers: reactions to consensus, physical store presence, brand familiarity, and generalized suspicion. Journal of Retailing, 86(4), 322–335. https://doi.org/10.1016/j.jretai.2010.04.002
Bowerman, B. L., O'Connell, R. T. ve Hand, L. M. (2001). Business Statistics in Practice . McGraw-Hill.
Casaló, L. V., Flavián, C., Guinalíu, M. ve Ekinci, Y. (2015). Avoiding the dark side of positive online consumer reviews: Enhancing reviews’ usefulness for high risk-averse travelers.
Journal of Business Research, 68(9), 1829–1835. https://doi.org/10.1016/j.jbusres.2015.01.010
Chen, J., Teng, L., Yu, Y. ve Yu, X. (2016). The effect of online information sources on purchase intentions between consumers with high and low susceptibility to informational influence. Journal of Business Research, 69(2), 467–475. https://doi.org/10.1016/j.jbusres.2015.05.003
Chen, Z. ve Lurie, N. H. (2013). Temporal Contiguity and Negativity Bias in the Impact of Online Word of Mouth. Journal of Marketing Research, 50(4), 463–476. https://doi.org/10.1509/0022-2437-50.4.463
Cheng, Y. H. ve Ho, H. Y. (2015). Social influence’s impact on reader perceptions of online reviews. Journal of Business Research, 68(4), 883–887. https://doi.org/10.1016/j.jbusres.2014.11.046
Felbermayr, A. ve Nanopoulos, A. (2016). The Role of Emotions for the Perceived Usefulness in Online Customer Reviews. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2016.05.004
Filieri, R. (2015). What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research, 68(6), 1261–1270. https://doi.org/10.1016/j.jbusres.2014.11.006
Gershoff, A. D., Mukherjee, A. ve Mukhopadhyay, A. (2004). Consumer Acceptance of Online Agent Advice: Extremity and Positivity Effects. Journal of Consumer Psychology, 13(1–2), 161–170. https://doi.org/10.1207/s15327663jcp13-1&2_14
Hair, J. F., Black, W. C., Babin, B. J. ve Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Pearson Education.
Hamby, A., Daniloski, K. ve Brinberg, D. (2015). How consumer reviews persuade through narratives. Journal of Business Research, 68(6), 1242–1250. https://doi.org/10.1016/j.jbusres.2014.11.004
Hamilton, R. W. ve Thompson, D. V. (2007). Is There a Substitute for Direct Experience? Comparing Consumers’ Preferences after Direct and Indirect Product Experiences. Journal of Consumer Research. https://doi.org/10.1086/520073
Hayes, A. (2013). Model Templates for PROCESS for SPSS and SAS. Nisan 13, 2017 tarihinde http://www.personal.psu.edu/jxb14/M554/specreg/templates.pdf adresinden alındı
Hoch, S. J. (2002). Product Experience Is Seductive. Journal of Consumer Research. https://doi.org/10.1086/344422
Ito, T. A., Larsen, J. T., Smith, N. K. ve Cacioppo, J. T. (1998). Negative information weighs more heavily on the brain: The negativity bias in evaluative categorizations. Journal of Personality and Social Psychology. https://doi.org/10.1037//0022-3514.75.4.887
Jiménez, F. R. ve 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(3), 226–235. https://doi.org/10.1016/j.intmar.2013.04.004
Koo, D. (2015). The strength of no tie relationship in an online recommendation: Focused on interactional effects of valence, tie strength, and type of service. European Journal of Marketing, 49(7/8), 1163–1183. https://doi.org/10.1179/str.2006.53.4.005
Lee, M., Rodgers, S. ve Kim, M. (2009). Effects of valence and extremity of eWOM on attitude toward the brand and website. Journal of Current Issues and Research in Advertising, 31(2), 1–11. https://doi.org/10.1080/10641734.2009.10505262
Li, H., Daugherty, T. ve Biocca, F. (2001). Characteristics of virtual experience in electronic commerce: A protocol analysis. Journal of Interactive Marketing. https://doi.org/10.1002/dir.1013
Li, L., Lee, K. Y., Lee, M. ve Yang, S.-B. (2020). Unveiling the cloak of deviance: Linguistic cues for psychological processes in fake online reviews. International Journal of Hospitality Management, 87(February), 102468. https://doi.org/10.1016/j.ijhm.2020.102468
MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. Routledge.
Mafael, A., Gottschalk, S. A. ve Kreis, H. (2016). Examining Biased Assimilation of Brand-related Online Reviews. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2016.06.002
Malhotra, N. K. (2007). Marketing Research: An Applied Orientation, 5th Edition. Prentice-Hall, Inc, New Jersey, USA.
Mert, M. (2016). Yatay Kesit Veri Analizi Bilgisayar Uygulamaları. Ankara: Detay Yayıncılık.
Moore, S. G. (2015). Attitude predictability and helpfulness in online reviews: The role of explained actions and reactions. Journal of Consumer Research, 42(1), 30–44. https://doi.org/10.1093/jcr/ucv003
Munzel, A. (2016). Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus. Journal of Retailing and Consumer Services, 32, 96–108. https://doi.org/10.1016/j.jretconser.2016.06.002
Nunnally, J. (1978), Psychometric Methods, New York: McGraw-Hill.
Ozer, M. (2011). The moderating roles of prior experience and behavioral importance in the predictive validity of new product concept testing. Journal of Product Innovation Management. https://doi.org/10.1111/j.1540-5885.2010.00784.x
Pan, Y. ve Zhang, J. Q. (2011). Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews. Journal of Retailing, 87(4), 598–612. https://doi.org/10.1016/j.jretai.2011.05.002
Park, C. ve Lee, T. M. (2009a). Antecedents of Online Reviews’ Usage and Purchase Influence: An Empirical Comparison of U.S. and Korean Consumers. Journal of Interactive Marketing, 23(4), 332–340. https://doi.org/10.1016/j.intmar.2009.07.001
Park, C. ve Lee, T. M. (2009b). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67. https://doi.org/10.1016/j.jbusres.2007.11.017
Peng, L., Cui, G., Zhuang, M. ve Li, C. (2016). Consumer perceptions of online review deceptions: an empirical study in China. Journal of Consumer Marketing. https://doi.org/10.1108/JCM-01-2015-1281
Purnawirawan, N., De Pelsmacker, P. ve Dens, N. (2012). Balance and Sequence in Online Reviews: How Perceived Usefulness Affects Attitudes and Intentions. Journal of Interactive Marketing, 26(4), 244–255. https://doi.org/10.1016/j.intmar.2012.04.002
Purnawirawan, N., Eisend, M., Pelsmacker, P. De ve Dens, N. (2015). A Meta-analytic Investigation of the Role of Valence in Online Reviews. Journal of Interactive Marketing, 31, 17–27. https://doi.org/10.1016/j.intmar.2015.05.001
Reimer, T. ve Benkenstein, M. (2016). Altruistic eWOM marketing: More than an alternative to monetary incentives. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2016.04.003
Rozin, P. ve Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and Social Psychology Review. https://doi.org/10.1207/S15327957PSPR0504_2
Schlosser, A. E. (2011). Can including pros and cons increase the helpfulness and persuasiveness of online reviews? The interactive effects of ratings and arguments. Journal of Consumer Psychology, 21(3), 226–239. https://doi.org/10.1016/j.jcps.2011.04.002
Singh, J. P., Irani, S., Rana, N. P., Dwivedi, Y. K., Saumya, S. ve Kumar Roy, P. (2017). Predicting the “helpfulness” of online consumer reviews. Journal of Business Research, 70, 346–355. https://doi.org/10.1016/j.jbusres.2016.08.008
Sussman, S. W. ve Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research. https://doi.org/10.1287/isre.14.1.47.14767
Tabachnick, B. ve Fidell, L. (2013). Using Multivariate Statistics (International b.). New Jersey: Pearson.
Wu, P. F. (2013). In search of negativity bias: An empirical study of perceived helpfulness of online reviews. Psychology and Marketing. https://doi.org/10.1002/mar.20660
Wu, Y., Ngai, E. W. T., Wu, P. ve Wu, C. (2020). Fake online reviews : Literature review , synthesis , and directions for future research. Decision Support Systems, (February), 113280. https://doi.org/10.1016/j.dss.2020.113280
Zhang, L., Gao, Y. ve Zheng, X. (2020). Let’s Talk About This in Public: Consumer Expectations for Online Review Response. Cornell Hospitality Quarterly. https://doi.org/10.1177/1938965519864864
Perceived Helpfulness of Online Review: The Role of Product Usage Period and Review’s Credibility
Consumers are increasingly suspicious of the accuracy and objectivity of online reviews of products and services. Therefore, to make the consumers to believe in the online reviews and to perceive online reviews useful, firms suggest their consumers provide clues while writing online reviews. One of these clues, stating the presence of product usage period in online reviews, is addressed in the current research. Thus, the effect of stating the product usage period on the perceived usefulness of online reviews; how this effect differs for positive and negative ones, and the mediating role of the review credibility in this relationship were examined. For this purpose, the online review was manipulated with three pre-studies; afterwards, a between-subjects factorial experimental design model was developed with four different scenarios. As a result of the analysis, it was observed that stating the product usage period in online review significantly increases the perceived usefulness. Stating the product usage period in negative online reviews is less effective on the perceived usefulness of online reviews than in positive online reviews. In addition, the presence of product usage period in online review affects perceived usefulness by affecting the credibility of online review.
Agnihotri, A. ve Bhattacharya, S. (2016). Online review helpfulness: Role of qualitative factors. Psychology and Marketing. https://doi.org/10.1002/mar.20934
Ansari, A., Essegaier, S. ve Kohli, R. (2000). Internet Recommendation Systems. Journal of Marketing Research, 37(3), 363–375. https://doi.org/10.1509/jmkr.37.3.363.18779
Baron, R. M. ve Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
Benedicktus, R. L., Brady, M. K., Darke, P. R. ve Voorhees, C. M. (2010). Conveying trustworthiness to online consumers: reactions to consensus, physical store presence, brand familiarity, and generalized suspicion. Journal of Retailing, 86(4), 322–335. https://doi.org/10.1016/j.jretai.2010.04.002
Bowerman, B. L., O'Connell, R. T. ve Hand, L. M. (2001). Business Statistics in Practice . McGraw-Hill.
Casaló, L. V., Flavián, C., Guinalíu, M. ve Ekinci, Y. (2015). Avoiding the dark side of positive online consumer reviews: Enhancing reviews’ usefulness for high risk-averse travelers.
Journal of Business Research, 68(9), 1829–1835. https://doi.org/10.1016/j.jbusres.2015.01.010
Chen, J., Teng, L., Yu, Y. ve Yu, X. (2016). The effect of online information sources on purchase intentions between consumers with high and low susceptibility to informational influence. Journal of Business Research, 69(2), 467–475. https://doi.org/10.1016/j.jbusres.2015.05.003
Chen, Z. ve Lurie, N. H. (2013). Temporal Contiguity and Negativity Bias in the Impact of Online Word of Mouth. Journal of Marketing Research, 50(4), 463–476. https://doi.org/10.1509/0022-2437-50.4.463
Cheng, Y. H. ve Ho, H. Y. (2015). Social influence’s impact on reader perceptions of online reviews. Journal of Business Research, 68(4), 883–887. https://doi.org/10.1016/j.jbusres.2014.11.046
Felbermayr, A. ve Nanopoulos, A. (2016). The Role of Emotions for the Perceived Usefulness in Online Customer Reviews. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2016.05.004
Filieri, R. (2015). What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research, 68(6), 1261–1270. https://doi.org/10.1016/j.jbusres.2014.11.006
Gershoff, A. D., Mukherjee, A. ve Mukhopadhyay, A. (2004). Consumer Acceptance of Online Agent Advice: Extremity and Positivity Effects. Journal of Consumer Psychology, 13(1–2), 161–170. https://doi.org/10.1207/s15327663jcp13-1&2_14
Hair, J. F., Black, W. C., Babin, B. J. ve Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Pearson Education.
Hamby, A., Daniloski, K. ve Brinberg, D. (2015). How consumer reviews persuade through narratives. Journal of Business Research, 68(6), 1242–1250. https://doi.org/10.1016/j.jbusres.2014.11.004
Hamilton, R. W. ve Thompson, D. V. (2007). Is There a Substitute for Direct Experience? Comparing Consumers’ Preferences after Direct and Indirect Product Experiences. Journal of Consumer Research. https://doi.org/10.1086/520073
Hayes, A. (2013). Model Templates for PROCESS for SPSS and SAS. Nisan 13, 2017 tarihinde http://www.personal.psu.edu/jxb14/M554/specreg/templates.pdf adresinden alındı
Hoch, S. J. (2002). Product Experience Is Seductive. Journal of Consumer Research. https://doi.org/10.1086/344422
Ito, T. A., Larsen, J. T., Smith, N. K. ve Cacioppo, J. T. (1998). Negative information weighs more heavily on the brain: The negativity bias in evaluative categorizations. Journal of Personality and Social Psychology. https://doi.org/10.1037//0022-3514.75.4.887
Jiménez, F. R. ve 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(3), 226–235. https://doi.org/10.1016/j.intmar.2013.04.004
Koo, D. (2015). The strength of no tie relationship in an online recommendation: Focused on interactional effects of valence, tie strength, and type of service. European Journal of Marketing, 49(7/8), 1163–1183. https://doi.org/10.1179/str.2006.53.4.005
Lee, M., Rodgers, S. ve Kim, M. (2009). Effects of valence and extremity of eWOM on attitude toward the brand and website. Journal of Current Issues and Research in Advertising, 31(2), 1–11. https://doi.org/10.1080/10641734.2009.10505262
Li, H., Daugherty, T. ve Biocca, F. (2001). Characteristics of virtual experience in electronic commerce: A protocol analysis. Journal of Interactive Marketing. https://doi.org/10.1002/dir.1013
Li, L., Lee, K. Y., Lee, M. ve Yang, S.-B. (2020). Unveiling the cloak of deviance: Linguistic cues for psychological processes in fake online reviews. International Journal of Hospitality Management, 87(February), 102468. https://doi.org/10.1016/j.ijhm.2020.102468
MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. Routledge.
Mafael, A., Gottschalk, S. A. ve Kreis, H. (2016). Examining Biased Assimilation of Brand-related Online Reviews. Journal of Interactive Marketing. https://doi.org/10.1016/j.intmar.2016.06.002
Malhotra, N. K. (2007). Marketing Research: An Applied Orientation, 5th Edition. Prentice-Hall, Inc, New Jersey, USA.
Mert, M. (2016). Yatay Kesit Veri Analizi Bilgisayar Uygulamaları. Ankara: Detay Yayıncılık.
Moore, S. G. (2015). Attitude predictability and helpfulness in online reviews: The role of explained actions and reactions. Journal of Consumer Research, 42(1), 30–44. https://doi.org/10.1093/jcr/ucv003
Munzel, A. (2016). Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus. Journal of Retailing and Consumer Services, 32, 96–108. https://doi.org/10.1016/j.jretconser.2016.06.002
Nunnally, J. (1978), Psychometric Methods, New York: McGraw-Hill.
Ozer, M. (2011). The moderating roles of prior experience and behavioral importance in the predictive validity of new product concept testing. Journal of Product Innovation Management. https://doi.org/10.1111/j.1540-5885.2010.00784.x
Pan, Y. ve Zhang, J. Q. (2011). Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews. Journal of Retailing, 87(4), 598–612. https://doi.org/10.1016/j.jretai.2011.05.002
Park, C. ve Lee, T. M. (2009a). Antecedents of Online Reviews’ Usage and Purchase Influence: An Empirical Comparison of U.S. and Korean Consumers. Journal of Interactive Marketing, 23(4), 332–340. https://doi.org/10.1016/j.intmar.2009.07.001
Park, C. ve Lee, T. M. (2009b). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67. https://doi.org/10.1016/j.jbusres.2007.11.017
Peng, L., Cui, G., Zhuang, M. ve Li, C. (2016). Consumer perceptions of online review deceptions: an empirical study in China. Journal of Consumer Marketing. https://doi.org/10.1108/JCM-01-2015-1281
Purnawirawan, N., De Pelsmacker, P. ve Dens, N. (2012). Balance and Sequence in Online Reviews: How Perceived Usefulness Affects Attitudes and Intentions. Journal of Interactive Marketing, 26(4), 244–255. https://doi.org/10.1016/j.intmar.2012.04.002
Purnawirawan, N., Eisend, M., Pelsmacker, P. De ve Dens, N. (2015). A Meta-analytic Investigation of the Role of Valence in Online Reviews. Journal of Interactive Marketing, 31, 17–27. https://doi.org/10.1016/j.intmar.2015.05.001
Reimer, T. ve Benkenstein, M. (2016). Altruistic eWOM marketing: More than an alternative to monetary incentives. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2016.04.003
Rozin, P. ve Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and Social Psychology Review. https://doi.org/10.1207/S15327957PSPR0504_2
Schlosser, A. E. (2011). Can including pros and cons increase the helpfulness and persuasiveness of online reviews? The interactive effects of ratings and arguments. Journal of Consumer Psychology, 21(3), 226–239. https://doi.org/10.1016/j.jcps.2011.04.002
Singh, J. P., Irani, S., Rana, N. P., Dwivedi, Y. K., Saumya, S. ve Kumar Roy, P. (2017). Predicting the “helpfulness” of online consumer reviews. Journal of Business Research, 70, 346–355. https://doi.org/10.1016/j.jbusres.2016.08.008
Sussman, S. W. ve Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research. https://doi.org/10.1287/isre.14.1.47.14767
Tabachnick, B. ve Fidell, L. (2013). Using Multivariate Statistics (International b.). New Jersey: Pearson.
Wu, P. F. (2013). In search of negativity bias: An empirical study of perceived helpfulness of online reviews. Psychology and Marketing. https://doi.org/10.1002/mar.20660
Wu, Y., Ngai, E. W. T., Wu, P. ve Wu, C. (2020). Fake online reviews : Literature review , synthesis , and directions for future research. Decision Support Systems, (February), 113280. https://doi.org/10.1016/j.dss.2020.113280
Zhang, L., Gao, Y. ve Zheng, X. (2020). Let’s Talk About This in Public: Consumer Expectations for Online Review Response. Cornell Hospitality Quarterly. https://doi.org/10.1177/1938965519864864
Yetkin Özbük, R. M. (2020). Çevrimiçi Yorumdan Algılanan Fayda: Ürün Kullanım Süresinin ve Yorumun İnandırıcılığının Rolü. Erciyes Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi(56), 97-122. https://doi.org/10.18070/erciyesiibd.703697