Browse > Article
http://dx.doi.org/10.15813/kmr.2022.23.2.012

An Empirical Study on the Under-reporting Bias of Online Reviewers: Focusing on Steam Online Game Platform  

Jang, Juhyeok (Korea University)
Baek, Hyunmi (Korea University)
Lee, Saerom (Kyungpook National University)
Bae, Sunghun (Kyungpook National University)
Publication Information
Knowledge Management Research / v.23, no.2, 2022 , pp. 229-251 More about this Journal
Abstract
Online reviews are useful for other consumers to make reasonable purchase decisions by providing previous buyers' experiences. However, when online reviewers are biased, online reviews do not accurately reflect the true quality of the product. Therefore, we investigated the characteristics of reviewers with underreporting bias to cope with the problem of declining reliability of online reviews. In this context, this study attempted to examine the characteristics of reviewers with underreporting bias using 14,165 reviews of Steam, an online game platform. As a result of the analysis, reviewers with underreporting bias mainly write reviews positively, write reviews within a short period from the game release date, but tend to write reviews after playing games for longer time, and write reviews when purchasing high-priced games. Since this study has explored the characteristics of reviewers showing underreporting bias, it will be meaningful as a basic study to cope with the problem caused by underreporting bias.
Keywords
Online review; Review bias; Under-reporting bias; Knowledge management;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Ye, Q., Li, H., Wang, Z., & Law, R. (2014). The influence of hotel price on perceived service quality and value in e-tourism: An empirical investigation based on online traveler reviews. Journal of Hospitality & Tourism Research, 38(1), 23-39.   DOI
2 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.   DOI
3 Gao, G., Greenwood, B. N., Agarwal, R., & McCullough, J. S. (2015). Vocal minority and silent majority: How do online ratings reflect population perceptions of quality. MIS Q, 39(3), 565-590.   DOI
4 Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & 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, 18(1), 38-52.   DOI
5 De Langhe, B., Fernbach, P. M., & Lichtenstein, D. R. (2016). Navigating by the stars: Investigating the actual and perceived validity of online user ratings. Journal of Consumer Research, 42(6), 817-833.   DOI
6 Bjering, E., Havro, L. J., & Moen, O. (2015). An empirical investigation of self-selection bias and factors influencing review helpfulness. International Journal of Business and Management, 10(7), 16-30.
7 Brandes, L., Godes, D., & Mayzlin, D. (2019). What drives extremity bias in online reviews? Theory and experimental evidence. Theory and Experimental Evidence.
8 Cheung, C. M., & Lee, M. K. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision Support Systems, 53(1), 218-225.   DOI
9 Hong, H., Xu, D., Wang, G. A., & Fan, W. (2017). Understanding the determinants of online review helpfulness: A meta-analytic investigation. Decision Support Systems, 102, 1-11.   DOI
10 Chatterjee, P. (2001). Online reviews: Do consumers use them? ACR 2001 Proceedings, 129-134.
11 Chua, A. Y., & Banerjee, S. (2015). Understanding review helpfulness as a function of reviewer reputation, review rating, and review depth. Journal of the Association for Information Science and Technology, 66(2), 354-362.   DOI
12 Constant, D., Kiesler, S., & Sproull, L. (1994). What's mine is ours, or is it? A study of attitudes about information sharing. Information Systems Research, 5(4), 400-421.   DOI
13 Anderson, E. W. (1998). Customer satisfaction and word of mouth. Journal of Service Research, 1(1), 5-17.   DOI
14 Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of Marketing, 70(3), 74-89.   DOI
15 Liu, Z., & Park, S. (2015). What makes a useful online review? Implication for travel product websites. Tourism Management, 47, 140-151.   DOI
16 Clemons, E. K. (2008). How information changes consumer behavior and how consumer behavior determines corporate strategy. Journal of Management Information Systems, 25(2), 13-40.   DOI
17 야오즈옌, 박지영, 홍태호 (2021). 레스토랑의 온라인 리뷰를 통해 감성과 감정이 리뷰 유용성에 미치는 영향에 관한 연구. 지식경영연구, 22(1), 243-267.   DOI
18 이은주, 박도형 (2021). 평점이 수렴되지 않는 리뷰의 제품들이 더 좋을 수도 있을까?: 제품 리뷰평점의 분산과 소비자의 조절초점 성향에 따른 소비자 태도 변화. 지식경영연구, 22(3), 273-293.   DOI
19 장리, 최강준, 이재영 (2017). 온라인 구전량 및 평점과 시기별 영화 흥행과의 관계. 지식경영연구, 18(2), 65-83.   DOI
20 정희정, 이현애, 정남호, 구철모 (2018). Which is more important in useful online review? Heuristic-systematic model perspective. 지식경영연구, 19(4), 1-17.   DOI
21 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.   DOI
22 Askay, D. A. (2015). Silence in the crowd: The spiral of silence contributing to the positive bias of opinions in an online review system. New Media & Society, 17(11), 1811-1829.   DOI
23 Huang, L., Tan, C. H., Ke, W., & Wei, K. K. (2018). Helpfulness of online review content: The moderating effects of temporal and social cues. Journal of the Association for Information Systems, 19(6), 3.
24 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.   DOI
25 Ghose, A., & Ipeirotis, P. G. (2010). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498-1512.   DOI
26 Han, S., & Anderson, C. K. (2020). Customer motivation and response bias in online reviews. Cornell Hospitality Quarterly, 61(2), 142-153.   DOI
27 Kapoor, G., & Piramuthu, S. (2009). Sequential bias in online product reviews. Journal of Organizational Computing and Electronic Commerce, 19(2), 85-95.   DOI
28 Balahur, A., Hermida, J. M., & Montoyo, A. (2012). Detecting implicit expressions of emotion in text: A comparative analysis. Decision Support Systems, 53(4), 742-753.   DOI
29 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.   DOI
30 Bakshi, S., Dogra, N., & Gupta, A. (2019). What motivates posting online travel reviews? Integrating gratifications with technological acceptance factors. Tourism and Hospitality Management, 25(2), 335-354.   DOI
31 Bethlehem, J. (2010). Selection bias in web surveys. International Statistical Review, 78(2), 161-188.   DOI
32 Brightlocal. (2020). Local Consumer Review Survey. http://www.brightlocal.com/learn/local-consumer-review-survey. Accessed on 2020.10.25.
33 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, 21(4), 23-45.   DOI
34 Chua, A. Y., & Banerjee, S. (2018). Intentions to trust and share online health rumors: An experiment with medical professionals. Computers in Human Behavior, 87, 1-9.   DOI
35 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.   DOI
36 Sikora, R. T., & Chauhan, K. (2012). Estimating sequential bias in online reviews: A Kalman filtering approach. Knowledge-Based Systems, 27, 314-321.   DOI
37 Ghasemaghaei, M., Eslami, S. P., Deal, K., & Hassanein, K. (2018). Reviews' length and sentiment as correlates of online reviews' ratings. Internet Research, 28(3), 544-563.   DOI
38 Ham, J., Lee, K., Kim, T., & Koo, C. (2019). Subjective perception patterns of online reviews: A comparison of utilitarian and hedonic values. Information Processing & Management, 56(4), 1439-1456.   DOI
39 Hu, N., Pavlou, P. A., & Zhang, J. (2006, June). Can online reviews reveal a product's true quality? Empirical findings and analytical modeling of online word-of-mouth communication. In Proceedings of the 7th ACM Conference on Electronic Commerce, 324-330.
40 Bhole, B., & Hanna, B. (2017). The effectiveness of online reviews in the presence of self-selection bias. Simulation Modelling Practice and Theory, 77, 108-123.   DOI
41 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.   DOI
42 Hu, N., Pavlou, P. A., & Zhang, J. J. (2017). On self-selection biases in online product reviews. MIS Q, 41(2), 449-471.   DOI
43 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.   DOI
44 Koh, N. S., Hu, N., & Clemons, E. K. (2010). Do online reviews reflect a product's true perceived quality? An investigation of online movie reviews across cultures. Electronic Commerce Research and Applications, 9(5), 374-385.   DOI
45 Hlee, S., Lee, J., Yang, S. B., & Koo, C. (2019). The moderating effect of restaurant type on hedonic versus utilitarian review evaluations. International Journal of Hospitality Management, 77, 195-206.   DOI
46 Ballantine, P. W., & Yeung, C. A. (2015). The effects of review valence in organic versus sponsored blog sites on perceived credibility, brand attitude, and behavioural intentions. Marketing Intelligence & Planning, 33(4), 508-521.   DOI
47 Katawetawaraks, C., & Wang, C. (2011). Online shopper behavior: Influences of online shopping decision. Asian Journal of Business Research, 1(2).
48 Rucker, D. D., Tormala, Z. L., Petty, R. E., & Brinol, P. (2014). Consumer conviction and commitment: An appraisal-based framework for attitude certainty. Journal of Consumer Psychology, 24(1), 119-136.   DOI
49 Korda, A. P., & Snoj, B. (2007, September). Direct and indirect effects of perceived price on perceived value of mobile phones. In Annales des telecommunications (Vol. 62, No. 9, pp. 967-989). Springer-Verlag.   DOI
50 Ba, S., & Pavlou, P. A. (2002). Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS Quarterly, 26(3), 243-268.   DOI
51 Floyd, K., Freling, R., Alhoqail, S., Cho, H. Y., & Freling, T. (2014). How online product reviews affect retail sales: A meta-analysis. Journal of Retailing, 90(2), 217-232.   DOI
52 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.   DOI
53 Pinch, T., & Kesler, F. (2011). How aunt Ammy gets her free lunch: A study of the top-thousand customer reviewers at amazon. com. Managing Overflow in Affluent Societies.
54 Korfiatis, N., Garcia-Bariocanal, E., & Sanchez-Alonso, S. (2012). Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content. Electronic Commerce Research and Applications, 11(3), 205-217.   DOI
55 Lauw, H. W., Lim, E. P., & Wang, K. (2008). Bias and controversy in evaluation systems. IEEE Transactions on Knowledge & Data Engineering, 20(11), 1490-1504.   DOI
56 Lee, I. (2018). Usefulness, funniness, and coolness votes of viewers: An analysis of social shoppers' online reviews. Industrial Management & Data Systems, 118(4), 700-713.   DOI
57 Hu, N., Pavlou, P. A., & Zhang, J. J. (2009). Why do online product reviews have a J-shaped distribution? Overcoming biases in online word-of-mouth communication. Communications of the ACM, 52(10), 144-147.   DOI
58 Huang, A. H., Chen, K., Yen, D. C., & Tran, T. P. (2015). A study of factors that contribute to online review helpfulness. Computers in Human Behavior, 48, 17-27.   DOI
59 Tormala, Z. L., Clarkson, J. J., & Henderson, M. D. (2011). Does fast or slow evaluation foster greater certainty? Personality and Social Psychology Bulletin, 37(3), 422-434.   DOI
60 You, L., & Sikora, R. (2014). Performance of online reputation mechanisms under the influence of different types of biases. Information Systems and e-Business Management, 12(3), 417-442.   DOI
61 Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2), 133-148.   DOI
62 Zhu, H., Tu, R., Feng, W., & Xu, J. (2018). The impacts of evaluation duration and product types on review extremity. Online Information Review, 43(5), 694-709.   DOI
63 Schuckert, M., Liu, X., & Law, R. (2016). Insights into suspicious online ratings: Direct evidence from TripAdvisor. Asia Pacific Journal of Tourism Research, 21(3), 259-272.   DOI
64 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.   DOI
65 Resnick, P., Kuwabara, K., Zeckhauser, R., & Friedman, E. (2000). Reputation systems. Communications of the ACM, 43(12), 45-48.   DOI
66 Schindler, R. M., & Bickart, B. (2005). Published word of mouth: Referable, consumer-generated information on the Internet. Online Consumer Psychology: Understanding and Influencing Consumer Behavior in the Virtual World, 32, 35-61.
67 Shen, X., Pan, B., Hu, T., Chen, K., Qiao, L., & Zhu, J. (2020). Beyond self-selection: The multilayered online review biases at the intersection of users, platforms and culture. Journal of Hospitality and Tourism Insights, 4(1), 77-97.   DOI
68 Smironva, E., Kiatkawsin, K., Lee, S. K., Kim, J., & Lee, C. H. (2020). Self-selection and non-response biases in customers' hotel ratings-a comparison of online and offline ratings. Current Issues in Tourism, 23(10), 1191-1204.   DOI
69 Yang, S. B., Hlee, S., Lee, J., & Koo, C. (2017). An empirical examination of online restaurant reviews on Yelp. com: A dual coding theory perspective. International Journal of Contemporary Hospitality Management, 29(2), 817-839.   DOI
70 Peddibhotla, N. B., & Subramani, M. R. (2007). Contributing to public document repositories: A critical mass theory perspective. Organization Studies, 28(3), 327-346.   DOI
71 Luo, Y., Pan, R., Choi, J. H., Mellish, L., & Strobel, J. (2011). Why choose online learning: Relationship of existing factors and chronobiology. Journal of Educational Computing Research, 45(4), 379-397.   DOI
72 Li, Q., Cui, J., & Gao, Y. (2015, January). The influence of social capital in an online community on online review quality in China. In 2015 48th Hawaii International Conference on System Sciences, IEEE, 562-570.
73 Li, X., & Hitt, L. M. (2008). Self-selection and information role of online product reviews. Information Systems Research, 19(4), 456-474.   DOI
74 Lis, B., & Nessler, C. (2014). Electronic word of mouth. Business & Information Systems Engineering, 6(1), 63-65.   DOI
75 Mudambi, S. M., & Schuff, D. (2010). Research note: What makes a helpful online review? A study of customer reviews on Amazon. com. MIS Quarterly, 34(1), 185-200.   DOI
76 Kordzadeh, N. (2019). Investigating bias in the online physician reviews published on healthcare organizations' websites. Decision Support Systems, 118, 70-82.   DOI
77 Park, S., & Nicolau, J. L. (2015). Asymmetric effects of online consumer reviews. Annals of Tourism Research, 50, 67-83.   DOI