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Open AccessOpen Access JUSTC Management 27 August 2024

The in-depth transmission and reception process of the factors influencing review helpfulness from the signaling timeline perspective

  • 1.

    Key Laboratory of Brain–Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai 201620, China

  • 2.

    Mckelvey School of Engineering, Washington University in St. Louis, St. Louis 63130, United States

Cite this:
https://doi.org/10.52396/JUSTC-2023-0113
More Information
  • Author Bio:

    Mohan Wang is an Assistant Professor at School of Business and Management, Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, China. She received her Ph.D. degree in Information Systems from the Harbin Institute of Technology in 2015. Her research mainly focuses on electronic word of mouth, consumer behavior, and online marketing strategy

    Fei Wan is an Associate Professor at School of Business and Management, Shanghai International Studies University, China. She received her Ph.D. degree in Management Science and Engineering from Peking University in 2017. Her research mainly focuses on the impact of information technology on firm performance, social media marketing, and online consumer behavior

  • Corresponding author: E-mail: wanfei0304@shisu.edu.cn
  • Received Date: 25 July 2023
  • Accepted Date: 20 November 2023
    • Available Online: 27 August 2024
    Abstract

  • Abstract

    Many existing studies have considered the factors influencing review helpfulness, mainly focusing on reviewer impact, review informativeness, and managerial response, based on signaling theory. However, previous studies have simply regarded these factors as independent signals, thus ignoring their in-depth transmission and reception processes. The conclusions about the impact of reviewers on review helpfulness are also inconsistent due to the inaccurate measurement of variables. To fill the above gaps, we followed the signaling timeline theoretical framework used in signaling theory and employed a bootstrapping analysis to examine how reviewer impact, review informativeness, and hotel managerial responses interact to influence review helpfulness. In this study, we used a unique dataset that included official labels from one leading online travel agency. The results show that reviewer impact may affect review helpfulness sequentially through review informativeness and hotel managerial response. Furthermore, by using official labels, both reviewer expertise and reviewer experience significantly affect review helpfulness. Finally, we discuss the theoretical and practical implications of these findings.

    Graphical abstract

    Following the theoretical framework of the signaling timeline in signaling theory, this study examines how reviewer impact, review informativeness, and hotel managerial responses interact to influence review helpfulness.

    Abstract

    Many existing studies have considered the factors influencing review helpfulness, mainly focusing on reviewer impact, review informativeness, and managerial response, based on signaling theory. However, previous studies have simply regarded these factors as independent signals, thus ignoring their in-depth transmission and reception processes. The conclusions about the impact of reviewers on review helpfulness are also inconsistent due to the inaccurate measurement of variables. To fill the above gaps, we followed the signaling timeline theoretical framework used in signaling theory and employed a bootstrapping analysis to examine how reviewer impact, review informativeness, and hotel managerial responses interact to influence review helpfulness. In this study, we used a unique dataset that included official labels from one leading online travel agency. The results show that reviewer impact may affect review helpfulness sequentially through review informativeness and hotel managerial response. Furthermore, by using official labels, both reviewer expertise and reviewer experience significantly affect review helpfulness. Finally, we discuss the theoretical and practical implications of these findings.

    • Public Summary

    • Previous studies have simply regarded reviewer impact, review informativeness, and managerial response as independent signals, thus ignoring their in-depth transmission and reception processes.
    • We followed the theoretical framework of the signaling timeline in signaling theory and employed a bootstrapping analysis to examine how reviewer impact, review informativeness, and hotel managerial responses interact to influence review helpfulness.
    • Reviewer impact may affect review helpfulness sequentially through review informativeness and hotel managerial responses.

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    • References(65)
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    Figure  1.  Signaling timeline[28].

    Figure  2.  Signaling timeline in this study.

    Figure  3.  Research framework.

    Figure  4.  A snapshot of a review web page on Ctrip.com.

    Figure  5.  An IT filter tool based on the trip purpose to identify reviews on Ctrip.com.

    [1]
    Yacouel N, Fleischer A. The role of cybermediaries in reputation building and price premiums in the online hotel market. Journal of Travel Research, 2011, 51 (2): 219–226. doi: 10.1177/0047287511400611
    [2]
    Torres E N, Adler H, Behnke C. Stars, diamonds, and other shiny things: The use of expert and consumer feedback in the hotel industry. Journal of Hospitality and Tourism Management, 2014, 21: 34–43. doi: 10.1016/j.jhtm.2014.04.001
    [3]
    Akhtar N, Ahmad W, Siddiqi U I, et al. Predictors and outcomes of consumer deception in hotel reviews: The roles of reviewer type and attribution of service failure. Journal of Hospitality and Tourism Management, 2019, 39: 65–75. doi: 10.1016/j.jhtm.2019.03.004
    [4]
    Ma Y, Xiang Z, Du Q, et al. Effects of user-provided photos on hotel review helpfulness: An analytical approach with deep leaning. International Journal of Hospitality Management, 2018, 71: 120–131. doi: 10.1016/j.ijhm.2017.12.008
    [5]
    Hu H F, Krishen A S. When is enough, enough? Investigating product reviews and information overload from a consumer empowerment perspective. Journal of Business Research, 2019, 100: 27–37. doi: 10.1016/j.jbusres.2019.03.011
    [6]
    Liu Z W, Park S. What makes a useful online review? Implication for travel product websites. Tourism Management, 2015, 47: 140–151. doi: 10.1016/j.tourman.2014.09.020
    [7]
    Gupta P, Harris J. How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective. Journal of Business Research, 2010, 63 (9-10): 1041–1049. doi: 10.1016/j.jbusres.2009.01.015
    [8]
    Kumar N, Benbasat I. Research note: The influence of recommendations and consumer reviews on evaluations of websites. Information Systems Research, 2006, 17 (4): 425–439. doi: 10.1287/isre.1060.0107
    [9]
    Pan Y, Zhang J Q. Born unequal: A study of the helpfulness of user-generated product reviews. Journal of Retailing, 2011, 87 (4): 598–612. doi: 10.1016/j.jretai.2011.05.002
    [10]
    Hlee S. How reviewer level affects review helpfulness and reviewing behavior across hotel classifications: the case of Seoul in Korea. Industrial Management & Data Systems, 2021, 121 (6): 1191–1215. doi: 10.1108/IMDS-03-2020-0150
    [11]
    Siering M, Muntermann J, Rajagopalan B. Explaining and predicting online review helpfulness: The role of content and reviewer-related signals. Decision Support Systems, 2018, 108: 1–12. doi: 10.1016/j.dss.2018.01.004
    [12]
    Huang A H, Chen K, Yen D C, et al. A study of factors that contribute to online review helpfulness. Computers in Human Behavior, 2015, 48: 17–27. doi: 10.1016/j.chb.2015.01.010
    [13]
    Otterbacher J. ‘Helpfulness’ in online communities: A measure of message quality. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York: ACM, 2009 : 955–964.
    [14]
    Fang B, Ye Q, Kucukusta D, et al. Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tourism Management, 2016, 52: 498–506. doi: 10.1016/j.tourman.2015.07.018
    [15]
    Yang S B, Hlee S, Lee J, et al. An empirical examination of online restaurant reviews on Yelp.com. International Journal of Contemporary Hospitality Management, 2017, 29 (2): 817–839. doi: 10.1108/IJCHM-11-2015-0643
    [16]
    Lee I. Usefulness, funniness, and coolness votes of viewers. Industrial Management & Data Systems, 2018, 118 (4): 700–713. doi: 10.1108/IMDS-04-2017-0151
    [17]
    Li C, Kwok L, Xie K L, et al. Let photos speak: The effect of user-generated visual content on hotel review helpfulness. Journal of Hospitality & Tourism Research, 2023, 47 (4): 665–690. doi: 10.1177/10963480211019113
    [18]
    An Q, Ma Y, Du Q, et al. Role of user-generated photos in online hotel reviews: An analytical approach. Journal of Hospitality and Tourism Management, 2020, 45: 633–640. doi: 10.1016/j.jhtm.2020.11.002
    [19]
    Kwok L, Xie K L. Factors contributing to the helpfulness of online hotel reviews. International Journal of Contemporary Hospitality Management, 2016, 28 (10): 2156–2177. doi: 10.1108/IJCHM-03-2015-0107
    [20]
    Zhou S, Guo B. The order effect on online review helpfulness: A social influence perspective. Decision Support Systems, 2017, 93: 77–87. doi: 10.1016/j.dss.2016.09.016
    [21]
    Chen Y, Jin W, Hu Y, et al. Does managerial response moderate the relationship between online review characteristics and review helpfulness?. Current Issues in Tourism, 2021, 25: 2679–2694. doi: 10.1080/13683500.2021.1988523
    [22]
    Yadav M L, Roychoudhury B. Effect of trip mode on opinion about hotel aspects: A social media analysis approach. International Journal of Hospitality Management, 2019, 80: 155–165. doi: 10.1016/j.ijhm.2019.02.002
    [23]
    Agnihotri A, Bhattacharya S. Online review helpfulness: Role of qualitative factors. Psychology Marketing, 2016, 33 (11): 1006–1017. doi: 10.1002/mar.20934
    [24]
    Mudambi S M, Schuff D. What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Quarterly, 2010, 34 (1): 185–200. doi: 10.2307/20721420
    [25]
    Yang S, Zhou Y, Yao J, et al. Understanding online review helpfulness in omnichannel retailing. Industrial Management & Data Systems, 2019, 119 (8): 1565–1580. doi: 10.1108/IMDS-10-2018-0450
    [26]
    Wang M, Lu Q, Chi R T, et al. How word-of-mouth moderates room price and hotel stars for online hotel booking an empirical investigation with expedia data. Journal of Electronic Commerce Research, 2015, 16 (1): 72–80.
    [27]
    Spence M. Signaling in retrospect and the informational structure of markets. American Economic Review, 2002, 92 (3): 434–459. doi: 10.1257/00028280260136200
    [28]
    Connelly B L, Certo S T, Ireland R D, et al. Signaling theory: A review and assessment. Journal of Management, 2011, 37 (1): 39–67. doi: 10.1177/0149206310388419
    [29]
    Spence M. Job market signaling. In: Uncertainty in Economics. New York: Academic Press, 1978: 281–306.
    [30]
    Kirmani A, Rao A R. No pain, no gain: A critical review of the literature on signaling unobservable product quality. Journal of Marketing, 2000, 64 (2): 66–79. doi: 10.1509/jmkg.64.2.66.18000
    [31]
    Ross S A. The determination of financial structure: the incentive-signalling approach. The Bell Journal of Economics, 1977, 8: 23–40. doi: 10.2307/3003485
    [32]
    Moss T W, Neubaum D O, Meyskens M. The effect of virtuous and entrepreneurial orientations on microfinance lending and repayment: A signaling theory perspective. Entrepreneurship Theory and Practice, 2015, 39 (1): 27–52. doi: 10.1111/etap.12110
    [33]
    Bristor J. Enhanced explanations of word of mouth communications: The power of relations. Research in Consumer Behavior, 1990, 4: 51–83.
    [34]
    Gotlieb J B, Sarel D. Comparative advertising effectiveness: The role of involvement and source credibility. Journal of Advertising, 1991, 20 (1): 38–45. doi: 10.1080/00913367.1991.10673205
    [35]
    Racherla P, Friske W. Perceived ‘usefulness’ of online consumer reviews: An exploratory investigation across three services categories. Electronic Commerce Research and Applications, 2012, 11: 548–559. doi: 10.1016/j.elerap.2012.06.003
    [36]
    Hoenig D, Henkel J. Quality signals? The role of patents, alliances, and team experience in venture capital financing. Research Policy, 2015, 44 (5): 1049–1064. doi: 10.1016/j.respol.2014.11.011
    [37]
    Filieri R. What makes an online consumer review trustworthy. Annals of Tourism Research, 2016, 58: 46–64. doi: 10.1016/j.annals.2015.12.019
    [38]
    Park C W, Sutherland I, Lee S K. Effects of online reviews, trust, and picture-superiority on intention to purchase restaurant services. Journal of Hospitality and Tourism Management, 2021, 47: 228–236. doi: 10.1016/j.jhtm.2021.03.007
    [39]
    Lee S, Choeh J Y. Predicting the helpfulness of online reviews using multilayer perceptron neural networks. Expert Systems with Applications, 2014, 41 (6): 3041–3046. doi: 10.1016/j.eswa.2013.10.034
    [40]
    Hu X, Yang Y. What makes online reviews helpful in tourism and hospitality? A bare-bones meta-analysis. Journal of Hospitality Marketing & Management, 2021, 30 (2): 139–158. doi: 10.1080/19368623.2020.1780178
    [41]
    Radojevic T, Stanisic N, Stanic N, et al. The effects of traveling for business on customer satisfaction with hotel services. Tourism Management, 2018, 67: 326–341. doi: 10.1016/j.tourman.2018.02.007
    [42]
    Rhee H T, Yang S B. How does hotel attribute importance vary among different travelers? An exploratory case study based on a conjoint analysis. Electronic Markets, 2015, 25 (3): 211–226. doi: 10.1007/s12525-014-0161-y
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