Abstract
Online recommendations and their impact on customers’ decision-making process during online shopping are still growing. Customer reviews represent a particular type of content created by random users without professional expertise who base their opinions on their subjective experience. Therefore, user reviews are very different from traditional reviews, where an expert evaluates the goods. The paradox is that user reviews have recently become more popular and more sought after on the Internet than traditional, professional reviews. Customers are more often interested in the layman’s view and the opinion of other users, in which they can empathize, than in professional reviews, which can be either too technical or sometimes commercially colored. However, what makes a review credible and influential remains a question. In this chapter, we propose a credibility model of online recommendations based on previous research conducted in this area.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akerlof G (1978) The market for “lemons”: quality uncertainty and the market mechanism. In: Uncertainty in economics. Academic, pp 235–251. https://doi.org/10.1016/b978-0-12-214850-7.50022-x
Baek H, Ahn J, Choi Y (2012) Helpfulness of online consumer reviews: readers’ objectives and review cues. Int J Electron Commer 17:99–126. https://doi.org/10.2753/jec1086-4415170204
Bhatnagar A, Misra S, Rao H (2000) On risk, convenience, and Internet shopping behavior. Commun ACM 43:98–105. https://doi.org/10.1145/353360.353371
Chaiken S, Maheswaran D (1994) Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. J Pers Soc Psychol 66:460–473. https://doi.org/10.1037/0022-3514.66.3.460
Chan I, Lam L, Chow C et al (2017) The effect of online reviews on hotel booking intention: the role of reader-reviewer similarity. Int J Hosp Manag 66:54–65. https://doi.org/10.1016/j.ijhm.2017.06.007
Cheung C, Sia C, Kuan K (2012) Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. J Assoc Inf Syst 13:618–635. https://doi.org/10.17705/1jais.00305
Deutsch M, Gerard H (1955) A study of normative and informational social influences upon individual judgment. J Abnorm Soc Psychol 51:629–636. https://doi.org/10.1037/h0046408
Dinulescu C, Prybutok V (2021) In authority, or peers we trust? Reviews and recommendations in social commerce. Behav Inform Technol 1–18. https://doi.org/10.1080/0144929x.2021.1957016
Dowling G, Staelin R (1994) A model of perceived risk and intended risk-handling activity. J Consum Res 21:119. https://doi.org/10.1086/209386
Elwalda A, Lü K, Ali M (2016) Perceived derived attributes of online customer reviews. Comput Hum Behav 56:306–319. https://doi.org/10.1016/j.chb.2015.11.051
Fogg B (2003) Prominence-interpretation theory. CHI ’03 extended abstracts on human factors in computing systems - CHI ’03. DOI: https://doi.org/10.1145/765891.765951.
Fogg B, Tseng H (1999) The elements of computer credibility. Proceedings of the SIGCHI conference on human factors in computing systems the CHI is the limit - CHI ’99. DOI: https://doi.org/10.1145/302979.303001.
Fogg B, Soohoo C, Danielson D et al. (2003) How do users evaluate the credibility of Web sites?. Proceedings of the 2003 conference on designing for user experiences - DUX ’03. DOI: https://doi.org/10.1145/997078.997097.
Garbarino E, Strahilevitz M (2004) Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. J Bus Res 57:768–775. https://doi.org/10.1016/s0148-2963(02)00363-6
Greer J (2003) Evaluating the credibility of online information: a test of source and advertising influence. Mass Commun Soc 6:11–28. https://doi.org/10.1207/s15327825mcs0601_3
Ha N (2020) The impact of perceived risk on consumers’ online shopping intention: an integration of TAM and TPB. In: Management science letters, pp 2029–2036. doi: https://doi.org/10.5267/j.msl.2020.2.009.
Hajli M, Sims J, Featherman M, Love P (2014) Credibility of information in online communities. J Strateg Mark 23:238–253. https://doi.org/10.1080/0965254x.2014.920904
Hilligoss B, Rieh S (2008) Developing a unifying framework of credibility assessment: construct, heuristics, and interaction in context. Inf Process Manag 44:1467–1484. https://doi.org/10.1016/j.ipm.2007.10.001
Ho-Dac N, Carson S, Moore W (2013) The effects of positive and negative online customer reviews: Do brand strength and category maturity matter? J Mark 77:37–53. https://doi.org/10.1509/jm.11.0011
Hovland C, Weiss W (1951) The influence of source credibility on communication effectiveness. Pub Opn Q 15:635. https://doi.org/10.1086/266350
Kamalul Ariffin S, Mohan T, Goh Y (2018) Influence of consumers’ perceived risk on consumers’ online purchase intention. J Res Interact Mark 12:309–327. https://doi.org/10.1108/jrim-11-2017-0100
Lankes R (2008) Credibility on the Internet: Shifting from authority to reliability. J Doc 64:667–686. https://doi.org/10.1108/00220410810899709
Laroche M, McDougall G, Bergeron J, Yang Z (2004) Exploring how intangibility affects perceived risk. J Serv Res 6:373–389. https://doi.org/10.1177/1094670503262955
Lucassen T, Schraagen J (2011) Factual accuracy and trust in information: the role of expertise. J Am Soc Inf Sci Technol 62:1232–1242. https://doi.org/10.1002/asi.21545
Lucassen T, Muilwijk R, Noordzij M, Schraagen J (2012) Topic familiarity and information skills in online credibility evaluation. J Am Soc Inf Sci Technol 64:254–264. https://doi.org/10.1002/asi.22743
Ma T, Atkin D (2017) User-generated content and credibility evaluation of online health information: a meta-analytic study. Telematics Inform 34:472–486. https://doi.org/10.1016/j.tele.2016.09.009
Metzger M (2007) Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research. J Am Soc Inf Sci Technol 58:2078–2091. https://doi.org/10.1002/asi.20672
Metzger M, Flanagin A (2013) Credibility and trust of information in online environments: the use of cognitive heuristics. J Pragmat 59:210–220. https://doi.org/10.1016/j.pragma.2013.07.012
Metzger M, Flanagin A, Medders R (2010) Social and heuristic approaches to credibility evaluation online. J Commun 60:413–439. https://doi.org/10.1111/j.1460-2466.2010.01488.x
Miyazaki A, Fernandez A (2001) Consumer perceptions of privacy and security risks for online shopping. J Consum Aff 35:27–44. https://doi.org/10.1111/j.1745-6606.2001.tb00101.x
Mo Z, Li Y, Fan P (2015) Effect of online reviews on consumer purchase behavior. J Serv Sci Manag 08:419–424. https://doi.org/10.4236/jssm.2015.83043
Mohd Suki N, Mohd Suki N (2017) Modeling the determinants of consumers’ attitudes toward online group buying: Do risks and trusts matters? J Retail Consum Serv 36:180–188. https://doi.org/10.1016/j.jretconser.2017.02.002
Mudambi SM, Schuff D (2010) Research note: What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Q 34(185). https://doi.org/10.2307/20721420
Noort G, Kerkhof P, Fennis B (2008) The persuasiveness of online safety cues: the impact of prevention focus compatibility of web content on consumers’ risk perceptions, attitudes, and intentions. J Interact Mark 22:58–72. https://doi.org/10.1002/dir.20121
Pappas N (2016) Marketing strategies, perceived risks, and consumer trust in online buying behaviour. J Retail Consum Serv 29:92–103. https://doi.org/10.1016/j.jretconser.2015.11.007
Park S, Nicolau J (2015) Asymmetric effects of online consumer reviews. Ann Tour Res 50:67–83. https://doi.org/10.1016/j.annals.2014.10.007
Peter J, Tarpey L Sr (1975) A comparative analysis of three consumer decision strategies. J Consum Res 2:29. https://doi.org/10.1086/208613
Petty R, Cacioppo J (1986) The elaboration likelihood model of persuasion. In: Communication and persuasion, pp 1–24. DOI: https://doi.org/10.1007/978-1-4612-4964-1_1.
Rieh S (2002) Judgment of information quality and cognitive authority in the Web. J Am Soc Inf Sci Technol 53:145–161. https://doi.org/10.1002/asi.10017
Roselius T (1971) Consumer rankings of risk reduction methods. J Mark 35:56–61. https://doi.org/10.1177/002224297103500110
San Martín S, Camarero C (2009) How perceived risk affects online buying. Online Inf Rev 33:629–654. https://doi.org/10.1108/14684520910985657
Schindler R, Bickart B (2012) Perceived helpfulness of online consumer reviews: the role of message content and style. J Consum Behav 11:234–243. https://doi.org/10.1002/cb.1372
Scholz-Crane A (1998) Evaluating the future: a preliminary study of the process of how undergraduate students evaluate web sources. Ref Serv Rev 26:53–60. https://doi.org/10.1108/00907329810307759
Sperber D, Clément F, Heintz C et al (2010) Epistemic vigilance. Mind Lang 25:359–393. https://doi.org/10.1111/j.1468-0017.2010.01394.x
Stubb C, Nyström A, Colliander J (2019) Influencer marketing. J Commun Manag 23:109–122. https://doi.org/10.1108/jcom-11-2018-0119
Tam K, Ho S (2005) Web personalization as a persuasion strategy: an elaboration likelihood model perspective. Inf Syst Res 16:271–291. https://doi.org/10.1287/isre.1050.0058
Tham K, Dastane O, Johari Z, Ismail N (2019) Perceived risk factors affecting consumers’ online shopping behaviour. SSRN Electron J. https://doi.org/10.2139/ssrn.3498766
Wathen C, Burkell J (2002) Believe it or not: factors influencing credibility on the Web. J Am Soc Inf Sci Technol 53:134–144. https://doi.org/10.1002/asi.10016
Winter S, Krämer N (2014) A question of credibility – effects of source cues and recommendations on information selection on news sites and blogs. Communications. https://doi.org/10.1515/commun-2014-0020
Xu K, Liao S, Li J, Song Y (2011) Mining comparative opinions from customer reviews for competitive intelligence. Decis Support Syst 50:743–754. https://doi.org/10.1016/j.dss.2010.08.021
Yang B, Lester D, James S (2007) Attitudes toward buying online as predictors of shopping online for British and American respondents. Cyberpsychol Behav 10:198–203. https://doi.org/10.1089/CPB.2006.9968
Yin D, Bond S, Zhang H (2014) Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Q 38:539–560. https://doi.org/10.25300/misq/2014/38.2.10
Zhang Y, Wang J, Zhang X (2021) Personalized sentiment classification of customer reviews via an interactive attributes attention model. Knowl-Based Syst 226:107135. https://doi.org/10.1016/j.knosys.2021.107135
Zhu F, Zhang X (2010) Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J Mark 74:133–148. https://doi.org/10.1509/jm.74.2.133
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Lamr, M., Dostál, M. (2022). The Credibility of Online Recommendations. In: Semerádová, T., Weinlich, P. (eds) Achieving Business Competitiveness in a Digital Environment. Contributions to Management Science. Springer, Cham. https://doi.org/10.1007/978-3-030-93131-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-93131-5_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-93130-8
Online ISBN: 978-3-030-93131-5
eBook Packages: Business and ManagementBusiness and Management (R0)