A Unified Model for the Adoption of Electronic Word of Mouth on Social Network Sites: Facebook as the Exemplar

CITATION

Aghakhani, N., Karimi, J. & Salehan, M. (2018) A Unified Model for the Adoption of Electronic Word of Mouth on Social Network Sites: Facebook as the Exemplar, International Journal of Electronic Commerce, 22(2), 202-231

For library access / research help in a similar topic: anyangoceline19@gmail.com


ABSTRACT
Electronic word of mouth (eWOM) has gained increased attention from
both practitioners and academia. Its importance lies in its simplicity and yet its profound
impact on customers’ attitudes toward specific brands or goods, and thus affecting
customers’ loyalty and purchase behaviors. Although social network services (SNSs)
have emerged as a new platform for eWOM communication, less attention has been
paid in the literature to eWOM adoption on SNSs. Using the elaboration likelihood
model (ELM) and the affect-as-information theory, this study identifies factors that affect
eWOM adoption on Facebook. We identify product-related information in a review,
source credibility, peer image building, and tie strength as theoretically important
variables in our study, and we examine their effect on cognitive and affective attitudes.
We find that eWOM types (explicit vs. implicit) moderate the effects of cognitive and
affective attitude on eWOM adoption. We further find that the effect of cognitive
attitude on eWOM adoption is higher when the eWOM is explicit, while the effect of
affective attitude is higher when the eWOM is implicit. For information systems (IS)
researchers, this study advances the eWOM adoption literature by highlighting the role
of eWOM types in the eWOM adoption process and integrating the ELM and affect-asinformation
theories to explore the antecedents of eWOM adoption. For IS practice, this
study also provides new insights for online retailers and social media marketers about
the antecedents of eWOM adoption.


REFERENCES
1. Adams, D.A.; Nelson, R.R.; and Todd, P.A. Perceived usefulness, ease of
use, and usage of information technology: A replication. MIS Quarterly
(1992), 16 (2),227–247.

2. Angst, C.M., and Agarwal, R. Adoption of electronic health records in the
presence of privacy concerns: The elaboration likelihood model and individual
persuasion. MIS Quarterly, 33, 2 (2009), 339–370.

3. Aral, S., and Walker, D. Creating social contagion through viral product
design: A randomized trial of peer influence in networks. Management
Science, 57, 9 (2011), 1623–1639.

4. Arnold, H.J., and Feldman, D.C. Social desirability response bias in selfreport
choice situations. Academy of Management Journal, 24, 2 (1981), 377–385.

5. Awad, N.F., and Ragowsky, A. Establishing trust in electronic commerce
through online word of mouth: An examination across genders. Journal of
Management Information Systems, 24, 4 (2008), 101–121.

6. Baek, H.; Ahn, J.; and Choi, Y. Helpfulness of online consumer reviews:
Readers’ objectives and review cues. International Journal of Electronic
Commerce, 17, 2 (2012), 99–126.

7. Bakshy, E.; Eckles, D.; Yan, R.; and Rosenn, I. Social influence in social
advertising: evidence from field experiments. In Proceedings of the Thirteenth
ACM Conference on Electronic Commerce (EC). Valencia, Spain: ACM, 2012, pp.
146–161.

8. Barclay, D.; Higgins, C.; and Thompson, R. The partial least squares (PLS)
approach to causal modeling: Personal computer adoption and use as an
illustration. Technology studies, 2, 2 (1995), 285–309.

9. Berger, J., and Milkman, K.L. What makes online content viral? Journal of
Marketing Research, 49, 2 (2012), 192–205.

10. Bhattacherjee, A., and Sanford, C. Influence processes for information
technology acceptance: An elaboration likelihood model. MIS Quarterly, 30, 4
(2006), 805–825.

11. Brown, J.J., and Reingen, P.H. Social ties and word-of-mouth referral
behavior. Journal of Consumer Research, 14, 3 (1987), 350–362.

12. Casteleyn, J.; Mottart, A.; and Rutten, K. How to use data from Facebook
in your market research. International Journal of Market Research, 51, 4 (2009),
439–447.

13. Chen, R. Member use of social networking sites: An empirical examination.
Decision Support Systems, 54, 3 (2013), 1219–1227.

14. Cheung, C.M.-Y.; Sia, C.-L.; and Kuan, K.K. 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 (2012),
618–635.

15. Cheung, C.M.; Lee, M.K.; and Rabjohn, N. The impact of electronic wordof-
mouth: The adoption of online opinions in online customer communities.
Internet Research, 18, 3 (2008), 229–247.

16. Cheung, M.Y.; Luo, C.; Sia, C.L.; and Chen, H. Credibility of electronic
word-of-mouth: Informational and normative determinants of on-line consumer
recommendations. International Journal of Electronic Commerce, 13, 4
(2009), 9–38.

17. Chin, W.W. Issues and opinion on structural equation modeling. MIS
Quarterly, 22, 1 (1998), 7–16.

18. Chin, W.W. The partial least squares approach to structural equation
modeling. Modern Methods for Business Research, 295, 2 (1998), 295–336.

19. Chin, W.W.; Marcolin, B.L.; and Newsted, P.R. A partial least squares
latent variable modeling approach for measuring interaction effects: Results
from a Monte Carlo simulation study and an electronic-mail emotion/
adoption study. Information Systems Research, 14, 2 (2003), 189–217.

20. Chu, S.-C., and Choi, S.M. Electronic word-of-mouth in social networking
sites: A cross-cultural study of the United States and China. Journal of Global
Marketing, 24, 3 (2011), 263–281.

21. Chu, S.-C., and Kamal, S. The effect of perceived blogger credibility and
argument quality on message elaboration and brand attitudes: An exploratory
study. Journal of Interactive Advertising, 8, 2 (2008), 26–37.

22. Chu, S.-C., and Kim, Y. Determinants of consumer engagement in electronic
word-of-mouth (eWOM) in social networking sites. International journal
of Advertising, 30, 1 (2011), 47–75.

23. Cooper, S. Facebook is leading the way in social commerce. http://www.
businessinsider.com/social-commerce-2015-report-2015-7 (accessed on
March 25, 2017).

24. Corson, Y., and Verrier, N. Emotions and false memories valence or
arousal? Psychological Science, 18, 3 (2007), 208–211.

25. Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance
of information technology. MIS Quarterly, 13, 3 (1989), 319–340.

26. Ebermann, J.; Stanoevska-Slabeva, K.; and Wozniak, T. Influential factors
of recommendation behaviour in social network sites-an empirical analysis. In
Proceedings of the Nineteenth European Conference on Information Systems (ECIS).
Helsinki: Association for Information Systems (AIS). (2011), paper no. 259.

27. Edell, J.A., and Burke, M.C. The moderating effect of attitude toward an
ad on ad effectiveness under different processing conditions. In T.C. Kinnear
(ed.), Advances in Consumer Research. Provo, UT: Association for Consumer
Research, 1984, pp. 644–649.

28. eMarketer. Facebook is no. 1 for social commerce. https://www.emark
eter.com/Article/Facebook-No-1-Social-Commerce/1010721 (accessed on
March 25, 2017).

29. Eroglu, S.A.; Machleit, K.A.; and Davis, L.M. Empirical testing of a model
of online store atmospherics and shopper responses. Psychology and
Marketing, 20, 2 (2003), 139–150.

30. Fang, Y.-H. Beyond the credibility of electronic word of mouth: Exploring
eWOM adoption on social networking sites from affective and curiosity
perspectives. International Journal of Electronic Commerce, 18, 3 (2014), 67–102.

31. Forgas, J.P. Mood and judgment: The affect infusion model (AIM).
Psychological Bulletin, 117, 1 (1995), 39–66.

32. Forgas, J.P., and George, J.M. Affective influences on judgments and
behavior in organizations: An information processing perspective.
Organizational Behavior and Human Decision Processes, 86, 1 (2001), 3–34.

33. Forman, C.; Ghose, A.; and Wiesenfeld, B. Examining the relationship
between reviews and sales: The role of reviewer identity disclosure in electronic
markets. Information Systems Research, 19, 3 (2008), 291–313.

34. Fornell, C., and Larcker, D.F. Evaluating structural equation models with
unobservable variables and measurement error. Journal of Marketing Research,
18, 1 (February 1981), 39–50.

35. Gefen, D.; Benbasat, I.; and Pavlou, P. A research agenda for trust in
online environments. Journal of Management Information Systems, 24, 4 (2008),
275–286.

36. Ghose, A., and Ipeirotis, P.G. Estimating the helpfulness and economic
impact of product reviews: Mining text and reviewer characteristics. IEEE
Transactions on Knowledge and Data Engineering, 23, 10 (2011), 1498–1512.

37. Granovetter, M.S. The strength of weak ties. American Journal of Sociology,
78 (1973), 1360–1380.

38. Gupta, P., and Harris, J. How e-WOM recommendations influence product
consideration and quality of choice: A motivation to process information
perspective. Journal of Business Research, 63, 9 (2010), 1041–1049.

39. Hansen, S.S., and Lee, J.K. What drives consumers to pass along marketer-
generated eWOM in social network games? Social and game factors in play. Journal of Theoretical and Applied Electronic Commerce Research, 8, 1
(2013), 53–68.

40. Hennig-Thurau, T.; Gwinner, K.P.; Walsh, G.; and Gremler, D.D.
Electronic word-of-mouth via consumer-opinion platforms: What motivates
consumers to articulate themselves on the Internet? Journal of Interactive
Marketing, 18, 1 (2004), 38–52.

41. Huang, G.-H., and Korfiatis, N. Trying before buying: The moderating
role of online reviews in trial attitude formation toward mobile applications.
International Journal of Electronic Commerce, 19, 4 (2015), 77–111.

42. Huang, J.; Su, S.; Zhou, L.; and Liu, X. Attitude toward the viral ad:
Expanding traditional advertising models to interactive advertising. Journal
of Interactive Marketing, 27, 1 (2013), 36–46.

43. Jansen, B.J.; Zhang, M.; Sobel, K.; and Chowdury, A. Twitter power:
Tweets as electronic word of mouth. Journal of the American Society for
Information Science and Technology, 60, 11 (2009), 2169–2188.

44. Kaplan, A.M., and Haenlein, M. Users of the world, unite! The challenges
and opportunities of Social Media. Business Horizons, 53, 1 (2010), 59–68.

45. Karimi, J., and Walter, Z. The role of dynamic capabilities in responding
to digital disruption: A factor-based study of the newspaper industry. Journal
of Management Information Systems, 32, 1 (2015), 39–81.

46. Keenan, A., and Shiri, A. Sociability and social interaction on social
networking websites. Library Review, 58, 6 (2009), 438–450.

47. Kuan, K.K.; Hui, K.-L.; Prasarnphanich, P.; and Lai, H.-Y. What makes a
review voted? An empirical investigation of review voting in online review
systems. Journal of the Association for Information Systems, 16, 1 (2015), 48–71.

48. Lee, J., and Lee, J.-N. Understanding the product information inference
process in electronic word-of-mouth: An objectivity–subjectivity dichotomy
perspective. Information and Management, 46, 5 (2009), 302–311.

49. Lee, J.; Park, D.-H.; and Han, I. The effect of negative online consumer
reviews on product attitude: An information processing view. Electronic
Commerce Research and Applications, 7, 3 (2008), 341–352.

50. Lee, M., and Youn, S. Electronic word of mouth (eWOM): How eWOM
platforms influence consumer product judgement. International Journal of
Advertising, 28, 3 (2009), 473–499.

51. Lee, W.; Xiong, L.; and Hu, C. The effect of Facebook users’ arousal and
valence on intention to go to the festival: Applying an extension of the
technology acceptance model. International Journal of Hospitality Management,
31, 3 (2012), 819–827.

52. Lenhart, A. Adults and social network websites. http://www.pewinter
net.org/2009/01/14/adults-and-social-network-websites (accessed on
March 25, 2017).

53. LePage, E. All the social media advertising stats you need to know.
https://blog.hootsuite.com/social-media-advertising-stats (accessed on
March 25, 2017).

54. Leung, X.Y.; Bai, B.; and Stahura, K.A. The marketing effectiveness of
social media in the hotel industry a comparison of facebook and twitter.
Journal of Hospitality and Tourism Research, 39, 2 (2015), 147–169.

55. Liang, H.; Saraf, N.; Hu, Q.; and Xue, Y. Assimilation of enterprise
systems: the effect of institutional pressures and the mediating role of top
management. MIS quarterly, 31, 1 (2007), 59–87.

56. Liang, T.-P.; Li, X.; Yang, C.-T.; and Wang, M. What in consumer reviews
affects the sales of mobile apps: A multifacet sentiment analysis approach.
International Journal of Electronic Commerce, 20, 2 (2015), 236–260.

57. Lin, R., and Utz, S. The emotional responses of browsing Facebook:
Happiness, envy, and the role of tie strength. Computers in Human Behavior,
52 (2015), 29–38.

58. Liu, H. Social network profiles as taste performances. Journal of Computer-
Mediated Communication, 13, 1 (2007), 252–275.

59. Luarn, P.; Yang, J.-C.; and Chiu, Y.-P. Why people check in to social
network sites. International Journal of Electronic Commerce, 19, 4 (2015), 21–46.

60. MacKenzie, S.B.; Lutz, R.J.; and Belch, G.E. The role of attitude toward
the ad as a mediator of advertising effectiveness: A test of competing
explanations. Journal of Marketing Research, 23, 2 (1986), 130–143.

61. Mamonov, S.; Koufaris, M.; and Benbunan-Fich, R. The role of the sense
of community in the sustainability of social network sites. International
Journal of Electronic Commerce, 20, 4 (2016), 470–498.

62. Mangold, W.G., and Faulds, D.J. Social media: The new hybrid element
of the promotion mix. Business Horizons, 52, 4 (2009), 357–365.

63. Mani, D.; Barua, A.; and Whinston, A. An empirical analysis of the
impact of information capabilities design on business process outsourcing
performance. MIS Quarterly, 34, 1 (2010), 39–62.

64. McCroskey, J.C.; Hamilton, P.R.; and Weiner, A.N. The effect of interaction
behavior on source credibility, homophily, and interpersonal attraction.
Human Communication Research, 1, 1 (1974), 42–52.

65. Mooney, C.Z.; Duval, R.D.; and Duval, R. Bootstrapping: A Nonparametric
Approach to Statistical Inference. Newbury Park, CA: Sage, 1993.

66. Mudambi, S.M., and Schuff, D. What makes a helpful review? A study of
customer reviews on Amazon. com. MIS Quarterly, 34, 1 (2010), 185–200.

67. Okazaki, S. Social influence model and electronic word of mouth: PC versus
mobile internet. International Journal of Advertising, 28, 3 (2009), 439–472.

68. Pan, L.-Y., and Chiou, J.-S. How much can you trust online information?
Cues for perceived trustworthiness of consumer-generated online information.
Journal of Interactive Marketing, 25, 2 (2011), 67–74.

69. Pang, J., and Qiu, L. Effect of online review chunking on product attitude:
The moderating role of motivation to think. International Journal of Electronic
Commerce, 20, 3 (2016), 355–383.

70. Park, D.-H.; Lee, J.; and Han, I. The effect of on-line consumer reviews on
consumer purchasing intention: The moderating role of involvement.
International Journal of Electronic Commerce, 11, 4 (2007), 125–148.

71. Pavlou, P.A., and Gefen, D. Building effective online marketplaces with
institution-based trust. Information Systems Research, 15, 1 (2004), 37–59.

72. Petty, R.E., and Cacioppo, J.T. Elaboration likelihood model. In L.
Berkowitz (ed.), Advances in Experimental Social Psychology. San Diego:
Academic Press, 1986, pp. 123–205.

73. Pham, M.T.; Cohen, J.B.; Pracejus, J.W.; and Hughes, G.D. Affect monitoring
and the primacy of feelings in judgment. Journal of Consumer Research,
28, 2 (2001), 167–188.

74. purelybranded. Why People ‘Like’ and ‘Unlike’ Brands on Facebook. 2016.
http://www.purelybranded.com/insights/why-people-like-and-unlikebrands-
on-facebook/

75. Qiu, L.; Pang, J.; and Lim, K.H. Effects of conflicting aggregated rating on
eWOM review credibility and diagnosticity: The moderating role of review
valence. Decision Support Systems, 54, 1 (2012), 631–643.

76. Raguseo, E., and Vitari, C. The effect of brand on the impact of e-WOM
on hotels’ financial performance. International Journal of Electronic Commerce,
21, 2 (2017), 249–269.

77. Riegner, C. Word of mouth on the web: The impact of Web 2.0 on
consumer purchase decisions. Journal of Advertising Research, 47, 4 (2007),
436–447.

78. Riordan, M.A., and Kreuz, R.J. Emotion encoding and interpretation in
computer-mediated communication: Reasons for use. Computers in Human
Behavior, 26, 6 (2010), 1667–1673.

79. Salehan, M., and Kim, D. Predicting the performance of online consumer
reviews: A sentiment mining approach to big data analytics. Decision
Suppport Systems, 81 (2016), 30–40.

80. Sanbonmatsu, D.M., and Kardes, F.R. The effects of physiological arousal
on information processing and persuasion. Journal of Consumer Research, 15, 3
(1988), 379–385.

81. Schindler, R.M., and Bickart, B. Perceived helpfulness of online consumer
reviews: The role of message content and style. Journal of Consumer Behaviour,
11, 3 (2012), 234–243.

82. Sen, S., and Lerman, D. Why are you telling me this? An examination into
negative consumer reviews on the web. Journal of Interactive Marketing, 21, 4
(2007), 76–94.

83. Shih, H.-p.; Lai, K.-h.; and Cheng, T. Informational and relational influences
on electronic word of mouth: An empirical study of an online consumer
discussion forum. International Journal of Electronic Commerce, 17, 4
(2013), 137–166.

84. Shimp, T.A. Attitude toward the ad as a mediator of consumer brand
choice. Journal of Advertising, 10, 2 (1981), 9–48.

85. Söderlund, M., and Rosengren, S. Receiving word-of-mouth from the
service customer: An emotion-based effectiveness assessment. Journal of
Retailing and Consumer Services, 14, 2 (2007), 123–136.

86. Storbeck, J., and Clore, G.L. Affective arousal as information: How
affective arousal influences judgments, learning, and memory. Social and
Personality Psychology Compass, 2, 5 (2008), 1824–1843.

87. Sussman, S.W., and Siegal, W.S. Informational influence in organizations:
An integrated approach to knowledge adoption. Information Systems Research,
14, 1 (2003), 47–65.

88. Svensson, A. Facebook—the social newspaper that never sleeps: A study
of Facebook eWOM’s persuasiveness on the receivers. https://gupea.ub.gu.se/bitstream/2077/26249/1/gupea_2077_26249_1.pdf (accessed on March
25, 2017).

89. Vogt, J.; De Houwer, J.; Koster, E.H.; Van Damme, S.; and Crombez, G.
Allocation of spatial attention to emotional stimuli depends upon arousal
and not valence. Emotion, 8, 6 (2008), 880–885.

90. Wathen, C.N., and Burkell, J. Believe it or not: Factors influencing credibility
on the Web. Journal of the American Society for Information Science and
Technology, 53, 2 (2002), 134–144.

91. Xu, Q. Should I trust him? The effects of reviewer profile characteristics
on eWOM credibility. Computers in Human Behavior, 33 (2014), 136–144.

92. Yin, D.; Bond, S.; and Zhang, H. Anxious or angry? Effects of discrete
emotions on the perceived helpfulness of online reviews. MIS Quarterly, 38, 2
(2014), 539–560.

93. York, A. Social media demographics to inform a better segmentation
strategy. http://sproutsocial.com/insights/new-social-media-demographics
(accessed on March 25, 2017).

94. Zadra, J.R., and Clore, G.L. Emotion and perception: The role of affective
information. Wiley Interdisciplinary Reviews: Cognitive Science, 2, 6 (2011), 676–
685.