The Effects of Interpersonal Tie Strength and Subjective Norms on Consumers' Brand-Related eWOM Referral Intentions

REFERENCES

• Aaker, David A. (1996), Building Strong Brands, New York: Free Press.
   Google Scholar
• Aaker, Jennifer, Susan Fournier, and Adam S. Brasel (2004), “When Good Brands Do Bad,” Journal of Consumer Research, 31 (June), 1–17.
   Web of Science ®Google Scholar
• Ajzen, Icek (1991), “The Theory of Planned Behavior,” Organizational Behavior and Human Decision Processes, 50 (2), 179–211.
   Web of Science ®Google Scholar
• ——— (2002), “Perceived Behavioral Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behavior,” Journal of Applied Social Psychology, 32 (4), 665–83.
   Web of Science ®Google Scholar
• ———, and Martin Fishbein (1980), Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Bagozzi, Richard P., Nancy Wong, Shuzo Abe, and Massimo Bergami (2000), “Cultural and Situational Contingencies and the Theory of Reasoned Action: Application to Fast Food Restaurant Consumption,” Journal of Consumer Psychology, 9 (2), 97–106.
   Web of Science ®Google Scholar
• ———, Utpal M. Dholakia and Lisa R. Klein Pearo (2007), “Antecedents and Consequences of Online Social Interactions,” Media Psychology, 9 (1), 77–114.
   Web of Science ®Google Scholar
• Baker, Rosland K., and Katherine M. White (2010), “Predicting Adolescents' Use of Social Networking Sites from an Extended Theory of Planned Behaviour Perspective,” Computers in Human Behavior, 26 (6), 1591–97.
   Web of Science ®Google Scholar
• Blackston, Max (1993), “Beyond Brand Personality: Building Brand Equality,” In Brand Equity and Advertising, D. Aaker and A. Biel, eds., Hillsdale, NJ: Erlbaum, 113–24.
   Google Scholar
• Brown, Jo, Amanda J. Broderick, and Nick Lee (2007), “Word of Mouth Communication within Online Communities: Conceptualizing the Online Social Network,” Journal of Interactive Marketing, 21 (3), 2–20.
   Web of Science ®Google Scholar
• Brown, Jacqueline J., and Peter H. Reingen (1987), “Social Ties and Word-of-Mouth Referral Behavior,” Journal of Consumer Research, 14 (3), 350–62.
   Web of Science ®Google Scholar
• Buda, Richard, and Yong Zhang (2000), “Consumer Product Evaluation: The Interactive Effect of Message Framing, Presentation Order, and Source Credibility,” Journal of Product and Brand Management, 9 (4), 229–42.
   Google Scholar
• Cheung, Man Y., Chuan Luo, Choon L. Sia, and Huaping Chen (2009), “Credibility of Electronic Word-of-Mouth: Information and Normative Determinants of On-Line Consumer Recommendations,” International Journal of Electronic Commerce, 13 (4), 9–38.
   Web of Science ®Google Scholar
• Cho, Soyoen, Jisu Huh, and Ronald, J. Faber (2014), “The Influence of Sender Trust and Advertiser Trust on Multistage Effects of Viral Advertising,” Journal of Advertising, 43 (1), 100–14.
   Web of Science ®Google Scholar
• Chi, Hsu-Hsien (2011), “Interactive Digital Advertising vs. Virtual Brand Community: Exploratory Study of User Motivation and Social Media Marketing Responses in Taiwan,” Journal of Interactive Advertising, 12 (1), 44–61.
   Google Scholar
• Chiou, Jyh-Shen (1998), “The Effects of Attitudes, Subjective Norms, and Perceived Behavioral Control on Consumers' Purchase Intentions: The Moderating Effects of Product Knowledge and Attention to Social Comparison Information,” National Science Council, 9 (2), 298–308.
   Google Scholar
• Chiu, Hung-Chang, Yi-Ching Hsieh, Ya-Hui Kao, and Monie Lee (2007), “The Determinants of Email Receivers' Disseminating Behaviors on the Internet,” Journal of Advertising Research, 47 (4), 524–34.
   Web of Science ®Google Scholar
• Chu, Shu-Chuan (2011), “Viral Advertising in Social Media: Participation in Facebook Groups and Responses Among College-Aged Users,” Journal of Interactive Advertising 12 (1), 30–43.
   Google Scholar
• ———, and Yoojung Kim (2011), “Determinants of Consumer Engagement in Electronic Word of Mouth (eWOM) in Social Networking Sites,” International Journal of Advertising, 30 (1), 47–75.
   Web of Science ®Google Scholar
• Cruz, Danilo, and Chris Fill (2008), “Evaluating Viral Marketing: Isolating the Key Criteria,” Marketing Intelligence and Planning, 26 (7), 743–58.
   Google Scholar
• De Bruyn, Arnaud, and Gary L. Lilien (2008), “A Multi-Stage Model of Word-of-Mouth Influence Through Viral Marketing,” International Journal of Research in Marketing, 25 (3), 151–63.
   Web of Science ®Google Scholar
• eMarketer (2015), “Worldwide Social Network Ad Spending: Midyear 2014 Complete Forecast,” http://www.emarketer.com/Article/APAC-Ranks-No-2-Worldwide-Social-Network-Ad-Spend-Share/1011221.
   Google Scholar
• Fournier, Susan (1998), “Consumers and Their Brands: Developing Relationship Theory in Consumer Research,” Journal of Consumer Research, 24 (March), 343–73.
   Web of Science ®Google Scholar
• ———, and Claudio Alvarez (2012), “Brands as Relationship Partners: Warmth, Competence, and In-Between,” Journal of Consumer Psychology, 22, 177–85.
   Web of Science ®Google Scholar
• Freberg, Karen (2012), “Using the Theory of Planned Behavior to Predict Intention to Comply with a Food Recall Message,” Health Communication, 28, 359–65.
   PubMed Web of Science ®Google Scholar
• Goldenberg, Jacob, Barak Libai, Sarit Moldovan, and Eitan Muller (2001), “Talk of the Network: A Complex Systems Look at the Underlying Process of Word-of-Mouth,” Marketing Letters, 12 (3), 211–23.
   Web of Science ®Google Scholar
• ———, Barak Libai, Sarit Moldovan, and Eitan Muller (2007), “The NPV of Bad News,” International Journal of Research in Marketing, 24, 186–200.
   Web of Science ®Google Scholar
• Granovetter, Mark S. (1973), “The Strength of Weak Ties,” American Journal of Sociology, 78 (6), 1360–80.
   Web of Science ®Google Scholar
• ———. (2004), “The Impact of Social Structures on Economic Development,” Journal of Economic Perspective, 19 (1), 33–50.
   Web of Science ®Google Scholar
• Hayes, Jameson, and Karen W. King (2014), “The Social Exchange of Viral Ads: Referral and Coreferral of Ads Among College Students,” Journal of Interactive Advertising, 14 (2), 98–100.
   Google Scholar
• Heiman, Gary (2002), Basic Statistics for the Behavioral Science, 4th ed., Belmont, CA: Wadsworth.
   Google Scholar
• Herr, Paul M., Frank R. Kardes, and John Kim (1991), “Effects of Word-of-Mouth and Product-Attitude Information on Persuasion: An Accessibility-Diagnosticity Perspective,” Journal of Consumer Research, 17 (4), 454–62.
   Web of Science ®Google Scholar
• Ho, Jason Y.C., and Melanie Dempsey (2010), “Viral Marketing: Motivations to Forward Online Content,” Journal of Business Research, 63 (9–10), 1000–06.
   Web of Science ®Google Scholar
• Hsu, Chin-Lung, and Judy C.C. Lin (2008), “Acceptance of Blog Usage: The Role of Technology Acceptance, Social Influence, and Knowledge Sharing Motivation,” Information and Management, 45 (1), 65–74.
   Web of Science ®Google Scholar
• Huber, Frank, Johannes Vogel, and Frederik Meyer (2009), “When Brands Get Branded,” Marketing Theory, 9 (1), 131–36.
   Web of Science ®Google Scholar
• Huitema, Bradley (2011), The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies, 2nd ed., Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Jobs, Charles, and David M. Gilfoil (2012), “Less Is More for Online Marcom in Emerging Markets: Linking Hofstede's Cultural Dimensions and Higher Relative Preferences for Micoblogging in Developing Nations,” Academic of Marketing Studies Journal, 16 (2), 79–96.
   Google Scholar
• Kang, Hyunmo, Minhi Hahn, David R. Fortin, Yong J. Hyun, and Yunni Eom (2006), “Effects of Perceived Behavioral Control on the Consumer Usage Intention of e-Coupons,” Psychology and Marketing, 23, 841–64.
   Web of Science ®Google Scholar
• Kiecker, Pamela, and Deborah Cowles (2001), “Interpersonal Communication and Personal Influence on the Internet: A Framework for Examining Online Word-of-Mouth,” Journal of Euromarketing, 11 (2), 71–88.
   Google Scholar
• Kim, Eunice, Yongjun Sung, and Hamsu Kang (2014), “Brand Followers' Retweeting Behavior on Twitter: How Brand Relationships Influence Brand Electronic Word-of-Mouth,” Computer in Human Behavior, 37, 18–25.
   Web of Science ®Google Scholar
• Lee, Joonghwa, and Mira Lee (2009), “Predicting the Use of Online Video Advertising: Using the Theory of Reasoned Action,” In Proceedings of the 2009 Conference of American Academy of Advertising, Glen Nowak, ed., Cincinnati: American Academy of Advertising, 29.
   Google Scholar
• ———, Chang-Dae Ham, and Mikyoung Kim (2013), “Why People Pass Along Online Video Advertising: From the Perspectives of the Interpersonal Communication Motives Scale and the Theory of Reasoned Action,” Journal of Interactive Advertising, 13 (1), 1–13.
   Google Scholar
• Lee, Su-Fang, Yuan-Cheng Tsai, and Wen-Jang Jih (2006), “An Empirical Examination of Customer Perceptions of Mobile Advertising,” Information Resources Management Journals, 19 (4), 39–55.
   Google Scholar
• Levin, Danel Z., and Rob Cross (2004), “Mediating Role of Trust in Effective Knowledge Transfer,” Management Science, 50 (11), 1477–90.
   Web of Science ®Google Scholar
• Manning, Mark (2009), “The Effects of Subjective Norms on Behavior in the Theory of Planned Behavior: A Meta-Analysis,” British Journal of Social Psychology, 48, 647–705.
   Web of Science ®Google Scholar
• Morimoto, Mariko, and Susan Chang (2006), “Consumers' Attitudes toward Unsolicited Commercial E-mail and Postal Direct Mail Marketing Methods: Intrusiveness, Perceived Loss of Control, and Irritation,” Journal of Interactive Advertising, 7 (1), 8–20.
   Google Scholar
• Nan, Xiaoli, and Ronald J. Faber (2004), “Advertising Theory: Reconceptualizing the Building Blocks,” Marketing Theory, 4 (1–2), 7–30.
   Google Scholar
• Nielsen (2013), “Under the Influence: Consumer Trust in Advertising.” Retrieved from http://www.nielsen.com/us/en/insights/news/2013/under-the-influence-consumer-trust-in-advertising.html.
   Google Scholar
• Norman, Andrew, and Cristel A. Russell (2006), “The Pass-Along Effect: Investigating Word-of-Mouth Effects on Online Survey Procedures,” Journal of Computer-Mediated Communication, 11 (4), 1085–103.
   Web of Science ®Google Scholar
• Petty, Reichert E., John T. Cacioppo, and David Schumann (1983), “Central and Peripheral Routes to Advertising Effectiveness: The Moderating Role of Involvement,” Journal of Consumer Research, 10, 135–46.
   Web of Science ®Google Scholar
• Phelps, Joseph E., Regina Lewis, Lynne Mobilio, David Perry, and Raman Niranjan (2004), “Viral Marketing or Electronic Word-of-Mouth Advertising: Examining Consumer Responses and Motivations to Pass Along Email,” Journal of Advertising Research, 44 (4), 333–48.
   Web of Science ®Google Scholar
• Plummer, Joseph T. (2007), “Editorial: Word of Mouth—A New Advertising Discipline?,” Journal of Advertising Research, 47 (4), 385–86.
   Web of Science ®Google Scholar
• Rusbult, Caryl E., John M. Martz, and Christopher R. Agnew (1998), “The Investment Model Scale: Measuring Commitment Level, Satisfaction Level, Quality of Alternatives, and Investment Size,” Personal Relationships, 5 (4), 357–87.
   Web of Science ®Google Scholar
• Saeri, Alexander K., Claudette Ogilvie, Stephen T. La Macchia, Joanne R. Smith, and Winnifred R. Louis (2014), “Predicting Facebook Users' Online Privacy Protection: Risk, Trust, Norm Focus Theory, and the Theory of Planned Behavior,” Journal of Social Psychology, 15 (4), 352–69.
   Web of Science ®Google Scholar
• Sawyer, Alan G. (1975), “Detecting Demand Characteristics in Laboratory Experiments in Consumer Research: The Case of Repetition-Affect Research,” Advances in Consumer Research, 2, 713–24.
   Google Scholar
• Smith, Ted, James R. Coyle, Elizabeth Lightfoot, and Amy Scott (2007), “Reconsidering Models of Influence: The Relationship between Consumer Social Networks and Word-of-Mouth Effectiveness,” Journal of Advertising Research, 47, 387–97.
   Web of Science ®Google Scholar
• Trusov, Michael, Randolph E. Bucklin, and Koen Pauwels (2009), “Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site,” Journal of Marketing, 73 (September), 90–102.
   Web of Science ®Google Scholar
• van Noort, Guda, Marjolijn L. Antheunis, and Eva A. van Reijmersdal (2012), “Social Connections and the Persuasiveness of Viral Campaigns in Social Network Sites: Persuasive Intent as the Underlying Mechanism,” Journal of Marketing Communication, 18 (1), 39–53.
   Google Scholar
• Williams, Kevin D. (2011), “The Effects of Homophily, Identification, and Violent Video Games on Players,” Mass Communication and Society, 14, 3–24.
   Web of Science ®Google Scholar
• Wright, Kevin (2000), “Perceptions of On-Line Support Providers: An Examination of Perceived Homophily, Source Credibility, Communication, and Social Support Within On-Line Support Groups,” Communication Quarterly, 48 (1), 44–59.
   Google Scholar
• Xie, Qinwei, and Matthew Kukla (2012), “Share It on Facebook: Examining Viral Marketing and Motives to Pass Along Electronic Content on SNS,” in Proceedings of the 2012 Conference of American Academy of Advertising, Margaret Morrison, ed., Cincinnati: American Academy of Advertising, 148–60.
   Google Scholar
• Yang, Hongwei, and Liuning Zhou (2011), “Extending TPB and TAM to Mobile Viral Marketing: An Exploratory Study on American Young Consumers' Mobile Viral Marketing Attitude, Intent and Behavior,” Journal of Targeting, Measurement, and Analysis for Marketing, 19, 85–98.
   Google Scholar
• Yang, Kiseol (2012), “Consumer Technology Traits in Determining Mobile Shopping Adoption: An Application of the Extended Theory of Planned Behavior,” Journal of Retailing and Consumer Services, 19 (5), 484–91.
   Google Scholar
• Yeh, Yi-Hsin, and Sejung Marina Choi (2011), “MINI-Lovers, Maxi-Mouths: An Investigation of Antecedents to eWOM Intention Among Brand Community Members,” Journal of Marketing Communications, 17 (3), 145–62.
   Google Scholar
• Zhang, Jing, and En Mao (2008), “Understanding the Acceptance of Mobile SMS Advertising among Young Chinese Consumers,” Psychology & Marketing, 25 (8), 787–805.
   Web of Science ®Google Scholar