Customer-to-Customer Communication: Referral of High and Low Involvement Products through Stimulated Word-of-Mouth

References

• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
   Web of Science ®Google Scholar
• Azmat, A., Ul Haq, J., Hussain, S., Qadir, A., & Bukhari, S. (2022). OCEAN traits: Who shares more word-of-mouth? Journal of Promotion Management, 28(6), 749–773. https://doi.org/10.1080/10496491.2021.2015510
   Google Scholar
• Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to consumer influence. Journal of Consumer Research, 15(4), 473–481. https://www.jstor.org/stable/2489543 https://doi.org/10.1086/209186
   Web of Science ®Google Scholar
• Berman, B. (2016). Referral marketing: Harnessing the power of your customers. Business Horizons, 59(1), 19–28. https://doi.org/10.1016/j.bushor.2015.08.001
   Web of Science ®Google Scholar
• Brown, J., Broderick, A. J., & Lee, N. (2007). Word-of-mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir.20082
   Web of Science ®Google Scholar
• Browne, B. A., & Kaldenberg, D. O. (1997). Conceptualizing self-monitoring: Links to materialism and product involvement. Journal of Consumer Marketing, 14(1), 31–44. https://doi.org/10.1108/07363769710155848
   Google Scholar
• Carmack, H. J., & Heiss, S. N. (2018). Using the theory of planned behavior to predict college students’ intent to use Linkedin for job searches and professional networking. Communication Studies, 69(2), 145–160. https://doi.org/10.1080/10510974.2018.1424003
   Web of Science ®Google Scholar
• Chandon, P., Morwitz, V. G., & Reinartz, W. J. (2005). Do intentions really predict behavior? Self-generated validity effects in survey research. Journal of Marketing, 69(2), 1–14. https://doi.org/10.1509/jmkg.69.2.1.60755
   Web of Science ®Google Scholar
• Chen, Y. (2022). Identifying typology of tie strength: A latent class analysis. In Y. Chen (Ed.), Causal effects of social capital (pp. 347–377). Palgrave Macmillan. https://doi.org/10.1007/978-981-19-5912-7_11
   Google Scholar
• Cheng, H. H., & Huang, S. W. (2013). Exploring antecedents and consequence of online group-buying intention: An extended perspective on theory of planned behavior. International Journal of Information Management, 33(1), 185–198. https://doi.org/10.1016/j.ijinfomgt.2012.09.003
   Web of Science ®Google Scholar
• Chung, H., & Zhao, X. (2003). Humour effect on memory and attitude: Moderating role of product involvement. International Journal of Advertising, 22(1), 117–144. https://doi.org/10.1080/02650487.2003.11072842
   Google Scholar
• Court, D., Elzinga, D., Mulder, S., Vetvik, O. J. (2009). The consumer decision journey. McKinsey & Company. https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/the-consumer-decision-journey
   Google Scholar
• Davis, L. E., Ajzen, I., Saunders, J., & Williams, T. (2002). Theory of planned behavior questionnaire. APA PsycTests. https://doi.org/10.1037/t15482-000
   Google Scholar
• Fan, C. L., Su, Y. L., Chang, S. T., & Liu, D. Y. Y. (2014). Exploring how referral reward program design affects consumer intent to purchase from a recipient perspective. International Journal of Business and Management, 9(11), 21–30. https://doi.org/10.5539/ijbm.v9n11p21
   Google Scholar
• Frenzen, J., & Nakamoto, K. (1993). Structure, cooperation, and the flow of market information. Journal of Consumer Research, 20(3), 360–375. https://www.jstor.org/stable/2489353 https://doi.org/10.1086/209355
   Web of Science ®Google Scholar
• Furrer, O., Kerguignas, J. Y., & Landry, M. (2021). Customer captivity, negative word-of-mouth and well-being: A mixed-methods study. Journal of Services Marketing, 35(6), 755–773. https://doi.org/10.1108/JSM-07-2020-0311
   Web of Science ®Google Scholar
• Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380. https://www.jstor.org/stable/2776392 https://doi.org/10.1086/225469
   Web of Science ®Google Scholar
• Gunawan, D. D., & Huarng, K. (2015). Viral effects of social network and media on consumers’ purchase intention. Journal of Business Research, 68(11), 2237–2241. https://doi.org/10.1016/j.jbusres.2015.06.004
   Web of Science ®Google Scholar
• Guo, Z. (2012). Optimal decision making for online referral marketing. Decision Support Systems, 52(2), 373–383. https://doi.org/10.1016/j.dss.2011.09.004
   Web of Science ®Google Scholar
• Han, M. C., & Kim, Y. (2017). Why consumers hesitate to shop online: Perceived risk and product involvement on Taobao.com. Journal of Promotion Management, 23(1), 24–44. https://doi.org/10.1080/10496491.2016.1251530
   Google Scholar
• Hanssens, D. M., Pauwels, K. H., Srinivasan, S., Vanhuele, M., & Yildirim, G. (2014). Consumer attitude metrics for guiding marketing mix decisions. Marketing Science, 33(4), 534–550. https://doi.org/10.1287/mksc.2013.0841
   Web of Science ®Google Scholar
• Howard, J. A., & Sheth, J. N. (1969). The theory of buyer behavior. Wiley.
   Google Scholar
• Jin, L., & Huang, Y. (2014). When money does not work: The differential effects of monetary versus in-kind rewards in referral reward programs. International Journal of Research in Marketing, 31(1), 107–116. https://doi.org/10.1016/j.ijresmar.2013.08.005
   Web of Science ®Google Scholar
• Kim, S., Kim, J., & Kim, E. (2017). Metaphor as visual thinking in advertising and its effects: Focus on brand familiarity and product involvement. Journal of Promotion Management, 23(5), 654–672. https://doi.org/10.1080/10496491.2017.1297982
   Google Scholar
• Kim, E., & Park, F. S. (2023). Do Facebook friends make me donate? Factors involved in online donations via SNS. Journal of Promotion Management, 29(6), 849–872. https://doi.org/10.1080/10496491.2023.2165210
   Google Scholar
• Kotler, P., & Armstrong, G. (2012). Principles of marketing (14th ed.). Prentice Hall.
   Google Scholar
• Kotler, P., & Keller, K. L. (2009). Marketing management (13th ed.). Pearson Prentice Hall.
   Google Scholar
• Lascu, D. N., & Zinkhan, G. (1999). Consumer conformity: Review and applications for marketing theory and practice. Journal of Marketing Theory and Practice, 7(3), 1–12. https://doi.org/10.1080/10696679.1999.11501836
   Google Scholar
• Leboff, G. (2014). Stickier marketing (2nd ed.). Kogan Page.
   Google Scholar
• Lemon, K., & Verhoef, P. (2016). Understanding customer experience throughout the consumer journey. Journal of Marketing, 80(6), 69–96. https://doi.org/10.1509/jm.15.0420
   Web of Science ®Google Scholar
• Leung, K., & Morris, M. W. (2015). Values, schemas, and norms in the culture-behavior nexus: A situated dynamics framework. Journal of International Business Studies, 46(9), 1028–1050. https://doi.org/10.1057/jibs.2014.66
   Web of Science ®Google Scholar
• Levin, D. Z., & Cross, R. (2004). The strength of weak ties you can trust: The mediating role of trust in effective knowledge transfer. Management Science, 50(11), 1477–1490. https://doi.org/10.1287/mnsc.1030.0136
   Web of Science ®Google Scholar
• Lin, S.-C., Tseng, H.-T., & Shirazi, F. (2022). Consumer decision journey for online group buying: Psychological and intentional procedure perspectives. British Food Journal, 124(12), 4387–4405. https://doi.org/10.1108/BFJ-12-2021-1277
   Web of Science ®Google Scholar
• Lin, X., & Spence, P. R. (2018). Identity on social networks as a cue: Identity, retweets, and credibility. Communication Studies, 69(5), 461–482. https://doi.org/10.1080/10510974.2018.1489295
   Web of Science ®Google Scholar
• Liviatan, I., Trope, Y., & Liberman, N. (2008). Interpersonal similarity as a social distance dimension: Implications for perception of others’ actions. Journal of Experimental Social Psychology, 44(5), 1256–1269. https://doi.org/10.1016/j.jesp.2008.04.007
   PubMed Web of Science ®Google Scholar
• López, L., & Sicilia, M. (2014). eWOM as source of influence: The impact of participation in eWOM and perceived source trustworthiness on decision making. Journal of Interactive Advertising, 14(2), 86–97. https://doi.org/10.1080/15252019.2014.944288
   Google Scholar
• Magnusson, M. K., Arvola, A., Koivisto Hursti, U., Aberg, L., & Sjödén, P. (2001). Attitudes towards organic foods among Swedish consumers. British Food Journal, 103(3), 209–227. https://doi.org/10.1108/00070700110386755
   Google Scholar
• Mainardes, E. W., Portelada, P. H. M., & Damasceno, F. S. (2023). The influence on cosmetics purchase intention of electronic word-of-mouth on Instagram. Journal of Promotion Management, 29(7), 961–991. https://doi.org/10.1080/10496491.2023.2167897
   Google Scholar
• Marsden, P., & Campbell, K. (1984). Measuring tie strength. Social Forces, 63(2), 482–501. https://doi.org/10.2307/2579058
   Web of Science ®Google Scholar
• McCombes, S. (2019). An introduction to sampling methods. https://www.scribbr.com/methodology/sampling-methods/
   Google Scholar
• Melumad, S., Inman, J. J., & Pham, M. T. (2019). Selectively emotional: How smartphone use changes user-generated content. Journal of Marketing Research, 56(2), 259–275. https://doi.org/10.1177/0022243718815429
   Web of Science ®Google Scholar
• Ngarmwongnoi, C., Oliveira, J. S., AbedRabbo, M., & Mousavi, S. (2020). The implications of eWOM adoption on the customer journey. Journal of Consumer Marketing, 37(7), 749–759. https://doi.org/10.1108/JCM-10-2019-3450
   Web of Science ®Google Scholar
• Orsingher, C., & Wirtz, J. (2018). Psychological drivers of referral reward program effectiveness. Journal of Services Marketing, 32(3), 256–268. https://doi.org/10.1108/JSM-07-2017-0247
   Web of Science ®Google Scholar
• Park, H. S. (2000). Relationships among attitudes and subjective norms: Testing the theory of reasoned action across cultures. Communication Studies, 51(2), 162–175. https://doi.org/10.1080/10510970009388516
   Google Scholar
• Pelling, E. L., & White, K. M. (2009). The theory of planned behavior applied to young people’ s use of social networking web sites. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 12(6), 755–759. https://doi.org/10.1089/cpb.2009.0109
   PubMedGoogle Scholar
• Plummer, J. T. (2007). Editorial: Word-of-mouth—A new advertising discipline? Journal of Advertising Research, 47(4), 385–386. https://doi.org/10.2501/S0021849907070390
   Web of Science ®Google Scholar
• Podnar, K., & Javernik, P. (2012). The effect of word-of-mouth on consumers’ attitudes toward products and their purchase probability. Journal of Promotion Management, 18(2), 145–168. https://doi.org/10.1080/10496491.2012.668426
   Google Scholar
• Prentice, D. A., & Miller, D. T. (1993). Pluralistic ignorance and alcohol use on campus: Some consequences of misperceiving the social norm. Journal of Personality and Social Psychology, 64(2), 243–256. https://doi.org/10.1037/0022-3514.64.2.243
   PubMed Web of Science ®Google Scholar
• Raza, S. H., Abu Bakar, H., & Mohamad, B. (2019). The effects of advertising appeals on consumers’ behavioral intention towards global brands: The mediating role of attitude and the moderating role of uncertainty avoidance. Journal of Islamic Marketing, 11(2), 440–460. https://doi.org/10.1108/JIMA-11-2017-0134
   Web of Science ®Google Scholar
• Rejón-Guardia, F., & Martínez-López, F. J. (2014). The pervasive influence of electronic word-of-mouth (eWOM) on today’s social consumer. In F. Martínez-López (Ed.), Handbook of strategic e-business management (pp. 821–839). Progress in IS. Springer. https://doi.org/10.1007/978-3-642-39747-9_34
   Google Scholar
• Rickards, G., Magee, C., & Artino, A. R. (2012). You can’t fix by analysis what you’ve spoiled by design: Developing survey instruments and collecting validity evidence. Journal of Graduate Medical Education, 4(4), 407–410. https://doi.org/10.4300/JGME-D-12-00239.1
   PubMedGoogle Scholar
• Ryu, G., & Feick, L. (2007). A penny for your thoughts: Referral reward programs and referral likelihood. Journal of Marketing, 71(1), 84–94. https://doi.org/10.1509/jmkg.71.1.84
   Web of Science ®Google Scholar
• Sanne, P. N. C., & Wiese, M. (2018). The theory of planned behavior and user engagement applied to Facebook advertising. South African Journal of Information Management, 20(1), a915. https://doi.org/10.4102/sajim.v20i1.915
   Web of Science ®Google Scholar
• Schiffman, L. G., & Kanuk, L. L. (2008). Consumer behavior (7th ed.). Index.
   Google Scholar
• Schlenker, B. R., & Leary, M. R. (1982). Social anxiety and self-presentation: A conceptualization model. Psychological Bulletin, 92(3), 641–669. https://doi.org/10.1037/0033-2909.92.3.641
   PubMed Web of Science ®Google Scholar
• Schmitt, B., & Zarantonello, L. (2013). Consumer experience and experiential marketing: A critical review. In N. K. Malhotra (Ed.), Review of marketing research (Vol. 10, pp. 25–61). https://doi.org/10.1108/S1548-6435(2013)0000010006
   Google Scholar
• Schmitt, P., Skiera, B., & Van den Bulte, C. (2011). Referral programs and customer value. Journal of Marketing, 75(1), 46–59. https://doi.org/10.1509/jm.75.1.46
   Web of Science ®Google Scholar
• Shan, Y., & King, K. W. (2015). The effects of interpersonal tie strength and subjective norms on consumers’ brand-related eWOM referral intentions. Journal of Interactive Advertising, 15(1), 16–27. https://doi.org/10.1080/15252019.2015.1016636
   Google Scholar
• Sivakumar, S. (2021). Application of Howard Sheth model of consumer decision making for the purchase of a television. SSRN Electronic Journal. Emerald Group Publishing Limited. https://doi.org/10.2139/ssrn.3899873
   Google Scholar
• Sundaram, D. S., Mitra, K., & Webster, C. (1998). Word-of-mouth communications: A motivational analysis, in NA. In J. W. Alba & J. W. Hutchinson (Eds.), Advances in consumer research (Vol. 25, pp. 527–531) Association for Consumer Research.
   Google Scholar
• Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
   Web of Science ®Google Scholar
• Terry, D. J., & O’Leary, J. E. (1995). The theory of planned behavior: The effects of perceived behavioral control and self-efficacy. The British Journal of Social Psychology, 34(2), 199–220. https://doi.org/10.1111/j.2044-8309.1995.tb01058.x
   PubMed Web of Science ®Google Scholar
• Tong, S., Luo, X., & Xu, B. (2020). Personalized mobile marketing strategies. Journal of the Academy of Marketing Science, 48(1), 64–78. https://doi.org/10.1007/s11747-019-00693-3
   Web of Science ®Google Scholar
• Tuk, M. A., Verlegh, P. W. J., Smidts, A., & Wigboldus, D. H. J. (2009). Sales and sincerity: The role of relational framing in word-of-mouth marketing. Journal of Consumer Psychology, 19(1), 38–47. https://doi.org/10.1016/j.jcps.2008.12.007
   Web of Science ®Google Scholar
• Van den Bulte, C., & Wuyts, S. H. K. (2007). Social networks in marketing (MSI Relevant Knowledge Series), Marketing Science Institute.
   Google Scholar
• Verlegh, P. W. J., Ryu, G., Tuk, M. A., & Feick, L. (2013). Receiver responses to rewarded referrals: The motive inferences framework. Journal of the Academy of Marketing Science, 41(6), 669–682. https://doi.org/10.1007/s11747-013-0327-8
   Web of Science ®Google Scholar
• Wang, L., & Chen, Z. (2022). The effect of incentive structure on referral: The determining role of self-construal. Journal of the Academy of Marketing Science, 50(5), 1091–1110. https://doi.org/10.1007/s11747-022-00852-z
   Web of Science ®Google Scholar
• Wangenheim, F. V., & Bayón, T. (2007). The chain from customer satisfaction via word-of-mouth referrals to new customer acquisition. Journal of the Academy of Marketing Science, 35(2), 233–249. https://doi.org/10.1007/s11747-007-0037-1
   Web of Science ®Google Scholar
• Wirtz, J., & Chew, P. (2002). The effects of incentives, deal proneness, satisfaction and tie strength on word-of-mouth behavior. International Journal of Service Industry Management, 13(2), 141–162. https://doi.org/10.1108/09564230210425340
   Google Scholar
• Wirtz, J., Orsingher, C., Chew, P., & Tambyah, S. (2013). The role of metaperception on the effectiveness of referral reward programs. Journal of Service Research, 16(1), 82–98. https://doi.org/10.1177/1094670512462138
   Web of Science ®Google Scholar
• Wirtz, J., Tang, C., & Georgi, D. (2019). Successful referral behavior in referral reward programs. Journal of Service Management, 30(1), 48–74. https://doi.org/10.1108/JOSM-04-2018-0111
   Web of Science ®Google Scholar
• Xiao, P., Tang, C. S., & Wirtz, J. (2011). Optimizing referral reward programs under impression management considerations. European Journal of Operational Research, 215(3), 730–739. https://doi.org/10.1016/j.ejor.2011.05.042
   Web of Science ®Google Scholar
• Xu, M., Yu, Z., & Tu, Y. (2023). I will get a reward, too: When disclosing the referrer reward increases referring. Journal of Marketing Research, 60(2), 355–370. https://doi.org/10.1177/00222437221117113
   Web of Science ®Google Scholar
• Xue, F., & Muralidharan, S. (2015). A green picture is worth a thousand words?: Effects of visual and textual environmental appeals in advertising and the moderating role of product involvement. Journal of Promotion Management, 21(1), 82–106. https://doi.org/10.1080/10496491.2014.971209
   Google Scholar
• Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revision, and application to advertising. Journal of Advertising, 23(4), 59–70. https://doi.org/10.1080/00913367.1943.10673459
   Web of Science ®Google Scholar