Consumer Decision-making Processes in Mobile Viral Marketing Campaigns

Abstract

The high penetration of cell phones in today's global environment offers a wide range of promising mobile marketing activities, including mobile viral marketing campaigns. However, the success of these campaigns, which remains unexplored, depends on the consumers’ willingness to actively forward the advertisements that they receive to acquaintances, e.g., to make mobile referrals. Therefore, it is important to identify and understand the factors that influence consumer referral behavior via mobile devices. The authors analyze a three-stage model of consumer referral behavior via mobile devices in a field study of a firm-created mobile viral marketing campaign. The findings suggest that consumers who place high importance on the purposive value and entertainment value of a message are likely to enter the interest and referral stages. Accounting for consumers’ egocentric social networks, we find that tie strength has a negative influence on the reading and decision to refer stages and that degree centrality has no influence on the decision-making process.

Effect of marketing activities, benefits, risks, confusion due to over-choice, price, quality and consumer trust on online tourism purchasing

“…These results confirm those of the study by Pescher et al (2014), indicating that online purchasing perceived benefits and risks affect the online marketing process. Thus, when potential buyers believe that the benefits outweigh the risks they are more likely to trust the product and finally to buy it , something in which marketing can play a vital role through the construction of consumer perceptions.…”

“…The Internet may provide an efficient alternative for the transmission and delivery of advertising messages to potential customers, as indicated by the increasing number of successful online marketing campaigns in recent years (Pescher et al 2014). Targeted online marketing activities can help in the reduction of perceived risks introduced by frequent technological advances, the rapid growth and diffusion of technology among consumers and competitors, and the reduction of confusion due to over-choice caused by the increasing number of product alternatives available to consumers (Pantano et al 2013).…”

“…Targeted online marketing activities can help in the reduction of perceived risks introduced by frequent technological advances, the rapid growth and diffusion of technology among consumers and competitors, and the reduction of confusion due to over-choice caused by the increasing number of product alternatives available to consumers (Pantano et al 2013). On the other hand, online purchasing's perceived benefits and risks and consumers' trust in products affect the online marketing process (Pescher et al 2014), since it has to take into consideration consumer characteristics (purposive and entertainment values), the quantity of alternative products offered, and the process of perceived benefit and risk formulation (Okazaki 2008). …”

Effect of Instant Messaging Advertising on the Hierarchy‐of‐Effects Model Amid Teenagers in South Africa

“…As predicted, the IM platform was predominantly accessed via mobile devices, representing 75.6% of responses. This prolific use of mobile device trend (especially to access social media) among adolescents is confirmed by both South African (GeoPoll and World Wide Worx, 2015;Jovago, 2015;Nhlapo, 2015;Swanepoel, 2015) and global research (Pescher et al, 2014;Annalect, 2015;eMarketer, 2015;IAB, 2015). Mxit's length of usage was reasonably evenly distributed between less than one year to greater than five years on this IM channel.…”

Elements of a Design Theory of Nano-Viral Messages: A Case Study of #Solar Nanovirals

“…Business and management researchers have explored a number of different issues related to sharing viral messages including: motivation (Berger, 2014;Ho and Dempsey, 2010;Pescher, Reichhart, and Spann, 2014); social network characteristics (Bampo, Ewing, Mather, Stewart, and Wallace, 2008;Hinz, Skiera, Barrot, and Becker, 2011;Leskovec, Adamic, and Huberman, 2007;Liu-Thompkins and Rogerson, 2012;Smith, Coyle, Lightfoot, and Scott, 2007); interpersonal factors (Cho, Huh, and Faber, 2014;De Bruyn and Lilien, 2008;Harvey, Stewart, and Ewing, 2011;Hayes, King, and Ramirez, 2016); personality (Chiu, Hsieh, Kao, and Lee, 2007); meta-and para-textual features (Blichfeldt and Smed, 2015;Seo, Li, Choi, and Yoon, 2018); and sharing mechanism details (Aral and Walker, 2011;Schulze, Schöler, and Skiera, 2014).…”