Dynamic Effects of Social Influence and Direct Marketing on the Adoption of High-Technology Products

Abstract

Many firms capitalize on their customers' social networks to improve the success rate of their new products. In this article, the authors analyze the dynamic effects of social influence and direct marketing on the adoption of a new high-technology product. Social influence is likely to play a role because the decision to adopt a high-involvement product requires extensive information gathering from various sources. The authors use call detail records to construct ego networks for a large sample of customers of a Dutch mobile telecommunications operator. Using a fractional polynomial hazard approach to model adoption timing and multiple social influence variables, they provide a fine-grained analysis of social influence. They show that the effect of social influence from cumulative adoptions in a customer's network decreases from the product introduction onward, whereas the influence of recent adoptions remains constant. The effect of direct marketing is also positive and decreases from the product introduction onward. This study provides new insights into the adoption of high-technology products by analyzing dynamic effects of social influence and direct marketing simultaneously.

Indicators of opinion leadership in customer networks: self-reports and degree centrality

“…More specifically, we include the average number of DMs per week a customer receives during the observation period (AVG_direct_marketing) as an additional variable (Risselada et al 2014). The average number of DMs per week is a proxy for how likely it is that a customer receives a DM.…”

“…The telecom industry is well suited for social influence research because network data can be obtained and linked to behavioral data (e.g., Nitzan and Libai 2011;Risselada et al 2014). Family calling plans were not available at this telecom operator during the observation period.…”

Digital Native Advertising: Practitioner Perspectives and a Research Agenda

“…Advertisers increasingly use new media communication strategies to create engagement in order to shape consumers' perceptions of brands or organizations (Grant, Botha, and Kietzman 2015). Such interactions create word-of-mouth effects with vast reach and impact, especially considering the speed of diffusion and disruption of geographical boundaries (Risselada, Verhoef, and Bijmolt 2014). Evaluations of the effectiveness of digital native advertising thus should include both attitudinal and conversion measures.…”

Exploring the social influence of multichannel access in an online health community

“…In addition, new technologies provide significant resources for studying social influence using a high number of participants and retrieving more datasets. Numerous studies propose and present significant effects of social influence on high-technology product adoption through mobile telecommunication (Risselada, Verhoef, & Bijmolt, 2014), product ratings in e-commerce (Sridhar & Srinivasan, 2012), and buying decisions in online social networks (Bond et al, 2012).…”

“…Johnson (2008) Assimilation of electronic channel Efficiency, learning orientation Gupta et al (2004) Channel-switching Risk perception, search price, evaluation effort, waiting time Ansari et al (2008) Channel migration Purchase, income, age, catalogs Our study Multichannel access Social influence, rating effects of social influence in the adoption or use of new technology and systems (Wang, Meister, & Gray, 2013). In marketing, many scholars explored the effects of social influence between customers in the decision to adopt a new product (Risselada et al, 2014;Shen, Zhang, & Zhao, 2016), demonstrating the value of investment in advertisement to enhance social influence (Terlutter & Capella, 2013). In e-commerce, neighbors or friends have been observed to purchase similar products and adopt similar sales channels (Bapna & Umyarov, 2015).…”