Determinants of Social Contagion during New Product Adoption

Abstract

Social contagion has been shown to play an important role during new product adoption by consumers. Social contagion is the process by which consumers influence each other to adopt and use a product in a specific way. Current literature makes a basic assumption that social contagion is caused by the characteristics of consumers, who they interact with or who they live near to, and thus are most likely to come into contact with. However, the role that the product has in stimulating social contagion is conspicuously absent in this research. The current study focuses on identifying determinants of social contagion and investigates their indirect effect on the market demand for a new product. Determinants are drawn from both product attributes and consumer characteristics. Based on a three-part theory of social contagion, the authors propose variables that influence the fecundity, fidelity, and longevity of a product. Fecundity is the extent to which many consumers make copies of the behavior related to the adoption or use of that product. Sometimes, they will have to buy the product beforehand (like mobile telephony), and sometimes they will not (like Internet banking, assuming they already have a bank account and an Internet connection). The fidelity of a product is the extent to which consumers make accurate copies of the product-related behavior, in other words how the product supports the users in easily carrying out the behavior. The longevity of the product is the extent to which consumers keep on expressing the behavior over a long period of time. The main contributions of this study are that the relative importance of these determinants of social contagion are investigated empirically, and that the predictive power of this approach for estimating market demand is examined. Data are analyzed from 124 product-segment combinations of information and communication technology products from the telecom and financial sectors. These are mass-market products that have passed their initial growth phase. Using partial least squares path modeling, the main determinants of social contagion are identified, and the positive, significant relationship between social contagion and market demand is confirmed. Specifically, a main finding is that consumer characteristics have only a weak effect on the probability that social contagion occurs, while the main success factors are those product attributes that stimulate the creation of new copies of the product-related behavior; that is, product fecundity. This study offers product developers a new approach to assess the market potential for innovations, and the results provide recommendations for improving their products to increase the market potential. The authors note with respect to the practical applicability of their method that it does not require a working prototype, a market pilot, or other costly steps. It can be carried out with simply a description of the product, which means that it can be applied very early in the product development process.

Factors Influencing the Behavior Intention of Mobile Commerce Service Users: An Exploratory Study in Hong Kong

“…10, No. 7;2015 18-24, 25-34, 35-44 and 45 or above is 5.13, 5.07, 4.95 and 5.06 respectively, indicating that age does not affect the behavior intention of consumers using mobile commerce services in Hong Kong. As there are no significant differences in the mean values of different subgroups in terms of gender, marital status, education level and age, all that data could be analyzed as a whole.…”

“…Compatibility is defined as the degree to which using mobile commerce services is perceived as being consistent with the user's existing lifestyle, values, needs and preferences (Chen, Gillenson, & Sherrell, 2002;Langley, Bijmolt, Ortt, & Pals, 2012). Chen, Gillenson and Sherrell (2002) found that compatibility has a positive influence on consumer behavior in online shopping.…”

Co-diffusion of social contagions

“…A new brand can increase the entire market potential due to its promotion or compete for the same market potential and slow down diffusion [20]. Given the role of social contagions in the process of innovation [21], synergy quantification frames cooperation and competition in precise, numerical terms consider general purpose technologies (GPTs). GPTs are technologies that have an impact across sectors and spillover effects as network externalities with economic benefits [22].…”

Patterns of Herding and their Occurrence in an Online Setting

“…According to Cialdini (2008), influence occurs through six mechanisms: reciprocity, commitment and consistency, social proof, authority, liking, and scarcity. Contagion, or social contagion, is similar to influence but adopts the metaphor of viral infection such that the focus is on the behavior that makes use of people to propagate itself (Du and Kamakura, 2011;Langley et al 2012). Influence and contagion are two processes with the focus at the individual level.…”