Article Preview
Top1. Introduction
The technology-mediated community extends social space and social networks from face-to-face to online communication (Treiblmaier and Chong, 2011; Wellman, 1996), where consumers share and exchange content of interests (Hagel, 1999); attach/detach to/from groups (Granitz and Ward, 1996; Ebner et al., 2009); shape delight, engagement, trust, and loyalty toward products; and impose compound influences on others via reviews, comments, and online communication. Notably, the ineffectiveness of information exchange and the declined vitality have become an issue, called information stickiness. Information stickiness is a widely-seen but under-estimated phenomenon, with symptoms including slow information exchange, discontinuous updates, growing information loss, and large information processing costs (Von Hippel, 1998). Though it has been discussed in other contexts hypothetically, it has not been fully explained. Some studies have found that message direction and strength, message relevance to receivers, message travel route, and relative information strength of transferal determine online information’s stickiness (Faust and Svensson, 2001; Gupta and Kim, 2004; Meng, 2022). Some organisational studies including ones by multinational corporations (Montazemi et al., 2012), have proved that group features (Olmos-Peñuela et al., 2014), the intervention of an opinion leader such as a consultant (Olmos-Peñuela et al., 2014), group learning support (Krishnaveni and Sujatha, 2012), group characteristics such as network structure (Reagans and Mcevily, 2003), individual heterogeneity (Bhagat et al., 2002), and trust (Zhao and Lavin, 2012) can alleviate the symptoms of information stickiness to allow a flowing transmission between destinations. Although these identified factors have been spotted for causing information stickiness from various aspects, a systematic framework is required to integrate all the considerations, which range from personal to interpersonal societal influences.
Inspired by these phenomena, the paper brings up a few questions to consider. First, given that stickiness is almost everywhere, how to describe and quantify its symptoms in the context of online communication at the aggregate level? In particular, is it possible to provide generalizable measures of the symptoms embedded in aggregate social relations? Secondly, what are the antecedents that cause the stickiness, and how do these antecedents lead to the formation and evolution of information stickiness? To answer the above questions, this paper collects the literature with the antecedents of interpersonal information exchange stickiness, examining the relationship of explanatory factors and the key symptoms via experiments.
Theoretically, the findings show that the personal, interpersonal, and environmental factors of stickiness enrich the theories of information exchange online. Methodologically, the approach considers the significance of testing relations within a complex socioeconomic network with multiple players with high internal validity and contributes to the knowledge of information stickiness. This paper claims that to better understand stickiness at an aggregate level, a self-developing approach to link it with the interests and actions of individuals receiving information should be adopted. Next, this research composes and runs a model to report on four aspects of information stickiness: overall sharing speed, information vitality, information growth, and times of disengagement. The results show that information stickiness exists as a phenomenon with different symptoms and is embedded in and traceable back to online customers’ micro-level motives and restriction of information exchange and belief-framing.