Building Sustainable Online Communities: Investigating Changes in User Behavioral Intention as an Online Community Develops

建立可持續發展的網絡社區﹕研究隨著網絡社區發展不同階段的用戶行為動機

Student thesis: Doctoral Thesis

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Award date5 Jan 2022

Abstract

Despite the substantial process in the field of user behavior study in the online community context, little research has adopted a dynamic view of variations in user motivation factors as an online community develops. Notably, various previous studies have generalized the antecedents of user behavioral intention across different user types without considering differences in their decision-making. However, user behavioral motivation may change as an online community develops, necessitating a stage-dependent view to enable practitioners to develop customized strategies across the various development stages and, hence, make the community and the platform sustainable. Therefore, this dissertation uses the life cycle of an online community as a lens through which to conduct three studies specifically considering the relevant challenges at the start-up stage, the later stage, and the commercialization stage of online communities, aiming to help the online community to achieve the sustainable success.

The first study primarily focuses on user participation behavior at the start-up stage, as well as considering differences in motivators compared with users at later stages. Many online communities fail to at the start-up stage due to the cold-start problem, which describes the challenge confronted by newly established online communities of accumulating an initial batch of content that is voluntarily provided by users. Drawing on the chasm theory and perceived value theory, this study investigates user participation behavior, specifically comparing early users and late users to understand stage-related user motivation. Survey data from 589 TikTok users enabled the identification of changes in motivators of user participation that coincided with the online community’s development. The fundamental differences between early and later stage users produce a chasm between the two stages that can endanger the possibility of an online community reaching mainstream users after successful diffusion at the early stage.

Going a step further, the second paper probes the strategies used to retain users as an online community moves to the later stage, exploring the reasons that modern short video online communities, such as TikTok, are more successful than traditional ones (such as YouTube) at maintaining user interest. Adopting technology affordance theory enables this study to identify the main technologies that contribute to the TikTok user experience, recognizing that its AI recommendation algorithm and the simplicity of navigating the platform most encourage user engagement. Furthermore, user experience level was introduced as a moderator to understand differences in preferences between new and old users. This study collected 432 valid questionnaires from TikTok users, with empirical results suggesting that three technology affordances (namely, perceived effortlessness, perceived recommendation accuracy, and perceived recommendation serendipity) contribute to the optimal flow experience for TikTok users. Meanwhile, multi-group analysis results indicated that individuals react differently to the same stimuli as their experience level increases. The factors contributing to a new relationship and a long-term relationship are varied.

Finally, the third study focuses on the commercialization stage of an online short video community, namely, TikTok. In 2020, TikTok moved to the next stage of commercialization and monetization by integrating e-commerce features, cultivating particularly fertile ground for companies to sell their products. However, TikTok user purchase behavior has yet to receive substantial research attention, and little is currently known about their purchase motivations. Consequently, this study assesses the motivators for TikTok-based user purchase intention. The proposed research model engaged user experience and commitment theory, with customer type introduced as a moderator to explore motivational differences between potential customers and repeat customers. Data from 458 TikTok users revealed that four user experience dimensions (namely, information experience, entertainment experience, relationship-based experience, and micro-time killing experience) significantly impact user commitment to both the influencer and the platform, which, in turn, modify purchase intention. Notably, the moderating effect of customer type indicated differences in preferences between potential customers and repeat customers.

These three studies make several major contributions. Few studies have taken a dynamic approach to investigate user motivation in the online community context, especially in terms of adopting a stage-dependent perspective. Thus, these three studies extend the existing literature by specifically investigating user behavioral variance across the evolution of an online community. Additionally, as a burgeoning industry, the success of short-format video platforms, especially TikTok, and the behavior and preferences of their users have been largely under-investigated, despite the potentially critical insights available. These studies also enrich the literature by introducing and investigating context-specific user motivations and inspiring future research to consider context-specific factors when investigating user behavior in the short video platform context. On a practical level, these studies provide insights for developers wanting to build and develop sustainable online communities. There is a need for customized strategies, especially as online communities evolve and specifically for different user types.