The Impact of Individual Motivations and Social Capital on the Continuous Usage Intention of Mobile Social Apps

Abstract

Mobile social apps have experienced enormous growth as online personal networking media. Social exchange theory (for individual motivation), theories of collective action and social capital theory (for social capital) can be applied in order to understand how an individual’s behavior may exert effects on or receive influences from other users with regard to the continuance usage intention of mobile social apps. This study examines individual motivations and social capital affecting relationship quality in terms of trust in and satisfaction with mobile social apps and how these factors influence continuance usage intentions of mobile social apps. An online survey is used to collect 320 responses from users of mobile social apps. Our results indicate that promotional motivation and innovativeness affect relationship quality levels. Maintaining relational enhancement, social homogeneity, and social identity along with service usefulness have effects on the relationship quality level, which in turn affects continuance usage intention. Given the lack of studies regarding the application of the theories of collective action and social capital to gain a better understanding of continuance usage intentions, this study provides additional insight into how individual motivations and social capital affect continuous usage.

The Students’ Flow Experience With the Continuous Intention of Using Online English Platforms

“…Research has described flow encounters in various pursuits, including reading, dancing, rock climbing, chess, etc. Provided the reduced figures of returning users, studies that examine the crucial issues that affect continuance use intent are vital to individuals who formulate marketing tactics for online platforms ( Lee and Kim, 2020 ). The sustainable use of online platforms in business processes is critical to generating commercial value.…”

Attribute of Big Data Analytics Quality Affecting Business Performance

“…While precision and completeness have been well suggested in previous studies, value innovation and social impact have been studied less. Value innovation can be an attribute based on how much BDA obtains meaningfulness, value added, and relevance from BDA, which have been suggested in previous studies [63,64] . Social impact can be explained in terms of alignment and relevance in the social context of BDA as data quality attributes.…”

“…Predictability is the extent to which it is possible to predict phenomena and provide meaning and insights in relation to them. Interpretability is the extent to which it is possible to interpret relationships among specific events, objects, and groups [64] . In a similar vein, Feki and Mnif [63] suggested meaningfulness as a data quality dimension.…”

Toward a Unified Theory of Customer Continuance Model for Financial Technology Chatbots

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