Achieving loyalty for sharing economy platforms: an expectation–confirmation perspective

Users' continuance intention towards an AI painting application: An extended expectation confirmation model

With the rapid advancement of technology, Artificial Intelligence (AI) painting has emerged as a leading intelligence service. This study aims to empirically investigate users' continuance intention toward AI painting applications by utilizing and expanding the Expectation Confirmation Model (ECM), Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and the Flow Theory. A comprehensive research model is proposed. A total of 443 questionnaires were distributed to users with AI painting experiences for data collection. The hypotheses were tested through structural equation modeling. The primary conclusions drawn from this research include: 1) Confirmation plays a crucial role, significantly and positively predicting satisfaction and social impact. 2) Personal innovativeness has a significant effect on confirmation. 3) Satisfaction, flow experience, and social influence directly and positively predict intention, with social influence showing the most significant impact, while perceived usefulness, perceived enjoyment, and performance expectancy show no significant impact on intention. 4) Habit plays a negative moderating role in the association between social influence and continued intention to use. These findings offer valuable insights and inspiration for users seeking to understand the appropriate utilization of AI painting and provide actionable directions for the development of AI painting.

Do ride-hailing drivers' psychological behaviors influence operational performance?

Purpose

The proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.

Design/methodology/approach

The authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.

Findings

Ride-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.

Practical implications

The results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.

Originality/value

This study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.

Value configurations in sharing economy business models

The sharing economy gains momentum and develops a major economic impact on traditional markets and firms. However, only rudimentary theoretical and empirical insights exist on how sharing networks, i.e., focal firms, shared goods providers and customers, create and capture value in their sharing-based business models. We conduct a qualitative study to find key differences in sharing-based business models that are decisive for their value configurations. Our results show that (1) customization versus standardization of shared goods and (2) the centralization versus particularization of property rights over the shared goods are two important dimensions to distinguish value configurations. A second, quantitative study confirms the visibility and relevance of these dimensions to customers. We discuss strategic options for focal firms to design value configurations regarding the two dimensions to optimize value creation and value capture in sharing networks. Firms can use this two-dimensional search grid to explore untapped opportunities in the sharing economy.