Purpose: Online retailers are pioneering the incentivization of customers to generate more product reviews by rewarding them. However, little is known about the impact of reward types on customers' review behavior, including review frequency and sentiment. To address this gap, we investigated the effects of different reward types on customers' review behavior and how these rewards influence customers' review behavior.Design/methodology/approach: We collected secondary data and empirically tested the hypothesis by analyzing the change in reward policy. Regression and two-stage Heckman models were applied to investigate the effects, with the latter used to control potential selection issues.Findings: The results revealed that monetary rewards can stimulate customers to generate more positive product reviews. Furthermore, the reward amount has a negative moderating effect on the aforementioned relationship. Additionally, customer tenure negatively moderates the relationship between monetary rewards and review behavior.Originality/value: This study contributes to the understanding of user-generated content motivation and provides managerial implications for reward programs.

Purpose: This study aims to investigate the impact of technological turbulence on entrepreneurial orientation (EO) in Chinese e-commerce enterprises. It also examines the mediating roles of business ties and political ties, and the moderating effect of transaction uncertainty on these relationships.Design/methodology/approach: A sample of 173 Chinese e-commerce enterprises was analyzed using survey data. Structural equation modeling was employed to test the proposed hypotheses, including the direct effects of technological turbulence on EO, the mediating roles of business and political ties, and the moderating effect of transaction uncertainty.Findings: The results indicate a positive correlation between technological turbulence and EO. Business ties mediate the relationship between technological turbulence and EO, while political ties do not. Transaction uncertainty negatively moderates the relationship between business ties and EO but does not significantly affect the relationship between political ties and EO. Additionally, EO positively impacts market performance.Originality/value: This study extends the understanding of how external environmental factors, such as technological turbulence, influence EO in the context of Chinese e-commerce. It highlights the differential roles of business and political ties and provides insights into the moderating effects of transaction uncertainty. The findings offer practical implications for e-commerce firms seeking to enhance their entrepreneurial capabilities in turbulent environments.

After the COVID-19 epidemic, a growing number of commercial entities have decided to enter the online platform and operated as an electronic business venture. However, the timing of entering the online market is a strategically important issue. On the basis of social capital theory and resource-based view, this study attempts to understand the different impacts of two strategic orientations (i.e., Guanxi orientation and entrepreneurial orientation) and perceived environmental turbulence (i.e., market turbulence and political turbulence) on online market entry timing. We test four hypotheses using data collected from 174 Chinese companies. Our results confirm that entrepreneurial orientation negatively impacts online market entry timing, and this effect is moderated by perceived market turbulence such that the negative relationship between entrepreneurial orientation and online market entry timing will be strengthened in higher market turbulence. By contrast, Guanxi orientation positively impacts online market entry timing, and the positive relationship between Guanxi orientation and online market entry timing will be weakened in higher political turbulence. Implications and future research directions are discussed.

Purpose: This research investigates the effects of disclosing AI usage on social media platforms on brand loyalty. Design/methodology/approach: Three experiments using between-subjects designs (N = 700) test a moderated mediation model. Study 1 establishes the main effect and mediating mechanism using a fictitious brand. Study 2 employs a real brand to examine how existing relationship strength (followers vs. non-followers) moderates the disclosure effect. Study 3 investigates consumers' AI-trust propensity as an individual-level moderator. Findings: AI disclosure significantly weakens brand loyalty through diminished perceived relational investment. Consumers interpret AI-mediated interactions as signals of reduced brand effort and care. Moreover, brand followers demonstrate greater resilience to AI disclosure than non-followers, and consumers with high AI-trust propensity exhibit alleviated negative reactions. The indirect effect through perceived relational investment is weaker for both followers and AI-trusting consumers. Practical implications: Instead of universal AI disclosure policies, companies should pursue segmented disclosure strategies based on relationship depth and consumers' technology attitudes. Companies should focus on relational investment through enhanced personalization, human oversight messaging or hybrid AI-human service models. Originality/value: This research introduces perceived relational investment as a new mechanism linking AI disclosure to loyalty, challenging the supposition that AI transparency always yields positive outcomes.