Livestreaming shopping platforms have emerged as dynamic and innovative channels for e-commerce, mobile commerce, and social commerce, revolutionizing the way consumers engage with online retail. Drawing upon the Technology Acceptance Model 3 framework, this research seeks to provide a comprehensive understanding of the interplay between perceived risk, trust, innovativeness and deal proneness in shaping consumers’ purchasing behavior in the livestreaming social commerce context. A snowball sampling method was applied to collect data from 675 Chinese livestreaming customers in December 2022. A PLS-SEM analysis was used to measure the proposed model. The results confirm that the present model has weak explanatory power except for medium predictive accuracy in explaining consumers’ purchasing behavior in the livestreaming social commerce context (R² = 0.35; Q² = 0.31). This research contributes to the social commerce literature by extending the Technology Acceptance Model 3 (TAM 3) to the novel domain of the livestreaming social commerce context, offering insights into the unique drivers of consumers’ purchasing behavior. It also provides practical implications for platform developers and marketers aiming to enhance consumer experiences and increase sales performance, thereby increasing economic growth.

Background/problem: In contemporary Chinese university management, fostering knowledge sharing is critical for achieving collaboration against reduced human resources. While leadership as an antecedent to facilitate knowledge sharing has been extensively studied, identity leadership has not yet been addressed. Objective/purpose: The study aimed to examine the mediating role of team identification between identity leadership and knowledge sharing behaviors. It also proposed to investigate the effect of team identification on ingroup bias and the potential influence on knowledge sharing. Design and Methodology: This quantitative study collected the data from 385 administrative staff members of Chinese universities using quota sampling. Data was analyzed using partial least squares structural equation modelling (PLS-SEM). Results: The findings revealed a positive effect of identity leadership on team identification (β = .65, p < .001), of team identification on knowledge sharing behaviors (β = .38, p < .001), and on ingroup bias (β = .39, p < .001). Team identification mediated the effect of identity leadership and knowledge sharing behaviors (β = .23, p < .001), while the ingroup bias failed to show positive mediation between team identification and knowledge sharing behaviors (β = -.02, p = .34). Conclusion and Implications: The study highlights the role of identification on knowledge sharing and ingroup bias. The findings indicate that while advancement of team identification by engaging identity leadership benefits ingroup knowledge sharing, ingroup bias that has been introduced with overly strong identification should be balanced. It reflects the attitudinal degrading towards the outgroup but failed to promote knowledge sharing among the ingroup.

County-level innovation capability is a key link in promoting the deepening development of the national innovation system. Although there has been extensive research on the factors that affect county-level innovation capabilities, most studies have a mismatch between theory and methods. In theory, it is most appropriate to explain the reasons for improving county-level innovation capabilities from the perspective of complex systems. However, research methods lack the ability to capture the complex interactive effects between various conditions that affect innovation capability. In addition, it is necessary to seek new explanatory perspectives for the many conflicting findings in the literature. This study is based on the theories of complex systems and regional innovation systems, utilizing relevant data from 52 counties in Zhejiang, China, and using the fsQCA method from a holistic configuration perspective to study the multiple paths and mechanisms that promote synergy between the government and the effective market, attract factors to "reverse flow," and drive the improvement of county innovation capabilities. Research has found that a single factor is not a necessary condition to enhance the high county innovation capacity. The configuration that generates high county innovation capabilities can be summarized into four types: the joint driving model of innovative entities and responsible government; the joint driving model of collaborative production factors and responsible government; driven by the traditional industrial upgrading model; and the joint driving model of traditional industrial upgrading and responsible government. The research conclusion also reveals that the business environment plays an important role in the process of enhancing county innovation capabilities, but the innovation main body is the new force in enhancing county innovation capabilities. The various elements that affect the innovation capacity of the county adapt to each other, co-evolve, and evolve into different ecosystems, forming a diversified and differentiated driving path.

Purpose: Live streaming commerce is an emerging shopping channel that facilitates real-time, two-way interaction not only between consumers and vendors, but also among consumers. This study conceptualizes Online Live Streaming Interaction (OLSI) as a multidimensional construct, grounded in social presence theory, and develops a measurement tool that captures the unique dynamics of interactions in live streaming environments. Design/methodology/approach: The study follows a rigorous, four-step process for scale development and validation. Inductive and deductive methods were employed for item generation. Quantitative data were then collected from 394 Chinese participants and 159 French participants, ensuring cross-cultural relevance. The data were analyzed using exploratory and confirmatory factor analyses to assess the reliability and validity of the scale. Findings: The results establish the OLSI scale as a multidimensional construct encompassing six key dimensions: online discussion engagement, streamer-viewer interactions, preference for online social interactions, communication effectiveness for streamers, online interaction propensity, and perceived value of the online community. Research limitations/implications: This study's primary limitation is its limited exploration of nomological validity, future research should investigate the relationships between the OLSI dimensions and behavioral outcomes (e.g. purchase intention, satisfaction, loyalty). Practical implications: The findings provide practical insights for managers and enable them to develop content and engagement strategies that align with audience preferences; this will lead to both an optimization of communication and enhancement of viewer experiences. Originality/value: This study provides a comprehensive framework for understanding the unique interaction dynamics within live streaming commerce and offers a robust measurement tool for future research.

Social commerce, the integration of e-commerce and social media (Mohammad et al. 2024), is progressively more important in the world of e-commerce. The use of social media platforms enables users t...

Artificial Intelligence generated content (AIGC) is rapidly reshaping higher education. Guided by the Technology Acceptance Model (TAM), this study examines how perceived ease of use (PEOU) and perceived usefulness (PU) predict Chinese faculty members’ AIGC use behaviour, with perceived self-efficacy (PSE) and institutional support (IS) modelled as external variables. Survey data from 295 faculty members was analysed and structural equation modelling was employed to test the hypothesized relationships. The results reveal that both PEOU and PU are critical predictors of AIGC adoption, while PSE and IS significantly enhance faculty perceptions of ease of use and usefulness, thereby facilitating actual usage behaviour. The model accounted for 55.2% of the variance in AIGC adoption. Furthermore, gender differences emerged as a significant moderating factor, where female faculty members were more strongly influenced by PEOU, whereas male faculty members with PU. These findings highlight the importance of strengthening faculty confidence and digital competence through differentiated training and institutional support mechanisms. The study extends TAM in an AIGC context and offers practical guidance for inclusive AIGC adoption strategies in higher education.