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The popularisation of user-generated content has boosted the integration of social media with online retail, especially in the emerging context of interest-based e-commerce (IBEC). As the content brings new incentives for consumers’ impulsivity in consumption, it remains unclear understanding of the mechanism of impulse buying in IBEC from the current literature. This study aims to examine how content creativity encourages impulse buying intention though attitude, and whether the effect is moderated by consumers’ online shopping experience.

This study administered a two-wave online survey to a purposive sample of 286 consumers with shopping experience in Douyin. The hypotheses and a moderated-mediation effect were tested using structural equation modelling in Mplus8.3.

The empirical results revealed that content creativity, including dual dimensions of relevance and divergence, can drive positive attitude towards platforms through the direct effect of subjective norm and mediation effect through perceived usefulness, which induces an urge to buy impulsively. The mediation effect is further moderated by consumers’ online shopping experience in IBEC.

This study expands the stream of impulse buying research in retailing by proposing a context of IBEC and bringing empirical evidence of the relationship between content and consumers’ urge to buy. The study provides strategic insights for retailers to achieve marketing value by managing consumers’ impulse purchases in IBEC.

This study aims to establish an evaluation method for cross-regional major infrastructure project (CRMIP) supportability. The focus is to identify evaluation indicators from a complexity perspective and develop an evaluation model using qualitative and quantitative methods. Case studies are carried out to verify the reliability of the evaluation model, thereby providing theoretical and practical guidance for CRMIP operations and maintenance (O&M).

Guided by the idea of complexity management, the evaluation indicators of CRMIP supportability are determined through literature analysis, actual O&M experience and expert interviews. A combination of qualitative and quantitative methods, consisting of sequential relationship analysis, entropy weighting, game theory and cloud model, is developed to determine the indicator weights. Finally, the evaluation model is used to evaluate the supportability of the Hong Kong–Zhuhai–Macao Bridge (HZMB), which tests the rationality of the model and reveals its supportability level.

The results demonstrate that CRMIPs' supportability is influenced by 6 guideline-level and 18 indicator-level indicators, and the priority of the influencing factors includes “organization,” “technology,” “system,” “human resources,” “material system,” and “funding.” As for specific indicators, “organizational objectives,” “organizational structure and synergy mechanism,” and “technical systems and procedures” are critical to CRMIPs' O&M supportability. The results also indicate that the supportability level of the HZMB falls between good and excellent.

Under the guidance of complexity management thinking, this study proposes a supportability evaluation framework based on the combined weights of game theory and the cloud model. This study provides a valuable reference and scientific judgment for the health and safety of CRMIPs' O&M.

The primary objective of this research is to explore the impact of the repeated two-syllable communication strategy on the interaction effectiveness between AI and customers.

This study adopts an experimental research methodology to investigate the role of the repeated two-syllable communication strategy employed by AI customer service agents.

Study 1 shows that AI agents using the repeated two-syllable strategy enhance the interaction effectiveness between AI and customers. Study 2 identifies humanization perception as a key factor linking the strategy to better interaction effectiveness. Study 3 highlights how consumer materialism moderates this effect, while Study 4 examines how the type of agent (AI vs. human) influences the results.

This study extends the application of AI communication strategies in interactive marketing, specifically how AI agents enhance consumer interaction through repeated two-syllable communication. It pioneers the exploration of AI-human interaction, enriching the humanization theory by revealing how AI can evoke emotional responses. The study also integrates consumer materialism as a moderating factor, offering new theoretical and practical insights for brands to optimize AI-customer service interactions and improve engagement in real-world marketing contexts.