Mingjie Fang

Background/Objectives: This study investigates the interaction and coordinated development of the digital economy and the tourism economy in China’s Yangtze River Delta urban agglomeration, using panel data from 27 cities covering the period from 2013 to 2022. Methods: Composite indices are constructed for the two subsystems, with indicator weights determined using the entropy method. A coupling coordination model is then applied to assess the extent and quality of their joint development. Exploratory spatial data analysis is further employed to examine spatial dependence and clustering patterns, with Moran’s I serving as a key analytical measure. Results: The findings indicate that both subsystems improved over the study period, although the digital economy advanced more quickly and showed greater regional disparity. The overall coordination level rose from a medium stage to a relatively high stage, yet uneven development persisted, particularly in Anhui. Spatially, coordination followed an east-high, west-low pattern, and high-level areas gradually spread outward from leading cities to form a core–periphery structure. Positive spatial clustering was evident in most years, pointing to clear regional agglomeration in digital–tourism coordination. Conclusions: These results underscore the importance of differentiated regional policies, stronger inter-city collaboration, and deeper integration between digital development and tourism transformation.

In highly dynamic and information-intensive logistics environments, understanding how firms achieve modeling and simulation ambidextrous innovation (MSAI) through strategic alignment is crucial. Drawing on organizational information processing theory (OIPT), we develop an integrative framework that links strategic congruence with capability development and innovation outcomes. The study examines (1) whether buffering–bridging congruence (B–B congruence) exists and how it enhances MSAI through operational stability, financial flexibility, and knowledge management capability; (2) how these three capabilities shape the differentiated pathways toward exploitative and explorative simulation innovation; and (3) how firms may leverage a simulation-driven decision framework to achieve strategic–capability alignment in the highly dynamic maritime logistics environment. The framework is empirically tested using polynomial regression models based on survey data from Chinese maritime logistics firms, analyzed with SPSS 27.0 and STATA 15. Our empirical results indicate that, regardless of the level of buffering strategy or bridging strategy, the firm’s operational stability, financial flexibility, and knowledge management capabilities are always higher when buffering and bridging strategy are congruent. The results also show that the three capabilities influence MSAI differently. Specifically, knowledge management capability exerts positive effects on both exploitative and exploratory modeling innovation. Financial flexibility mainly promotes exploitative innovation, while its influence on exploratory innovation is not significant. In contrast, operational stability does not enhance exploitative innovation but unexpectedly shows a positive effect on exploratory innovation. The findings advance OIPT’s theoretical application in simulation-intensive settings and offer guidance for firms seeking to align capabilities and strategy in complex systems, providing both theoretical and practical insights.

Purpose: Omnichannel retailing offers consumers more channels and opportunities to engage in logistics. This study revisits the concept of consumer logistics with two objectives: establishing a comprehensive framework of consumer logistics in the context of omnichannel retailing and exploring potential consumer clusters by focusing on their involvement patterns in logistics activities. Design/methodology/approach: Two exploratory studies were conducted. Study 1 involved exploratory factor analysis to identify the dimensions of consumer logistics activities. Subsequently, K-means clustering analysis was conducted to categorise “logsumers” based on their current preferences for logistics activities. Findings: The findings reveal five dimensions within consumer logistics activities: pre-shopping strategic planning, pre-shopping information exploration, physical involvement in delivery, intellectual engagement in delivery and post-delivery return activities. Further, this study identifies four types of logistics activity participants: enthusiastic logistics participants, apathetic logistics participants, intellectual activity engagers and physical activity activators. Research limitations/implications: This study expands the understanding of consumer logistics by offering a comprehensive segmentation framework across all logistics stages, including post-delivery returns. By integrating clustering analysis with logistics management, it reveals consumer logistics behavioural patterns. However, its findings are limited by regional and temporal contexts, suggesting that generalisations should be cautious. Originality/value: This study provides a comprehensive framework for understanding consumer logistics and lays the groundwork for market segmentation research in this domain. Furthermore, our findings contribute to a deeper understanding of consumer engagement by examining logistics activity attributes and “logsumer” types, enabling retailers and logistics service providers to formulate differentiated strategies for diverse consumer groups.

Purpose: Effective inventory management matters for a firm’s circular economy (CE) performance due to its relevance to waste reduction and slack resource creation. Thus, drawing on the resource orchestration theory, we investigate the influence of inventory leanness on a firm’s CE performance and the boundary conditions of this link. Design/methodology/approach: The hypotheses are tested using fixed-effects models applied to a large-scale panel dataset of Chinese manufacturing firms spanning the period from 2012 to 2022. Various additional analyses are conducted to verify the robustness of the results. Findings: The results reveal an inverse U-shaped relationship between inventory leanness and CE performance, where both low and high levels of inventory leanness are associated with poorer CE performance than a moderate level of leanness. We further demonstrate that the turning point of the inverse U-shape, where CE performance is maximized, occurs at a lower level of inventory leanness when the firm exhibits higher labor productivity. Finally, our empirical results suggest that the firm’s market power moderates the relationship by flattening the curve, causing the marginal effect of inventory leanness on CE performance to decrease at a decreasing rate. Originality/value: The findings of the present research provide nuanced theoretical insights into inventory management and CE literature. Moreover, our identification of the optimal level of inventory leanness offers valuable practical implications for firms seeking to “do more with less.”

In an era where financial resilience and ethical integrity are pivotal to supply chain success, this study explores how firms can harness digitalization capability to enhance supply chain finance (SCF) performance, with a particular emphasis on its role in promoting supply chain transparency (SCT) and mitigating partner firms' unethical behavior. Specifically, we develop a theoretical model based on the organizational information processing theory and social exchange theory and test it by employing partial least squares structural equation modeling analysis on data from 172 Chinese manufacturing firms. The results reveal that firms' digitalization capability advantage (DCA) is an effective means to achieve the fit between information processing needs and capabilities in improving SCT and reducing the unethical behavior of partner firms. This fit is further strengthened when firms and their partners exhibit a higher level of cultural congruence. Additionally, the study demonstrates that improving SCT and mitigating unethical behavior are crucial mechanisms that facilitate reciprocal resource interactions, fostering high‐quality social relationships between focal firms and their partners, and ultimately contributing to enhanced SCF performance. Overall, this study provides a clear and theoretically grounded explanation of how DCA can be utilized to enhance supply chain operations and SCF performance.

Purpose: This study aims to analyze the impact of big data analytics powered by artificial intelligence (AI–BDA) on the sustainable practice performance in shipping organizations and to establish a strategic mechanism to achieve sustainable management of the shipping industry. Design/methodology/approach: We employed the organizational information processing theory (OIPT) and the knowledge-based view (KBV) as theoretical lenses to develop our research model. To empirically validate the hypotheses, we collected data from 182 shipping organizations and utilized a nine-tier hierarchical moderating regression model, complemented by a three-way interaction analysis. Findings: AI-powered big data analytics can positively affect the sustainable practice performance of shipping organizations. Organizational flexibility can help achieve this effect, and interpartner resource sharing increases the impact intensity. Simultaneously, intellectual capital as a boundary condition can promote the moderating effects of organizational flexibility and interpartner resource sharing on the relationship between AI-powered big data analytics and the sustainable practice performance of shipping organizations. The results of qualitative triangulation largely support the quantitative analysis findings, while also highlighting potential issues related to data security and third-party service platforms. Originality/value: The results provide theoretical and practical contributions to the research on the sustainable development of shipping and the application of AI-BDA and provide a new research direction by combining OIPT and KBV.