As increasing numbers of customers pay attention to product and service sustainability when shopping online, more and more firms in the online market engage in promoting perceived sustainability to establish close customer relationships. Prior studies implied the effects of perceived sustainability on transactional customer relationships, however, the role of perceived sustainability in influencing nontransactional customer relationships has received little attention. Drawing on existing conceptual models, this study aimed at exploring the effects of perceived sustainability on rational and emotional customer engagement (CE) in the online shopping environment. The data were collected through a questionnaire survey in China. Using the partial least squares (PLS) approach-based structural equation modeling (SEM) method, the authors found that perceived sustainability positively affects the two CE orientations through influencing short- and long-term transactional attitudes (satisfaction and commitment). A strong interrelationship between rational and emotional CE was also found. This is the first study presenting empirical evidence of the effects of perceived sustainability on nontransactional customer relationships from the rational and emotional perspectives. It also provides critical implications for online sellers in designing engagement programs.

Enterprises often post branded content on social media and adopt a proactive response approach to improve digital customer engagement to gain a competitive advantage. However, there are many brands which fail to operate social media as effectively as expected. The effective use of brand social media strategies to improve digital customer engagement remains an ongoing challenge for the enterprises. Based on firm-generated content theory and social presence theory, this study aims to identify the impact of brand social media strategies on different levels of digital customer engagement, including positive filtering, cognitive and affective processing as well as advocacy from content strategy and response strategy. Based on 1,519 brand posts on the official Weibo pages of eight of the top 500 Chinese brands in 2021, this study uses a multiple linear regression model to examine the impact of brand social media strategies on digital customer engagement and the moderating effects of brand image and discretionary purchases. The findings show that, on the one hand, among the brand social media content strategies, action content strategy is associated with higher levels of digital customer engagement. On the other hand, different brand social media response strategies have a differential impact on digital customer engagement levels, with cohesive response being the best strategy for increasing digital customer engagement level. In addition, the effectiveness of brand social media response strategy in digital customer engagement is further moderated by the brand image and discretionary purchases. In contrast, the effectiveness of brand social media response strategy in digital customer engagement is stronger when the brand image emphasizes its “competence” or the discretionary purchases focus on “material purchases.” This study not only enriches the research on digital customer engagement but also provides a reference for the brand strategy selection, design and management based on social media.

This paper conducted a bibliometric analysis based on 4687 papers on supplier management from 1997 to 2017. Through a comparative analysis of the four stages using Bibexcel and Ucinet6 software, this paper explores the evolution of supplier management from the theme and cluster perspectives. The results show that supplier management research has made breakthroughs in both breadth and depth. Representative research themes, such as “sustainable supply chain”, “corporate social responsibility”, “knowledge management”, etc., have gradually penetrated into the field of supplier management. Research related to “supplier selection” and “supplier relations” have always been of the highest strategic importance, and themes in “supplier relations” cluster such as “trust” and “commitment” have gradually attracted more and more researchers’ attention. The “inventory” cluster has also been a research focus, and the structural stability and maturity of the cluster have gradually improved. The “innovation” cluster is a relatively “open” cluster, and its impact on the entire research filed of supplier management has been gradually increasing. More importantly, the “sustainability” cluster is an evolving cluster, research themes related to “sustainability”, such as “green supply chain”, “sustainable supply chain” and “green supplier selection”, will play an increasingly important role in the field of supplier management.

Industrialized processing has increased the complexity of the food supply chain. Concerns about food-related risks have increased consumer interest in food traceability. Traceability systems are regarded as effective tools for mitigating information asymmetry and enhancing food quality and safety. However, the design of traditional food traceability systems overlooks the risk of information overload. Based on information overload theory, this study designs an artificial intelligence (AI) traceability assistant as an innovative tool to optimize traditional food traceability systems and examines its positive effects. This study focuses on prepared foods as the research objects, selecting three types of prepared foods (Kung Pao chicken, fish-flavored shredded pork, and pickled fish) and three food traceability tasks (preservatives, sweeteners, and drug residues) as experimental stimuli. Through three online scenario experiments, 747 valid responses were collected. This study explores the impact of AI traceability assistant design on positive consumer engagement behaviors and its underlying mechanism. The results reveal that the AI traceability assistant significantly promotes positive consumer engagement behaviors. This positive effect is mediated by perceived system ease of use. Furthermore, perceived product risk positively moderates the impact of the AI traceability assistant on perceived system ease of use. Perceived product risk strengthens the mediating effect of perceived system ease of use. This study contributes a novel theoretical perspective for research on food traceability systems and reveals the underlying mechanism through which the AI traceability assistant exerts its positive effect. In practice, it provides actionable guidance for food producers implementing digital traceability solutions.