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The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

This study aims to theorize and empirically examine how guanxi in Chinese collectivistic culture affects entrepreneurs to leverage the structural holes they occupy when it comes to promoting knowledge transfer.

To examine the hypotheses, this study used a mixed-methods research approach where quantitative questionnaires and social network analyses were used through 365 Chinese entrepreneurs, and qualitative semistructured interviews were conducted through 50 Chinese entrepreneurs.

In a Chinese entrepreneur’s guanxi network, structural holes will impede knowledge transfer among network members, but guanxi will moderate this impeding effect.

By revealing how “structural hole controllers” become “structural hole fillers” under the moderating influence of guanxi in Chinese collectivistic culture, this study recognizes the different roles that persons who occupy a structural hole play in different situations, which advances structural hole theory. In addition, by exploring how entrepreneurs orchestrate these structural holes to create a strong guanxi network that can be infinitely extended, this study reveals a means to achieve both advantages of bonding and bridging social capital simultaneously, which generates a theoretical contribution to social capital integration.

This study suggests Chinese entrepreneurs to cultivate guanxi to improve their needs in decision-making by giving renqing, returning renqing, earning mianzi and giving mianzi.

By showing how Chinese entrepreneurs leverage their guanxi and structural holes to facilitate knowledge transfer, this study identifies the critical entrepreneurial behavior that promotes business development, thereby contributing to the literature of knowledge management, entrepreneurship and social network.

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.

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.

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.

This study contributes to the understanding of user-generated content motivation and provides managerial implications for reward programs.

Consumers worldwide are increasingly ordering groceries from grocery delivery platforms (GDPs). This study aimed to explore the role of brick-and-mortar (B&M) retailers and GDPs in online grocery shopping (OGS) experience, attitude and continuous purchase intention under the platform model of online grocery retailing.

This study used a mixed method approach. A qualitative analysis was conducted based on 30 in-depth interviews and relevant literature to identify key attributes of the OGS experience. Then, data from 352 online grocery shoppers was used to examine the associations between service attributes, attitude and continuous purchase intention using a structural equation model.

The authors identified six key attributes of the OGS experience related to B&M retailers and GDPs. The quantitative study results showed that customer service, price value and instant delivery significantly impact attitude towards GDPs, while product quality, product assortment, customer service, price value and attitude toward GDPs positively impact online attitude toward B&M retailers. Online attitude toward B&M retailers significantly influences continuous purchase intention.

B&M retailers and GDPs should strengthen cooperation and joint oversight.

This study identified key attributes of the OGS experience associated with B&M retailers and GDPs under the platform model, giving a comprehensive understanding of the relationship between the OGS experience and behavioural intention when B&M retailers collaborate with GDPs.