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This paper aims to explore how enterprise microblogging can influence consumer loyalty and thus generate business value for firms. The study aims to expand traditional brand community theory.

The paper is based on brand community theory, social identity theory and usage and gratifications theory. Using a pre-survey of the fans of an enterprise microblog and a random sample survey of such fans on Sina Weibo, the authors tested the structural equation model with LISREL, which includes multiple fit indices.

The paper provides empirical insights about how enterprise microblogging can influence consumer loyalty and thus generate business value for firms. It suggests that consumers’ perceived value could strengthen their microblog identification, which will influence their perceived relationship with the enterprise and its products directly and indirectly through the mediation of enterprise identification. Perceived relationship can further influence purchase and recommendation intentions.

Because of the chosen data collecting approach, the research results may be still subjective. Moreover, the study overlooks the effects of the different types of enterprise microblogging and consumers.

Enterprises should operate their official microblogging from the perspective of maintaining brand community to improve consumer loyalty. They can generate more value for consumers through their microblogging and predict the operating performance by evaluating the degree of consumers’ relationship perception.

This paper considers enterprise microblogging as a new form of virtual brand community and identifies its features, and expands theories of brand community, and social media/IT business value, social identity theory and gratifications theory.

Tacit knowledge in frontline operations is primarily reflected in the holders’ intuition about dynamic systems. Despite the implicit nature of tacit knowledge, the understanding of complex systems it encapsulates can be displayed through formalization methods. This study seeks to develop a methodology for formalizing tacit knowledge in a dynamic delivery system.

This study employs a structured survey to gather experiential knowledge from dispatchers engaged in last-mile delivery operations. This knowledge is then formalized using a value function approximation approach, which transforms tacit insights into structured inputs for dynamic decision-making. We apply this methodology to optimize delivery operations in an online-to-offline pharmacy context.

The raw system feature data are not strongly correlated with the system’s development trends, making them ineffective for guiding dynamic decision-making. However, the system features obtained through preprocessing the raw data increase the predictiveness of dynamic decisions and improve the overall effectiveness of decision-making in delivery operations.

This research provides a foundational framework for studying sequential dynamic decision problems, highlighting the potential for improved decision quality and system optimization through the formalization and integration of tacit knowledge.

This approach proposed in this study offers a method to preserve and formalize critical operational expertise. By embedding tacit knowledge into decision-making systems, organizations can enhance real-time responsiveness and reduce operational costs.

This study presents a novel approach to integrating tacit knowledge into dynamic decision-making frameworks, demonstrated in a real-world last-mile delivery context. Unlike previous research that focuses primarily on explicit data-driven methods, our approach leverages the implicit, experience-based insights of operational staff, leading to more informed and effective decision-making strategies.

With the development of social media and Internet technology, many firms have started to use various crowdsourcing innovation platforms to operate their open innovation business modes. The purpose of this study is to explore how such platforms' assurance mechanisms enhance the effectiveness of crowdsourcing innovations and how to apply assurance mechanisms to handle different innovation tasks, thereby motivating more seekers to use crowdsourcing innovations.

The authors use a Python-based technology to collect the research data comprising 2,302 solvers and 8,390 trade records from zbj.com and apply statistical methods to test the postulated hypotheses.

The effectiveness of assurance mechanism is confirmed by its positive relationship with solver's behaviour, thereby improving seeker's retention behaviour. However, task complexity, task novelty and task professionalization have different moderating effects on the relationships among assurance mechanism, solver's (innovator's) behaviour and seeker's behaviour.

This study enriches the literature on crowdsourcing innovations and extends the application of uncertainty reduction theory to innovation research. It also makes the theoretical contribution that the assurance mechanism adopted by the platform has different impacts on user's behaviour depending on the task characteristics.

The findings provide guidance to the platform operator on how to design the assurance mechanism to match the innovation task and innovator's behaviour to reduce seeker's uncertainty, thereby facilitating the seeker's decision-making.

A particular value of this study lies in exploring the impact of the platform assurance mechanism of social media-based crowdsourcing innovations on innovator's behaviour, which may further improve seeker's behaviour, based on uncertainty reduction theory.

The purpose of this study is to map the intellectual structure of sustainable finance and accounting (SFA) literature by identifying the influential aspects, main research streams and future research directions in SFA.

The results are obtained using bibliometric citation analysis and content analysis to conduct a bibliometric review of the intersection of sustainable finance and sustainable accounting using a sample of 795 articles published between 1991 and November 2023.

The most influential factors in the SFA literature are identified, highlighting three primary areas of research: corporate social responsibility and environmental disclosure; financial and economic performance; and regulations and standards.

SFA has experienced rapid development in recent years. The results identify the current research domain, guide potential future research directions, serve as a reference for SFA and provide inspiration to policymakers.

SFA typically encompasses sustainable corporate business practices and investments. This study contributes to broader social impacts by promoting improved corporate practices and sustainability.

This study expands on previous research on SFA. The authors identify significant aspects of the SFA literature, such as the most studied nations, leading journals, authors and trending publications. In addition, the authors provide an overview of the three major streams of the SFA literature and propose various potential future research directions, inspiring both academic research and policymaking.