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This study aims to analyze the existing body of knowledge concentrating on institutional investors’ behavior. It seeks to track how this domain has evolved through collaborative networks, as well as significant contributors, themes and research opportunities for future work.

The present study applies bibliometric analysis to examine the trends in the selected research field, using 446 articles from highly recognized journals indexed in the Scopus database.

The authors discovered that research on institutional investors’ behavior has significantly increased over the past four decades due to academic interest in the topic. This study observed five themes that unite the research in this field: institutional investors and corporate behavior; determinants of institutional investors’ trading patterns and performance; trading activity and its outcomes; herding, causes and consequences; and institutional investment and corporate performance. Moreover, future directions are penned down, such as how institutional investors’ control influences governance disclosures.

This study serves as a guide by mapping and analyzing the intellectual development of the research literature on institutional investors’ behavior. The authors contribute to the knowledge base by providing a solid foundation for further studies.

This study delves into the nuanced relationship between financial constraints, ownership structures (state-owned and foreign) and innovation engagement within China’s A-share market, aiming to uncover how these dynamics vary across different industries and regional contexts.

By retrieving data from various datasets in China (2010–2022), this study analyzed the effectiveness of each variable, employing various dimensions to reflect innovation engagement among Chinese listed companies. Meanwhile, for the measurement of financial constraints, this study tested all four typical ones and opted for the KZ Index, as it is the most suitable for China’s A-share market. Then, by fixing the industry and year effects, the study examined the main and moderating effects. At last, in order to address endogeneity issues and capture the dynamic nature of innovation activities, this study follow the suggestion of Khatib (2024) and employed the two-step system Generalized Method of Moments (GMM) estimation.

The results demonstrate that while the government has introduced many policies to promote innovation, state-owned ownership does not consistently enhance innovation engagement as expected, especially when firms are in financial dilemma. Particularly, in Hi-tech industries, foreign ownership demonstrates greater interest and confidence in the innovation capabilities of China’s A-share market. Findings also reveal significant regional heterogeneity in the moderating role of ownership structures. While state-owned and foreign ownerships have a buffering effect against financial constraints in the eastern and western regions, but this effect is notably different in the middle part, even though it is China’s political heartland.

The findings offer a different insight for policymakers and corporate strategists, suggesting that targeted financial and regulatory policies that leverage specific ownership structures can foster innovation in different ways, particularly in financially constrained environments. However, how to stimulate innovation vitality in the middle part of China still requires further research.

This paper aims to propose a solution for dissolving the “privacy paradox” in social networks, and explore the feasibility of adopting a synergistic mechanism of “deep-learning algorithms” and “differential privacy algorithms” to dissolve this issue.

To validate our viewpoint, this study constructs a game model with two algorithms as the core strategies.

The “deep-learning algorithms” offer a “profit guarantee” to both network users and operators. On the other hand, the “differential privacy algorithms” provide a “security guarantee” to both network users and operators. By combining these two approaches, the synergistic mechanism achieves a balance between “privacy security” and “data value”.

The findings of this paper suggest that algorithm practitioners should accelerate the innovation of algorithmic mechanisms, network operators should take responsibility for users’ privacy protection, and users should develop a correct understanding of privacy. This will provide a feasible approach to achieve the balance between “privacy security” and “data value”.

These findings offer some insights into users’ privacy protection and personal data sharing.

Distributed photovoltaic (DPV) projects generally have output risks, and the production effort of the supplier is often private information, so the buyer needs to design the optimal procurement contract to maximise its procurement utility.

Based on the principal-agent theory, we design optimal procurement contracts for DPV projects with fixed payments and incentive factors under three situations, i.e. symmetry information, asymmetry information without monitoring and asymmetry information with monitoring. We obtain the optimal production effort and expected utility of the supplier, the expected output and expected utility of the buyer and analyse the value of the information and monitoring.

The results show that under asymmetric information without monitoring, risk-averse suppliers need to take some risk due to output risk, which reduces the optimal production effort of the supplier and the expected output and expected utility of the buyer. Therefore, when the monitoring cost is below a certain threshold value, the buyer can introduce a procurement contract with monitoring to address the asymmetry information. In addition, under asymmetric information without monitoring, the buyer should choose a supplier with a low-risk aversion.

Considering the output risk of DPV projects, we study the optimal procurement contract design for the buyer under asymmetric information. The results provide some theoretical basis and management insights for the buyer to design optimal procurement contracts in different situations.

This paper aims to examine the blockchain introduction and altruistic preference decisions of the supplier in agricultural food supply chains and discuss how the supplier decisions are influenced by blockchain technology and altruistic preference levels.

The author considers a single period two-level supply chain model to describe the supplier’s decisions. The supplier, as the leader of the game, decides whether to introduce blockchain technology and his own level of altruistic preferences. Consumers have environmental awareness and heterogeneity in green trust. Supply chain members determine their own product pricing and green effort level under Stackelberg game.

The results reveal the negative impact of unit verification cost in the technology introduction process on the supply chain. In addition, the supplier can adjust their profits by adjusting their altruistic preferences after introducing blockchain to offset the impact of blockchain through the influence of altruistic preferences as discussed by the author.

This paper investigates how the profits and green efforts of supply chain members are influenced by blockchain technology and altruistic preferences.

This study explores how the high-end equipment manufacturing industry (HEMI) achieves intelligent development through the digital innovation ecosystem. While this industry urgently needs to achieve intelligent development through innovation breakthroughs, existing research lacks a deep analysis in conjunction with the digital innovation ecosystem. Considering the sophisticated nature of HEMI and the unique characteristics of the digital innovation ecosystem, this paper aims to uncover the innovation potential and synergetic development opportunities that arise from their integration.

This study uses Dynamic Qualitative Comparative Analysis (QCA) to explore the evolving relationship between the digital innovation ecosystem and intelligent development in HEMI enterprises. Data from 60 HEMI enterprises were collected from 2015 to 2022, and the study window was divided into two-year intervals for analysis. Compared to traditional QCA methods, this approach overcomes the limitations of cross-sectional analysis, fully accounting for time’s influence on causal relationships for more accurate results.

The study reveals that the digital innovation ecosystem of HEMI drives intelligent development through the coordinated interactions of its elements within each time window. Configuration paths and key driving factors evolve dynamically, reflecting the complexity of the ecosystem’s role in driving intelligent development. The study suggests that enterprises dynamically adjust their strategies to different stages, enhancing the effectiveness of intelligent transformation.

The paper proposes and validates a digital innovation ecosystem framework for HEMI, systematically exploring its role in driving intelligent development. The study fills a research gap and extends innovation ecosystem theory by identifying core driving factors and their evolutionary trends through Dynamic QCA. It offers a new perspective on the dynamic role of digital innovation ecosystems in intelligent transformation.

Advances in information technology and the increasing digitalization of the general public have favored the growth of the sharing economy. The sharing economy is based on transactions of idle resources between individuals to satisfy cogent needs. Notwithstanding the great interest in this emerging phenomenon, it is still not clear which factors are driving the shift in consumer consumption behavior from the traditional economy toward this new economic model. Grounded in self-determination theory, we contend that what is needed is a holistic approach that considers the three elements involved in sharing economy transactions, namely (1) consumer motivations, (2) web-based platforms and (3) types of assets exchanged.

To conduct our study, we used the Flash Eurobarometer 467 database titled “The Use of the Collaborative Economy,” collected by the European Union with Flash Eurobarometer datasets and openly available to the public. Consequently, our study aims to provide results based on a large-scale quantitative analysis involving a large number of individuals and multiple sectors.

Our findings provide empirical evidence of the positive effects of the shift in consumption behavior toward the sharing economy brought about by (1) consumers’ intrinsic motivations, (2) the quality of the platform and (3) the human asset-based categories of products offered.

This research seeks to advance understanding of the factors that facilitate the adoption of the sharing economy, and we provide managers and policymakers with suggestions regarding the factors they may leverage to further favor the spread of this economic model.

The development of financial technology (fintech), especially digital payments (e-payments), aims to increase the efficiency and effectiveness of economic transactions. This study aims to see the extent to which microentrepreneurs in Indonesia and Malaysia take advantage of the existence of e-payments in developing their business and the factors that influence the adoption of e-payments.

This study uses qualitative and quantitative approach. For quantitative approach, partial least squares structural equation modeling (PLS-SEM 4.0) was used to analyze the data. Using the nonprobability convenient sampling technique, this study collected 400 respondents from microenterprises in Indonesia and Malaysia in various regions.

Most of the microentrepreneurs in Indonesia and Malaysia have used fintech platforms, especially e-wallet and ATM debit. However, for quick response code-based fintech for business transactions, most microentrepreneurs have not taken advantage of the platform. Then the results of the digital payment adoption factor also differ for each country.

This study is valuable for decision-makers and regulators. These results can be used to find a roadmap for regulators to build a digital economy, especially digital payments for microenterprises in both countries. In addition, these results can be used as a basis for making policies regarding digital payments.

To the best of the authors’ knowledge, this is the first study to compare e-payment adoption by microentrepreneurs in Indonesia and Malaysia. Indonesia and Malaysia are two countries in the Southeast Asia region that have great attention in fintech development. This study provides new insights about fintech, especially digital payments as a strategic approach in the digitalization era.

This study aimed to utilize Epistemic Network Analysis (ENA) for a thorough evaluation of policy documents concerning the digital transformation in Vietnam's higher education sector.

Adopting a quantitative ethnography approach, this research employed ENA to analyse a curated collection of 21 documents that specifically addressed higher education (HE) and digital transformation within Vietnam. The study also incorporated qualitative content analysis, utilizing the constant comparison method as outlined by Onwuegbuzie et al. (2009), for data coding. ENA facilitated the examination of connections among various policy aspects.

The study revealed a consistent overarching theme in Vietnam's digital transformation policies during and post-pandemic, focusing on key areas such as ADMINISTRATION, VISION, QUALITY, and INFRASTRUCTURE. However, a temporal shift in emphasis was observed: during the pandemic, policies were more focused on ADMINISTRATION and INFRASTRUCTURE, while post-pandemic, there was an increased emphasis on COLLAB, VISION, and TEACH_LEARN.

This research represents one of the initial efforts to showcase the utility and significance of ENA in analysing policy documents. It underscores ENA's potential in elucidating the complex interplay of policy elements in the context of digital transformation in higher education, particularly within a developing country setting.

Of critical concern to the world is the need to reduce consumption and waste of natural resources. This study provides a multi-level exploration of the ways situational and transformational links between levels and challenges are related to the adoption and utilization of material flow cost accounting in Vietnam, to encourage green productivity.

Based on triangulation of public documents at different institutional levels and a set of semi-structured interviews, situational and transformational links and challenges for material flow cost accounting in Vietnam are examined using purposive and snowball sampling of key actors.

Using a multi-level framework the research identifies six situational and transformational barriers to implementation of material flow cost accounting and suggests opportunities to overcome these. The weakest links identified involve macro-to meso-situational and micro-to macro-transformational links. The paper highlights the dominance of meso-level institutions and lack of focus on micro transformation to cut waste and enable improvements in green productivity.

The paper identifies ways for companies in Vietnam to reduce unsustainability and enable transformation towards sustainable management and waste reduction.

The paper is the first to develop and use a multi-level/multi-time period framework to examine the take-up of material flow cost accounting to encourage transformation towards green productivity. Consideration of the Vietnamese case builds understanding of the challenges for achieving United Nations Sustainable Development Goal number 12, to help enable sustainable production and consumption patterns.