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Social network group decision-making (SNGDM) has rapidly developed because of the impact of social relationships on decision-making behavior. However, not only do social relationships affect decision-making behavior, but decision-making behavior also affects social relationships. Such complicated interactions are rarely considered in current research. To bridge this gap, this study proposes an SNGDM model that considers the interaction between social trust relationships and opinion evolution.

First, the trust propagation and aggregation operators are improved to obtain a complete social trust relationship among decision-makers (DMs). Second, the evolution of preference information under the influence of trust relationships is measured, and the development of trust relationships during consensus interactions is predicted. Finally, the iteration of consensus interactions is simulated using an opinion dynamics model. A case study is used to verify the feasibility of the proposed model.

The proposed model can predict consensus achievement based on a group’s initial trust relationship and preference information and effectively captures the dynamic characteristics of opinion evolution in social networks.

This study proposes an SNGDM model that considers the interaction of trust and opinion. The proposed model improves trust propagation and aggregation operators, determines improved preference information based on the existing trust relationships and predicts the evolution of trust relationships in the consensus process. The dynamic interaction between the two accelerates DMs to reach a consensus.

This study aims to undertake a comprehensive analysis of innovation models, tracing their evolution from Innovation 1.0 to Innovation 4.0 and introducing the concept of Innovation 5.0. It explores the intersection between innovation models and the principles of sustainability, resilience and human-centeredness, providing insights into their implications for Industry 5.0, and their potential to foster a resilient ecosystem amidst challenges and multiple crisis.

To achieve this objective, the authors used a systematic literature review approach, considering academic articles on Innovation 4.0, Industry 5.0 (specifically in the context of innovation) and helix models of innovation. The authors conducted thematic analysis and content analysis, followed by keyword co-occurrence analysis, enabling us to systematically synthesize and interpret the relevant literature.

The results conclude that Innovation 5.0 is a new paradigm for innovation that fosters broader societal engagement, and emphasizes sustainability, resilience and human-centeredness. Innovation 5.0 is evolving, but it has the potential to transform the way we produce, consume and live. Using insights from the sextuple helix model, this research leverages media and ICT as sixth helix vital role of knowledge sharing, digital transformation, innovation ecosystem and next industrial revolution in this process.

This study contributes to the ongoing discourse on exploring Innovation 5.0 through the sextuple helix model, offering a fresh perspective on innovation models and their collaborative potential. Its contribution lies in providing practical insights into the transition to Innovation 5.0, emphasizing the need for sustainability, regulatory support and awareness while also offering clear recommendations for future research.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.

This article summarizes the international scientific research output of global forest product models, infers future research trends and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

In 1999, Joseph Buongiorno, a scholar at the University of Wisconsin in the United States of America, proposed the global forest products model (GFPM), which was first applied to research in the global forestry sector. GFPM is a recursive dynamic model based on five assumptions: macroeconomics, local equilibrium, dynamic equilibrium, forest product conversion flow and trade inertia. Using a certain year from 1992 to present as the base period, it simulates and predicts changes in prices, production and import and export trade indicators of 14 forest products in 180 countries (regions) through computer programs. Its advantages lie in covering a wide range of countries and a wide variety of forest products. The data mainly include forest resource data, forest product trade data, and other economic data required by the model, sourced from the Food and Agriculture Organization (FAO) of the United Nations and the World Bank, respectively.

Compared to international quantitative and modeling research in the field of forest product production and trade, China's related research is not comprehensive and in-depth, and there is not much quantitative and mathematical modeling research, resulting in a significant gap. This article summarizes the international scientific research output of global forest product models, infers future research trends, and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

On the basis of summarizing and analyzing the international scientific research output of GFPM, sorting out the current research status and progress at home and abroad, this article discusses potential research expansion directions in 10 aspects, including the types, yield and quality of domestic forest product production, international trade of forest products, and external impacts on the forestry system, in order to provide new ideas for global forest product model research in China.

This study aims to provide a comprehensive analysis of various approaches to the residential property market evolution modelling and to examine the macroeconomic fundamentals that have shaped this market development in Ukraine in recent years.

The study uses a comprehensive data set encompassing relevant macroeconomic indicators and historical apartment prices. Multifactor linear regression (MLR) and ridge regression (RR) models are constructed to identify the impact of multiple predictors on apartment prices. Additionally, the ARIMAX model integrates time series analysis and external factors to enhance modelling and forecasting accuracy.

The investigation reveals that MLR and RR yield accurate predictions by considering a range of influential variables. The hybrid ARIMAX model further enhances predictive performance by fusing external indicators with time series analysis. These findings underscore the effectiveness of a multidimensional approach in capturing the complexity of housing price dynamics.

This research contributes to the real estate modelling and forecasting literature by providing an analysis of multiple linear regression, RR and ARIMAX models within the specific context of property price prediction in the turbulent Ukrainian real estate market. This comprehensive analysis not only offers insights into the performance of these methodologies but also explores their adaptability and robustness in a market characterized by evolving dynamics, including the significant influence of external geopolitical factors.

In the extant research on online knowledge communities (OKCs), little attention has been paid to the influence of membership fluidity on the coevolution of the social and knowledge systems. This article aims to fill this gap.

Based on the attraction-selection-attrition (ASA) framework, this paper constructs a simulation model to study the coevolution of these two systems under different levels of membership fluidity.

By analyzing the evolution of these systems with the vector autoregression (VAR) method, we find that social and knowledge systems become more orderly as the coevolution progresses. Furthermore, in communities with low membership fluidity, the microlevel of the social system (i.e. users) drives the coevolution, whereas in communities with high membership fluidity, the microlevel of the knowledge system (i.e. users' views) drives the coevolution.

This paper extends the application of the ASA framework and enriches the literature on membership fluidity of online communities and the literature on driving factors for coevolution of the social and knowledge systems in OKCs. On a practical level, our work suggests that community administrators should adopt different strategies for different membership fluidity to efficiently promote the coevolution of the social and knowledge systems in OKCs.

The purpose of this paper is to analyze the symbiotic evolution decisions of digital innovation enterprises, research institutes and the government in the digital innovation ecosystem.

Based on innovation ecosystem theory and an evolutionary game model, this study constructs a tripartite symbiotic evolution game model of digital innovation ecosystems with digital innovation enterprises, research institutes and the government as the main bodies and analyzes the influencing factors as well as the evolution paths of the different behavioral strategies of each subject through numerical simulation.

The research shows that the digital innovation ecosystem has the characteristic of self-organization, which requires the symbiotic cooperation of each subject. The government plays an active role in any stage of symbiotic evolution, and the system cannot enter symbiosis under a low level of subsidies and penalties. Only when the initial willingness to cooperate of digital innovation enterprises and scientific research institutes is at a medium or high level is the system likely to become symbiotic. While digital innovation enterprises are more sensitive to government subsidies and punishments, scientific research institutes are more sensitive to the distribution proportion of cooperation income.

This study includes government regulation into the research scope, expands the research mode of the digital innovation ecosystem and overcomes the difficulties of empirical research in collecting dynamic large sample data. It vividly and systematically simulates the symbiotic evolution process of the digital innovation ecosystem, which provides a theoretical and practical reference for digital innovation ecosystem governance.

This study aims to explore the dissemination and evolutionary path of online public opinion from a crisis management perspective. By clarifying the influencing factors and dynamic mechanisms of online public opinion dissemination, this study provides insights into attenuating the negative impact of online public opinion and creating a favorable ecological space for online public opinion.

This research employs bibliometric analysis and CiteSpace software to analyze 302 Chinese articles published from 2006 to 2023 in the China National Knowledge Infrastructure (CNKI) database and 276 English articles published from 1994 to 2023 in the Web of Science core set database. Through literature keyword clustering, co-citation analysis and burst terms analysis, this paper summarizes the core scientific research institutions, scholars, hot topics and evolutionary paths of online public opinion crisis management research from both Chinese and international academic communities.

The results show that the study of online public opinion crisis management in China and internationally is centered on the life cycle theory, which integrates knowledge from information, computer and system sciences. Although there are differences in political interaction and stage evolution, the overall evolutionary path is similar, and it develops dynamically in the “benign conflict” between the expansion of the research perspective and the gradual refinement of research granularity.

This study summarizes the research results of online public opinion crisis management from China and the international academic community and identifies current research hotspots and theoretical evolution paths. Future research can focus on deepening the basic theories of public opinion crisis management under the influence of frontier technologies, exploring the subjectivity and emotionality of web users using fine algorithms and promoting the international development of network public opinion crisis management theory through transnational comparison and international cooperation.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

This paper reviews the literature on the business models of small and medium-sized enterprises (SMEs). It seeks to examine the profile, conceptual and intellectual structure of the literature whilst leveraging the findings to suggest promising future paths to advance our knowledge on business models of SMEs.

The study resorts to a systematic literature review that conducts descriptive, bibliometric (i.e. co-word occurrence analysis and bibliographic coupling of documents analysis) and content analyses to review the literature on business models of SMEs. The research protocol included 301 articles collected in the Web of Science (WoS) database in the descriptive and bibliometric analyses. The bibliometric analysis was performed using the VOSviewer software.

The descriptive analysis portrayed the profile of this research stream. The systematisation of the co-word occurrence analysis describes the four clusters that comprise the conceptual structure of this research field. The content analysis of the bibliographic coupling of documents’ clusters portrays the seven clusters that involve the intellectual structure of this research area.

The integrated and holistic approach adopted in this study provides a detailed overview of the literature on business models of SMEs. We propose an integrative framework for the literature that bridges the main themes that form the conceptual and intellectual structure of this field of research. A comprehensive agenda for future research is suggested and implications for theory, policy and practice are stated.