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Building on the Lau and Murnighan’s theory of fault line strength, Flache and Mäs (2008b) proposed a computational opinion dynamics model to explore the effect of demographic fault line strength on team cohesion. This study aims to extend the Flache–Mäs (FM) model to incorporate geographical location and the dyadic communication regime in opinion formation process. More specifically, we make spatially proximate agents more likely to interact with each other in the dyadic communication regime. Our results show that when agents update their opinion after each pairwise encounter, opinion polarization is lower at steady state compared to when they update their opinion after interacting with all agents. In addition, if nearby agents are more likely to interact with each other, we see greater polarization compared to the FM model with the dyadic communication regime. An immediate policy implication of this result is that organizational managers should design work space in a way that encourage wider communications between members of a team and avoid geographically local communication.

We introduce our computational models to study the effect of location and the dyadic communication regime on team performance (as measured by agents’ opinions on various work-related issues) in the presence of a strong demographic fault line. Our models are extensions of the FM model. For clarification purposes, first we describe the FM model and then elaborate our extensions.

The most important finding of this paper is that the timing of interactions plays an important role in steady state of opinion space in a given population. The reason can be traced to the path-dependent nature of social systems, in which initial adopters of a certain opinion or an ideology can significantly change the final configuration of a population. For example, if an early adopter of a given work-related issue in an organization has an extremely positive view toward that issue, and s/he interacts with nearby employees who have similar demographic attributes, we would expect to find an extreme opinion cluster with respect to that issue after a while. However, depending on factors that affect the timing of interaction between individuals, we would expect different outcome in the same organization. If, for instance, more extreme people are more likely to interact, the results would be different compared to when moderate agents are more likely to interact.

One immediate policy implication of the results of this paper is that organizational managers should design work space in a way that encourage wider communications between members of a team and avoid geographically local communication, if they are to temper the negative effect of a strong demographic fault line. However, they should be cautious and take other related findings into account to avoid undesirable outcomes. For example, according to Flache and Mäss’s results, managers can also initially encourage discussion within demographically homogenous groups and avoid controversial work-related issues. In addition, previous studies showed that more contacts between agents may increase opinion polarization. Our results provide no evidence for more complex and modern organizational designs where individuals or teams do not have a fixed location or stable geographical pattern. For instance, in a modern car manufacturing shop floor, it is possible that workers have to move with cars, or operational engineers have to move between different sections and places. Furthermore, there may be a flexible and dynamic work schedule for workers such that they share a same work station but in different time, which requires a more complex model than what we presented in this paper. In this sense, the geographical setting analyzed in this paper should not be generalized to all organizations or companies. We also have no evidence about other critical factors that might affect the communication and activation regime of individuals. For example, one could imagine a case that workers with the same level of skill in a specific work-related issue are more likely to interact with each other. Moreover, some specific organizational structures could impose additional restrictions on who can/should interact with whom.

The purpose of this paper is to review the recent studies on opinion polarization and disagreement.

In this work, recent advances in opinion polarization and disagreement and pay attention to how they are evaluated and controlled are reviewed.

In literature, three metrics: polarization, disagreement and polarization-disagreement index are usually adopted and there is a tradeoff between polarization and disagreement. Different strategies have been proposed in literature which can significantly control opinion polarization and disagreement based on these metrics.

This review is of crucial importance to summarize works on opinion polarization and disagreement and to the better understanding and control of them.

In the organizational technology acceptance (TA) decision-making process, stakeholders have many divergence opinions. Sometimes, an opposing stakeholder of a decision can stop the whole process of decision-making. In such a case, consensus may take a long time followed by a high risk. The purpose of this study is twofold. First, to find the best model with the least prediction error for the simulation of the consensus process in TA decisions. Second, to investigate the time required for the consensus process to yield the TA decision in different scenarios and to propose solutions to reduce the required time in a case study.

This study uses real-world data containing 1,186 actual observations. Stakeholders are decision-maker agents, and the observations are derived from survey data and used for simulation. Data were obtained from 126 experts in the Iranian rail freight industry. Opinion dynamics theory was used for agent-based simulation of stakeholders’ behavior. The agents interacted over time and their effects on other agents’ opinions were investigated.

The results illustrate an appropriate opinion changing model, a data-gathering method and a simulation scenario for TA consensus. The suitable model was selected after examining the advantages and disadvantages of and comparing the prediction results for different models with the real database of opinions. To reduce the consensus process time, the results suggest gathering the team members and networking with some leaders as advocators. A large number of advocators with high acceptability and continuous exchanging messages with other agents can improve the acceptance rate and have the most significant impact on other stakeholders’ opinions.

To the best of the authors’ knowledge, previous studies simulate individual TA processes. However, there is a difference between the individual TA and the organizational TA. The organizational TA requires the simultaneous decision-making of different stakeholders. In this research, the organizational TA was investigated.

The sudden outbreak of COVID-19 has become a major public health emergency of global concern. Studying the Internet public opinion dissemination mechanism of public health emergencies is of great significance for creating a legalized network environment, and it is also helpful for managers to make scientific decisions when encountering Internet public opinion crisis.

Based on the analysis of the process of spreading the Internet public opinion in major epidemics, a dynamic model of the Internet public opinion spread system was constructed to study the interactive relationship among the public opinion events, network media, netizens and government and the spread of epidemic public opinion. The Shuanghuanglian event in COVID-19 in China was taken as a typical example to make simulation analysis.

Research results show three points: (1) the government credibility plays a decisive role in the spread of Internet public opinion; (2) it is the best time to intervene when Internet public opinion occurred at first time; (3) the management and control of social media are the key to public opinion governance. Besides, specific countermeasures are proposed to assist control of Internet public opinion dissemination.

The epidemic Internet public opinion risk evolution system is a complex nonlinear social system. The system dynamics model is used to carry out research to facilitate the analysis of the Internet public opinion propagation mechanism and explore the interrelationship of various factors.

The aim of this section is to develop a model of the linkage between the macro-dynamics of price and the micro-dynamics of individual buyers and sellers, drawing on classical micro-economic theory (Jehle & Reny, 2001). Jehle and Reny's book is in three parts. The first part discusses economic agents, namely consumers and firms. The second part discusses markets, in other words what happens when the economic agents interact; and welfare, namely the social value of the outcome. The third part is on strategic behaviour, covering game theory, information economics and auctions and mechanism design. Here, the emphasis will be on the core concepts rather than on the mathematical details. In emphasising the core concepts, attention will be drawn to the fact that these core concepts have a much wider range than simply micro-economics.

Under the new media environment, while enjoying the convenience brought by the propagation of public opinion information (referred to as public opinion), learning the evolution process of public opinion and strengthening the governance of the spreading of public opinion are of great significance to promoting economic development and maintaining social stability as well as effectively resisting the negative impact of its propagation.

Thinking about the results of empirical research and bibliometric analysis, this paper focused on introducing key factors such as information content, social strengthening effects, etc., from both internal and external levels, dynamically designed public opinion spreading rules and netizens' state transition probability. Subsequently, simulation experiments were conducted to discuss the spreading law of public opinion in two types of online social networks and to identify the key factors which influencing its evolution process. Based on the experimental results, the governance strategies for the propagation of negative public opinion were proposed finally.

The results show that compared with other factors, the propagation of public opinion depends more on the attributes of the information content itself. For the propagation of negative public opinion, on the one hand, the regulators should adopt flexible guidance strategy to establish a public opinion supervision mechanism and autonomous system with universal participation. On the other hand, they still need to adopt rigid governance strategy, focusing on the governance timing and netizens with higher network status to forestall the wide-diffusion of public opinion.

The research conclusions put forward the enlightenment for the governance of public opinion in management practice, and also provided decision-making reference for the regulators to reasonably respond to the propagation of public opinion.

Our research proposed a research framework for the discussion of public opinion propagation process and had important practical guiding significance for the governance of public opinion propagation.

The present research builds on three complementary theories to explore how social influence processes in interaction bring about opinion and sentiment change: expectation states theory, affect control theory, and social influence network theory.

An experimental study is used to test intersections between the theories and assess how performance expectations, affective impressions of group members, and emergent perceptions of their influence work together to generate opinion and sentiment change.

Respondent opinions shifted in the direction of group leaders’ opinions, regardless of behavioral interchange patterns. Opinion change was greater when a third group member shared the leader’s opinion. Change in affective impressions was shaped by the group leader’s opinion, the assertiveness of their behavior, and the support of a third group member. The perceived influence composition of the group predicted opinion and sentiment change, above and beyond the effects of conditional manipulations. Features of the group interaction led to inferences about status characteristics that reinforced the influence order of the group.

The chapter tests hypotheses from earlier work and explores status signals not yet tested as predictors of opinion change – behavioral interchange patterns and the degree of support for one’s ideas. In addition, it examines inferences about status characteristics following the group discussion, and influence effects on the prevailing definition of the situation.

This chapter contributes to recent integrative work that explores the relationship between performance expectations, affective impressions, and social influence. Synergistic processes forwarded by earlier research are tested, along with several newly proposed linkages.

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 study aims to propose a conceptual framework for the acceptability of city branding on social media. The conceptual framework of the acceptability of city branding is necessary to achieve a successful city brand in the social media era. It tries to develop the use of social media in city branding practices and its acceptability, especially in the areas of urban planning and development. The study also explores important issues in the use of social media and its acceptability in city branding practices.

This study was initially conducted using a literature review of relevant, recent, and trustworthy scholarly publications (books, journals, reports, and proceedings) about city branding and acceptability from the electronic database by using relevant terms and keywords to find the relevant literature. The next step was to identify the essential variable described in the literature and assess how these are connected to one another. The last step was to create a conceptual framework using the variables that were found and their interrelationships.

Social media is crucial for determining a successful model of city branding strategy. Incorporating social media in the city branding process may lead to emerging bottom-up forms of influencing the city branding process, creating better-accepted city branding from wider audiences and guaranteeing a long-term successful city brand. The results of this paper indicate that one can utilize social media user-generated content (from residents and visitors), local government-created content, peer interaction, electronic word of mouth (e-WOM), and the engagement and participation medium to understand whether city branding is accepted by stakeholders through nine dimensions of acceptability: knowledge, information diffusion, experience, attachment, congruence, behavioral intention, perceived quality, engagement, and participation.

This research outcome can be used to evaluate and extend the classical theory of the acceptability of city branding, or even the overall umbrella term of branding, in the digital age. Despite its contribution, this study is not without limitations. The conceptual framework herein is best suited to a branded city with a high social media penetration rate to better represent real-life phenomena in the offline environment; in other contexts, it presents certain reliability concerns regarding its implementation.

The conceptual framework herein is best suited to a branded city with a high social media penetration rate to better represent the real-life phenomena in the offline environment; in other contexts, it presents certain reliability concerns regarding its implementation.

This research highlight some acceptability dimensions of city branding practice and also emphasize social media platform as useful tool to understand people's opinion, attitude and behavior. Combining these two concepts of the acceptability of city branding and the use of social media provides an opportunity to achieve the goals of meaningful, authentic and resilient city branding.

This research paper aims to investigate the critical factors influencing the live commerce industry and their implications for Key Opinion Leaders (KOLs) and brands.

The study comprehensively reviews previous research, develops relevant hypotheses and utilizes personal information from 66 anchors, along with data from 23,000 product links obtained from the backends of live commerce platforms.

The study emphasizes that KOLs with higher traffic significantly influence Gross Merchandise Volume (GMV). Intriguingly, KOLs with lower traffic levels exhibit a more pronounced effect on Return on Investment (ROI), highlighting their significance in driving profitability. Furthermore, the study explores the correlation between KOL hashtags and GMV/ROI and the intricate relationship between product types and KOL hashtags.

The findings significantly enhance the understanding of live shopping behavior and provide valuable insights for business management strategies. Practitioners can leverage this empirical evidence to make informed decisions, utilizing extensive data samples of KOLs and brands.

This research contributes unique insights into the live-streaming commerce industry using backend data from Live Streaming E-commerce platforms. The findings are more accurate based on market data than previous studies that relied on platform reviews or questionnaires. Additionally, this paper investigates the impact of KOLs on the performance of live e-commerce from three perspectives: GMV, ROI and hot-selling products.