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Various decision opinions comprise the foundation of emergency decision-making. However, decision-makers have difficulty establishing trust relationships within a short time because of decision-making groups being temporary. The paper aims to develop an ambiguity-incorporated opinion formation model that considers ambiguous opinions on relevant risks from a psychological perspective during the consensus reaching process.

Addressing the problem of forming a consensus decision-making opinion in an ambiguous environment and relevant risk opinions, different social network structures were first proposed. Subsequently, psychological factors affecting the decision-makers' perception of ambiguous opinions and tolerance for ambiguity under the multi-risk factors were considered. Accordingly, an ambiguity-incorporated opinion formation model was proposed by considering the ambiguity and relevant opinions on multi-risk factors.

A comparison between the ambiguity-incorporated opinion formation model and the F–J model illustrates the superiority of the proposed model. By applying the two types of network structures in the simulation process, the results indicate that the convergence of opinions will be affected by different decision-making network structures.

The research provides a novel opinion formation model incorporating psychological factors and relevant opinions in the emergency decision-making process and provides decision support for practitioners to quantify the influence of ambiguous opinions. The research allows the practitioners to be aware of the influence of different social network structures on opinion formation and avoid inaccurate opinion formation due to unreasonable grouping in emergency decision-making.

The purpose of this paper is to define the sustainable university in Turkey, by considering perspectives of various stakeholders such as experts, intellectual, public, political parties and media using public opinion formation analysis. The paper aims to re-define the “sustainable university” with all dimensions including environmental, economic and social factors in Turkey.

In this study, the model of shaping the policy agenda and public opinion formation by certain groups, presented by Papadakis (1996), was used to determine the main characteristics of a sustainable university. Based on this model, the researchers collected data from intellectuals, experts, political parties, media and public simultaneously. Focus groups and archival search were used.

The results of the public opinion formation process presented that the definition of sustainable universities in Turkey includes the economic, ecological and social aspects and a holistic view of different groups. The findings of the study presented that the definition of sustainable universities in Turkey has many facets. Different groups in the public opinion formation process share almost similar views, though these points are usually mentioned under different headings. Thus, nearly each respondent in the public opinion formation process discusses the concept of being a “trade mark” as a university.

The research may lack generalizability, as it takes place in Turkey, which is a non-Western country.

The research sheds a light for universities, which are the major cornerstones of higher education, especially in the area of sustainability and sustainable development. Also, universities have a great impact in regional development, which stresses once again the importance of sustainability in higher education. They should modify their education programs and curricula in accordance with sustainability. University–industry cooperation should be provided. They should manage to become a trademark.

Universities being the major cornerstones of higher education play a vital role in regional development of countries; therefore, their sustainable development should be well handled to enable regional development.

The universities are the major actors which should pursue sustainability, as they affect society. The studies on sustainability and universities have been generally grouped under two main subjects in the literature. First group of studies highlights the support of universities for sustainability of corporations, whereas other studies stress the importance of becoming a sustainable university. There are not many studies on this subject which considers the public opinion formation process throughout the literature; therefore, this study contributes to the literature with this aspect. The study takes place in Izmir, Turkey, which is a non-Western country. Most of the studies on this subject take place in Western countries, so as the study is deployed in a non-Western country, it reflects a different point of view.

In modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).

First, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.

The results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.

This study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.

This research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.

The purpose of this paper is to assess the influence mechanism of the word-of-mouth reputation of influencers.

This study explored word-of-mouth reputation from four characteristics of information source of influencers: credibility, professionalism, interactivity and attractiveness. The grounded theory was used to extract the characteristic indicators of influencers and used questionnaire surveys to obtain 218 valid samples. The fuzzy-set qualitative comparative analysis (fsQCA) was used for the configuration analysis.

The results revealed the following: (1) a causal asymmetric correlation exists between the driving mechanism of high word-of-mouth reputation and non-high word-of-mouth reputation; (2) influencers matching high word-of-mouth reputation comprises potential, developmental and almighty types, whereas live streaming influencer matching non-high word-of-mouth reputation comprises elementary and groping types; and (3) all factors must be combined to play a role, and neutral permutations of two solutions were found among the three overall solutions to attain high word-of-mouth reputation; (4) the combination of high user activity and high exposure is the core configuration that results in high word-of-mouth reputation.

This study provides recommendation for consumers, live streamers, brand and e-commerce platform on how to promote the sustainable and healthy development of influencer marketing.

This study focused on elucidating how the characteristics of information source affect the word-of-mouth reputation of influencers and have a reference value for the research on word-of-mouth reputation in the context of live commerce.

The purpose of this paper is to solve the problem of tuning of EKF parameters (process and measurement noise co-variance matrices) designed for attitude estimation using Global Positioning System (GPS) aided inertial sensors by employing a Human Opinion Dynamics (HOD)-based optimization technique and modifying the technique using maximum likelihood estimators and study its performance as compared to Particle Swarm Optimization (PSO) and manual tuning.

A model for the determination of attitude of flight vehicles using inertial sensors and GPS measurement is designed and experiments are carried out to collect raw sensor and reference data. An HOD-based model is utilized to estimate the optimized process and measurement noise co-variance matrix. Added to it, few modifications are proposed in the HOD model by utilizing maximum likelihood estimator and finally the results obtained by the proposed schemes analysed.

Analysis of the results shows that utilization of evolutionary algorithms for tuning is a significant improvement over manual tuning and both HOD and PSO-based methods are able to achieve the same level of accuracy. However, the HOD methods show better convergence and is easier to implement in terms of tuning parameters. Also, utilization of maximum likelihood estimator shows better search during initial iterations which increases the robustness of the algorithm.

The paper is unique in its sense that it utilizes a HOD-based model to solve tuning problem of EKF for attitude estimation.

The study aims to reveal regularities of collective decision in groups of varying cooperativity and to investigate the influence of individualism–collectivism cultural dimension on the emergence of collective behavioral entities.

An agent-based model of group behavior is used to simulate the logic of collective binary decisions defined by reaching a consensus threshold. The key parameter of the model is the cooperativity of interaction between individuals which locates the group in individualism–collectivism cultural dimension. The probabilities of collective decisions are measured as a function of individual preferences and the strength of cooperation between agents.

Strong, weak and middle point cooperativities of inter-individual interaction define three distinct regimes of collective decision logic, namely, individualism, conformism and criticality. The critical organization allows the group to generate coherent non-predetermined collective behavior in statistical agreement with individual preferences.

Emergent collective behavior with coherent and nondeterministic decision-making can be modeled in an agent-based approach with local interaction between individuals tuned to a critical point. Variation of a single cooperativity parameter accounts for a continuous transition between organizations of the group inherent to inert matter and living systems.

A new organization of social systems distinguished by internally relaxed relations and large-scale freedom is found beyond the traditional individualism–collectivism contraposition. This state is reached by tuning behavioral logic of individuals to a critical balance of individual and collective values.

Individualist, conformist and critical regimes of collective organization distinct in terms of integrity, complexity and determinism are recognized as universal organizational classes of nature spanning both inert and living systems. In particular, individualist and conformist regimes produce simple deterministic behavior typical for gases and solid bodies, whereas the critical organization generates complex nondeterministic behavior inherent to living organisms.

Aims to take an atomistic view on emotions, where emotions are seen as discrete entities interacting with one another.

Takes an unconventional route in simulation of mental processes – studying emotions in terms of artificial, abstract, chemical systems, where emotions are seen as chemical species and chemical reactions correspond to rules of emotional interactions.

An affective solution is a theoretical construct which represents emotions spreading and interacting in massive pools of locally interacting entities. Molecules in the affective solution stand for basic emotions: happiness, anger, fear, confusion and sadness, which diffuse and react with each other by quasi‐chemical laws. In computational experiments with affective solutions, in well‐stirred and thin‐layer reactors, uncovers varieties of behavioural modes of emotion interactions.

Tests applicability of affective solutions in an example of emotional abuse therapy.

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.

Much of the literature in organizational change has taken a single approach to explain employee expectation formation regarding the outcomes of a change event. A conceptual model is developed to integrate two existing streams of research (the information effects approach and the social effects approach) and to develop a comprehensive picture of outcome expectation formation. We propose that information and social effects function simultaneously to shape an employee's outcome expectations. The strength and content consistency of information and social effects jointly determine what people expect regarding change outcomes and how confident they feel about those expectations. Implications are discussed in terms of setting the boundaries for information and social effects as well as future research directions.

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.