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The paper aims to propose an analytical framework for social influence and mathematical formulation for its main components: conformity and peer-pressure. The framework is conceived to explain why certain behaviours and beliefs propagate in a society and some others disappear. It can also be used to study the emergence and the evolution of the status of the norms in terms of their adoption by the population.

The paper is theoretical, making use of economic quantitative methods. The author proposes a new formulation for the evolutionary dynamics, increasingly borrowed by social scientists. Then, mathematically treating the equation, the author draws general conclusions in form of lemmas, which are proved.

The author's main contribution is to show that even behavioural rules and beliefs that emerge in a minority subset of the population, do not procure any benefit for the agents adopting them can under certain conditions, evolve into the consensus of a society, become a norm.

More general conclusion (theorems and lemmas) could be stated and proved. But given that the main contribution of the paper is to the fields of social and behavioural economics, along a number of disciplines less mathematical than economics, the author kept the analysis that required fairy advance mathematics for later.

The paper contributes to the evolutionary game theory, evolution of preferences, and evolution of beliefs and social norms. More precisely, the equation proposed in the paper can be used in the contexts the patterns of heterogeneity in a population are affected or caused by social influence. Or in the contexts, the social institutions are susceptible to affect an agent's sense of identity (e.g. voting, fashion industry, marketing).

In this paper, for the first time, a mathematical formulation is proposed for the social influence and its main psychological components (conformity and status seeking). Using the above, the author proposed a new parametric fitness function for the evolutionary dynamics. The author believes the paper matters to a multidisciplinary public. It answers a question that challenged and puzzled the economists (as well other social scientists): the reasons behind the emergence and the prevalence of social norms do not positively contribute to the utility or payoff of the agents adopting them (and at times they are costly).

With the recent development of science and technology, research on information diffusion has become increasingly important.

To analyze the process of information diffusion, researchers have proposed a framework with graphical evolutionary game theory (EGT) according to the theory of biological evolution.

Through this method, one can study and even predict information diffusion.

This paper summarizes three existing works using graphical EGT to discuss how to obtain the static state and the dynamics of information diffusion in social network.

The purpose of this paper is to provide a feasible scheme for local governments to regulate corporate environmental data fraud and to discuss whether the influence of the construction of online information disclosure platform on the environmental behavior of enterprises is better than the offline spot check.

Under the background of changing environmental fees into taxes in China, this paper conducts evolutionary game analysis between local governments and enterprises in view of the existing problem of environmental data fraud. Furthermore, through the introduction of government information disclosure platform, this paper discusses the impact of the integration of direct government regulation and indirect public concern regulation on the evolution of environmental behavior of both sides. Finally, the evolutionary game is simulated by adopting system dynamics to analyses the implementation effect of different cases on the game process and game equilibrium.

The results showed that the introduction of information disclosure platform mechanism can effectively suppress the fluctuations existing in the game play and stabilize the game. Moreover, it is worth noting that the regulatory effect of local governments investing part of the monitoring cost in the construction of online information platform is proved to be better than that of putting all the monitoring cost into offline investigation. While optimizing the monitoring cost allocation, the local government still needs to attach great importance to organically combine the attention of the public and media with the governmental official platform.

The obtained results confirm that the proposed model can assist local government in refining the effects of their environmental regulatory decisions, especially in the case of corporate data fraud under environmental tax enforcement.

Previous literature only suggested that local governments should reduce the cost of supervision to change the corporate behavior to a better direction, but no further in-depth study. Thus, this study fills the gap by discussing the positive transformation effect of local government cost allocation scheme on corporate environmental behavior.

Recently, the concept of financial technology (FinTech) has attracted extensive attention from international organisations and regulators, in particular, how to achieve a “win–win” situation between financial institutions' FinTech innovation and effective regulation has become a hot topic. This study purposes to explore the evolutionary game relationship between FinTech innovation and regulation by constructing both static and dynamic earmarking game models.

A simulation experiment was conducted using primary data obtained from a commercial bank in China.

The results of the theoretical analysis of evolutionary game models were consistent with the corresponding simulation results, proving the validity of the proposed evolutionary game models. It was also found that the dynamic earmarking game model was more stable and effective than the static earmarking game model in promoting FinTech innovation and regulation. Furthermore, when the regulators utilised a dynamic earmarking mechanism, the evolutionary path of financial institutions and regulators' behaviour strategies took the shape of a spiral and eventually converged to a central point, indicating the existence of an evolutionary stable strategy and Nash equilibrium. Finally, because the behaviour strategies of financial institutions were mainly influenced by the regulators' policies, the regulators were inspired to adjust the corresponding regulation policies on FinTech innovation.

This study bridges the knowledge gap in the existing literature on financial innovation and regulation, in particular by establishing evolutionary game models from the perspective of financial earmarking policies. Also, the case study for simulation experiments can gain a more intuitive insight into FinTech innovation and financial earmarking policies.

The purpose of this paper is to determine how high-tech firms should choose between independent research and development and technology introduction as well as to ascertain the effects of the three elements of competitive dynamics on the evolution of innovative behavior-based decisions and competitive results.

This paper describes the construction of an evolutionary game model and a multi-agent-based model of innovative behavior-based decisions by heterogeneous high-tech firms. The models are used to analyze the evolution path and evolutionarily stable strategy of innovative behavior-based decisions. In addition, multi-agent-based simulation is used to gain insight into the effects of competitive dynamics on the dynamic evolution of innovative behavior-based decisions.

This paper reveals four evolutionary equilibrium states of the innovation behavior-based decisions of high-tech firms. Based on the findings, these overall evolutionary trends are not affected by the timing of competitive market entry or the intensity of competition. In addition, simulated evidence is added that the timing of competitive market entry is an important factor affecting market-leading innovative strategies and dynamic competition results, and competition intensity is closely related to the evolutionary speed of innovation behavior-based decisions.

The key contribution of this paper is its new view of innovative behavior-based decisions from a competitive dynamics perspective. The new competitive dynamics-based framework for innovative behavior-based decisions of high-tech firms proposed in the paper can resolve the problem of obtaining a sustainable competitive advantage for high-tech firms in a competitive dynamics context.

The purpose of this paper is to investigate the dynamics and evolution of trust in organizational cross alliances.

In alliances between corporations and nonprofit organizations, trust in decision-making is a dynamic process. Using the replicated dynamics model of evolutionary game theory, this paper provides a trust decision model and analyzes four scenarios under different parameters. A numerical simulation is developed to present an intuitive interpretation of the dynamic development of trust decisions and the effects of incentive and punishment mechanisms.

Under different parameters, bounded rationality and utilities result in different but stable evolutionary strategies; the initial probability of adopting a trust strategy leads directly to whether participants adopt the strategy when the system reaches stability after continued games; and incentive and punishment mechanisms can significantly reduce the initial probability of adopting a trust strategy where the system evolves to meet stable state needs.

The establishment of trust relationships is an important influence on the stable and coordinated development of an alliance. The proposed model can help the alliance build closer trust relationships and provide a theoretical basis for the design of the trust mechanism.

Incentive and punishment bound by some degree of trust are introduced to address the problems of trust decisions and their dynamics; the model created reflects the bounded rationality and utility of each game stage. Useful evolutionary stable strategies using different variables are proposed to address the decision-making problems of trust in cross alliances.

Knowledge has become the basis of enhancing the core competitiveness of enterprises in this era of knowledge-driven economies. Collaborative knowledge management not only realizes the real-time exchange and communication of knowledge among different enterprises, but also facilitates the collaboration and integration of knowledge. Collaborative knowledge management has been successfully applied to different fields. To address the poor ecological responsibility of enterprises, the purpose of this paper is to introduce the concept of collaborative knowledge management in this research to determine if the evolution of the decision-making process in collaborative knowledge management is involved in corporate ecological responsibility (CER).

This research established an evolutionary game model of collaborative knowledge management for CER. The behavioral, evolutionary law and stable behavioral, evolutionary strategy of the participants was identified according to the replicator dynamics equation. Simulation analysis was conducted using MATLAB software.

Research results demonstrated that, first, the strategic selection of firms is influenced by cost and interest coefficients. Second, the strategy, selection of enterprises, is related to the common benefits of enterprise cooperation. Third, during the systematic evolution and stabilization of strategies, enterprises adopt the same knowledge strategies.

On the basis of the research findings, policy suggestions were proposed to encourage enterprises to implement collaborative knowledge management strategies in ecological responsibility.

Although green logistics has become a new focus of cooperation between government and enterprises under environmental constraints, how local governments formulate subsidy policies to effectively guide the green transformation of regional logistics and how to facilitate the reasonable cost-sharing are rather critical. This paper will deeply explore the dynamic process of the tripartite participation (government, platform, and logistics enterprises) in the selection of regional green logistics strategy, and reveal the evolutionary game relationship of the three parties.

To explore the dynamics involving the government, platform and logistics enterprises for the green logistic transformation, and reveal the evolutionary gaming among the three parties, based on the bounded rationality premise, this study constructs the tripartite asymmetric evolutionary game models, uses the stability theorem of differential equation to explore the evolution and stability strategy of the system in different cases and explicates the paths of influence on the tripartite behaviors via simulations.

Results of this study indicate that there exist stable equilibrium strategies among the three parties regarding the regional green logistics, and they are affected by different factors. The government's subsidy, subsidy intensity and the platform's cost-sharing proportion can generate positive effects, but the latter two can also impact negatively beyond the effective ranges. The findings provide a theoretical basis for local governments, platforms and logistics enterprises to formulate justifiable subsidy intensity and determine reasonable sharing proportion.

Firstly, considering the significant relevance of local government, it is included in the evolution model, and the tripartite game (among government, platform and enterprises) is explored; Secondly, by comparing the equilibrium results under different game conditions, this paper analyzes the evolution of each party's game strategy to achieve the optimal return under bounded rationality and the important factors determining the strategic selection; Finally, the key factor of platform cost sharing is involved, and to what extent the change of platform cost sharing ratio will influence the systematic stability is explored.

Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

Knowledge sharing in a master-apprentice pattern is the process of transferring tacit knowledge from masters to apprentices. In addition, 90 per cent of knowledge required for organizational innovation is tacit knowledge in the master-apprentice pattern. The purpose of this paper is to analyze the evolution of knowledge sharing in master-apprentice pattern and explore the consequences of how to improve the knowledge sharing in the master-apprentice pattern.

This paper uses asymmetric evolutionary game theory to study the evolutionary track of knowledge sharing in master-apprentice pattern of innovative organizations by analyzing the utility of masters and apprentices during the process of knowledge sharing in master-apprentice pattern of the innovative organization.

The results reveal that when the masters obtained utility from sharing knowledge is greater than that from hoarding knowledge, and the apprentices obtained utility from studying hard is greater than the costs, the innovative organization can get the largest utility from the knowledge sharing in the mater-apprentice pattern.

The limitation of the research is that this paper mainly studies knowledge sharing among individuals and does not research knowledge sharing between individuals and organizations.

This research has extended the understanding of knowledge sharing in master-apprentice and its evolution path. Also, the obtained findings are conducive to promoting knowledge sharing in master-apprentice and improving human resource management in innovative organizations.

This paper attempts to construct the evolution path of knowledge sharing in master-apprentice pattern, which is a useful exploration of the dynamics of knowledge sharing in master-apprentice pattern and makes up for the shortcomings of the existing research.