Research On The Mechanism Of Green Behavior Diffusion Of Resource-based Enterprises Based On Complex Social Networks

The issue of resources, environment and development has been one of thecentral concerns for the international community. Since the1980s, the concept ofgreen has swept around the whole world and the international community has begunto adjust the whole social economic system in the aim of “green economy”. In thenew century, especially during the recent years, it is generally recognized thatdeveloping green economy is the inevitable choice in dissolving the contradictionbetween economic development and resources and environment.Rigidly constrained by the increasing resources endowment and ecologicalenvironment, as the unit and micro basis of developing circular economy and theimplementing green concept, the decision and implementation of green behaviors bythe resource-based enterprises is the important driver for developing green economy,implementing green transformation and upgrading, and realizing the harmonious andsustainable development of resources, environment, economy and society.According to the theory of social network, individual always exists in a socialnetwork which interacts with the external environment and other individuals. This network is a dynamic process in which individuals repeatedly contact, analyze,evaluate and make decision. The network is also a platform for large numbers ofindividuals to share and obtain resources.From an economic perspective, in the interaction between individuals, if onesubject’s strategy can bring more profit, others subjects will imitate. It will lead tothe spread of the behaviors, then a specific behavior patterns will be formed andfinally the problems of resource allocation for the whole society (group) will besolved.It is also true for the resource-based enterprises whose social interaction formsgreen behavior. The interaction between individuals and groups will benefit thetransferring and sharing of the skills, knowledge and information betweenresource-based enterprises, enterprises and other organizations. Under the doublepressure of the resource consumption and environment protection, resource-basedenterprises always make behavioral decision by imitating or innovating. When greenbehavior is adopted by many adopters, green behavior will be diffused. Therefore,the green behavior of resource-based enterprises diffusion in essence, is the dynamicinteractive process for enterprises and other individuals to contact, analyze, studyand make decisions.The social network of resource-based enterprises is a breakthrough of rigidboundaries for business entities and is also the important carrier to implement thediffusion of the green behavior. The structure characteristics of social networkinfluence the method, channel, depth and breadth of the diffusion of the greenbehavior. The social network of the resource-based industry cluster is undoubtedly acomplex networks with of scale-free and small-world characteristics. Thecomplicacy of topology affects the path of green behavior diffusion ofresource-based enterprises.Social network can represent any structure directly, including dynamicallychanging topology with complexity and versatility. Therefore, the purpose of thetheory of complex social networks is to explain the complexity of real world andtherefore, to better understand the internally hidden dynamic property of complexsystem. This theory can help provide scientifically quantitative method and instrument for the diffusion of green behavior of resource-based enterprises, simulatethe objective world, make a more realistic description of the dynamic process of thediffusion of green behaviors, and deepen the recognition of complexity ofsocio-economic system. This is of great practical significance for the diffusion ofresource-based enterprises’ green behavior which itself provides the complexnetworks theory with more social background and theoretical value.The theory of complex social networks is widely used in the research ofsocio-economic system. With further research, the inclusion of the diffusion of greenbehavior into social network has come to a major concern for many scholars,governments and resource-based enterprises. Green behavior diffusion exhibitedsome new features in the complex social networks environment which will be furtherstudied.This dissertation will abstract the socio-economic system into the networkmodel for the convenience of study, from the perspective of complex social networks,the interactive bandwagon effect between adopters of green behavior and greenbehavior and the impact of network dynamic evolution towards diffusion of greenbehavior. It not only improves the enterprises’ green management theory andeco-industrial network theory in industrial ecology, but also greatly enriches thespecific application of complex networks theory, complements and expands thediffusion model. The paper also provides a new perspective on how to choose andimplement the green strategies and how to upgrade path for China’s resource-basedenterprises.This dissertation studies the diffusion of green behavior of China’s enterprisesof resource-based industry cluster based on the resource-based theory, sustainabledevelopment theory, behavioral diffusion theory, complex social networks theory,regional economics theory and other related academic achievements. Thedissertation firstly constructs the framework of decision-making influencing factorsof the green behavior of resource-based industry clusters, identifying and analyzingthe key factors by using the entropy weight decision-making model; confirming thatthe expected revenue driving and environmental regulation constraints are the twotypes of sources of the green behavior of resource-based enterprises, and the diffusion of corporates’ green behavior in social network using cluster as anintermediary. Then the dissertation analyses the influence of the adopters complexnetworks topology on the diffusion of green behavior by using the game theory asthe analysis tool, and explores the relationship between average step numbers of thediffusion of corporates’ green behavior and the average number of adjacencyuninformed contiguous network. The dissertation secondly researches the networkdynamic evolution of green behavior evolution by using adopters green behaviorbipartite network and the adoption behavior of the network. Thirdly, it incorporatesthe comprehensive influenceCEt from the key element contains social networkstructure of the cluster to the adoption potential N (t), then constructs the greendiffusion behavior forecasting model of potential dynamics, and compares greendynamic diffusion behavior forecasting model of adopters potential amount with theBass basic model. Finally, it provides the conclusion and further prospect.There are seven parts in this dissertation. In the first part, this dissertationcomprehensively introduces the main research background and significance,emphasizes that perspective of complex social networks could transform andimprove traditional research of behavior diffusion by defining resource-basedenterprises, analyzing the connotation of enterprises’ green behavior, expounding theforesight and importance of the research. Then the paper puts forward the researchideas and methodology, and summarizes the main contents and structure framework.The second part introduces the basic theories associated with this dissertation,as well as research progress of each theory which clarify complex social networkstheory’s importance for dissertation on traditional behavior diffusion. Firstly, itillustrates complex social networks theory from five respects including researchprocess, general characteristics, representation, measurement indicators and networkgeneration models, which provides dissertation perspectives. Secondly, based on thedefinition of behavior diffusion, it introduces and summaries several basic diffusionmodels systematically and comments on the models’ shortages in the dissertation onthe diffusion in social network. It points out the trend that the dissertation onbehavior diffusion shifting to the diffusion dynamics models in complex social networks, which demonstrates the reason for this dissertation’s focus on complex social networks. The diffusion model provides analysis tool for this dissertation.The third part establishes the decision-making influencing factors’ framework of resource-based industry’s green behavior, and uses entropy decision model to identify and analyze the key influencing factors and further analyzes the differences of criticality of key factors’ influence on green behavior of state-owned enterprises and private enterprises in industrial clusters. Under the confidence level of λ=0.99, the criticalities of five key factors including enterprise’s expected revenue (y2), environmental regulation (y1), ecological environment (y12), network characteristics of industrial clusters (y7) and enterprises’ social responsibility (y4) are μ(d2)=0.9998,μ(d1)=0.9982,μ(d12)=0.9977,μ(d7)=0.9963and μ(d4)=0.9948respectively. Although the nature of enterprises fails to affect their overall grasp of the key influencing factors, but the criticalities of the five key influencing factors varies from different nature of enterprises. Among them, the state-owned enterprises and private enterprises have consistency in the pursuit of expected revenue and face the same environmental regulation pressure. But for state-owned enterprises, they tend to make green behavior decisions based more on ecological environment and enterprises’social responsibility. In Chinese resource-based industrial clusters, resource-based state-owned enterprises usually dominates, they are more likely to affect the decisions of other enterprises. And the private enterprises’operations are highly flexible due to their small size and they are more susceptible to industrial clusters of the network, which is also consistent with the reality of the situation. Overall, however, expected revenue’s drive and environmental regulation’s constraints are two types of origin of resource-based enterprises’green behavior and enterprises’green behavior diffuses with the intermediary of social network cluster. Lastly, qualitative theory methods of nonlinear dynamical system is applied to analyze the effects of time delay on equilibrium point of the Logistic correction model about green behavior diffusion in resource-based industry cluster. The results show that diffusion efficiency of green behavior in resource-based industry cluster will be constrained if time delav more than With the perspective of adoption network game, the fourth part analyzes the diffusion rules and influence of green behavior in resource-based industrial cluster. Firstly, with the help of game theory, the dissertation establishes a multi game model on green behavior diffusion, and through the Nash equilibrium analysis of green behavior diffusion game, reveal the relationship between other parameters and the probability p*which player informed of green behavior take diffusion strategy or the probability q*which player uninformed of green behavior take the adopt strategy:the probability p*which player informed of green behavior A take diffusion strategy is proportional to the difference m-n of player uninformed of green behavior adopt cost m and refuse cost n, and is inversely proportional to the total expected revenue s+aK. It means that in order to keep the competitive advantage, the greater the expected revenue is, the more conservative of diffusion attitude that player informed of green behavior tend to be. On the other side, the probability q*which player uninformed of green behavior Aki take adopt strategy is proportional to the eventually blocked cost cKβ of player informed of green behavior, is inversely proportional to the number of the player uninformed k in the adoption network. When s, K, α,β are certain, the greater the k value is, the smaller the q*value is. Then this dissertation take the Markov chain analysis to the green behavior diffusion, and find the diffusion process of green behavior in adoption network is a typical Markov chain, but also an absorbing chain. The number of green behavior diffusion steps is inversely proportional to the number of average adjacent player uninformed of green behavior k in the adoption network. Finally, the author will explore on the influence of the complex structural characteristics of the green behavior adoption network to the resource-based enterprise.The fifth part analyzes the evolution of the network herding behavior from two aspects of adopter-green behavior bipartite network and adoption behavior network. By constructing the adopter-green behavior bipartite network, with the theoretical derivation, analyze the herd behavior evolution adoption under the three different ranges of imitation probability in the steady state of the adopter-green behavior bipartite network:when the event effect strength is λ=1, in a adopter-green behavior bipartite network with M adopters and N kinds of green behaviors, the average degree of green behavior nodes meets k=M/N. There are:1) when the imitation probability of green adopters is pim∈[0,k/1+k=),the trend of adopters that adopted green behaviors obeys the binomial distribution.If so, the green behavior choice exhibits a very weak herding effect;2) when the imitation probability of green adopters is pim∈[k/1+k,1-1/M], the trend of adopters that adopted green behaviors exhibit the different degree of herding behavior. The adoption behavior of adopters obey the power-law distribution with different exponentially truncate.A few green behaviors have been widely adopted, but most green behavior is adopted by adopters dispersedly;3) when the imitation probability of green adopters is pim∈(1-/M,1], the trend of adopters that adopted green behaviors obeys the pulse distribution.The green behavior choice, thus, exhibits a very strong herding effect.In the sixth part, this dissertation takes the Bass model to research the diffusion of green behavior of resource-based enterprises.Firstly, it builds a macroscopic diffusion model of green behavior influence based on the Bass model,and provides a theoretical basis for the prediction of the Bass model.Secondly, it research the prediction of the diffusion of practical green behavior based on the basic principle, modelling elements and data requirements of the Bass model,and further confirms the feasibility of the forecast research.Thirdly, it uses the time function which contains the resource-based enterprises instead of the latent capacity of fixed value of the original Bass model by the knowledge that the dynamic changes in the number of resource-based enterprises will lead to dynamic changes in the amount of green behavior of the potential adopters, and it incorporates the comprehensive influence CEt from the key element contains social network structure of the cluster to the adoption potential N(t), then constructs the green diffusion behavior forecasting model of potential dynamics. Finally, it comprises green dynamic diffusion behaviorforecasting model of adopters potential amount with the Bass basic model, theimproved model’s fitting and forecasting precision are improved.The seventh part summarizes the main research work, conclusions, innovationsof this dissertation. This part then points out the limitations of the research and thedirections for future research.