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The paper attempts to analyze the network structure of value activity in manufacturing clusters, propose the model of value creation of cluster's value activity network, and explore the inner mechanism and optimization strategies of value creation in manufacturing clusters from the perspective of cluster's value activity network.

This paper applies a genetic algorithm to optimally search in the target space, and repeatedly exerts genetic operation (select, cross, variation) on the population to explore the optimal configuration strategy between value creation activity and resource utilization. It also analyzes the relation between object function of value creation and relative parameters.

The total value created by value activity network was impacted by the degree of effective configuration between all kinds of resources and value activities; the total value created by value activity network is positively related to activity units' elasticity coefficient of value creation of human resource, material resources and relations resource, and is negatively correlated to cost coefficient of human resource, material resources and relations resource; when the cooperative relations between activity units create positive relationship profit, the total value created by value activity network increases with the increase of cooperative relations between activity units.

Enterprises in clusters should reasonably configure and incorporate the resource among value activities through adding, deleting or reconfiguring activities, which makes the value activities network create maximum value; enterprises can transform the type of activity units to increase elasticity coefficient of value creation of human resources, such as transforming production activities into the high value‐added activities; enterprises can optimally incorporate the technical, material resources and human resources among activities to increase value creation elastic coefficient of material resources; enterprises can decrease cost coefficient by maintaining the stability of long‐term cooperation with the suppliers and strengthening the cultivation of talents; enterprises can increase profits from relation resource or reduce cost coefficient of relationship by updating activities, building trust mechanism and communication mechanisms and establishing long‐term cooperation relationship to improve value creation activities.

This paper proposes the model of value creation from the perspective of cluster's value activity network, and applies a genetic algorithm to explore the optimal configuration strategies between value creation activity and resource utilization.

This paper aims to construct evaluation index system of industrial economy-ecology-coordinated development based on “driving-force-pressure-state-impact-response” conceptual model. Grey target theory is introduced to evaluate industrial economy-ecology-coordinated development level and identify its key influencing factors. On that basis, the countermeasures are proposed to improve industrial economy-ecology-coordinated development in China.

Bull's-eye degree of grey target theory is introduced to evaluate industrial economy-ecology-coordinated development level of 31 provinces, municipalities and autonomous regions in China. The contribution degree of influence factors is analyzed by contribution degree theory.

The results show that first, the overall level of industrial economy-ecology-coordinated development in China is not high, there is a big gap of coordinated development level between provinces, municipalities and autonomous region, and there is still a large room to improve the status quo. Second, the major factors affecting industrial economy-ecology-coordinated development are gross industrial output value (GIOV) share of investment completed in the treatment of industrial pollution, common industrial solid wastes produced per GIOV, sulphur dioxide emission per GIOV, energy consumption per 10,000 yuan of gross regional product.

This paper constructs evaluation index system of industrial economy-ecology-coordinated development and applies grey target theory to evaluate industrial economy-ecology-coordinated development level and identify its key influencing factors.

The purpose of this paper is to attempt to calculate the trust degree between two enterprises in an industrial network using grey correlation degree algorithm for exploring characteristics of community structure and evolution rules of cluster cooperation networks in axle‐type and satellite‐type clusters.

Starting from analysis of trust formation mechanism of inter‐enterprise in industrial networks, adjacency of inter‐enterprise relationship, their information acquisition ability, their influence power in network and their past interaction experience are chosen as influencing factors of the trust between two enterprises. Grey correlation degree algorithm was chosen to calculate the trust degree between two enterprises in an industrial network. According to the rules of dynamic adjustment of trust degree originated from thoughts of the prisoners' dilemma model, computer simulation is applied to explore characteristics of community structure and evolution rules of cluster cooperation network in axle‐type and satellite‐type clusters.

With the dynamic adjustment of enterprises' trust degree, the network density of axle‐type and satellite‐type cluster networks was decreasing as the cluster scale was enlarging, and eventually tended to be stable; community structure was emerged in axle‐type and satellite‐type industrial clusters as the cluster scale was enlarging; community characteristics were obviously stronger in axle‐type cluster networks than in satellite‐type; communities were overlapped in axle‐type cluster networks, that is, bridge nodes emerged between communities.

This paper is the first to apply the grey correlation degree algorithm to calculate the trust degree between two enterprises in cluster networks for designing the rules of dynamic adjustment of trust degree.

It has been ten years since the policy was implemented, but the effect of the policy needs to be tested empirically. This paper aims to explore the mechanism of policy influence on regional innovation ability by measuring the effectiveness of policy by innovation ability indicators. Further, it reflects the problems in the process of the transformation and development of resource-based cities in recent years and points out the direction for the development of the cities in the future. In addition, this paper discusses the differences between regions and cities in China and seeks the path to narrow the gap.

This paper mainly uses the difference-in-difference method for the research. This study divided China’s resource-based cities and non-resource-based cities into experimental groups and control groups, and explored the effect of the transformation and development of resource-based cities and the changes of their innovation ability under the influence of the National Sustainable Development Plan for Resource-based Cities (NSDPRC). More carefully, this paper uses the fixed effects regression model, propensity score matching method, bootstrap method and other methods to improve the empirical results.

This paper finds that NSDPRC significantly improves the innovation ability of resource-based cities, although there is some lag in this effect. Research on the influence mechanism of policies shows that NSDPRC improves the marketization degree of resource-based cities and reduces the proportion of the secondary industry in such cities. Finally, the results of the heterogeneity analysis confirm that policies are more popular in western China and that resource-based cities in growth, maturity and decline are more vulnerable to policy influence. The development of policy effectiveness also requires the size of a city, and maintaining a healthy and reasonable scale is necessary for urban development.

First, the existing research on the development of resource-based cities is mainly from the perspective of economy and environment, but rarely from the perspective of innovation ability, and the index to measure urban development is relatively single. This paper will compensate for this deficiency. Second, different from the European and American countries that have basically completed the industrial transformation, the research on Chinese cities will provide a reference for the transformation of developing countries. Finally, from the perspective of resource endowment theory and innovation theory, this paper discusses the influence of SDPNRBC mechanism on the innovation ability improvement of resource-based cities, and further improves and enriches the theory.