Coordination game model of co-opetition relationship on cluster supply chains

The research of cluster supply chains is a new direction and a hotspot of the industrial cluster theory. On the condition of the coordination game, the enterprises may be stuck on the non-efficient equilibrium status, which becomes an important problem that must be considered on cluster supply chains. A symmetrical coordination game model is constituted to describe the competition and cooperation relationship of the same-quality manufacturers on cluster supply chains. The methods of the non-cooperation game theory and the evolutionary game theory are respectively used to analyze the model, whose parameters＇ influences under each method are then compared. It can be concluded that the analysis of the evolutionary game theory is more realistic and practical. Finally, three approaches are considered to break away from being path-dependence locked-in non-efficient status during this coordination game evolutionary process, which provide the development of cluster supply chains with an effective forecasting and Pareto optimizing method.

The Construction and Competitiveness of Operation Model of Agricultural Industrial Cluster

Through reviewing the viewpoints of former scholars, the connotation and features of supply chain of agricultural industrial cluster are introduced. The agricultural industrial cluster model constituted by core network and supporting network is constructed. Three operation models of this kind of supply chain is described: the model takes wholesale market of agricultural products as the core; the model take pillar industries of agricultural industrialization as core; model takes the chains of retail enterprises as core. The competitiveness of agricultural industrial cluster is researched. The research assumes that the competiveness of supply chain of agricultural industrial cluster is mainly represented to make the agricultural industrial cluster to acquire more capabilities in terms of innovation and knowledge sharing capability, resource allocation capability, agile market adaptability and distinct value creation capability.

Similarity Search Algorithm over Data Supply Chain Based on Key Points

In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented data supply chains because the high complexity of the data supply chain makes the computation of similarity extremely complex and inefficient. In this paper, we propose a feature space representation model based on key points,which can extract the key features from the subsequences of the original data supply chain and simplify it into a feature vector form. Then, we formulate the similarity computation of the subsequences based on the multiscale features. Further, we propose an improved hierarchical clustering algorithm for a similarity search over the data supply chains. The main idea is to separate the subsequences into disjoint groups such that each group meets one specific clustering criteria; thus, the cluster containing the query object is the similarity search result. The experimental results show that the proposed approach is both effective and efficient for data supply chain retrieval.