Knowledge Flows In The Manufacturing Supply Chain Enterprise Optimization Studies

With the development of knowledge economy, the strategic value of knowledge has become increasingly prominent in promoting economic development and enhancing the core competitiveness of organizations. Identifying knowledge, accessing knowledge and absorbing knowledge to organization's core competitiveness, has become hot and difficult research pots. In recent years, knowledge flows and knowledge sharing attracts scholars to study as an effective way to get knowledge. Especially, the knowledge flow in strategic alliances, multinational corporations and other organizations can be gradually in-depth study. Supply chain as a new mode of cooperation has been more fully studied in logistics, capital flow and information flow, but knowledge flows would have to be further explored.In this paper, knowledge flow between enterprises in supply chain would be studied, specifically including the following:(1) Building an affecting index system of knowledge flow in supply chain, and using Conjoint Analysis and fuzzy-AHP to determine the index weights firstly.On the basis of analysis and summary about the literature on knowledge flow,96 indicators are teased with fishbone diagram to combine with features of enterprise in supply chain. It builds the indicator system, which contains four-level indicators, such as knowledge characteristics, characteristics of inter-firm relations, characteristics of different firms themselves and environmental features; 11 secondary indicators, including the knowledge expressiveness, knowledge ambiguity, quality of relationship, knowledge distance, cultural differences, organizational distance, physical distance, knowledge willingness and ability of different firms, knowledge flow channels and IT support. And then, to explore the importance of various indicators, the paper applies Conjoint Analysis and fuzzy-AHP respectively to determine the relative index weights what has confirmed the characteristics of relationship between firms is the most important indicator of knowledge flow, and then characteristics of different firms themselves; quality of relationship of the secondary indicators seemed more prominent.(2) Static effects of knowledge flow for manufacturing supply chain has been studied by rough set-BP neural network and validated with tobacco industryIn the index system and the weight determined based on the rough set theory and the combination of BP neural network method, introduced into the flow of knowledge research, the manufacturing supply chain to achieve a flow of knowledge between enterprises evaluate the static effects. By rough set theory about complex indicator system for simple, come to represent the original reduction target indicator system combination, thus reducing the burden of BP neural network, to achieve the manufacturing supply chain effects of inter-firm knowledge flows quickly and effectively simulation. The use of simulation to achieve the optimal supply chain network of the tobacco industry to evaluate the effect of knowledge flows, determine the tobacco industry supply chain, the general effect of knowledge flows, the results of this evaluation and《China Statistical Yearbook of Science and Technology》of new products in tobacco manufacturing output and output data show the number of patents are basically the same ranking, proved rough set-BP neural network can effectively assess the manufacturing supply chain effects of inter-firm flow of knowledge, also shows that the tobacco industry supply chain, the flow of knowledge between enterprises still need to substantially upgrade the level of to meet the tobacco industry's high, sharp, fine development.(3) Dynamic effects of knowledge flow for manufacturing supply chain has been studied by DEAStatic evaluation of the chain to achieve the overall flow of knowledge on the effects of different assessment, but the flow of knowledge, after all, is a dynamic concept, the changes will inevitably affect the overall effect of knowledge flows, this flow of knowledge from the study of the time dimension, using the DEA method based on time (packet network method) for 9 manufacturing industries (food industry, beverage industry, general equipment manufacturing, pharmaceutical manufacturing, electrical machinery and equipment manufacturing, fabricated metal products, transportation equipment manufacturing, communication equipment, computer manufacturing, Educational and Sports Goods) the effect of the dynamic flow of knowledge evaluation.Using《China Statistical Yearbook of Science and Technology》on Manufacturing R & D investment (R & D) intensity, the industry output value of new products/industrial GDP, the industry has a growth rate of the number of patents (2004 to 2009) and expert evaluation of the manufacturing data scoring industry nine industry knowledge flow effect, the results show that the cumulative effect because of the time, knowledge flows in the initial year of poor results, but as time goes on, getting good results flow of knowledge. At the same time that communications equipment, computer manufacturing supply chain flow of knowledge between the best, and metal manufacturing industry, represented by the traditional manufacturing supply chain less effective flow of knowledge between enterprises, need to demand from the degree of knowledge, knowledge, and degree of cooperation and other aspects of relationship quality improved.(4) path-optimization model has been built to optimize knowledge flow path inter-enterprise supply chain about tobacco industry, and one-way path and cycle path have been used to simulate.Inter-enterprise supply chain flow of knowledge is the ultimate goal of the evaluation is less effective flow of knowledge to effectively improve the industry, knowledge flow path from the lowest cost point of view, assessment of the tobacco industry supply chain flow of knowledge between the shortest path problem, namely the use of Dijkstra's algorithm (Dijkstra) and Lingo calculated the shortest one-way flow of knowledge path, using improved ant colony algorithm to simulate the flow of knowledge the shortest cycle path, calculated by comparing the results found that the tightness of the tobacco business manufacturing supply chain, the flow of knowledge between enterprises have an important impact on path selection.This cooperation between enterprises from supply chain perspective to build a supply chain flow of knowledge between the indicators and the indicators of factors affecting the relative weight; The time dimension into static and dynamic evaluation studies to assess the effect of the flow of knowledge; The lowest cost path from the perspective of knowledge flows to optimize the flow path of knowledge, as much as possible the content of the quantitative research study, with a view to the supply chain between enterprises in different sectors of the study provide a reference flow of knowledge, to promote knowledge management to strengthen our business to provide a reference.