欢迎访问林业科学,今天是

林业科学 ›› 2015, Vol. 51 ›› Issue (11): 103-112.doi: 10.11707/j.1001-7488.20151114

• 问题讨论 • 上一篇    下一篇

林业产业集群企业网络结构与创新绩效的关系——基于福建林业产业集群的调查数据

洪燕真1, 戴永务2   

  1. 1. 福建农林大学经济学院 福州 350002;
    2. 福建农林大学管理学院 福州 350002
  • 收稿日期:2014-11-21 修回日期:2015-04-30 出版日期:2015-11-25 发布日期:2015-12-08
  • 通讯作者: 戴永务
  • 基金资助:
    国家自然科学基金项目"补贴政策对农户林业生产行为调整和生产效率的影响研究"(71403053); 福建省自然科学基金项目"基于农户视角的福建省木本粮油产业发展潜力研究"(2013J05107); 福建省财政厅项目"木材加工业产业集群企业国际竞争力研究"(K81150012)。

Research on Relationship between Network Structure and Innovation Performance of Forestry Industry Cluster--Based on Data of Fujian Forestry Industry Cluster

Hong Yanzhen1, Dai Yongwu2   

  1. 1. College of Economics, Fujian Agriculture and Forestry University Fuzhou 350002;
    2. College of Management, Fujian Agriculture and Forestry University Fuzhou 350002
  • Received:2014-11-21 Revised:2015-04-30 Online:2015-11-25 Published:2015-12-08

摘要: [目的]以福建省主要林业产业集群82家林业企业为研究对象,梳理集群网络结构产生创新绩效的作用机制,并定量识别引起企业创新绩效差异的关键因素,为针对性地制定林业产业集群创新政策、实现林业产业转型升级提供参考。[方法]首先,基于企业社会资本理论,结合林业产业集群特点构建林业产业集群企业创新网络结构框架,分析网络结构、网络关系对企业创新绩效的作用机制,并运用国内外学者广泛采用的社会网络分析研究范式从网络结构和网络关系维度刻画林业产业集群企业创新活动的特征,提出研究假设;其次,使用Likert 5点量表法设计测量量表,确定因变量为创新绩效,自变量为网络规模、网络密度、网络开放度、网络居间性、网络资源丰富度等网络结构特征变量和网络关系强度、网络关系互惠性、网络关系稳定性、网络反馈机制等网络关系特征变量,并对测量量表进行信度和效度检验;然后,基于访谈问卷调查法收集的82家样本林业企业数据,利用SPSS16.0软件对回归模型进行OLS拟合;最后利用R软件进行偏最小二乘回归建模,得出影响林业产业集群企业创新绩效差异的关键因素。[结果] 1)从林业产业集群创新网络结构看,网络居间性(1%显著水平)和网络资源丰富度(1%显著水平)对企业创新绩效有显著的正向影响; 2)从网络关系看,网络反馈机制(5%显著水平)对企业创新绩效有显著的正向影响,网络关系互惠性(5%显著水平)对企业创新绩效有显著的负向影响。[结论]随着林业产业转型升级步伐的加快,林业企业创新越来越依赖于创新网络环境,优势的集群创新网络结构是林业产业集群企业开展创新活动不可或缺的重要条件,尤其是企业在集群网络中所处的居间位置和集群内丰富的知识、信息、人才等创新资源,增强了集群内林业企业支配创新资源的能力;此外,良好的集群创新网络关系是企业创新成功演化的助推剂,网络关系互惠性对企业创新绩效有显著负向影响的结论虽与其他产业的研究结果不符,但与福建林业产业集群发展阶段及林业产业链特点具有一定的契合性。本文分别从企业和政府层面提出提升林业产业集群企业创新绩效的建议。

关键词: 林业产业集群, 网络结构, 创新绩效, 偏最小二乘法

Abstract: [Objective]Organization and market of forestry industry cluster has essentially ecological and social of groups, but the spillover effects of "industrial air" on each forestry enterprise which produce innovation performance are different. In this study, 82 forestry enterprises in forestry industry cluster of Fujian Province were taken as research objects, to hackle the mechanism of how cluster network structure generates innovation performance and quantitatively distinguish key factors that cause the differences of enterprise innovation performance. The conclusions are to provide references for formulating innovation policies of forestry industry cluster and achieving the transformation and upgrading of forestry industry.[Method]Firstly, based on the theory of corporate social capital and the characteristics of the forestry industrial cluster, the innovation network structure for enterprises of forestry industry cluster was constructed. The influence mechanism of network structure and network relationship on the enterprise innovation performance was analyzed. Then the social network analysis research paradigm which was widely used by domestic and foreign scholars was adopted to depict the characteristics of innovation activities for enterprises of forestry industry cluster from the network structure and the network relationship, and the research hypothesis was also put forwards. Secondly, using Likert five point table method to design measurement table, the dependent variable (i.e. innovation performance) and the independent variables, including the network structure characteristic variables (i.e. network scale, network density, network openness, network intermediary, network resources richness) and the network relationship characteristic variables (i.e. network relationship stringency, network relationship reciprocity, network relationship stability, network feedback mechanism) were determined. At the same time, the reliability and validity of the measurement table was also test. Then, based on the data of 82 forestry enterprises collected by questionnaire survey method, and analyzed by SPSS16.0 software to take OLS fitting for the regression model, the results showed that regression model present multicollinearity problems, so it was necessary to amend the OLS regression model. Finally, using R software to apply partial least squares regression and construct the model, the key factors which impact on innovation performance differences among enterprises of forestry industry cluster were obtained.[Result]The results showed that:1) From the perspective of innovation network structure of forestry industry cluster, network intermediary (1% significant level) and network resources richness (1% significant level) had significantly positive influences on the enterprise innovation performance. 2) From the perspective of network relationships, network feedback mechanism (5% significance level) also had a significantly positive effects on the enterprise innovation performance, while network reciprocity (5% significance level) had significantly negative effects on the enterprise innovation performance.[Conclusion]With the acceleration of transformation and promotion of forestry industry, forestry enterprise innovation has been increasingly depended on the network environment, the superior network structure of forestry industry cluster innovation would be an indispensable condition for enterprises to carry out innovation activities, especially the intermediate position of enterprises in the cluster network and the rich innovation resources in cluster, including knowledge, information and talent, etc., which will enhance the ability of forestry enterprises in cluster to dominate innovation resources. In addition, good relationship among cluster innovation network is a fine booster for successful innovation evolution. Although the conclusion in this study that network reciprocity has a significantly negative influence on the enterprise innovation performance do not consistent with other industries' results, however, it in a certain extent fit with the development stage of Fujian forestry industry cluster and the characteristics of forestry industry chain. This paper finally gives some advice on how to improve the innovation performance of forestry industry cluster by the enterprise and government aspects, respectively.

Key words: forestry industrial cluster, network structure, innovation performance, partial least-squares

中图分类号: