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Research on Evaluation of Enterprises’ Technology Innovation Performance from the Perspective of Industrial Cluster Networks
Available online at www.sciencedirect.com
Energy Procedia 5 (2011) 1279–1283
IACEED2010
Research on Evaluation of Enterprises’ Technology Innovation Performance from the Perspective of Industrial Cluster Networks Xu Youli, Li Huiwei School of Management, Zhejiang Shuren University,,Hangzhou , China(310015)
Abstract Based on relevant documents and the research of the cluster networks and the research of the content and features of cluster network innovation system, the new performance evaluation system is proposed which is for cluster network technological innovation. The system includes cluster network structural features, cluster network relationship, technical innovation capability and technology innovation results, which is a more comprehensive reflection of the technological innovation of clustering enterprises. It provides a scientifically measure for evaluating of enterprises’ technology innovation performance under industrial cluster networks and guidance for performance management.
© 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of RIUDS Key words: industrial clusters networks˗technology innovation performance;
1. Introducti on With economic g lobalizat ion and competition intensification, technical innovation is becoming more and mo re important. And industry cluster, which has characteristic of close geography and industrial correlation, is an impo rtant enterprise technical innovation platform . knowledge spillovers in industrial cluster enhance the speed of industry technical innovation and competition. It is the reason that clustering enterprises have more co mpetitive advantage than non-clustering enterprises . Practice has proved that clustering enterprises has stronger innovative power and better innovative performance than nonclustering enterprises. Do mestic and international academics studied evaluation of enterprise technical innovation from different aspects and achieved many constructive researches on technical innovation . Also there are a lot of research on industrial cluster innovation evaluation. But evaluation on performance of enterprise technical innovation based on industrial cluster is not. The domestic academics focus more on input-
1876–6102 © 2011 Published by Elsevier Ltd. doi:10.1016/j.egypro.2011.03.223
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Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
output process of technical innovation ability of technical innovation, and influence factor of technical innovation and so on . Therefore, this paper analy ze the influence factor of the enterprise technological innovation from the industrial cluster and establish evaluation system of clustering enterprise technological innovation, it shows theoretical and practical significance. 2. Evaluation system of clustering enterprise technological innovation 2.1 The design of evaluation system There are a lot of studies on evaluation system of technological innovation. These studies are in three ways to evaluate, which is the ability of technology innovation, the investment in technology innovation and technology innovation output. But for clustering enterprises, these factors can not comprehensively reflect performance evaluations of clustering enterprise’s technical innovation. These factors which influence clustering enterprise technological innovation are mult i-level dynamic system. The performance evaluations of clustering enterprise should include three fields at least: 1) cluster network own characteristics and the influence to the enterprise. 2) The innovative capabilities of enterprises . 3) Outcome of enterprises technical innovation, namely the new product, the product sales and profit, etc 2.2 The evaluate Content of clustering enterprises’ technology innovation 1)Industrial cluster Structural features. Location of clustering Enterprises has information value and control superiority. Characteristics of the different clusters decide that enterprises seek knowledge outside. Enterprises with high network centrality are usually knowledge distribution centers. Interactive exchange of innovative enterprises will reduce cost and risk. The nu mber of direct relat ionship of enterprises and heterogeneity of network relat ionship can measure Cluster network scale. And more nu mbers of business entities outside tied with enterprises will help to improve the technological innovative performance. The heterogeneity of the enterprise network relat ions will help to improve the ability to acquire knowledge resources at the same time the enterprise technological innovation is related with the nu mber of clustering enterprises and the specialization degree of industry cluster. Therefore , industry cluster Structural features can be scaled by Network centrality and Network scale of industry cluster. Network centrality. So me enterprises, because of their knowledge base or control of information, are at the center of the knowledge network. Net work centrality includes: the number of external entities related to enterprise, enterprises influence Network scale. The scale of knowledge networks and its heterogeneity determine the scale and heterogeneity of the network of knowledge resources . Scale of network consists of three aspects : Cluster number, Degree of multiplicity, Degree of specialization clustersDŽ 2)Cluster network relation level. Network relat ion affects the path and orientation of knowledge passed between clustering enterprises. Enterprises exchange with other entities within the cluster network ˄ such as Suppliers and customers, university , technology intermediary organizations ˅mo re frequently, more intimately and more trustfully, tacit knowledge and informat ion are easier to exchange based on complex knowledge, It is important to change tacit knowledge and informat ion with cluster network ..So Cluster network relations level can be scaled by strength of relations and quality of relations . Strength of relations. It is easy to form a co mmon technological paradig m in the knowledge transfer process of clustering enterprises. Under the guidance of the technological paradig m, the cluster enterprises can more quickly apply new knowledge to the specific production and practice. Strength of relations has two aspects, The frequency of contacts between organizations is emphasized with the quantity of resources exchanged between organizations
Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
Relationship quality. Trust and common knowledge are important factors in knowledge transfer and knowledge generate between enterprises. As heterogeneity among members o f the network, there are barriers in knowledge transfer across organizations , especially tacit knowledge. In o rder to reduce or overcome this obstacle of the main requirements of knowledge exchange in the same or similar background and reach a similar understanding, perception, enterprises should trust each other. Relationship quality content consists three aspects: Accuracy of the information provided, degree of goal congruence with other entities within the cluster, degree of Mutual trust between companies 3) Capability of technology innovation. Knowledge base show enterprise’s innovativeness and advanced which are the main factors for enterprise technical innovation; besides that, knowledge absorption capacity is necessary to technical innovation. Cluster network provide a lot of information to enterprises, and enterprise absorb, digest new external knowledge, then create useful knowledge for technological innovation ˄Hansen ˈ1999. At the same time enterprise technical innovation ability is close related to input of technical innovation and management capacity. Basic research, applied research, experimental develop ment and other technological activities need capital input. Finally, good organizational skills are necessary, the performance of this capability is the ability to create enthusiasm of innovation, to run and coordinate all sections of technological innovation, wh ich can reduce innovation risks and uncertainties to some extent. So technological innovative capabilities can be scaled by knowledge base, knowledge absorption capacity, input of technical innovation and management capacity. Knowledge base means enterprise existing advanced knowledge, including Nu mber o f Patents, number of advanced technologies . Knowledge absorptive capacity, the stronger the absorption capacity of enterprises is, the more opportunity to absorb rival’s spillover knowledge into enterprise, wh ich imp roves the innovative capability o f enterprise. Knowledge absorptive capacity includes: Knowledge acquisit ion and digestion, Knowledge transformation and exploitation capabilities. Investment rate of technological innovation include: Technical staff to total staff ratio, R & D expenses to total expenditure ratio. The organizat ional capacity in the process of innovation include: Organizat ional coordination capacity, Organizational reconfiguration capacity 4) Technological Innovation results. Technological innovation is a transformation process. It is a vision of transforming new technologies into new products or new technique, while technological innovation is a process of combining technology and market integration. New technologies transform into new products or new technology and to convert final sales or profits. Technological innovation results include Output capacity of technology innovation, process innovation, Sales of innovative products and marg ins of innovative products. T able 1 Evaluation of Enterprises’ T echnology Innovation Performance
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.One class index
T wo class index
T hree class index
Network centrality
the number of external entities is related to enterprise Enterprises influence
industry cluster Structural features.
Cluster number Network scale
Degree of multiplicity Degree of specialization clusters frequency of contacts between organizations
strength of relations
Accuracy of the information provided
industry Cluster relations level Enterprise technical innovation performance
quantity of resources which are exchanged between organizations
quality of relations
Degree of goal congruence with other entities within the cluster Degree of Mutual trust between companies
Appraisal Index System
knowledge base
T echnological innovative capabilities
Knowledge absorption capacity
Number of Patents number of advanced technologies Knowledge acquisition and digestion Knowledge transformation and exploitation capabilities
Investment rate of technological innovation
T echnical staff to total staff ratio
T he organizational capacity in the process of innovation
Organizational coordination capacity
R & D expenses to total expenditure ratio
Organizational reconfiguration capacity Output capacity of technology innovation
T he result of technology innovation
process innovation Sales of innovative product s margins of innovative products
Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
3. Conclusion With rapid develop ment of industrial cluster, the performance evaluation of technological innovation not only depends on the innovation input and output levels, but more on how to access and how to use effective knowledge via cluster. Based on the cluster network’s relevant literatures and research of the content and features of industrial cluster innovation system, the new performance evaluation system is proposed which is for industrial cluster technological innovation. The system includes industrial cluster structural features, cluster network relat ion level, technical innovation capability and technology innovation results, which is a more co mprehensive reflection of the technological innovation of ind ustrial cluster, so that we can understand more about the elements of technological innovation of industrial cluster. Enterprises can analysis exactly their advantages and disadvantages of technological innovation via the system, and make it easier to work out an appropriate innovation strategy.
References [1] Molina-Morales F.X., European industrial districts: influence of geographic concentration on performance of the firm [J]. Journal of International Management, 2001(7):277-294. [2] Baptista R., Do innovations diffuse faster within geographical clusters?[J]. International Journal of Industrial Organization, 2000(18):515-535. [3] Baptista R. Geographical clusters and innovation diffusion [J]. Technological Porecasting and Social Change, 2001, 66(1):31-46. [4] Capello. Spatial transfer of knowledge in High T echnology Milieux: learning versus collective learning process[J].Regional Studies,1999,33(4):353-265.] [5] Hansen, M.T. The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits[J].Administrative Science Quarterly,1999,44(1):82-112. [6] Kogut B. The network as knowledge: generative rules and the emergence of structure [J]. Strategic Managem ent Journal, 2000, 21 (3) : 405 - 425. [7] Renzulli L.A, Aldrich H, Moody J. Family matters: gender, networks, and entrepreneurial outcomes [J]. Social Forces, 2000, 79 (2) : 523 - 546. [8] Zahra, S.A., George, G. Absorptive capacity: A review, reconceptualization and extension [J].Academy of Management Review,2002,27(2):185-203.
1283
Energy Procedia 5 (2011) 1279–1283
IACEED2010
Research on Evaluation of Enterprises’ Technology Innovation Performance from the Perspective of Industrial Cluster Networks Xu Youli, Li Huiwei School of Management, Zhejiang Shuren University,,Hangzhou , China(310015)
Abstract Based on relevant documents and the research of the cluster networks and the research of the content and features of cluster network innovation system, the new performance evaluation system is proposed which is for cluster network technological innovation. The system includes cluster network structural features, cluster network relationship, technical innovation capability and technology innovation results, which is a more comprehensive reflection of the technological innovation of clustering enterprises. It provides a scientifically measure for evaluating of enterprises’ technology innovation performance under industrial cluster networks and guidance for performance management.
© 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of RIUDS Key words: industrial clusters networks˗technology innovation performance;
1. Introducti on With economic g lobalizat ion and competition intensification, technical innovation is becoming more and mo re important. And industry cluster, which has characteristic of close geography and industrial correlation, is an impo rtant enterprise technical innovation platform . knowledge spillovers in industrial cluster enhance the speed of industry technical innovation and competition. It is the reason that clustering enterprises have more co mpetitive advantage than non-clustering enterprises . Practice has proved that clustering enterprises has stronger innovative power and better innovative performance than nonclustering enterprises. Do mestic and international academics studied evaluation of enterprise technical innovation from different aspects and achieved many constructive researches on technical innovation . Also there are a lot of research on industrial cluster innovation evaluation. But evaluation on performance of enterprise technical innovation based on industrial cluster is not. The domestic academics focus more on input-
1876–6102 © 2011 Published by Elsevier Ltd. doi:10.1016/j.egypro.2011.03.223
1280
Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
output process of technical innovation ability of technical innovation, and influence factor of technical innovation and so on . Therefore, this paper analy ze the influence factor of the enterprise technological innovation from the industrial cluster and establish evaluation system of clustering enterprise technological innovation, it shows theoretical and practical significance. 2. Evaluation system of clustering enterprise technological innovation 2.1 The design of evaluation system There are a lot of studies on evaluation system of technological innovation. These studies are in three ways to evaluate, which is the ability of technology innovation, the investment in technology innovation and technology innovation output. But for clustering enterprises, these factors can not comprehensively reflect performance evaluations of clustering enterprise’s technical innovation. These factors which influence clustering enterprise technological innovation are mult i-level dynamic system. The performance evaluations of clustering enterprise should include three fields at least: 1) cluster network own characteristics and the influence to the enterprise. 2) The innovative capabilities of enterprises . 3) Outcome of enterprises technical innovation, namely the new product, the product sales and profit, etc 2.2 The evaluate Content of clustering enterprises’ technology innovation 1)Industrial cluster Structural features. Location of clustering Enterprises has information value and control superiority. Characteristics of the different clusters decide that enterprises seek knowledge outside. Enterprises with high network centrality are usually knowledge distribution centers. Interactive exchange of innovative enterprises will reduce cost and risk. The nu mber of direct relat ionship of enterprises and heterogeneity of network relat ionship can measure Cluster network scale. And more nu mbers of business entities outside tied with enterprises will help to improve the technological innovative performance. The heterogeneity of the enterprise network relat ions will help to improve the ability to acquire knowledge resources at the same time the enterprise technological innovation is related with the nu mber of clustering enterprises and the specialization degree of industry cluster. Therefore , industry cluster Structural features can be scaled by Network centrality and Network scale of industry cluster. Network centrality. So me enterprises, because of their knowledge base or control of information, are at the center of the knowledge network. Net work centrality includes: the number of external entities related to enterprise, enterprises influence Network scale. The scale of knowledge networks and its heterogeneity determine the scale and heterogeneity of the network of knowledge resources . Scale of network consists of three aspects : Cluster number, Degree of multiplicity, Degree of specialization clustersDŽ 2)Cluster network relation level. Network relat ion affects the path and orientation of knowledge passed between clustering enterprises. Enterprises exchange with other entities within the cluster network ˄ such as Suppliers and customers, university , technology intermediary organizations ˅mo re frequently, more intimately and more trustfully, tacit knowledge and informat ion are easier to exchange based on complex knowledge, It is important to change tacit knowledge and informat ion with cluster network ..So Cluster network relations level can be scaled by strength of relations and quality of relations . Strength of relations. It is easy to form a co mmon technological paradig m in the knowledge transfer process of clustering enterprises. Under the guidance of the technological paradig m, the cluster enterprises can more quickly apply new knowledge to the specific production and practice. Strength of relations has two aspects, The frequency of contacts between organizations is emphasized with the quantity of resources exchanged between organizations
Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
Relationship quality. Trust and common knowledge are important factors in knowledge transfer and knowledge generate between enterprises. As heterogeneity among members o f the network, there are barriers in knowledge transfer across organizations , especially tacit knowledge. In o rder to reduce or overcome this obstacle of the main requirements of knowledge exchange in the same or similar background and reach a similar understanding, perception, enterprises should trust each other. Relationship quality content consists three aspects: Accuracy of the information provided, degree of goal congruence with other entities within the cluster, degree of Mutual trust between companies 3) Capability of technology innovation. Knowledge base show enterprise’s innovativeness and advanced which are the main factors for enterprise technical innovation; besides that, knowledge absorption capacity is necessary to technical innovation. Cluster network provide a lot of information to enterprises, and enterprise absorb, digest new external knowledge, then create useful knowledge for technological innovation ˄Hansen ˈ1999. At the same time enterprise technical innovation ability is close related to input of technical innovation and management capacity. Basic research, applied research, experimental develop ment and other technological activities need capital input. Finally, good organizational skills are necessary, the performance of this capability is the ability to create enthusiasm of innovation, to run and coordinate all sections of technological innovation, wh ich can reduce innovation risks and uncertainties to some extent. So technological innovative capabilities can be scaled by knowledge base, knowledge absorption capacity, input of technical innovation and management capacity. Knowledge base means enterprise existing advanced knowledge, including Nu mber o f Patents, number of advanced technologies . Knowledge absorptive capacity, the stronger the absorption capacity of enterprises is, the more opportunity to absorb rival’s spillover knowledge into enterprise, wh ich imp roves the innovative capability o f enterprise. Knowledge absorptive capacity includes: Knowledge acquisit ion and digestion, Knowledge transformation and exploitation capabilities. Investment rate of technological innovation include: Technical staff to total staff ratio, R & D expenses to total expenditure ratio. The organizat ional capacity in the process of innovation include: Organizat ional coordination capacity, Organizational reconfiguration capacity 4) Technological Innovation results. Technological innovation is a transformation process. It is a vision of transforming new technologies into new products or new technique, while technological innovation is a process of combining technology and market integration. New technologies transform into new products or new technology and to convert final sales or profits. Technological innovation results include Output capacity of technology innovation, process innovation, Sales of innovative products and marg ins of innovative products. T able 1 Evaluation of Enterprises’ T echnology Innovation Performance
1281
1282
Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
.One class index
T wo class index
T hree class index
Network centrality
the number of external entities is related to enterprise Enterprises influence
industry cluster Structural features.
Cluster number Network scale
Degree of multiplicity Degree of specialization clusters frequency of contacts between organizations
strength of relations
Accuracy of the information provided
industry Cluster relations level Enterprise technical innovation performance
quantity of resources which are exchanged between organizations
quality of relations
Degree of goal congruence with other entities within the cluster Degree of Mutual trust between companies
Appraisal Index System
knowledge base
T echnological innovative capabilities
Knowledge absorption capacity
Number of Patents number of advanced technologies Knowledge acquisition and digestion Knowledge transformation and exploitation capabilities
Investment rate of technological innovation
T echnical staff to total staff ratio
T he organizational capacity in the process of innovation
Organizational coordination capacity
R & D expenses to total expenditure ratio
Organizational reconfiguration capacity Output capacity of technology innovation
T he result of technology innovation
process innovation Sales of innovative product s margins of innovative products
Xu Youli and Li Huiwei / Energy Procedia 5 (2011) 1279–1283
3. Conclusion With rapid develop ment of industrial cluster, the performance evaluation of technological innovation not only depends on the innovation input and output levels, but more on how to access and how to use effective knowledge via cluster. Based on the cluster network’s relevant literatures and research of the content and features of industrial cluster innovation system, the new performance evaluation system is proposed which is for industrial cluster technological innovation. The system includes industrial cluster structural features, cluster network relat ion level, technical innovation capability and technology innovation results, which is a more co mprehensive reflection of the technological innovation of ind ustrial cluster, so that we can understand more about the elements of technological innovation of industrial cluster. Enterprises can analysis exactly their advantages and disadvantages of technological innovation via the system, and make it easier to work out an appropriate innovation strategy.
References [1] Molina-Morales F.X., European industrial districts: influence of geographic concentration on performance of the firm [J]. Journal of International Management, 2001(7):277-294. [2] Baptista R., Do innovations diffuse faster within geographical clusters?[J]. International Journal of Industrial Organization, 2000(18):515-535. [3] Baptista R. Geographical clusters and innovation diffusion [J]. Technological Porecasting and Social Change, 2001, 66(1):31-46. [4] Capello. Spatial transfer of knowledge in High T echnology Milieux: learning versus collective learning process[J].Regional Studies,1999,33(4):353-265.] [5] Hansen, M.T. The search-transfer problem: the role of weak ties in sharing knowledge across organization subunits[J].Administrative Science Quarterly,1999,44(1):82-112. [6] Kogut B. The network as knowledge: generative rules and the emergence of structure [J]. Strategic Managem ent Journal, 2000, 21 (3) : 405 - 425. [7] Renzulli L.A, Aldrich H, Moody J. Family matters: gender, networks, and entrepreneurial outcomes [J]. Social Forces, 2000, 79 (2) : 523 - 546. [8] Zahra, S.A., George, G. Absorptive capacity: A review, reconceptualization and extension [J].Academy of Management Review,2002,27(2):185-203.
1283