Pertenencia a clústeres y comportamiento competitivo de las empresasun estudio de seis asociaciones-clúster en el País Vasco

  1. M. Isabel González Bravo 1
  2. Santiago M. López 1
  3. Jesús M. Valdaliso 2
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

  2. 2 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Revista:
Orkestra Working Paper Series in Territorial Competitiveness

ISSN: 1989-1288

Año de publicación: 2015

Número: 2

Tipo: Documento de Trabajo

Otras publicaciones en: Orkestra Working Paper Series in Territorial Competitiveness

Resumen

El trabajo examina si la pertenencia a una asociación-clúster produce algún efecto positivo sobre la competitividad y la productividad de las empresas afiliadas. El trabajo emplea un modelo no paramétrico DEA (Data Envelopment Analysis) aplicado a la población de empresas que forman parte de los sectores agrupados en seis asociacionesclúster del País Vasco (AFM, ACE, GAIA, FMV, HEGAN y Clúster del Papel). A partir de los datos de SABI para 2011, el trabajo realiza un doble análisis: inter-empresa, cuyo objetivo es comprobar si las empresas afiliadas a una asociación-clúster consiguen mejores resultados de eficiencia que las no afiliadas; intra-clúster, cuyo objetivo es analizar si la pertenencia a la asociación-clúster impulsa de forma diferente el comportamiento de las empresas dependiendo del grado de identidad sectorial de la empresa con el clúster. El trabajo muestra que las empresas afiliadas a las seis asociaciones-clúster analizadas consiguen resultados y niveles de eficiencia superiores que las no afiliadas. También obtienen una serie de ventajas operativas en la gestión que podrían ser consideradas como activos intangibles que influyen en sus niveles de eficiencia.

Referencias bibliográficas

  • ARAGÓN, C., ARANGUREN, M.J e ITURRIOZ, C. (2010). Evaluación de políticas clúster: El caso del País Vasco, Instituto Vasco de Competitividad, Deusto, Bilbao.
  • Aranguren, M.J., De la Maza, X., Parrilli, M.D., y Wilson, J.R. (2010). Asociaciones Clúster: Competitividad de la CAPV a través de la colaboración, San Sebastián: Orkestra.
  • ARANGUREN, M.J., DE LA MAZA, X, PARRILLI, M.D., VENDRELL-HERRERO, F. y WILSON, J.R. (2014). Nested Methodological Approaches for Cluster Policy Evaluation: An Application to the Basque Country, Regional Studies, 48(9), 1547-1562.
  • ARANGUREN, M.J., y NAVARRO, I. (2003). La política de clusters en la Comunidad Autónoma del País Vasco: una primera valoración, Ekonomiaz, 53: 90-113
  • ARANGUREN, M.J., y WILSON, J.R. (2013). What can experience with clusters teach us about fostering regional smart specialisation?, Ekonomiaz, 83: 126-145.
  • AVKIRAN, N. (1999). An application reference for data envelopment analysis in branch banking: helping the novice researcher, International Journal in Bank Market, 17: 206–220.
  • BAGWELL, S. (2008). Creative clusters and city growth, Creative Industries Journal, 1(1): 31-46.
  • BAHT, R., VERMA, B.B. Y REUBEN, E. (2001). Data Envelopment Análisis (DEA), Journal of Health Management, 3(2): 309-328.
  • BANKER,R. CHARNES, A. Y COOPER, W.W. (1984), Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30: 1078-1092.
  • BANKER, R., CHARNES, A., COOPER, W., SWARTS, J. and THOMAS, D. (1989). An introduction to data envelopment analysis with some of its models and their uses, Research in Governmental and Nonprofit Accounting 5: 125-163.
  • BARNEY J.B. y WRIGHT, P.M. (1997). On becoming a strategic partner: The role of human resources in gaining competitive advantage (CAHRS Working Paper 97-09). Ithaca, NY: Cornell University, School of Industrial and Labor Relations, Center for Advanced Human Resource Studies.
  • BARNEY, J. (1991). Firm Resources and Sustained Competitive Advantage, Journal of Management, 17: 99-120.
  • BELL,S.J., TRACEY, P. y HEIDE, J.B. (2009). The organization of regional clusters, Academy of Management Review, 34(4): 623-642.
  • BENNETT, R. y RAMSDEN, M., (2007). The contribution of Business Associations to SMEs, International Small Business Journal, 25(1): 49-76.
  • BURES, V., JASIKOVA,V., OTCENASKOVA, T., KOLEROVA, K., ZUBR, Va. y MASEROVA, P. (2012). A Comprehensive View on Evaluation of Cluster Initiatives, European Conference on Management, Leadership & Governance. Proceedings of the 8th European Conference on Management Leadership and Governance. Reading: Academic Publishing International Limited, s. 74-79.
  • CHARNES, A., COOPER, W.W. y RHODES, E. (1978). Measuring the efficiency of decision making units, European Journal of Operational Research, 2: 429-441.
  • CHEN, T.Y. (2002). Measuring firm performance with DEA and prior information in Taiwan´s banks, Applied Economics Letters, 9: 201-20.
  • CHERCHYE, L. (2001). Using data envelopment analysis to asses macroeconomic policy performance, Applied Economics, 33: 407-416.
  • CHERCHYE, L., MOESEN, W., ROGGE, N., VAN PUYENBROECK, T., SAISANA, M., SALTELLI, A., LISKA, R. y TARANTOLA, S. (2008). Creating composite indicators with DEA and robustness analysis: te case of the Technology Achievement Index, Journal of the Operational Research Society, 59: 239-252.
  • CHIESA, V. (2001). R&D Strategy and Organization, Managing Technical Change in Dynamic Contexts, Imperial Collage Press, London.
  • COOK, W.D. Y ZHU, J. (2005), Modeling Performance Measurement. Applications and Implementation Issues in DEA, Ed. Springer, Boston.
  • COOPER,W.W., SEIFORD, L.M., y TONE, K., (2006), Introduction to Data Envelopment Analysis and its Uses, Ed. Springer, New York.
  • COOPER, W.W., SEIFORD, L.M. Y ZHU, J. (2004). Handbook on Data Envelopment Analysis, Ed. Kluwer Academic Publishers, Boston.
  • Delgado, M., Porter, M.E., Stern, S. (2010). Clusters and entrepreneurship, Journal of Economic Geography, 10(4): 495-518.
  • Delgado, M., Porter, M.E., Stern, S. (2014). Clusters, convergence, and economic performance, Research Policy, 43: 1785-1799.
  • DE LA MAZA, X., ARANGUREN, M.J. y MURCIEGO A. (2008). Small enterprises involvement within the Basque cluster policy: a new challenge”. 11th European Network on Industrial Policy International Conference, Spain, 10-12 September 2009.
  • DE LA MAZA, X., VENDRELL, F. y WILSON, JR. (2012). Where is the value of cluster associtions for SMEs?, Intangible Capital, 8(2): 477-496.
  • DYCKHOFF, H. y ALLEN, K. (2001). Measuring ecological efficiency with data envelopment analysis, European Journal of Operational Research, 132: 312-325.
  • EMROUZNEJAD A. y THANASSOULIS, E. (1996). "An Extensive Bibliography of Data Envelopment Analysis (DEA) Volume I and II: Working Papers." Working Paper No. 244 and 245.
  • EMROUZNEJAD, A., PARKER, B.R., Y TAVARES, G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA, Socio-Economic Planning Sciences, 42: 151-157.
  • Franco, S., Murciego, A., y Wilson, J.R. (2014). Methodology and Findings Report for Correlation Analysis between Cluster Strength and Competitiveness Indicators, European Cluster Observatory Report.
  • GONZÁLEZ-BRAVO, M.I. (2007). Prior Ratio-Analysis procedure to improve data envelopment analysis for performance measurement, Journal of the Operational Research Society, 58: 1214-1222. GRAY, A. (2002). What clusters can do for your business, NZ business, 16(9): 19-21.
  • HALL,T. y TEAL, G. (2013). Understanding the Changing Nature of Cluster Drivers, International Journal on Business Review, 2(4): 81-93.
  • HOLVAD, T. (2001). An examination of efficiency level variations for bus services, Paper presented at the Seventh International Conference on Competition and Ownership in Land Passenger Transport (THREDBO 7), Molde, Norway, June 2001.
  • HSU, M.S, LAI, Y.L. y LIN, F.J. (2014). The impact of industrial clusters on Human Resource and Firms Performance, Journal of Modelling in Management, 9(2): 141-159.
  • HUANG, C.J. y LIU, C.J., (2005). Exploration for the relationship between innovation, IT and performance, Journal of Intellectual Capital, 6(2): 237-252.
  • JENKINS, L. y ANDERSON, M. (2003). A multivariate statistical approach to reducing the number of variables in data envelopment analysis, European Journal Operational Research, 147: 51–61.
  • KALAFSKY, R., y MACPHERSON, A. (2002). Regional differences in the competitive characteristics of US machine tool companies. Growth and Change 33(3): 269–90.
  • Ketels, C., Nauwelaers, C., Cassingena, J., Lindqvist, G., Lubicka, B., y Peck, F. (2013). The role of clusters in smart specialisation strategies. European CommisssionDirectorate General for Research and Innovation, Bruselas.
  • LEE, J. (2009). Does Size matter in Firm Performance? Evidence from U.S Public Firms, International Journal of the Economics of Business, 16(2): 189-203.
  • LI, J. y GENG, S. (2012). Industrial clusters, shared resources and firm performance, Entrepreneurship & Regional Development: An International Journal, 24(5-6): 357381.
  • López, S., Elola, A., Valdaliso, J. M., y Aranguren, M.J. (2008). Los orígenes históricos del clúster de la electrónica, la informática y las telecomunicaciones del País Vasco y su legado para el presente, ORKESTRA-Eusko Ikaskuntza, San Sebastián.
  • LÓPEZ, S., ELOLA, A., VALDALISO, J.M., y ARANGUREN, M.J. (2012). El cluster de la industria aeronáutica del País Vasco. Orígenes, evolución y trayectoria competitive, Orkestra-Eusko Ikaskuntza, San Sebastián.
  • MARTIN, F.; MAYER, T.; MAYNERIS, F. (2011). Spatial Concentration and FirmLevel Productivity in France. Journal of Urban Economics, 69(2): 182-195.
  • MCDONALD, F., HUANG, Q., TSAGDIS, D. y TÜSELMANN, H. (2007). Is there evidence to support Porter-type cluster policies? Regional Studies 41: 39–49.
  • NARDO, M., SAISANA, M., SALTELLI, A. y S. TARANTOLA, T. (2005). Tools for Compsoite Indicators Building, European Commission Joint Research Center, Ed. European Communities.
  • NAVICKAS, V. y MALAKAUSKAITE, A. (2009). The impact of clusterization on the development of small and medium‐sized enterprise (SME) sector, Journal of Business Economics and Management, 10(3): 255-259.
  • NEWLANDS, D. (2003). Competition and Cooperation in Industrial Clusters: The implications for Pulbics Policy, European planning Studies, 11(5): 521-532.
  • NIRESH, J.A. y VELNAMPY, T. (2014). Firm Size and Profitability: A study of Listed Manufacturing Firms in Sri Lanka, International Journal of Business and Management, 9(4): 57-64.
  • OECD (2008), Handbook on Constructing Composite Indicators: Methodology and User Guide, Ed. OECD.
  • PEDRAJA-CHAPARRO, F., SALINAS-JIMENEZ, J. Y SMITH, P. (1999). On the quality of the data envelopment analysis model, Journal of Operational Research Society, 50: 636-644.
  • PODINOVSKI, V., THANASSOULIS, E. (2007). Improving discrimination in data envelopment analysis: some practical suggestions, Journal of Productivity Analysis, 28: 117-126.
  • PORTER, M. (1998). Clusters and the New Economics of Competition, Harvard Business Review, 76(6): 77-90.
  • PORTER, M. (1999). Ser competitivo, Ed. Deusto, Bilbao.
  • PORTER, M. (2003). The economic performance of regions, Regional Studies, 37(6/7): 549-578.
  • REICHHELD, F. (1996). The Loyalty Effect: The Hidde3n Force Behind Growth, Profits, and Lasting Value, Ed. Harvard Business School Press, Boston.
  • SEIFORD, L. M. (1996). Data Envelopment Analysis: The Evolution of the State of the Art (1978–1995), Journal of Productivity Analysis 7(2/3): 99–138.
  • SERRANO-CINCA, C. y MAR MOLINERO, C. (2004). Selecting DEA specifications and ranking units via PCA, Journal of the Operational Research Society, 55: 521–52.
  • SINUANY-STERN Z y FRIEDMAN L (1998). DEA and the discriminant analysis of ratios to ranking units, European Journal Operational Research, 111: 470–478.
  • SCHMIEDEBERG, C (2010). Evaluation of Cluster Policy: A Methodological Overview, Evaluation, 16(4): 389-412.
  • SPENCER, GM, VINODRAI, T., GERTLER, M.S. y WOLFE, D.A., (2010). Do clusters Make a difeerence? Defining and Assessing their Economic Performance, Regional Studies, 44(6): 697-715.
  • STAAT M. (2001). The effect of sample size on the mean efficiency in DEA: Comment, Journal Productivity Analisys, 15: 129–137.
  • UE (2010). Clusters and clustering policy: a guide for regional and local policy makers.
  • Valdaliso, J. M., Aranguren, M. J., Elola, A., y López, S. (2008). Los orígenes históricos del clúster del papel en el País Vasco y su legado para el presente, ORKESTRA-Eusko Ikaskuntza, San Sebastián.
  • Valdaliso, J. M., Elola, A., Aranguren, M. J., y López, S. (2010). Los orígenes históricos del cluster de la industria marítima en el País Vasco y su legado para el presente, ORKESTRA-Eusko Ikaskuntza, San Sebastián.
  • VALDALISO, J.M., ELOLA, A., LÓPEZ, S., y FRANCO, S. (2014). El clúster de la energía del País Vasco. Orígenes, evolución y trayectoria competitiva, mimeo, San Sebastián.
  • WAKELIN, K. (2001). Productivity growth and R&D expenditure in UK manufacturing firms, Research Policy, 30: 1070-1090.
  • ZHU,J. (2000). Multi-factor performance measure model with an application to Fortune 500 companies, European Journal of Operational Research, 123: 105-124.