Knowledge production in competitive regions: an approach based on a latent variable modeling

Authors

  • Henry Caicedo-Asprilla Profesor asociado, Departamento de Administración y Organizaciones, Universidad del Valle, Cali, Colombia. https://orcid.org/0000-0003-1839-7061

DOI:

https://doi.org/10.18046/j.estger.2020.155.3257

Keywords:

function of knowledge production, innovation, structural equation modeling, partial least squares

Abstract

This article proposes a function of knowledge production based on the measurement of non-observable variables, that provides a practical solution to methodological problems in this field of study. In this sense, a function of knowledge production is defined depending on human capital, research and development expenditure, spillovers, and the innovative environment. The function is estimated with the partial least squares path modeling technique, which allows measuring the effect of non-observable variables. It was possible to show that these constructs (latent variables) are reliable and significant; furthermore, it is concluded that this function correctly describes how knowledge is created and exploited in a region.

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References

Anselin, L., Varga, A. y Acs, Z. (1997). Local Geographic Spillovers between University Research and High Technology Innovations. Journal of Urban Economics, 42(3), 422-448.

Antonelli, C. y Colombelli, A. (2015). External and internal knowledge in the knowledge generation function: Industry and innovation. Industry and Innovation, 22(4), 273-198. http://dx.doi.org/10.1006/juec.1997.2032

Arancegui, M. N., Martíns, J. J. G., Franco-Rodríguez, S. y Alonso, A. M. (2011). Territorial benchmarking methodology: The need to identify reference regions. Louvain-la-Neuve: European Regional Science Association.

Asheim, B., Boschma, R. y Cooke, P. (2011). Constructing regional advantage: platform policies based on related variety and differentiated knowledge bases. Regional Studies, 45(7), 893-904. http://dx.doi.org/10.1080/00343404.2010.543126

Audretsch, D. B., Lehmann, E. E., Menter, M. y Seitz, N. (2019). Public cluster policy and firm performance: Evaluating spillover effects across industries. Entrepreneurship & Regional Development, 31(1-2), 150-165. http://dx.doi.org/10.1080/08985626.2018.1537153

Autant-Bernard, C. y LeSage, J. P. (2019). A heterogeneous coefficient approach to the knowledge production function. Spatial Economic Analysis, 14(2), 196-218. https://doi.org/10.1080/17421772.2019.1562201

Aydalot, P. (1986). Milieux innovateurs en Europe. París: GREMI.

Balland, P. A., Boschma, R. y Frenken, K. (2015). Proximity and innovation: From statics to dynamics. Regional Studies, 49(6), 907-920. https://doi.org/10.1080/00343404.2014.883598

Bathelt, H. y Glückler, J. (2005). Resources in economic geography: From substantive concepts towards a relational perspective. Environment and Planning A, 37(9), 1545-1563. http://dx.doi.org/10.1068/a37109

Bramanti, A. (1999). From space to territory: Relational development and territorial competitiveness. Revue d’Economie Régionale et Urbaine, 3, 633-654.

Buesa, M., Heijs, J. y Baumert, T. (2010). The determinants of regional innovation in Europe: A combined factorial and regression knowledge production function approach. Research Policy, 39(6), 722-735. http://dx.doi.org/10.1016/j.respol.2010.02.016

Caicedo-Asprilla, H. (2018). El análisis de las diferencias en el proceso de transferencia de tecnología entre regiones. Cuadernos de Administración, 31(56), 163-194. https://doi.org/10.11144/Javeriana.cao.31-56.adpt

Capello, R. y Lenzi, C. (2013). Territorial patterns of innovation and economic growth in e uropean regions. Growth and Change, 44(2), 195-227. https://doi.org/10.1111/grow.12009

Carayannis, E. G., Grigoroudis, E., Campbell, D. F., Meissner, D. y Stamati, D. (2018). The ecosystem as helix: An exploratory theory-building study of regional co-opetitive entrepreneurial ecosystems as Quadruple/Quintuple Helix Innovation Models. R&D Management, 48(1), 148-162. http://dx.doi.org/10.1111/radm.12300

Cohen, W. M. y Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152. http://dx.doi.org/10.1016/B978-0-7506-7223-8.50005-8

Cooke, P., Uranga, M. G. y Etxebarria, G. (1997). Regional innovation systems: institutional and organizational dimensions. Research Policy, 26(4-5), 475-491. http://dx.doi.org/10.1016/S0048-7333(97)00025-5

Cowan, R., David, P. A. y Foray, D. (2000). The explicit economics of knowledge codification and tacitness. Industrial and Corporate Change, 9(2), 211-253. http://dx.doi.org/10.1093/icc/9.2.211

Crescenzi, R. y Rodríguez-Pose, A. (2011). Innovation and regional growth in the European Union. Berlín: Springer Science + Business Media. http://dx.doi.org/10.1007/978-3-642-17761-3

Dall’erba, S., Kang, D. y Fang, F. (2017). On deriving reduced-form spatial econometric models from theory and their ws from observed flows: example based on the regional knowledge production function. En R. Jackson y P. Schaeffer (Eds.), Regional Research Frontiers, vol. 2 (pp. 127-139). Switzerland: Springer International Publishing. http://dx.doi.org/10.1007/978-3-319-50590-9_7

Doloreux, D. y Parto, S. (2004). Regional Innovation Systems: A Critical Synthesis. UNU-INTECH Discussion Paper Series 17.

Fritsch, M. y Slavtchev, V. (2011). Determinants of the efficiency of regional innovation systems. Regional Studies, 45(7), 905-918. http://dx.doi.org/10.1080/00343400802251494

González, M., Alvarado, J. y Martínez, S. (2004). Una recopilación de recursos en ciudades del conocimiento y el desarrollo basado en el conocimiento. Diario de Gestión del Conocimiento, 8(5), 107-127. https://doi.org/10.1108/13673270410558819

Götz, O., Liehr-Gobbers, K. y Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. En V. Esposito, W. Chin, J. Henseler y H. Wang (Eds.), Handbook of Partial Least Squares (pp. 691-711). Springer, Berlin: Heidelberg. http://dx.doi.org/10.1007/978-3-540-32827-8_30

Griliches, Z. (1979). Problemas para evaluar la contribución de la investigación y el desarrollo al crecimiento de la productividad. Bell Journal of Economics, 10(1), 92-116.

Grupp, H. y Mogee, M. E. (2004). Indicators for national science and technology policy: How robust are composite indicators? Research Policy, 33(9), 1373-1384. http://dx.doi.org/10.1016/j.respol.2004.09.007

Henseler, J., Ringle, C. M. y Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. En R. Sinkovics y P. N. Ghauri (Eds.), New challenges to international marketing (pp. 277-319). Bingley, United Kingdom: Emerald. http://dx.doi.org/10.1108/S1474-7979(2009)0000020014

Huggins, R. y Izushi, H. (2008b). World Knowledge Competitiveness Index 2002: Benchmarking the globes high-performing regions. Cardiff (UK): Robert Huggins. Recuperado el 2 de agosto de 2018, de Recuperado el 2 de agosto de 2018, de http://eprints.aston.ac.uk/3311

Jaffe, A. B., Trajtenberg, M. y Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. The Quaterly Journal of Economics, 108(3), 577-598. http://dx.doi.org/10.2307/2118401

Jeannerat, H. y Crevoisier, O. (2016). From ‘territorial innovation models’ to ‘territorial knowledge dynamics’: On the learning value of a new concept in regional studies. Regional Studies, 50(2):185-188. http://dx.doi.org/10.1080/00343404.2015.1105653

Johnson, B., Lorenz, E. y Lundvall, B. Å. (2002). Why all this fuss about codified and tacit knowledge? Industrial and Corporate Change, 11(2), 245-262. http://dx.doi.org/10.1093/icc/11.2.245

Karlsson, C., Johansson, B., Kobayashi, K. y Stough, R. (2014). Knowledge, innovation and space. Stockholm, Sweden: CESIS. Paper N.º 367. http://dx.doi.org/10.1093/icc/11.2.245

Kasmi, F. (2018). Le milieu “éco-innovateur”: écologie industrielle et diversification de l’économie territoriale. Revue Technologie et Innovation, 18(3), 1-17. http://dx.doi.org/10.21494/ISTE.OP.2018.0238

Kerlinger, F. N. y Lee, H. B. (2002). Investigación del comportamiento: métodos de investigación en ciencias sociales (4.ª ed.). México: McGraw-Hill.

Lewin, A. Y. y Massini, S. (2004). Knowledge creation and organizational capabilities of innovating and imitating firms. En H. Tsoukas y N. Mylonopoulos (Eds.), Organizations as knowledge systems (pp. 209-237). London: Palgrave Macmillan. http://dx.doi.org/10.1057/9780230524545_10

Markusen, A. (2003). Conceptos confusos, escasa evidencia, distancia de la política: el caso del rigor y la relevancia de la política en los estudios regionales críticos. Estudios Regionales, 37(6-7), 701-717. https://doi.org/10.1080/00343409950075506

Maskell, P., Bathelt, H. y Malmberg, A. (2006). Construyendo líneas de conocimiento globales: el papel de los clusters temporales. Estudios de Planificación Europeos, 14(8), 997-1013. https://doi.org/10.1080/09654310600852332

Meusburger, P. (2013). Relations between knowledge and economic development: Some methodological considerations. En P. Meusburger, J. Glückler, y M. el Meskioui (Eds.). Knowledge and the Economy. Dordrecht: Springer. http://dx.doi.org/10.1007/978-94-007-6131-5_2

Michie, J., Oughton, C. y Pianta, M. (2002). Innovation and the economy. International Review of Applied Economics, 16(3), 253-264. http://dx.doi.org/10.1080/02692170210136091

Moulaert, F. y Sekia, F. (2003). Territorial innovation models: A critical survey. Re-gional studies, 37(3), 289-302. http://dx.doi.org/10.1080/0034340032000065442

Neves-Sequeira, T. y Cunha-Neves, P. (2020). Stepping on toes in the production of knowledge: A meta-regression analysis. Applied Economics, 52(3), 260-274. https://doi.org/10.1080/00036846.2019.1644447

Nonaka, I. y Takeuchi, H. (1995). La organización creadora de conocimiento. Cómo las compañías japonesas crean la dinámica de la innovación. México: Oxford University Press.

OCDE (2012). Promoting growth in all regions. París: OCDE. http://dx.doi.org/10.1787/9789264174634-en

OCDE (2018). Rethinking Regional Development Policy-making. París: OCDE . http://dx.doi.org/10.1787/9789264293014-en

R Core Development Team. (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Recuperado el 14 de enero de 2019, de Recuperado el 14 de enero de 2019, de https://bit.ly/2jNQhzW

Revuelta, D., Mulero, E. y García, T. (2009). Validación empírica de un modelo de balanced scorecard para la I+D a través de ecuaciones estructurales. España: Ministerio de Ciencia e Innovación.

Rigdon, E. E. (2016). Choosing PLS path modeling as analytical method in European management research: A realist perspective. European Mana-gement Journal, 34(6), 598-605. https://doi.org/10.1016/j.emj.2016.05.006

Rodríguez-Pose, A. (2013). Do institutions matter for regional development? Regional Studies, 47(7), 1034-1047. http://dx.doi.org/10.1016/j.emj.2016.05.006

Rodríguez-Pose, A. y Tselios, V. (2007). Analysis of educational distribution in Europe: Educational attainment and inequality within regions. Economic and Social Research Institute. Papers DYNREG08.

Romer, P. (1990). Endogenous technological change. Journal of Political Economy, 98(5), part 2, S71-S102.

Saltelli, A., Tarantola, S., Campolongo, F. y Ratto, M. (2004). Sensitivity analysis in practice: A guide to assessing scientific models. John Wiley & Sons, Ltd. https://doi.org/10.1002/0470870958

Sanchez, G., Trinchera, L. y Russolillo, G. (2013). plspm: Tools for Partial Least Squares Path Modeling (PLS-PM). R package version 0.4.1. Recuperado el 14 de marzo de 2019, de: Recuperado el 14 de marzo de 2019, de: http://cran.r-project.org/package=plspm

Scuotto, V., Del Giudice, M., Bresciani, S. y Meissner, D. (2017). Knowledge-driven preferences in informal inbound open innovation modes: An explorative view on small to medium enterprises. Journal of Knowledge Management, 21(3), 640-655. http://dx.doi.org/10.1108/JKM-10-2016-0465

Sotarauta, M. (2015). Leadership and the city power: Strategy and networks in the making of knowledge cities. London: Routledge. http://dx.doi.org/10.4324/9781315753256

Storper, M., y Venables, A. J. (2004). Buzz: Face-to-face contact and the urban economy. Journal of Economic Geography, 4(4), 351-370. http://dx.doi.org/10.1093/jnlecg/lbh027

Strambach, S. y Klement, B. (2011). Cumulative and combinatorial micro-dynamics of knowledge: The role of space and place in knowledge integration. European Planning Studies, 20(11), 1843-1866. http://dx.doi.org/10.1080/09654313.2012.723424

Strauf, S. y Scherer, R. (2008). Universities and their contribution to regional development: Transformations. Business & Economics, 7(1), 137-151. https://www.researchgate.net/publication/281407412_Universities_

Thierstein, A., Lüthi, S., Kruse, C., Gabi, S. y Glanzmann, L. (2008). The changing value chain of the swiss knowledge economy: Spatial impact of intra-firm and inter-firm networks within the emerging mega-city region of Northern Switzerland. Regional Studies, 42(8), 1113-1131. http://dx.doi.org/10.1080/00343400802154557

Tödtling, F. y Trippl, M. (2005). One size fits all?: Towards a differentiated regional innovation policy approach. Research Policy, 34(8), 1203-1219. https://doi.org/10.1016/j.respol.2005.01.018

Tubadji, A. y Pelzel, F. (2015). Culture based development: Measuring an invisible resource using the PLS-PM method. International Journal of Social Economics, 42(12), 1050-1070. http://dx.doi.org/10.1108/IJSE-01-2014-0005

Uyarra, E. y Flanagan, K. (2010). Understanding the Innovation Impacts of Public Procurement. European Planning Studies, 18(1), 123-143. http://dx.doi.org/10.1080/09654310903343567

Varga, A. y Horváth, M. (2014). Regional knowledge production function analysis. En C. Karlsson, M. Andersson y T. Norman (Eds.), Handbook of research methods and applications in economic geography (pp. 511-543). Cheltenham: Edward Elgar. http://dx.doi.org/10.4337/9780857932679.00033

Wold, H. (1975). Modelling in complex situations with soft information. Third World Congress of Econometric Society (pp. 21-26). Göteborg, Sweden: University, Institute of Statistics.

Published

2020-04-07

How to Cite

Knowledge production in competitive regions: an approach based on a latent variable modeling. (2020). Estudios Gerenciales, 36(155), 177-192. https://doi.org/10.18046/j.estger.2020.155.3257