Priorización de Carteras de Proyectos de I+D a través del Data Envelopment Analysis

  1. Francisca Cabrera Monroy 1
  2. Teresa García Valderrama 1
  3. Jaime Sánchez Ortiz 1
  1. 1 Universidad de Cádiz, Departamento de Economía Financiera y Contabilidad
Revista:
Revista española de financiación y contabilidad

ISSN: 0210-2412

Año de publicación: 2017

Volumen: 46

Número: 3

Páginas: 369-407

Tipo: Artículo

DOI: 10.1080/02102412.2017.1321903 DIALNET GOOGLE SCHOLAR

Otras publicaciones en: Revista española de financiación y contabilidad

Resumen

El objetivo de este trabajo es el análisis de la literatura sobre la utilización del Data Envelopment Analysis (DEA) en la priorización de carteras de proyectos en su fase inicial. Este modelo ayuda a los decisores a elegir entre proyectos con resultados previsiblemente mejores, dado unos recursos disponibles y escasos, La ordenación que realiza el modelo en términnos de eficiencia permite financiar adecuadamente los proyectos más rentables. La metodología empleada es la revisión de trabajos específicos en las bases de datos electrónicas ProQuest, ScienceDirect, Scopus y Google Scholar. La muestra contiene 31 trabajos que evalúan proyectos de I + D con un modelo DEA y describen las características del estudio de caso. El estudio estadístico descriptivo de los datos recopilados permite estudiar el comportamiento del año de publicación, revistas, métodos, modelos DEA aplicados y software. Los resultados indican que el modelo más adecuado para la obtención de un ranking de los proyectos de I + D es un DEA Supereficiente CCR orientado a los inputs y, además, que las variables inputs más representativas son coste, personas, horas y dificultad técnica y, por la parte de los outputs, contribución económica directa, contribución tecnológica, contribución económica indirecta y contribución científica.

Referencias bibliográficas

  • Allen, R., Athanassopoulos, A., Dyson, R. G., & Thanassoulis, E., (1997). Weights restrictions and value judgements in data envelopment analysis:Evolution, development and future directions. Annals of Operations Research, 73, 13–34. doi:10.1023/A:1018968909638
  • Andersen, P. Y., & Petersen, N. C., (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1294. doi:10.1287/mnsc.39.10.1261
  • Asosheh, A., Nalchigar, S., & Jamporazmey, M., (2010). Information technology project evaluation:An integrated data envelopment analysis and balanced scorecard approach. Expert Systems with Applications, 37, 5933–5938. doi:10.1016/j.eswa.2010.02.012
  • Banker, R., Charnes, A., Cooper, W. W., & Thomas, D. A., (1989). An introduction to data envelopment analysis with some of its models and their uses. Research in Governmental and Nonprofit Accounting, 5, 125–163. cOOI.
  • Banker, R.D, Charnes, A, & Coopers, W.W., (1984). Measuring de technical efficiency of production. Journal Economic Theory, 19, 150-164.
  • Boussofiane, A., Dyson, R. G., & Thanassoulis, E., (1991). Applied data envelopment analysis. European Journal of Operational Research, 52(1), 1–15. doi:10.1016/0377-2217(91)90331-O
  • Braglia, M. Y., & Petroni, A., (1999). Evaluating and selecting investments in industrial robots. International Journal Production Research, 37(8), 4157–4178. doi:10.1080/002075499189718
  • Cao, Q., & Hoffman, J. J., (2011). A case study approach for developing a project performance evaluation system. International Journal of Project Management, 29, 155–164. doi:10.1016/j.ijproman.2010.02.010
  • Charnes, A., Cooper, W. W., Lewin, A., & Seiford, L. M., (1994). Data envelopment analysis:Theory, methodology and application. Boston:Kluwer Academic Publishers.
  • Charnes, A., Cooper, W. W., & Rhodes, E., (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444. doi:10.1016/0377-2217(78)90138-8
  • Charnes, A., Cooper, W. W., & Rhodes, E., (1979). Short communication:Measuring the efficiency of decision-making units. European Journal of Operational Research, 3, 339. doi:10.1016/0377-2217(79)90229-7
  • Charnes, A., Cooper, W. W., & Rhodes, E., (1981). Evaluating program and managerial efficiency:An application of data envelopment analysis to program follows through. Management Science, 27(6), 668–697. doi:10.1287/mnsc.27.6.668
  • Conka, T., & Ercan, S., (2005, junio). The combined decision model for selecting and prioritizing research and development projects. In RAST 2005 - proceedings of 2nd international conference on recent advances in space technologies. En IEEE Transactions on Engineering Management (pp. 823–828).
  • Conka, T., Vayvay, O., & Sennaroglu, B., (2008). A combined decision model for R and D Project portfolio selection. International Journal of Business Innovation and Research, 2, 190–202. doi:10.1504/IJBIR.2008.016652
  • Cook, W. D., & Rodney, H. G., (2000). Project prioritization:A resource-constrained data envelopment analysis approach. Socio-Economic Planning Sciences, 24, 85–99. doi:10.1016/S0038-0121(99)00020-8
  • Cooper, W. W., Seiford, L. M., & Tone, K., (2006). Introduction to data envelopment analysis and its uses with DEA-Solver software and references. New York, NY:Springer.
  • Dyson, R. G., Allen, R., Camanho, A. S., Podinovski, V. V., Sarrico, C. S., & Shale, E. A., (2001). Pitfalls and protocols in DEA. European Journal of Operational Research, 132, 245–259. doi:10.1016/S0377-2217(00)00149-1
  • Eilat, H., Golany, B., & Shtub, A., (2006). Constructing and evaluating balanced portfolios of R&D projects with interactions:A DEA based methodology. European Journal of Operational Research, 172, 1018–1039. doi:10.1016/j.ejor.2004.12.001
  • Eilat, H., Golany, B., & Shtub, A., (2008). R&D project evaluation:An integrated DEA and balanced scorecard approach. Omega, 36, 895–912. doi:10.1016/j.omega.2006.05.002
  • Emrouznejad, A., Parker, B. R., & 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. doi:10.1016/j.seps.2007.07.002
  • Farrell, M. J., (1957). The measurement of productivity efficiency. Journal of the Royal Statistical Society, A 120, 253–290. doi:10.2307/2343100
  • Farris, J. A., Groesbeck, R. L., Van Aken, E. M., & Letens, G., (2006). Evaluating the relative performance of engineering design projects:A case study using Data Envelopment Analysis. IEEE Transactions on Engineering Management, 53(3), 471–482. doi:10.1109/TEM.2006.878100
  • Ghapanchi, A. H., Tavana, M., Khakbaz, M. H., & Low, G., (2012). A methodology for selecting portfolios of projects with interactions and under uncertainty. International Journal of Project Management, 30, 791–803. doi:10.1016/j.ijproman.2012.01.012
  • Glaser, B. G., & Straus, A. L., (1967). The discovery of Grounded Theory:Strategies for quantitative research. New York:Aldine.
  • Golany, B., & Roll, Y., (1989). An application procedure for DEA. Omega, 17(3), 237–250. doi:10.1016/0305-0483(89)90029-7
  • Green, R. H., Doyle, J. R., & Cook, W. D., (1996). Preference voting and project ranking using DEA and cross-evaluation. European Journal of Operational Research, 90(3), 461–472. doi:10.1016/0377-2217(95)00039-9
  • Hatami-Marbini, A., Emrouznejad, A., & Tavana, M., (2011). A taxonomy and review of the fuzzy data envelopment analysis literature:Two decades in the making. European Journal of Operational Research, 214(3), 457–472. doi:10.1016/j.ejor.2011.02.001
  • Hung, L.-C., Chiang, T.-A., Che, Z. H., & Wang, H. S., (2009). Using DEA approach to develop the evaluation and priority ranking methodology for NPD projects. In Global Perspective for Competitive Enterprise, Economy and Ecology - Proceedings of the 16th ISPE International Conference on Concurrent Engineering (pp. 159–166) IEEE. Technology Management Council.
  • Jayanthi, S., Witt, E. C., & Singh, V., (2009). Evaluation of potential of innovations:A DEA-based application to U.S. photovoltaic industry. IEEE Transactions on Engineering Management, 563, 478–493. doi:10.1109/TEM.2009.2013833
  • Jenkins, L., & Anderson, M., (2003). A multivariate statistical approach to reducing the number of variables in data envelopment analysis. European Journal of Operational Research, 147, 51–61. doi:10.1016/S0377-2217(02)00243-6
  • Kumar, U. D., Saranga, H., Ramírez-Márquez, J. E., & Nowicki, D., (2007). Six sigma project selection using data envelopment analysis. The TQM Magazine, 19(5), 419–441. doi:10.1108/09544780710817856
  • Lertworasirikul, S., Fang, S. C., Joines, J., & Nuttle, H., (2003). Fuzzy data envelopment analysis (DEA):A possibility approach. Fuzzy Sets and Systems, 139, 379–394. doi:10.1016/S0165-0114(02)00484-0
  • Linton, J. D., Morabito, J., & Yeomans, J. S., (2007). An extension to a DEA support system used for assessing R&D projects. R&D Management, 37(1), 29–36. doi:10.1111/j.1467-9310.2007.00456.x
  • Linton, J. D., Walsh, S. T., & Morabito, J., (2002). Analysis, ranking and selection of R&D projects in a portfolio. R&D Management, 32(2), 139–148. doi:10.1111/1467-9310.00246
  • Murias, M. P., (2004). Metodología de aplicación del análisis envolvente de datos:Evaluación de la eficiencia técnica de la Universidad de Santiago de Compostela (Ph. D. dissertation). Santiago de Compostela University.
  • Nunamaker, T. R., (1985, March). Using data envelopment analysis to measure the efficiency of non-profit organizations:A critical evaluation. Managerial and Decision Economics, 6, 1. doi:10.1002/mde.4090060109
  • OCDE. (2002). Manual de Frascati 2002. In Medición de las Actividades Científicas y Tecnológicas. Propuesta de norma práctica para encuestas de investigación y desarrollo experimental. Organización para la Cooperación y Desarrollo Económicos (OCDE). Ed. Fundación Española Ciencia y Tecnología (FECYT), Paris.
  • Oral, M., Kettani, O., & Lang, P., (1991). A methodology for collective evaluation and selection of industrial R&D projects. Management Science, 37(7), 871–885. doi:10.1287/mnsc.37.7.871
  • Quindos, M., Rubiera, F., & Vicente, M., (2003). Análisis de la eficiencia en el sector de los servicios avanzados a las empresas:una aplicación para el caso del principado de Asturias. Departamento De Economía Aplicada, Universidad de Oviedo. Obtenido October27, 2015, dehttp://www.uv.es/asepuma/XI/21.pdf
  • Saaty, T. L., (1980). The analytic hierarchy process:Planning, priority, setting resource allocation. New York:McGraw-Hill.
  • Sánchez, M. A., Gastaud Maçada, A. C., & Del Valle Sagardoy, M., (2014). A strategy-based method of assessing information technology investments. International Journal of Managing Projects in Business, 7(1), 43–60. doi:10.1108/IJMPB-12-2012-0073
  • Sánchez, M. A., & Toscana, L. I. D. I. A. S., (2012). Information technology project Portfolio and strategy alignment assessment based on data envelopment analysis. Revista de Gestão e Projetos, 3(2), 116-n/a. doi:10.5585/gep.v3i2.66
  • Sarabia Sánchez, F. J., (1999). Metodología para la investigación en marketing y dirección de empresas. Madrid:Ediciones Pirámide.
  • Scheel, H., (2001). Undesirable outputs in efficiency valuations. European Journal of Operational Research, 132(2), 400–410. doi:10.1016/S0377-2217(00)00160-0
  • Sowlati, T., (2005). Information systems project prioritizing using data envelopment analysis. Mathematical and Computer Modelling, 41, 1279–1298. doi:10.1016/j.mcm.2004.08.010
  • Tavana, M., Khalili- Damghani, K., & Sadi-Nezhad, S., (2013). A fuzzy group data envelopment analysis model for high-technology project selection:A case study an NASA. Computers & Industrial Engineering, 66, 10–23. doi:10.1016/j.cie.2013.06.002
  • Thore, S., & Lapao, L., (2002). Prioritizing R&D projects in the face of technological and market uncertainty:Combining scenario analysis and DEA. In S. A., Thore (Ed.), A research paper, chapter 3:“DEA and related analytical methods for evaluating the use and implementation of technical innovation (pp. 87–104). Boston:Kluwer Academic Publishers.
  • Thore, S., & Rich, G., (2002). Prioritizing a portfolio of R&D activities, employing data envelopment analysis. In S. A., Thore (Ed.), A research paper, chapter 2:“Technology Commercialization:DEA and related analytical methods for evaluating the use and implementation of technical innovation. Boston:Kluwer Academic Publishers.
  • Thore, S. A. O., (2002). Technology Commercialization:DEA and related analytical methods for evaluating the use and implementation of technical innovation. Edited by Sten A. Thore. Boston:Kluwer Academic Publishers.
  • Tohumcu, Z., & Karasakal, E., (2009). R&D Project performance evaluation with multiple and interdependent criteria. IEEE Transactions On Engineering Management, 78(99), 1–14.
  • Tohumcu, Z., & Karasakal, E., (2010). R&D project performance evaluation with multiple and interdependent criteria. IEEE Transactions on Engineering Management, 57(4), 620–633. doi:10.1109/TEM.2009.2036159
  • Vandaele, N., & Decouttere, C., (2013). Sustainable R&D portfolio assessment. Decision Support Systems, 54, 1521–1532. doi:10.1016/j.dss.2012.05.054
  • Verma, D., & Sinha, K. L., (2002). Toward a theory of project interdependencies in high tech R&D environments. Journal of Operational Management, 20(1), 451–468. doi:10.1016/S0272-6963(02)00024-4
  • Vitner, G., Rozenes, S., & Spraggett, S., (2006). Using data envelope analysis to compare analysis project efficiency in a multi-project environment. International Journal of Project Management, 24, 323–329. doi:10.1016/j.ijproman.2005.09.004
  • Wang, Y. M., (2013). Approaches to determining the relative importance weights for cross-efficiency aggregation in data envelopment analysis. The Journal of the Operational Research Society, 64(1), 60–69. doi:10.1057/jors.2012.43
  • Wilson, P. W., (1995). Detecting outlier in deterministic nonparametric frontier models with multiple outputs. Journal of Business & Economic Statistics, 11(3), 319–323.
  • Wu, J., Liang, L., Yang, F., & Yan, H., (2009). Bargaining game model in the evaluation of decision making units. Expert Systems with Applications, 36, 4357–4362. doi:10.1016/j.eswa.2008.05.001
  • Xu, Y., & Yeh, C. H., (2014). A performance-based approach to project assignment and performance evaluation. International Journal of Project Management, 32, 218–228. doi:10.1016/j.ijproman.2013.04.006
  • Yuan, B., & Huang, J. N., (2002). Applying data envelopment analysis to evaluate the efficiency of R&D projects- A case study of R&D in energy technology, technology commercialization. (Chapter 4, Ed., pp. 111–134). Boston:Kluwer Academy Publishers.
  • Yüksel, H., (2012). Evaluation of the success of Six Sigma projects by data envelopment analysis. International Journal of Business and Management, 7(13), 75–84. doi:10.5539/ijbm.v7n13p75
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