Herimalala, Rahobisoa and Gaussens, Olivier (2012): X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis.
Download (403kB) | Preview
This paper investigates X-(in)efficiency of innovation processes in Small and Medium-sized Enterprises (SMEs). We have adopted the following approach: (a) we provide both a concept of X-(in)efficiency and a model of innovation processes for each SME; (b) from this model we evaluate both the dimensions of the innovation processes and the X-(in)efficiency of these processes using a variant of the Data Envelopment Analysis (DEA) model; (c) finally, we characterize X-inefficiency by using techniques of exploratory analysis derived from an empirical analysis. Our approach has been applied to regional SMEs in Normandy (France) with a representative random sample of 80 innovative businesses. The results show the existence of X- inefficiency in the innovation processes of SMEs in 71% of cases. This X-inefficiency arises primarily from the difficulties that entrepreneurs face in implementing the interacting rules and standards of exploitation and exploration activities.
|Item Type:||MPRA Paper|
|Original Title:||X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis|
|English Title:||X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis|
|Keywords:||Data Envelopment Analysis; Multiple Projections; X-Efficiency; Innovation Process|
|Subjects:||D - Microeconomics > D0 - General
C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C43 - Index Numbers and Aggregation
Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q5 - Environmental Economics > Q55 - Technological Innovation
O - Economic Development, Technological Change, and Growth > O3 - Technological Change; Research and Development; Intellectual Property Rights > O32 - Management of Technological Innovation and R&D
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C67 - Input-Output Models
|Depositing User:||Herimalala Herimalala|
|Date Deposited:||28. Nov 2012 13:19|
|Last Modified:||15. Feb 2013 17:10|
Adler, P. S., Benner, M., Brunner, D. J., MacDuffie, J. P., Osono, E., Staats, B. R., Takeuchi, H., Tushman, M. L., and Winter, S. G. (2009). Perspectives on the productivity dilemma. Journal of Operations Management, 27(2):99–113.
Amit, R. and Schoemaker, P. J. (1993). Strategic assets and organizational rent. Strategic Management Journal, 14(1):3346.
Banker, R. D. and Morey, R. (1986). Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34(4):513521.
Brockett, P., Cooper, W., Deng, H., Golden, L., and Ruefli, T. (2004). Using DEA to Identify and Manage Congestion. Journal of Productivity Analysis, 22:207–226.
Chesbrough, H. and Rosenbloom, R. S. (2002). The role of the business model in capturing value from innovation: evidence from Xerox Corporation’s technology spin-off companies. Industrial and Corporate Change, 11(3):529–555.
Chiesa, V., Coughlan, P., and Voss, C. A. (1996). Development of a Technical Innovation Audit. Journal of Product Innovation Management, 13(2):105–136.
Cohen, W. M. (1995). Empirical studies of innovative activity. In Stoneman, P., editor, Hand- book of the Economics of Innovation and Technological Change, volume 182, pages 182–264. Blackwell Publishers Ltd.
Cooper, W., Gu, B., and Li, S. (2001). Comparisons and evaluations of alternative approaches to the treatment of congestion in DEA. European Journal of Operational Research, 132(1):62– 74.
Dodgson, M. and Hinze, S. (2000). Indicators used to measure the innovation process: defects and possible remedies. Research Evaluation, 8(2):101–114.
Fare, R. and Svensson, L. (1980). Congestion of production factors. Econometrica, 48(7):1745–1753.
Forsman, H. (2011). Innovation capacity and innovation development in small enterprises. A comparison between the manufacturing and service sectors. Research Policy, 40(5):739–750.
Gaussens, O. (2009). Innovation Capacity of SMEs: Business Models and Innovation Patterns. University of Caen Basse Normandie, France. Survey Support, French edition.
Geoffrion, A. M. (1968). Proper Efficiency and the Theory of Vector Maximization. Journal of Mathematics, Analysis and Applications, 22(3):618–630.
Gobbo Jr., J. A. and Olsson, A. (2010). The transformation between exploration and exploita- tion applied to inventors of packaging innovations. Technovation, 30(56):322 – 331.
Golany, B. (1988). An interactive molp procedure for the extension of dea to effectiveness analysis. The Journal of the Operational Research Society, 39(8):725–734.
Grupp, H. and Maital, S. (2001). Managing new product development and innovation: A Microeconomic Toolbox. Edward Elgar, first edition.
Guan, J., Yam, R. C., Mok, C. K., and Ma, N. (2006). A study of the relationship between competitiveness and technological innovation capability based on DEA models. European Journal of Operational Research, 170(3):971–986.
Hansen, J. (2001). Technology innovation indicators. In Feldman, M. P. and Link, A. N., editors, Innovation Policy in the Knowledge-Based Economy, pages 73–103. Springer.
Harryson, S. J. (2008). Entrepreneurship through relationships navigating from creativity to commercialisation. R&D Management, 38(3):290–310.
Hatchuel, A., Le Masson, P., and Weil, B. (2002). De la gestion des connaissances aux organi- sations orient´ees conception. Revue internationale des sciences sociales, 1(171):29–42.
Hatchuel, A. and Weil, B. (2009). C-K design theory: an advanced formulation. Research in Engineering Design, 19:181–192.
He, Z.-L. and Wong, P.-K. (2004). Exploration vs. Exploitation: An Empirical Test of the Ambidexterity Hypothesis. Organization Science, 15(4):481–494.
Holmqvist, M. (2004). Experiential Learning Processes of Exploitation and Exploration within and between Organizations: An Empirical Study of Product Development. Organization Science, 15(1):70–81.
Hosseinzadeh Lotfi, F., Noora, A., Jahanshahloo, G., Jablonsky, J., Mozaffari, M., and Gerami, J. (2009). An MOLP based procedure for finding efficient units in DEA models. Central European Journal of Operations Research, 17:1–11.
Izenman, A. J. (2008). Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning. Springer Texts in Statistics. Springer.
Kao, C. (2010). Congestion measurement and elimination under the framework of data envel- opment analysis. International Journal of Production Economics, 123(2):257–265.
Kline, S. J. and Rosenberg, N. (1986). An overview on innovation. In Landau, R. and Rosenberg, N., editors, The Positive Sum Strategy: Harnessing Technology for Economic Growth, pages 275–306. National Academy of Sciences.
Koopmans, T. (1951). Analysis of production as an efficient combination of activities. In Koopmans, T., editor, Activity analysis of production and allocation, pages 33–97. Wiley.
Le Masson, P., Weil, B., and Hatchuel, A. (2010). Strategic Management of Innovation and Design. Cambridge University Press.
Leibenstein, H. (1968). Entrepreneurship and Development. The American Economic Review, 58(2):72–83.
Leibenstein, H. (1969). Organizational or Frictional Equilibria, X-Efficiency, and the Rate of Innovation. The Quarterly Journal of Economics, 83(4):pp. 600–623.
Leibenstein, H. (1979). X-Efficiency: From Concept to Theory. Challenge, 22(4):13–22. Leibenstein, H. and Maital, S. (1992). Empirical Estimation and Partitioning of X-Inefficiency: A Data Envelopment Approach. The American Economic Review, 82(2):428–433.
Lins, M. P. E., Angulo-Meza, L., and Silva, A. C. M. (2004). A Multi-Objective Approach to Determine Alternative Targets in Data Envelopment Analysis. The Journal of the Operational Research Society, 55(10):pp. 1090–1101.
Lorino, P. (2007). Process based management, dialogism and the reflexive inquiry of collecte activity. The case of work safety in the building industry. Technical Report DR-07013, Paris ESSEC Research Center.
March, J. G. (1991). Exploration and Exploitation in Organizational Learning. Organization Science, 2(1):71–87.
Morel, C. (2012). Les d´ecisions absurdes: Tome 2, Comment les ´eviter, volume 2. Editions Gallimard.
Nooteboom, B. (2001). Learning and Innovation in Organizations and Economies. Oxford University Press, third edition.
OECD, editor (2005). OSLO Manual : Guidelines for Collecting and Interpreting Innovation Data. OECD Publishing, third edition.
Pastor, J., Ruiz, J., and Sirvent, I. (1999). An enhanced DEA Russell graph efficiency measure. European Journal of Operational Research, 115(3):596 – 607.
Pfeffer, J. and Sutton, R. (2006). Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-based Management. Harvard Business Press.
Ponssard, J.-P. and Tanguy, H. (1993). Planning in firms as an interactive process. Theory and Decision, 34:139–159.
Rothwell, R. and Dodgson, M. (2004). Innovation and size of firm. In Rothwell, R. and Dodgson, M., editors, The handbook of industrial innovation, pages 310–324. Edward Elgar.
Schon, D. A. (1984). Problems, frames and perspectives on designing. Design Studies, 5(3):132–136.
Simon, H. A. (1969). The Sciences of the Artificial. MIT Press, 3 edition.
Simon, H. A., editor (1986). Decision Making and Problem Solving. National Academy Press. Sueyoshi, T. and Sekitani, K. (2009). DEA congestion and returns to scale under an occurrence of multiple optimal projections. European Journal of Operational Research, 194(2):592 – 607.
Tone, K. and Sahoo, B. K. (2004). Degree of scale economies and congestion: A unified DEA approach. European Journal of Operational Research, 158(3):755–772.
Tushman, M. L. and O’Reilly, C. A. (1997). Winning Through Innovation: A Practical Guide to Leading Organizational Change and Renewal. Harvard Business School Pr.
Tushman, M. L. and O’Reilly, C. L. (1996). Ambidextrous organizations: Managing evolution- ary and revolutionary change. California Management Review, 8(29):8–29.
Zeleny, M. (1974). Linear multiobjective programming. Lecture notes in economics and mathe- matical systems. Springer-Verlag.
Zhu, J. (2000). Multi-factor performance measure model with an application to fortune 500 companies. European Journal of Operational Research, 123(1):105–124.
Available Versions of this Item
X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis. (deposited 14. Oct 2012 09:32)
X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis. (deposited 24. Nov 2012 17:46)
- X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis. (deposited 28. Nov 2012 13:19) [Currently Displayed]
- X-Efficiency of Innovation Processes: Concept and Evaluation based on Data Envelopment Analysis. (deposited 24. Nov 2012 17:46)