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Accounting for intra-industry technological heterogeneity in the measurement of operations efficiency

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  • Tsionas, Mike G.
  • Patel, Pankaj C.

Abstract

In operations management literature, efficiency is usually measured using parallel shifts of production functions. This practice is based on the assumption that operations technologies are similar across decision-making units. Relaxing this assumption is essential as firms endowed with heterogeneous operational technologies develop distinctive operational resources and capabilities that vary systematically within an industry, resulting in non-parallel shifts of production functions. By relaxing the assumption of parallel production functions, we focus on technological differences as a measure of inefficiency in production and use non-parametric local linear estimates. Our approach based on Bayesian methods and stochastic dominance is novel in that it models for non-parallel production curve slopes that account for unknown frontier technology which is not observed but can be estimated using intra-industry variation in individual firm operational technologies. The proposed approach makes an important contribution to operations management research by relaxing a non-trivial assumption of parallel shifts of production functions in efficiency analysis.

Suggested Citation

  • Tsionas, Mike G. & Patel, Pankaj C., 2023. "Accounting for intra-industry technological heterogeneity in the measurement of operations efficiency," International Journal of Production Economics, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:proeco:v:260:y:2023:i:c:s0925527323000671
    DOI: 10.1016/j.ijpe.2023.108835
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    as
    1. Chien-Ming Chen & Magali A. Delmas & Marvin B. Lieberman, 2015. "Production frontier methodologies and efficiency as a performance measure in strategic management research," Strategic Management Journal, Wiley Blackwell, vol. 36(1), pages 19-36, January.
    2. Michel A. Habib & Alexander Ljungqvist, 2005. "Firm Value and Managerial Incentives: A Stochastic Frontier Approach," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2053-2094, November.
    3. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    4. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    5. repec:exe:wpaper:99/14 is not listed on IDEAS
    6. Song, Malin & Zhu, Shuai & Wang, Jianlin & Zhao, Jiajia, 2020. "Share green growth: Regional evaluation of green output performance in China," International Journal of Production Economics, Elsevier, vol. 219(C), pages 152-163.
    7. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    8. Marvin B. Lieberman, 1989. "The learning curve, technology barriers to entry, and competitive survival in the chemical processing industries," Strategic Management Journal, Wiley Blackwell, vol. 10(5), pages 431-447, September.
    9. Chahal, Hardeep & Gupta, Mahesh & Bhan, Namrita & Cheng, T.C.E., 2020. "Operations management research grounded in the resource-based view: A meta-analysis," International Journal of Production Economics, Elsevier, vol. 230(C).
    10. Howard Hao‐Chun Chuang & Rogelio Oliva & Gregory R. Heim, 2019. "Examining the Link between Retailer Inventory Leanness and Operational Efficiency: Moderating Roles of Firm Size and Demand Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 28(9), pages 2338-2364, September.
    11. Claudia Girardone & Philip Molyneux & Edward Gardener, 2004. "Analysing the determinants of bank efficiency: the case of Italian banks," Applied Economics, Taylor & Francis Journals, vol. 36(3), pages 215-227.
    12. Daraio, Cinzia & Kerstens, Kristiaan & Nepomuceno, Thyago & Sickles, Robin C., 2019. "Empirical Surveys of Frontier Applications: A Meta-Review," Working Papers 19-005, Rice University, Department of Economics.
    13. Richard R. Nelson & Sidney G. Winter, 2002. "Evolutionary Theorizing in Economics," Journal of Economic Perspectives, American Economic Association, vol. 16(2), pages 23-46, Spring.
    14. Guo Li & Na Li & Suresh P. Sethi, 2021. "Does CSR Reduce Idiosyncratic Risk? Roles of Operational Efficiency and AI Innovation," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2027-2045, July.
    15. Spanos, Yiannis E. & Voudouris, Irini, 2009. "Antecedents and trajectories of AMT adoption: The case of Greek manufacturing SMEs," Research Policy, Elsevier, vol. 38(1), pages 144-155, February.
    16. Leiponen, Aija & Drejer, Ina, 2007. "What exactly are technological regimes?: Intra-industry heterogeneity in the organization of innovation activities," Research Policy, Elsevier, vol. 36(8), pages 1221-1238, October.
    17. Antonio Arbelo & Marta Arbelo-Pérez & Pilar Pérez-Gómez, 2022. "Are SMEs less efficient? A Bayesian approach to addressing heterogeneity across firms," Small Business Economics, Springer, vol. 58(4), pages 1915-1929, April.
    18. ANITA M. McGAHAN & MICHAEL E. PORTER, 1997. "How Much Does Industry Matter, Really?," Strategic Management Journal, Wiley Blackwell, vol. 18(S1), pages 15-30, July.
    19. Daniel A. Levinthal, 1997. "Adaptation on Rugged Landscapes," Management Science, INFORMS, vol. 43(7), pages 934-950, July.
    20. William C. Horrace & Yulong Wang, 2022. "Nonparametric tests of tail behavior in stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 537-562, April.
    21. Klein, Nadja & Herwartz, Helmut & Kneib, Thomas, 2020. "Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales," Journal of Econometrics, Elsevier, vol. 214(2), pages 513-539.
    22. Gunasekaran, Angappa & Ngai, Eric W.T., 2012. "The future of operations management: An outlook and analysis," International Journal of Production Economics, Elsevier, vol. 135(2), pages 687-701.
    23. David J. Ketchen & Lutz Kaufmann & Craig R. Carter, 2022. "Configurational approaches to theory development in supply chain management: Leveraging underexplored opportunities," Journal of Supply Chain Management, Institute for Supply Management, vol. 58(3), pages 71-88, July.
    24. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    25. Richard P. Rumelt, 1991. "How much does industry matter?," Strategic Management Journal, Wiley Blackwell, vol. 12(3), pages 167-185, March.
    26. Hahn, G.J. & Brandenburg, M. & Becker, J., 2021. "Valuing supply chain performance within and across manufacturing industries: A DEA-based approach," International Journal of Production Economics, Elsevier, vol. 240(C).
    27. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
    28. Ron Boschma & Ron Martin (ed.), 2010. "The Handbook of Evolutionary Economic Geography," Books, Edward Elgar Publishing, number 12864.
    29. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    30. Murray D. Smith, 2008. "Stochastic frontier models with dependent error components," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 172-192, March.
    31. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    32. Juan Martín & Concepción Román & Augusto Voltes-Dorta, 2009. "A stochastic frontier analysis to estimate the relative efficiency of Spanish airports," Journal of Productivity Analysis, Springer, vol. 31(3), pages 163-176, June.
    33. Robin C. Sickles & Zhichao Wang & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis for Healthcare, with Illustrations in R," CEPA Working Papers Series WP052022, School of Economics, University of Queensland, Australia.
    34. Kevin Cullinane & Dong-Wook Song, 2003. "A stochastic frontier model of the productive efficiency of Korean container terminals," Applied Economics, Taylor & Francis Journals, vol. 35(3), pages 251-267.
    35. Guermat, C. & Hadri, K., 1999. "Heteroscedasticity in Stochastic Frontier Models: a Monte Carlo Analysis," Discussion Papers 9914, University of Exeter, Department of Economics.
    36. Veiga, Gabriela Lobo & Pinheiro de Lima, Edson & Frega, José Roberto & Gouvea da Costa, Sérgio Eduardo, 2021. "A DEA-based approach to assess manufacturing performance through operations strategy lenses," International Journal of Production Economics, Elsevier, vol. 235(C).
    37. Wickham Skinner, 1984. "Operations Technology: Blind Spot in Strategic Management," Interfaces, INFORMS, vol. 14(1), pages 116-125, February.
    38. Lensink, Robert & Meesters, Aljar & Naaborg, Ilko, 2008. "Bank efficiency and foreign ownership: Do good institutions matter?," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 834-844, May.
    39. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    40. Fenn, Paul & Vencappa, Dev & Diacon, Stephen & Klumpes, Paul & O'Brien, Chris, 2008. "Market structure and the efficiency of European insurance companies: A stochastic frontier analysis," Journal of Banking & Finance, Elsevier, vol. 32(1), pages 86-100, January.
    41. Iwai, Katsuhito, 2000. "A contribution to the evolutionary theory of innovation, imitation and growth," Journal of Economic Behavior & Organization, Elsevier, vol. 43(2), pages 167-198, October.
    42. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    43. Giuliana Battisti & Carlo Pietrobelli, 2000. "Intra-Industry Gaps in Technology and Investments in Technological Capabilities: Firm-level evidence from Chile," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(2), pages 253-269.
    44. Bhattacharyya, Arunava & Lovell, C. A. K. & Sahay, Pankaj, 1997. "The impact of liberalization on the productive efficiency of Indian commercial banks," European Journal of Operational Research, Elsevier, vol. 98(2), pages 332-345, April.
    45. Kumbhakar, Subal C. & Tsionas, Mike G., 2021. "Dissections of input and output efficiency: A generalized stochastic frontier model," International Journal of Production Economics, Elsevier, vol. 232(C).
    46. Xun, Dengye & Hao, Han & Sun, Xin & Geng, Jingxuan & Liu, Zongwei & Zhao, Fuquan, 2022. "Modeling the evolvement of regional fuel cell vehicle supply chain: Implications for enhancing supply chain sustainability," International Journal of Production Economics, Elsevier, vol. 249(C).
    47. (Daniel) Kao, Ta-Wei & Su, Hung-Chung & Chen, Yi-Su, 2019. "The curvilinear relationships between structural embeddedness and productive efficiency: An exploratory study," International Journal of Production Economics, Elsevier, vol. 212(C), pages 176-185.
    48. Tsionas, Mike & Patel, Pankaj C. & Guedes, Maria João, 2022. "Endogenous efficiency of the dynamic profit maximization in the intertemporal production models of venture behavior," International Journal of Production Economics, Elsevier, vol. 246(C).
    49. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    50. Tsionas, Mike G. & Mamatzakis, Emmanuel, 2019. "Further results on estimating inefficiency effects in stochastic frontier models," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1157-1164.
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