Contents |
Authors:
Allam Yousuf, ORCID: https://orcid.org/0000-0003-0262-1890 University of Debrecen (Hungary) Vahid Zeynvand Lorestani, ORCID: https://orcid.org/0000-0003-4860-2900 University of Debrecen (Hungary) Janos Felföldi, ORCID: https://orcid.org/0000-0002-3895-6636 University of Debrecen (Hungary) Tetiana Zatonatska, ORCID: https://orcid.org/0000-0001-9197-0560 Taras Shevchenko National University of Kyiv (Ukraine) Serhii Kozlovskyi, ORCID: https://orcid.org/0000-0003-0707-4996 Vasyl’ Stus Donetsk National University (Ukraine) Oleksandr Dluhopolskyi, ORCID: https://orcid.org/0000-0002-2040-8762 West Ukrainian National University (Ukraine)
Pages: 30-37
Language: English
DOI: https://doi.org/10.21272/mmi.2021.1-03
Received: 15.10.2020
Accepted: 06.12.2021
Published: 30.03.2021
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Abstract
The article summarizes the arguments on minimizing the uncertainty level caused by numerous unforeseen circumstances due to using operational flexibility to increase companies’ efficiency (example of small and medium enterprises in the pharmaceutical sector of Iran). The research aims at investigating the relationship between operational flexibility and a company’s performance to examine the impact of environmental uncertainty on these relationships. This study was conducted as quantitative. The deductive method using the synergy of systematization of scientific background on the problem and the empirical proof of the formulated hypotheses became a methodological study tool. The article provides evidence of the economic-mathematical model based on data from small and medium-sized pharmaceutical Iranian companies. The study hypotheses are as follows: 1) operational flexibility has a positive effect on the productivity of the pharmaceutical sector of Iran, represented by small and medium-sized companies; 2) uncertainty determines the relationship between the operational flexibility and efficiency of small and medium-sized pharmaceutical companies in Iran. The model constructed by the authors allowed measuring the relationship between variables using regression analysis and moderation analysis (Hayes model). The total number of companies included in the sample is 113. In turn, 228 managers of these pharmaceutical companies took part in the surveys (Iran example). The empirical analysis results showed that the mix flexibility indicator has practically no effect on companies’ efficiency, and the volume flexibility and product development flexibility indicators generally have a positive effect on the performance of companies in the pharmaceutical sector. On the other hand, the environmental uncertainty indicator does not help reduce the relationship between the operational flexibility indicator and companies’ performance in the pharmaceutical sector of Iran’s economy. The study results could be useful for planning small and medium enterprises’ activities in the context of improving their performance.
Keywords: flexibility, small and medium-sized company, uncertainty, performance, statistical analysis.
JEL Classification: С01, D23, M11, M21, O25.
Cite as: Yousuf, A., Lorestani Zeynvand, V., Felfoldi, J., Zatonatska, T., Kozlovskyi, S., & Dluhopolskyi, O. (2021). Companies performance management: the role of operational flexibility. Marketing and Management of Innovations, 1, 30-37. https://doi.org/10.21272/mmi.2021.1-03
This work is licensed under a Creative Commons Attribution 4.0 International License
References
- Abramova, A., Beschastnyy, V., Zhavoronok, A., Fedyshyn, M., Lavrov, R., Dluhopolskyi, O., & Kozlovskyi, V. (2020). Financial technologies development prospects in the countries of Eastern Europe and Ukraine. International Journal of Management, 11(7), 384-398. [Google Scholar]
- Baarda, D. B., de Goede, M. P. M., & Teunissen, J. (2001). Basisboek kwalitatief onderzoek: praktische handleiding voor het opzetten en uitvoeren van kwalitatief onderzoek. Stenfert Kroese. [Google Scholar]
- Camison, C., & Lopez, A. V. (2010). An examination of the relationship between manufacturing flexibility and firm performance: The mediating role of innovation. International Journal of Operations & Production Management, 30(8), 853-878. [Google Scholar] [CrossRef]
- Chod, J., & Rudi, N. (2005). Resource flexibility with responsive pricing. Operations Research, 53(3), 532-548. [Google Scholar] [CrossRef]
- Cottrell, T., & Nault, B. R. (2004). Product variety and firm survival in the microcomputer software industry. Strategic Management Journal, 25(10), 1005-1025. [Google Scholar] [Google Scholar]
- De Toni, A., & Tonchia, S. (1998). Manufacturing flexibility: a literature review. International journal of production research, 36(6), 1587-1617. [Google Scholar] [CrossRef]
- DiFonzo, N., & Bordia, P. (2002). Corporate rumor activity, belief and accuracy. Public Relations Review, 28(1), 1-19. [Google Scholar] [CrossRef]
- Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of operations management, 28(1), 58-71. [Google Scholar] [CrossRef]
- Fynes, B., De Búrca, S., & Marshall, D. (2004). Environmental uncertainty, supply chain relationship quality and performance. Journal of Purchasing and Supply Management, 10(4-5), 179-190. [Google Scholar] [CrossRef]
- Gerwin, D. (1993). Manufacturing flexibility: a strategic perspective. Management science, 39(4), 395-410. [Google Scholar] [Google Scholar]
- Gorova, K., Dluhopolskyi, O., & Dluhopolska, T. (2019). Entering in the global manufacturing outsourcing market and innovative development of the Ukrainian industrial enterprises. Economy and Sociology. Theoretical and scientifically journal, 2, 20-31. [Google Scholar]
- Goyal, M., & Netessine, S. (2011). Volume flexibility, product flexibility, or both: The role of demand correlation and product substitution. Manufacturing & service operations management, 13(2), 180-193. [Google Scholar]
- Hallgren, M., & Olhager, J. (2009). Flexibility configurations: Empirical analysis of volume and product mix flexibility. Omega, 37(4), 746-756. [Google Scholar] [CrossRef]
- Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. [Google Scholar]
- Jabnoun, N., Khalifah, A., & Yusuf, A. (2003). Environmental uncertainty, strategic orientation, and quality management: a contingency model. Quality Management Journal, 10(4), 17-31. [Google Scholar] [CrossRef]
- Jack, E. P., & Raturi, A. (2002). Sources of volume flexibility and their impact on performance. Journal of operations management, 20(5), 519-548. [Google Scholar] [CrossRef]
- Kekre, S., & Srinivasan, K. (1990). Broader product line: a necessity to achieve success?. Management science, 36(10), 1216-1232. [Google Scholar] [CrossRef]
- Lummus, R. R., Vokurka, R. J., & Duclos, L. K. (2005). Delphi study on supply chain flexibility. International journal of production research, 43(13), 2687-2708. [Google Scholar] [CrossRef]
- Merschmann, U., & Thonemann, U. W. (2011). Supply chain flexibility, uncertainty and firm performance: An empirical analysis of German manufacturing firms. International Journal of Production Economics, 130(1), 43-53. [Google Scholar] [CrossRef]
- Miller, D., & Shamsie, J. (1996). The resource-based view of the firm in two environments: The Hollywood film studios from 1936 to 1965. Academy of management journal, 39(3), 519-543. [Google Scholar] [CrossRef]
- Narasimhan, R., & Kim, S. W. (2002). Effect of supply chain integration on the relationship between diversification and performance: evidence from Japanese and Korean firms. Journal of operations management, 20(3), 303-323. [Google Scholar] [CrossRef]
- Oke, A. (2005). A framework for analyzing manufacturing flexibility. International Journal of Operations & Production Management. [Google Scholar] [CrossRef]
- Pagell, M., & Krause, D. R. (2003). Re-examining the relationship between operational flexibility and environmental uncertainty. In: Academy of Management Proceedings, 1. Briarcliff Manor, NY 10510: Academy of Management. [Google Scholar]
- Ross, E. A. (1896). Uncertainty as a Factor in Production. The Annals of the American Academy of Political and Social Science, 8(2), 92-119. [Google Scholar] [CrossRef]
- Saenz, M. J., Knoppen, D., & Tachizawa, E. M. (2018). Building manufacturing flexibility with strategic suppliers and contingent effect of product dynamism on customer satisfaction. Journal of Purchasing and Supply Management, 24(3), 238-246. [Google Scholar] [CrossRef]
- Sanchez, A. M., & Pérez, M. P. (2005). Supply chain flexibility and firm performance: A conceptual model and empirical study in the automotive industry. International Journal of Operations & Production Management, 25(7), 681-700. [Google Scholar] [CrossRef]
- Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students. Pearson education. [Google Scholar]
- Scherrer, M., Deflorin, P., & Anand, G. (2014). Manufacturing flexibility through outsourcing: effects of contingencies. International Journal of Operations & Production Management, 34(9), 1210-1242. [Google Scholar] [CrossRef]
- Silva, A. A., & Ferreira, F. C. (2017). Uncertainty, flexibility, and operational performance of companies: modelling from the perspective of managers. RAM. Revista de Administração Mackenzie, 18(4), 11-38. [Google Scholar] [CrossRef]
- Slack, N. (2005). The flexibility of manufacturing systems. International Journal of Operations & Production Management, 25(12), 1190-1200. [Google Scholar] [CrossRef]
- Suarez, F. F., Cusumano, M. A., & Fine, C. H. (1991). Flexibility and performance: a literature critique and strategic framework. Massachusetts Institute of Technology. [Google Scholar]
- Suarez, F. F., Cusumano, M. A., & Fine, C. H. (1996). An empirical study of manufacturing flexibility in printed circuit board assembly. Operations research, 44(1), 223-240. [Google Scholar][Google Scholar]
- Swamidass, P. M., & Newell, W. T. (1987). Manufacturing strategy, environmental uncertainty and performance: a path analytic model. Management science, 33(4), 509-524. [Google Scholar][CrossRef]
- Yu, K., Cadeaux, J., & Luo, B. N. (2015). Operational flexibility: Review and meta-analysis. International Journal of Production Economics, 169, 190-202. [Google Scholar] [CrossRef]
- Vickery, S. N., Calantone, R., & Dröge, C. (1999). Supply chain flexibility: an empirical study. Journal of supply chain management, 35(2), 16-24. [Google Scholar] [CrossRef]
- Volberda, H. W. (1998). Building the flexible firm: how to remain competitive. Corporate Reputation Review, 2(1), 94-96. [Google Scholar]
- Zatonatska, T., & Dluhopolskyi, O. (2019). Modelling the efficiency of the cloud computing implementation at enterprises. Marketing and Management of Innovations, 3, 45-59. [Google Scholar][CrossRef]
- Zatonatska, T., Dluhopolskyi, O., Chyrak, I., & Kotys, N. (2019). The internet and e-commerce diffusion in European countries (modeling at the example of Austria, Poland and Ukraine). Innovative Marketing, 15(1), 66-75. [Google Scholar] [CrossRef]
- Zhang, Q., & Doll, W. J. (2001). The fuzzy front end and success of new product development: a causal model. European Journal of Innovation Management, 4(2), 95-112. [Google Scholar][CrossRef]
- Zhang, Q., Vonderembse, M. A., & Lim, J. S. (2003). Manufacturing flexibility: defining and analyzing relationships among competence, capability, and customer satisfaction. Journal of Operations Management, 21(2), 173-191. [Google Scholar] [CrossRef]
|