Abstract
This chapter attempts to initiate a discussion on relevance and utility of quantitative subjects in management given the conflicting background of perceived quantitative superiority of management graduates from premier institutions and partial failure of Indian business to adopt quantitative practices effectively to justify its utility in management education. This chapter introduces the readers to the standard format of quantitative courses in a management programme by segregating it into three broad areas: statistics, operations research and operations management. We elaborate on the typical courses offered by each of these areas to showcase their relevance to current management programmes and practice. We also compare the quantitative course offerings in management programmes with those in specific technical programmes in terms of their objectives, pedagogy and content. This comparison helps us in identifying the application focus in quantitative courses essential for managers in analytical domain, i.e. financial sector, data analytics, etc. We extend this discussion by providing an unbiased view about the current status, industry expectation and objective of management graduates while going through quantitative courses. We have highlighted the positives of quantitative orientation on management courses and its influence on current success of management education in India. To identify the ways of improvement in future, we focus on critical yet unaddressed areas by involving multiple stakeholders in the discussion: students, faculty members and industry. Although premier management institutes carry the repute of having students with excellent quantitative ability, unfortunately the industrial scenario in India is not able to recognize full potential of quantitative methodologies and hence fails to exploit the potential. This industry practice motivates management graduates to focus on jobs with a general management or consulting focus leaving the quantitative-focused roles for specific disciplines. We have suggested some initiatives, required from both industry and academia, to bridge this gap and make the quantitative part of management education relevant and useful. We also present our views on extending this effort in the field of management research by creating several industry-focused research groups that may help in bridging the industry academia gap to realize full potential of quantitative methods, tools and techniques.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
“B-schools increasingly loosing shine in India, says ASSOCHAM” Wednesday, January 30, 2013, <http://assocham.org/newsdetail.php?id=3877>.
References
Ahmad, S., & Schroeder, R. G. (2003). The impact of human resource management practices on operational performance: Recognizing country and industry differences. Journal of Operations Management, 21(1), 19–43.
Bennis, W., & Toole, J. (2005). How business schools lost their way. Harvard Business Review, 83(5), 96–104.
Boudreau, J., Hopp, W., McClain, J., & Thomas, L. (2003). On the interface between operations and human resources management. Manufacturing & Service Operations Management, 5(3), 179–202.
Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of Business Finance & Accounting, 30(3–4), 573–588.
Gans, N., & Zhou, Y. P. (2002). Managing learning and turnover in employee staffing. Operations Research, 50(6), 991–1006.
Hausman, W., Montgomery, D., & Roth, A. (2002). Why should marketing and manufacturing work together?: Some exploratory empirical results. Journal of Operations Management, 20(3), 241–275.
Iansiti, M. (2015, June). The history and future of Operations. Harvard Business Review.
Jayakrishnan, R., Mahmassani, H. S., & Hu, T. Y. (1994). An evaluation tool for advanced traffic information and management systems in urban networks. Transportation Research Part C: Emerging Technologies, 2(3), 129–147.
Lazaridis, I., & Tryfonidis, D. (2006). Relationship between working capital management and profitability of listed companies in the Athens stock exchange. Journal of Financial Management and Analysis, 19(1), 1–12.
Linoff, G. S., & Berry, M. J. (2011). In G. S. Linoff & M. J. Berry (Eds.), Data mining techniques: For marketing, sales, and customer relationship management. London: Wiley.
Lovejoy, W. (1998). Integrated operations: A proposal for operations management teaching and research. Production and Operations Management, 7(2), 106–124.
Malhotra, M. K., & Sharma, S. (2002). Spanning the continuum between marketing and operations. Journal of Operations Management, 20(3), 209–219.
Maltz, M. D. (1996). From poisson to the present: Applying operations research to problems of crime and justice. Journal of Quantitative Criminology, 12(1), 3–61.
Mandl, C. E. (1980). Evaluation and optimization of urban public transportation networks. European Journal of Operational Research, 5(6), 393–404.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1), 77–91.
Markowitz, H. (1987). In H. Markowitz (Ed.), Mean variance in portfolio choice and capital markets. Oxford: Blackwell Publishers.
Mercer, A. (1966). Applications of operational research in marketing. Journal of the Operational Research Society, 17, 235–252.
Mortenson, M., Doherty, N., & Robinson, S. (2015). Operational research from Taylorism to Terabytes: A research agenda for the analytics age. European Journal of Operational Research, 241, 583–595.
O’Leary-Kelly, S., & Flores, B. (2002). The integration of manufacturing and marketing/sales decisions: Impact on organizational performance. Journal of Operations Management, 20(3), 221–240.
Phillips, R. (Ed.). (2005). Pricing and revenue optimization. Stanford: Stanford University Press.
Rais, A., & Viana, A. (2011). Operations research in healthcare: A survey. International Transactions in Operational Research, 18(1), 1–31.
Rosenhead, J. (1981). Operational research in urban planning. Omega, 9(4), 345–364.
Talluri, K. T., & Van Ryzin, G. J. (2006). In K. T. Talluri & G. J. Van Ryzin (Eds.), The theory and practice of revenue management. Springer Science & Business Media.
Ziemba, W. T., & Mulvey, J. M. (1998). In W. T. Ziemba & J. M. Mulvey (Eds.), Worldwide asset and liability modeling. Cambridge: Cambridge University Press.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this chapter
Cite this chapter
Sharma, M., Basu, S. (2017). Management of Mathematics or Mathematics of Management: Quantitative Methods in Management. In: Thakur, M., Babu, R. (eds) Management Education in India. Springer, Singapore. https://doi.org/10.1007/978-981-10-1696-7_6
Download citation
DOI: https://doi.org/10.1007/978-981-10-1696-7_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-1695-0
Online ISBN: 978-981-10-1696-7
eBook Packages: EducationEducation (R0)