Research Productivity in Management Schools of India: A Directional Benefit-of-Doubt Model Analysis

Sahoo, Biresh and Singh, Ramadhar and Mishra, Bineet and Sankaran, Krithiga (2015): Research Productivity in Management Schools of India: A Directional Benefit-of-Doubt Model Analysis.

Abstract

Given the growing emphasis on research productivity in management schools in India, the present authors developed a composite indicator (CI) of research productivity, using the directional benefit-of-doubt (D-BOD) model, which can serve as a valuable index of research productivity in India. Specifically, we examined overall research productivity of the schools and the faculty members during the 1968-2014 and 2004-2014 periods in a manner never done before. There are four key findings. First, the relative weights of the journal tier, total citations, impact factor, author h-index, number of papers, and journal h-index varied from high to low in order for estimating the CI of a faculty member. Second, both public and private schools were similar in research productivity. However, faculty members at the Indian Institutes of Technology (IITs) outperformed those at the Indian Institutes of Management (IIMs). Third, faculty members who had their doctoral degrees from foreign, relative to Indian, schools were more productive. Among those trained in India, alumni of IITs, compared to those of IIMs, were more productive. Finally, IIMs at Ahmedabad and Bangalore and the Indian School of Business, Hyderabad have seemingly more superstars than other schools among the top 5% researchers during 2004-2014. These findings indicate a shift in the priority from mere training of managers to generating impactful knowledge by at least two of the three established public schools, and call attention to improving the quality of doctoral training in India in general and IIMs in particular. Suggestions for improving research productivity are also offered.

• Item Type: MPRA Paper
• Language: English
• Keywords: Data envelopment analysis; Research productivity; Composite indicator; Business schools
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis; D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity; I - Health, Education, and Welfare > I2 - Education and Research Institutions > I23 - Higher Education ; Research Institutions

References

[1] http://pmindia.gov.in/en/news_updates/text-of-pms-address-at-the-102nd-indian-science-congress/

[2] http://www.aicte-india.org/foreignuniversities.php

[3]http://www.livemint.com/Politics/JtHPA61PdLaQIzSxtwgZUI/Foreign-universities-open-India-centres.html

[4]http://www.timeshighereducation.co.uk/world-university-rankings/2014-15/subject-ranking/subject/social-sciences

[5] http://jindal.utdallas.edu/the-utd-top-100-business-school-research-rankings/

[6] http://www.shanghairanking.com/

[7] https://www.iimcal.ac.in/iims-meet-goa-discuss-emerging-issues-management

[8] http://www.ndtv.com/india-news/iit-iim-faculty-not-world-class-jairam-ramesh-456533

[9] http://timesofindia.indiatimes.com/city/ahmedabad/Sibal-defends-IIM-IIT-faculty/articleshow/8576121.cms

[10] Kumar N. Taking stock of Indian management research. Economic Times (http://economictimes.indiatimes.com/opinion/view-point/taking-stock-of-indian-management-research/articleshow/7440640.cms)

[11] Publish or Perish. Economic Times (http://articles.economictimes.indiatimes.com/2011-02-08/news/28425879_1_business-schools-paper-research)

[12] Khatri N, Ojha AK, Budhwar P, Srinivasan V, Varma A. Management research in India: current state and future directions. IIMB Management Review 2012; 24: 104-15.

[13] Singh R. Sloppy research versus disinterest in Indian data as a difficulty factor in international publications. Pan IIM World Management Conference, IIMK, November 5, 2014. http://www.iiimb.ernet.in/webpage/ramadhar-singh

[14] Kumar N. Indian Business schools still display pre-reforms mentality. Economic times(http://economictimes.indiatimes.com/opinion/view-point/indian-business-schools-still-display-pre-reforms-mentality/articleshow/8138503.cms)

[15] Madhavan N. Paper Lambs. Business Today, October 28, 2012 edition, (http://businesstoday.intoday.in/story/best-b-school-research-lag/1/188766.html)

[16]http://articles.economictimes.indiatimes.com/2012-07-03/news/32523925_1_iim-calcutta-iim-a-alumni-association-iim-bangalore

[17]http://www.iimidr.ac.in/iimi/images/IIM_INDORE_OVER_THE_YEARS/RULESREGULATIONSPART-2.pdf

[18] Hsieh P-N, Chang, P-L. An assessment of world-wide research productivity in production and operations management. Int J Prod Econ 2009; 120: 540-51.

[19] Malhotra MK, Kher HV. Institutional research productivity in production and operations management. J Oper Manag 1996; 14: 55-77.

[20] Hsieh P-N. Addendum to ‘‘an assessment of world-wide research productivity in production and operations management’’. Int J Prod Econ 2010; 125: 135-38.

[21] Young ST, Baird BC, Pullman ME. 1996. POM research productivity in US business schools. J Oper Manag 1996; 14: 41–53.

[22] Liu JS, Lu, LYY, Lu W-M, Lin BJY. Data envelopment analysis 1978–2010: a citation-based literature survey. Omega-Int J Manage S 2013; 41: 3-15.

[23] Ansari A, Lockwood D, Modarress B. Characteristics of periodicals for potential authors and readers in production and operations management. Int J Oper Prod Manage, 1992; 12: 56-65.

[24] Barman S, Hanna MD, LaForge RL. Perceived relevance and quality of POM journals: A decade later. J Oper Manag 2001; 19: 367-85.

[25] Barman S, Tersine R, Buckley MR. An empirical assessment of the perceived relevance and quality of POM related journals by academicians. J Oper Manag 1991; 10: 194-210.

[26] Olson JE. Top-25-business-school professors rate journals in operations management and related fields. Interfaces 2005; 35: 323-38.

[27] Soteriou AC, Hadjinicola GC, Patsia K. Assessing production and operations management related journals: the European perspective. J Oper Manag 1999; 17: 225-38.

[28] Mingers J, Leydesdorff L. A review of theory and practice in Scientometrics. Eur J Oper Res (2015), doi: 10.1016/j.ejor.2015.04.002

[29] Lawrence, PA. The mismeasurement of science. Curr Biol 2007; 17: 583-85.

[30] Singh R. Reinforcement and attraction: Specifying the effects of affective states. J Res Pers 1974; 8: 294-305.

[31] Singh R. Information integration theory applied to expected job attractiveness and satisfaction. J Appl Psychol 1975; 60: 621-23.

[32] Singh R. Leadership style and reward allocation: does least preferred co–worker scale measure task and relation orientation? Organ Behav Hum Perf 1983; 32: 178-97.

[33] Singh R. A test of the relative ratio model of reward division with students and managers in India. Genet Soc Gen Psych 1985; 111: 363-84.

[34] Singh R. “Fair” allocations of pay and workload: tests of a subtractive model with nonlinear judgment function. Organ Behav Hum Dec 1995; 62: 70-78.

[35] Singh R. Subtractive versus ratio model of "fair" allocation: Can group level analyses be misleading? Organ Behav Hum Dec 1996; 68: 123-44.

[36] Singh R. Group harmony and interpersonal fairness in reward allocation: on the loci of the moderation effect. Organ Behav Hum Dec 1997; 72: 158-83.

[37] Singh R, Simons JJP, Self, WT, Tetlock PE, Zemba Y, Yamaguchi S, et al. Association, culture, and collective imprisonment: Tests of a causal-moral model. Basic Appl Soc Psych, 2012; 34: 269-77.

[38] Singh R, Wegener DT, Singh S, Sankaran K, Lin PKF, Seow MX, et al. On the importance of trust in interpersonal attraction from attitude similarity. J Soc Pers Relat 2015 (in press).

[39] Greenberg R, Nunamaker TR. A generalized multiple criteria model for control and evaluation of nonprofit organizations. Financial Accountability and Management, 1987; 3: 331-42.

[40] Barrow M, Wagstaff A. Efficiency measurement in the public sector: an appraisal. Fisc Stud 1989; 10: 72-97.

[41] Cherchye L, Ooghe E, Van Puyenbroeck T. Robust human development rankings. J Econ Inequal 2008b; 6: 287-321.

[42] Sahoo BK, Acharya D. An alternative approach to monetary aggregation in DEA. Eur J Oper Res 2010; 204: 672-82.

[43] Sahoo BK, Acharya D. Constructing macroeconomic performance index of Indian states using DEA. J Econ Stud 2012; 39: 63-83.

[44] Melyn W, Moesen W. Towards a synthetic indicator of macroeconomic performance: unequal weighting when limited information is available. Public Economics Research Paper 17, 1991; Centre for Economic Studies, Leuven.

[45] Oral M, Oukil A, Malouin, J-L, Kettani O. The appreciative democratic voice of DEA: a case of faculty academic performance evaluation. Socio Econ Plan Sci 2014; 48: 20-28.

[46] Dyson RG, Allen R, Camanho AS, Podinovski VV, Sarrico CS, Shale EA. , 2001. Pitfalls and protocols in DEA. Eur J Oper Res 2001; 132: 245–59.

[47] Jones MJ, Brinn T, Pendlebury M. Journal evaluation methodologies: a balanced response. Omega-Int J Manage S 1996; 24: 607-12.

[48] Frey BS, Rost K. Do rankings reflect research quality? J Appl Econ 2010; 13: 1-38.

[49] Halkos GE, Tzeremes NG. Measuring economic journals' citation efficiency: a data envelopment analysis approach. Scientometrics 2011; 88: 979-1001.

[50] Tüselmann H, Sinkovics RR, Pishchulov G. Towards a consolidation of worldwide journal rankings – a classification using random forests and aggregate rating via data envelopment analysis. Omega-Int J Manage S 2015; 51: 11-23.

[51] Hult GTM, Reimann M, Schilke O. Worldwide faculty perceptions of marketing journals: rankings, trends, comparisons, and segmentations. GlobalEDGE Business Review 2009; 3: 1-23.

[52] Baum JAC. Free-riding on power laws: questioning the validity of the impact factor as a measure of research quality in organization studies. Organization 2011; 18: 449-66.

[53] Kulkarni, AV, Aziz B, Shams I, Busse JW. Comparisons of citations in web of science, Scopus, and Google scholar for articles published in general medical journals. JAMA 2009; 302: 1092-96.

[54] Vaughan L, Shaw D. A new look at evidence of scholarly citations in citation indexes and from web sources. Scientometrics, 2008; 74: 317-30.

[55] Meho LI, Yang K. A new era in citation and bibliometric analyses: web of science, scopus, and google scholar. J Am Soc Inf Sci Tec 2007; 58: 2105-25.

[56] Kousha K, Thelwall M. Google scholar citations and google web/url citations: a multi-discipline exploratory analysis. J Am Soc Inf Sci Tec 2007; 58: 1055-65.

[57] Kousha K, Thelwall M. (2008) Sources of google scholar citations outside the science citation index: a comparison between four science disciplines. Scientometrics, 2008; 74: 273-94.

[58] Harzing A-W. Google scholar – a new data source for citation analysis. http://www.harzing.com/pop_gs.htm

[59] Cooper WW, Seiford LM, Tone K. Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software, New York: Springer, 2007.

[60] Zhu J. Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets, New York: Springer, 2014.

[61] Alchian AA. Some economics of property rights. II Politico 1965; 30: 816-29.

[62] De Alessi L. The economics of property rights: a review of the evidence. In: Richard OZ, Editor. Research in law and economics: a research annual, Greenwich, C. T.: Jai Press; 1980, vol. 2, p. 1-47.

[63] Cherchye L, Vermeulen F. Robust rankings of multidimensional performances: an application to tour de France racing cyclists. J Sport Econ 2006; 7: 359-73.

[64] Munda G, Nardo M. Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting. Appl Econ 2009; 41: 1513-23.

[65] Fusco E. Enhancing non-compensatory composite indicators: a directional proposal. Eur J Oper Res 2015; 242: 620-30.

[66] Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. Eur J Oper Res 1978; 2: 429-41.

[67] Podinovski VV. Criteria importance theory. Math Soc Sci 1994; 27: 237-52.

[68] Chambers RG, Chung Y, Färe R. Profit, directional distance functions, and Nerlovian efficiency. J Optimiz Theory App 1998; 98: 351-64.

[69] Banker RD, Charnes A, Cooper WW. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage Sci 1984; 30: 1078-92.

[70] Sahoo BK, Mehdiloozad M, Tone K. Cost, revenue and profit efficiency measurement in DEA: a directional distance function approach. Eur J Oper Res 2014; 237: 921-31.

[71] Mehdiloozad M, Sahoo BK, Roshdi I. A generalized multiplicative directional distance function for efficiency measurement in DEA. Eur J Oper Res 2014; 232: 679-88.

[72] Government of India. Report of IIM review committee, negotiating the big leap - IIMs: from great teaching institutions to thought leadership centres, 25 September 2008. Available at http://mhrd.gov.in/sites/upload_files/mhrd/files/document-reports/bhargava_IIMreview_0.pdf

[73] Singh, R. Two problems in cognitive algebra: Imputations and averaging–versus–multiplying. In: Anderson NH, Editor. Contributions to information integration theory, Hillsdale, NJ: Erlbaum; 1991, vol. II, pp. 143-80.

[74] Singh, R. Imputing values to missing information in social judgment. In: Arkin RM, Editor. Most underappreciated: 50 prominent social psychologists describe their most unloved work, New York: Oxford University Press; 2011, pp. 159-64.

[75] http://www.psychologicalscience.org/index.php/members/psychological-scientists#singh

[76] Oswald A. An examination of the reliability of prestigious scholarly journals: evidence and implications for decision-makers. Economica 2007; 74: 21-31.