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Determinants of research efficiency in Canadian business schools: evidence from scholar-level data

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Abstract

Using a large sample of faculty members of Canadian business schools, this article attempts to shed new light on the efficiency of academic research as measured, at the researcher’s level, by the peer-reviewed article counts and citations. Metrics on outputs from the Web of Science and from the Google Scholar databases, augmented by a survey data on factors explaining the productivity and impact performances of these faculty members, are used to assess their academic research efficiency and to perform an empirical investigation of the determinants of researchers’ efficiency, using the two-stage Bootstrap DEA approach. Results reveal that there is substantial room for improvements of technical efficiency, both across the eight fields considered in this study, and within each field. The analyses also enabled to identify determinants that might explain the academic efficiency gap between scholars across the eight research fields considered in this study, notably certification from independent agencies, seniority, sources of funding, affiliation to a business school with a doctoral program, and prestige and reputation of university of affiliation.

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Notes

  1. A journal indexed in the Web of Science is used to be called an ISI journal. ISI means the Institute for Scientific Information, which developed and produced the Science Citation Index (SCI), Social Sciences Citation Index (SSCI), and the Arts and Humanities Citation Index (AHCI).

  2. Bowen and Schuster (1986) describe the faculty role as encompassing instruction, research, public service, and institutional governance and operation (e.g., administration).

  3. Detailed steps to obtain unbiased efficiency scores together with confidence intervals can be found in Simar and Wilson (2000) p. 788–791. In our analysis, the computation of efficiency scores was performed with Wilson’s FEAR 2.0 software (2008), and the truncated regression models were performed in R.

  4. We employed algorithm 2 from Simar and Wilson (2007), pp. 42–43.

  5. Confidence intervals are obtained from 1000 bootstrapping replications. As a robustness check, we also tried 2000 replications. The change of the number of bootstrap replications did not have a substantive impact on the results.

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Acknowledgments

The authors would like to acknowledge financial assistance provided by The Social Sciences and Humanities Research Council of Canada, and by The Fonds de recherche du Québec—Société et culture. We also would like to thank all the faculty members of Canadian business schools who participated in our survey.

Author information

Authors and Affiliations

  1. Department of Mathematical and Industrial Engineering, Polytechnique Montréal, 2900 Boulevard Edouard-Montpetit, Montreal, QC, H3T 1J4, Canada

    Mehdi Rhaiem

  2. Faculty of Business, Department of management, Université Laval, 2325 Rue de la Terrasse, Québec, QC, G1V 0A6, Canada

    Nabil Amara

Authors
  1. Mehdi Rhaiem
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  2. Nabil Amara
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Corresponding author

Correspondence to Mehdi Rhaiem.

Appendices

Appendix 1. Definitions of explanatory variables and descriptive statistics

Measure

Sub-items

Mean (SD)

Percentage (number)

 

Inputs

Time dedicated to research activities

Measured as the percentage of scholar’s time dedicated to research activities

35.30% (16.02%)

  

Research funds

The total research funding (for research projects and infrastructure) of all scholar’s research projects during the past 12 months

61263.33

137128.3

  

Outputs

Number of publications

Measured as the lifetime number of scholar’s scientific contributions as compiled by

   
 

 Web of Science database

7.51 (10.359)

  
 

 Google Scholar database

22.531 (31.917)

  

Number of citations

Measured as the lifetime number of scholar’s citations as compiled by

   
 

 Web of Science database

79.04 (225.513)

  
 

 Google Scholar database

284.198 (1017.651)

  

Factors driving or hampering academic research efficiency

Seniority [SENIOR]

The level of seniority in the academic ranks was measured as follows

   
 

 Assistant professor [ASSIST] is a binary variable coded 1 if the scholar is an assistant professor, and coded 0 otherwise

 

25.2% (203)

 
 

 Associate professor [ASSOC] is a binary variable coded 1 if the scholar is an associate professor, and coded 0 otherwise

 

39.0% (315)

 
 

 Full professor [FULL] is a binary variable coded 1 if the scholar is a full professor, and coded 0 otherwise. This last category of scholars was used as the reference category

 

35.8% (289)

Benchmark

Public sources of research funding [PUBLIC]

The level of scholar’s total research budget funded during the past 12 months by provincial and federal research councils was measured by the three following binary variables

   
 

 Non-funded by research Councils [NO_PFUND] is a binary variable coded 1 if the scholar was not funded over the past 12 months by provincial nor federal research councils, and coded 0 otherwise

 

50.8% (410)

 
 

 Partially funded by research Councils [PAR_PFUND] is a binary variable coded 1 if the percentage of scholar’s total research funding over the past 12 months funded by provincial and federal research councils ranges between 1 and 99%, and coded 0 otherwise

 

27.1% (219)

 
 

 Totally funded by research Councils [TOT_PFUND] is a binary variable coded 1 if, over the past 12 months, the funding from provincial and federal research councils represented 100% of scholar’s total research funding, and coded 0 otherwise. This last category was used as the reference category

 

22.1% (178)

Benchmark

Private sources of research funding [PRIVATE]

The level of scholar’s total research budget funded during the past 12 months by industry grants (contracts by third parties) was measured by the dichotomous variable

Coded 1 if the scholar over the past 12 months was funded by industry, and coded 0 otherwise

   
 

 Funded by industry

 

73.0% (589)

 
 

 Not funded by industry

 

27.0% (218)

 

World ranking of scholars’ universities of affiliation [PREST]

The academic ranking of scholars’ universities of affiliation is based on the 2010 Academic Ranking of World Universities (ARWU). ARWU is one of most popular and employed ranking tables (Lukman et al. 2010). Three types of universities were distinguished by the three following binary variables

   
 

 Third tier Universities [OUT_LIST] is a binary variable coded 1 if the scholar’s university of affiliation was not in the ARWU top-500 ranking for the year 2010, and coded 0 if his university was in the top-500 ranking for the year 2010

 

22,8% (184)

 
 

 Second tier Universities [IN_LIST] is a binary variable coded 1 if the scholar’s university of affiliation was in the ARWU top-500 ranking but not in the Canadian top-5 in this list for the year 2010, and coded 0 otherwise

 

66,4% (536)

 
 

 Top-5 Universities [TOP_5] is a binary variable coded 1 if the scholar’s university of affiliation was in the Canadian top-5 ARWU ranking for the year 2010, and coded 0 otherwise

 This last category was used as the reference category

 

10.8% (87)

Benchmark

Factors driving or hampering academic research efficiency

Accreditation [REPUT]

Dichotomous variable

Coded ‘1’ (with AASCB), if the scholar’s university of affiliation was accredited through The Association to Advance Collegiate Schools of Business (AACSB), and coded 0 otherwise (without accreditation)

   
 

 With certification

 

75.3 (608)

 
 

 Without certification

 

24.7% (199)

 

Size effects [DOCPROG]

Dichotomous variable

Coded ‘1’ (with doctoral program), if the scholar’s university of affiliation has a doctoral program, and coded 0 otherwise (without doctoral program)

   
 

 With doctoral program

 

75.7% (611)

 
 

 Without doctoral program

 

24.4% (196)

 

Strength of ties with companies [TIES]

Dichotomous variable

Coded ‘1’ (Strong ties), if the scholar described his working relationship with managers/employees in companies in the past 3 years as very close (practically like being in the same work group), or somewhat close (like discussing and solving issues together), and 0 otherwise (weak ties) (somewhat distant, like with people that you do not know well; distant, like a working group with which you can only have a quick exchange of information; or very distant, practically like with people that you do not know at all)

   
 

 Strong ties

 

59.9% (483)

 
 

 Weak ties

 

40.1% (324)

 

Frequency of contacts with companies [CONTACT]

Dichotomous variable

coded ‘1’, (Frequent contact) if the scholar has had Very often or Often person-to-person contact with managers and/or employees in companies in the past 3 years, and 0 otherwise (Never, Rarely, or Sometimes)

   
 

 Very often and Often

 

38.7% (312)

 
 

 Never, rarely, and sometimes

 

61.3% (495)

 

Control variable

Business disciplines

A series of eight dichotomous variables indicating the scholars’ business disciplines:

   
 

 Human resources management [HRM]

 

14.4% (116)

 
 

 Finance [FINAN]

 

9.7% (78)

 
 

 Marketing [MARK]

 

14.7% (119)

 
 

 Information management [INFOR]

 

7.9% (64)

 
 

Accounting [ACCOUNT]

 

12.8% (103)

 
 

Operational Research [OPER]

 

5.9% (48)

 
 

Economics [ECON]

 

7.2% (58)

 
 

Management [MNG]

 

27.4% (221)

 
  1. *It can be seen that all the tolerance statistic values are much higher than 0.2. This ensures that there is no multicollinearity concern (Field 2009; Menard 1995)

Appendix 2. Comparison of means of total number of papers published between faculty members in the FS and those in the ROP sample (Independent-samples T test on ranked data)

Total number of papers published according to WoS

FS

ROP

T test for equality of means††

Number of cases

807

2327

 

Means

1596.2

1557.5

1.089

Standard deviation

848.6

875.9

 

P value for the Levene test of equality of variances

0.039**

  
  1. The T test was performed on ranked data. Therefore, numbers in the row Means are mean rank
  2. ††,*,** and ***indicate that the test is significant at 10%, 5% and 1%, respectively

Appendix 3. Comparison of means of total number of citations between faculty members in the FS and in the ROP sample (Independent-samples T test on ranked data)

Total number of citations according to WoS

FS

ROP

T test for equality of means††

Number of cases

807

2327

 

Means

1573.7

1565.3

0.244

Standard deviation

848.6

875.9

 

P value for the Levene test of equality of variances

0.334

  
  1. The T test was performed on ranked data. Therefore, numbers in the row Means are mean rank
  2. ††,*,** and ***indicate that the test is significant at 10%, 5% and 1%, respectively

Appendix 4. Distribution of samples (FS vs. ROP) of faculty members according to academic rank (Chi square test)

Academic rank

All faculty members

FS

ROP

Pearson Chi square††

Number

%

Number

%

Number

%

Full professor

1169

37.3

289

35.8

880

37.8

1.629

Associate professor

1167

37.2

315

39.0

852

36.6

 

Assistant professor

798

25.5

203

25.2

595

25.6

 

Total

3134

100.0

807

100.0

2327

100.0

 
  1. The Chi square tests the independency between the variable indicating the academic rank of the scholar and the variable indicating if the scholar is from final sample, or ROP sample
  2. ††,*, ** and ***indicate that we can reject the null hypothesis (independency between the variable indicating the academic rank of the faculty members and the samples, FS or ROP), at 10%, 5% and 1% levels, respectively

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Rhaiem, M., Amara, N. Determinants of research efficiency in Canadian business schools: evidence from scholar-level data. Scientometrics 125, 53–99 (2020). https://doi.org/10.1007/s11192-020-03633-z

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