The Story Only Few Can Tell: Exploring the Disproportionately Gendered Professoriate in Business Schools

Abstract

In American business schools, the higher the position, the lower the female representation, especially when including additional intersections of identity such as race, sexual orientation, and ethnicity. Our article aims to supplement existing research regarding gender bias and underrepresentation in academia, particularly in business schools. Such research can uncover faculty gender issues, work toward mitigating the existing biases related to diversity and inclusion, and bring a needed voice and discussion for the purpose of moving toward solutions. To build our hypotheses, we provide a literature review regarding academic satisfaction, perceived performance weight–teaching and perceived performance weight–service differences between genders, and gender issues with the academic pipeline to full professor. Next, we utilize data collected from a sample of n = 696 academics from American business schools and find that women faculty have significantly lower academic satisfaction throughout all ranks and institutions. Our results further indicate that there are differences in perceived performance weight–teaching and perceived performance weight–service between female and male academics at the ranks of assistant and full professors at various types of institutions. Last, we offer conclusions and implications, limitations, and future research suggestions that include studies regarding intersectional faculty, academic mobbing and bullying, incivility, and academic satisfaction.

Keywords

diversity pipeline myth mobbing and bullying intersectionality female full professors satisfaction professoriate gender inequity

The pipeline myth is a common argument used to justify the disproportionate number of women in the upper levels of the professoriate; it claims that there are fewer women actually achieving higher degrees (Glazer-Raymo, 2001). However, this is truly a myth since actual data across all disciplines indicates that (a) since 1981, women have earned more than 50% of all bachelor’s degrees; (b) since 1987, women have earned more than 50% of all master’s degrees; and (c) since 2006, women have earned more than 50% of all doctoral degrees (Snyder, Brey, & Dillow, 2018). Despite these statistics, as of 2016, women comprise only 44% of associate professors and less than 30% of full professors throughout academia (Johnson, 2017). Specifically, in American business schools, the number of women in higher level faculty positions is not representative of the percentages of doctoral degrees conferred to women. As of 2019, 41.6% of all business doctoral degrees were conferred to females and 58.4% of them to males. In business schools, these ratios are almost identical at the assistant professor level (38.3% females vs. 61.7% males). However, they are farther apart at the associate professor level (33.5% females vs. 66.5% males) and much farther apart at the full professor level (22.0% females vs. 78.0% males; AACSB, 2019). In American business schools, the higher the position, the lower the female representation, especially when including additional intersections of identity, such as race, sexual orientation, and ethnicity (Krishen, Robleto, Meza, & Santana, 2019; Pan & Zhang, 2014). This pattern is exactly the opposite for male professors in business schools; for males, the higher the rank, the greater the representation. Unfortunately, there are fewer women in powerful positions in academia, and they also experience significant and persistent pay inequity at all ranks (Johnson, 2017; Tao, 2018).

Our article aims to supplement existing research regarding gender bias and underrepresentation in academia, particularly in business schools. Literature on gender representation in academic faculty is necessary to mitigate existing biases (Cislak, Formanowicz, & Saguy, 2018; Welde & Stepnick, 2014). Similar to Granitz, Koernig, and Harich (2008), the scope of our inquiry pertains to all business faculty, which includes marketing as well as other departments. For the purpose of this research, the authors utilize identity-first, gender-affirming terminology when referring to women and men. Throughout our research, women and men are defined by self-identification (Kachen & LaTour, 2019). The goal of our research is to study the effect of gender, academic rank, and institution type (PhD-granting vs. not) on faculty academic satisfaction (AS) as well as their perceived performance weights (PPW) for teaching, service, and research. The ultimate purpose of our research is to further the knowledge base regarding gender disparities in the upper ranks of marketing departments with a conceptual model (Crittenden & Peterson, 2011). Knowing that females are underrepresented in the upper ranks of business schools, our theoretically driven research aims to understand why this may be the case by answering the questions: To what extent, if any, do female academics in various ranks (a) perceive disproportionate expectations or weights for teaching, service, and/or research compared with their male colleagues and (b) have significantly lower satisfaction than their male colleagues?

This article is organized as follows. We first present literature and hypotheses regarding gender and academia, specifically AS, and perceived performance weightings for teaching, service, and research. To test the hypotheses, we utilize data collected from a sample of academics (n = 696; see Lee & Raschke, 2018). Next, we verify our hypotheses using multivariate analysis of variance to determine whether there are differences between genders. Last, we offer conclusions and implications, limitations, and future research suggestions.

Literature and Hypotheses

Give More and Get Less: Gendered Service and Teaching Expectations and Academic Satisfaction

The role of academics in higher education revolves around research, teaching, and service. Most professors are annually evaluated on these three aspects of their job, and as such, their relative weightings for performance assessments are likely to affect AS. Even though there may be objective measures of research, teaching, and service performance, faculty perceptions of their relative weightings are an important metric with which to further understand gender inequity. In particular, does a gender gap exist in terms of “should be” weighting of teaching such that females believe it should have a higher weighting in their overall annual performance assessment than it does? This same question can exist for service weighting or research weighting.

Second shift refers to the concept that due to societal pressures and cultural expectations, women serve as the primary caregivers and managers of dual-career homes (Hochschild & Machung, 2012; Scheinbaum, Krishen, Kachen, Mabry-Flynn, & Ridgway, 2017). Literature regarding second shift is rarely discussed, especially concerning higher education. Particularly in business schools, women faculty, in comparison with their male counterparts, perform a significantly larger service load throughout their institutions, a phenomenon Guarino and Borden (2017) likened to a second shift with the academic family. In addition to the second shift women face in their homes and the one they face in their academic units, they also have to contend with lack of family-friendly institutional policies that even marginally account for the realities of academic publication pressure (Ward & Wolf-Wendel, 2004). In academia, female scholars suffer from a service trap, that is, high teaching loads and extra service expectations, as well as become institutional housekeepers, having to serve on multiple gender, equity, and diversity committees for which they receive minimal credit (Bird, Litt, & Wang, 2004; Gerdes, 2003).

By studying the activity journals of several associate and full professors in research universities, O’Meara, Kuvaeva, Nyunt, Waugaman, and Jackson (2017) find that for teaching and service-related tasks, female faculty receive significantly more requests and spend significantly more time than male faculty; conversely, for research-related activities, male faculty spend significantly more time than female faculty. Although gender is not the focal point of Carter (2016), they find interesting and significant differences in student evaluations of teaching between faculty outcomes about highly published scholars. Specifically, their findings indicate that for male faculty, elite publications are correlated with higher student evaluations of teaching; however, this relationship does not hold for female faculty. Hanasono et al. (2019) find that female faculty tend to perform more hidden forms of service (e.g., mentoring faculty and/or graduate students and writing letters of recommendation) that are devalued in comparison with the more visible and rewarded forms of service performed by male faculty (e.g., chairing a curriculum committee and serving as editor of a journal).

Webber and Rogers (2018) show differences in both overall and departmental satisfaction based on gender, using a one-item measure of satisfaction. Research also indicates that various academic ranks, assistant versus associate versus full professors, show differences in satisfaction for multiple dimensions including satisfaction with equity of committee assignments, recognition for outreach, time spent on outreach, time spent on administrative tasks, ability to balance teaching, research, and service, attractiveness of committees, and discretion to choose committees (Mamiseishvili, Miller, & Lee, 2016). Given the previous research, we expect that women faculty will have lower AS and perceive that teaching and service should be weighted more heavily in their annual performance evaluations than male faculty. On the other hand, perceived research weighting is less likely to be different between genders. Specifically, unlike teaching and service, research output is not a within-institution metric and is “credited” outside of a university and across academic circles and networks through impact factors (e.g., Li, Sivadas, & Johnson, 2015; Theuβl, Reutterer, & Hornik, 2014). In fact, research performance is an expectation for most tenure track and tenured professors throughout business schools. As part of the advancement process (promotion to associate and/or full professor), most universities require faculty to achieve a national or international reputation and this requirement hinges primarily on research performance. For this reason, we expect that both women and men professors of all ranks will report relatively matching PPW for research. To further understand these “should-be” weightings, we utilized perceived weightings of research, teaching and service, namely, PPW-research (PPW-R), PPW-teaching (PPW-T), and PPW-service (PPW-S). We therefore hypothesize the following:

Hypothesis 1—Overall impact of gender: When comparing AS, PPW-T, PPW-S, and PPW-R between genders, we hypothesize that:

Hypothesis 1a: AS will be significantly different for female versus male professors.

Hypothesis 1b: PPW-S will be significantly different for female versus male professors.

Hypothesis 1c: PPW-T will be significantly different for female versus male professors.

Hypothesis 1d: PPW-R will not be significantly different for female versus male professors.

First it is Rusty and then it is Clogged: Gender and Academic Power

Using a quantitative study of over 30,000 career academics, Wolfinger, Mason, and Goulden (2008) find that the family role and responsibility structure itself is not the sole cause of the dearth of women moving up the academic ladder; rather, it is the male career model in the American workplace. This male career model can be characterized as a system often ruled by implicit and institutionalized biases and explains why even though universities continue to prioritize the hiring of diverse faculty, the full professor pipeline is still largely clogged for women and faculty of color (Carman, Clayton, Horiuchi, Htun, & Ortiz, 2018; Krishen et al., 2019; Winslow & Davis, 2016).

Knipfer, Shaughnessy, Hentschel, and Schmid (2017) cite role congruity theory as the primary reason for lack of advancement and upward mobility of women academics; that is, leadership positions are linked with masculine traits which men are expected to inhabit; this pattern is also prevalent for named professorships, which are rarely awarded to even the most meritorious women academics (Treviño, Gomez-Mejia, Balkin, & Mixon, 2018). The theory of gendered organizations discusses persistent gender inequality especially in organizations such as academia that offer long-term security, standardized jobs, and management who control evaluations (Hart, 2016). The persistent gender bias in academia also gives rise to expectations of women to adhere to feminine traits, such as being nurturing, noncompetitive “good girls” who will agree to do more than is fair; this can involve taking on extra service, mentoring more students and faculty, or constantly teaching a higher breadth or level of courses (Mattsson, 2015). Not being congruous with gendered expectations has direct and negative consequences for female scholars, as they are seen as deviants and face intensified bullying and harassment (Feng, Berdahl, & Schieman, 2014). From 1997 to 2012, the percentage of women in marketing journal editorships increased from 11% to 21%, but this does not reflect the increase in the number of eligible women academics (Pan & Zhang, 2014). The authors indicate that this discrepancy is likely related to the disproportionately lower number of female academics who advance to the full professor level. Current systems of academic assessment also perpetuate inequality through gendered metrics of performance which allow for interpretational flexibility by powerful seniority-based gatekeepers (Helgesson & Sjögren, 2019). Given Hypothesis 1, if female professors experience less satisfaction than male professors, this can also affect their motivation to perform at the level necessary to sustain productivity in a higher rank within a university. Research indicates that all associate professors, regardless of gender, are the unhappiest and most dissatisfied rank; also, the longer the length of stay in rank for associate professors, the higher the dissatisfaction (Mathews, 2014). Because of this overall dissatisfaction for both genders and the impact of time-in-rank that can influence relative outcomes, we do not propose significant gender differences at the rank of associate professor.

We therefore propose:

Hypothesis 2—Gender with rank: When comparing AS, PPW-T, and PPW-S, there will be differences based on gender and rank.

Hypothesis 2a: When comparing ranks, AS will be significantly different:

Hypothesis 2a1: For full professor females versus males.

Hypothesis 2a2: For assistant professor females versus males.

Hypothesis 2b: When comparing ranks, PPW-S will be significantly different:

Hypothesis 2b1: For full professor females versus males.

Hypothesis 2b2: For assistant professor females versus males.

Hypothesis 2c: When comparing ranks, PPW-T will be significantly different:

Hypothesis 2c1: For full professor females versus males.

Hypothesis 2c2: For assistant professor females versus males.

Hypothesis 3—Gender with rank and PhD program: When comparing AS, PPW-T, and PPW-S, there will be differences based on gender, rank, and whether the university offers a PhD program in business.

Hypothesis 3a: When comparing ranks, for PhD-granting institutions, AS will be significantly different:

Hypothesis 3a1: For full professor females versus males.

Hypothesis 3a2: For assistant professor females versus males.

Hypothesis 3b: When comparing ranks, for PhD-granting institutions, PPW-S will be significantly different:

Hypothesis 3b1: For full professor females versus males.

Hypothesis 3b2: For assistant professor females versus males.

Hypothesis 3c: When comparing ranks, for PhD-granting institutions, PPW-T will be significantly different:

Hypothesis 3c1: For full professor females versus males.

Hypothesis 3c2: For assistant professor females versus males.

For the purpose of providing clarity regarding our variables of interest, Figure 1 depicts our research framework, indicating the independent variables (gender, rank, and whether the university offers a PhD program) as well as the subjective outcome variables (PPW-R, PPW-T, PPW-S, and AS).

Figure 1.

Research framework.

Descriptive Study

Sampling Frame

The target population is defined as business school academics and the survey sampling frame uses the general population of AACSB-accredited business schools. The sampling technique used is probabilistic systematic sampling, which was implemented by selecting every fifth name from a list of AACSB-accredited business college academics in the United States to derive a sample of n = 7,217 academics across 517 colleges. The survey was distributed online using Dillman’s (2011) “Tailored Design” survey method. The data collection occurred over a 3-month period with reminders sent every 3 weeks. The survey generated n = 757 responses for a 10.5% overall response rate. The response rate is lower than the average of 35.7% (Baruch & Holtom, 2008); we attribute the lower than average response rate due to (a) an increasing proportion of non–tenure-track faculty in higher education who are assessed mainly on their teaching, (b) no incentive for participation other than goodwill, and (c) faculty time and performance pressures, as this would have been an additional voluntary task. As a quantitative survey, however, this response rate provided a large sample of business faculty with both breadth and depth from universities throughout the country and augments the scant quantitative research on this type of sample (cf. Granitz et al., 2008).

Overview, Study Design, and Measures

The descriptive questionnaire utilized multi-item constructs from the management and marketing literatures that were adapted to fit the academic context (e.g., Gu & Chi Sen Siu, 2009; Lund, 2003; Ouchi, 1979); it was piloted with a small group of academics for reliability and validity. Responses were screened for accuracy, outliers, normality, early and late response bias, and nonresponse bias. We also tested for common method bias to determine the extent to which our responses may create measurement errors and bias our results (Chin, Thatcher, & Wright, 2012). Therefore, prior to any analysis, the multiple-item constructs of PPW-T, PPW-R, PPW-S, and AS satisfied the reliability and validity benchmarks (Nunnally, 1978). The appendix shows the relevant measures from the survey instrument containing the multi-item constructs as well as their reliabilities; for consistency, all items utilized 7-point scales.

Academic Satisfaction

Researchers generally agree that job satisfaction relies on meeting the firm’s own expectations and the candidate’s expectations in a defined employment role. These expectations are almost always multifaceted and require contextual specification. In the context of higher education, based on existing research, five elements are important to AS, namely, compensation, physical facilities, collegiality, workload, and a sense of accomplishment (e.g., Bozeman & Gaughan, 2011). Thus, AS was measured through a 5-item scale asking academics to indicate their satisfaction with each of these elements in the past 3 years or since they joined their institution (whichever is shorter) with endpoints consisting of extremely unsatisfied/extremely satisfied.

PPW-R, PPW-T, and PPW-S

Using definitions from Ouchi (1979), the survey explains that outcome, behavioral, and social measures can be used to determine the annual performance of faculty members. The survey included examples of both objective and subjective measures for research, teaching, and service, respectively. For research, examples of objective measures include but are not limited to the number of journal publications, book chapters, and research grants. Examples of behavioral measures for research include but are not limited to attending research methods classes, being mentored by expert researchers, and serving on journal editorial boards. Examples of social measures for research include but are not limited to being a good research colleague, mentoring junior faculty, sharing data sets, providing constructive feedback, and attending conferences in the appropriate discipline.

For teaching, examples of outcome measures include but are not limited to teaching evaluation scores, number of new course preparations, number of different courses taught, and number of students taught. Examples of behavioral measures for teaching include but are not limited to updating courses, attending teaching methods classes, developing grading rubrics, and keeping office hours. Examples of social measures for teaching include but are not limited to being a good teaching colleague, mentoring junior faculty members in teaching, sharing class notes and assignments, and sharing teaching methods.

For service, examples of outcome measures include but are not limited to the number of professional service awards received and the number of university/college/departmental service awards received. Examples of behavioral measures for service include but are not limited to service on National Science Foundation panels, serving on university/college/departmental committees, and serving on organizing/planning committees for professional societies. Examples of social measures for service include but are not limited to being a good departmental citizen, covering classes for colleagues, meeting informally with students, working with alumni, and working with local/national/international companies.

The survey asked academic respondents to indicate whether they believe that the weight given to each type of research, teaching, and service measure should have been smaller or larger than what was applied in the determination of annual performance of faculty members at their business school in the past 3 years or since they joined the business school (whichever is shorter). Each element (PPW-R, PPW-T, and PPW-S) consisted of a 7-point three-item scale (detailed in the appendix) with endpoints consisting of very much smaller weight/very much larger weight.

Demographic Variables

The demographic information in the survey includes rank, gender, and PhD program. A full range was specified for rank including full professor, associate professor, and tenure-track assistant professor. Whereas the original data set included senior lecturer, lecturer, and adjunct faculty, our hypotheses are only interested in comparing the three ranks of assistant, associate, and full professor across genders. To test our hypotheses, we therefore utilized rank, gender, and PhD program availability as the main grouping variables.¹ Demographic information is provided in Table 1.

Table 1.

Demographics.

Demographic	n	%
Gender
Male	478	68.7
Female	205	29.5
Missing	13	1.9
PhD program
Yes	240	34.5
No	446	64.1
Missing	10	1.4
Rank
Professor	311	44.7
Associate professor	231	33.2
Assistant professor	154	22.1
Missing	0	0
Tenure level
Tenured	519	74.6
Tenure track	148	21.3
Non–tenure track	27	3.9
Missing	2	0.3

Results

Hypothesis 1

A single factor (gender: male vs. female) multivariate analysis of covariance with PPW-R, PPW-S, PPW-T, and AS as the dependent variables and PhD and rank as covariates yields a main effect for gender: F(1, 656) = 5.49, p = .001, Wilks’s Λ = .97. The main effect for gender is significant for AS, F(1, 659) = 7.26, p = .01; M_females = 4.63 versus M_males = 4.90, and PPW-S, F(1, 659) = 10.30, p < .01; M_females = 4.77 versus M_males = 4.41, confirming Hypotheses 1a and 1b; however, contrary to Hypothesis 1c, it is not significantly different for PPW-T, F(1, 659) = 0.44, p = .51; M_females = 4.60 versus M_males = 4.53. As expected in Hypothesis 1d, PPW-R is not significantly different for females versus males, F(1, 659) = 0.20, p = .65; M_females = 4.63 vs. M_males = 4.57. Figure 2 provides the results of the confirmed hypotheses for Hypothesis 1.

Figure 2.

Hypothesis 1 significant results (Gender).

Hypothesis 2

For both Hypotheses 2 and 3, a multivariate analysis of variance with three factors (gender: female vs. male; rank: assistant vs. associate vs. full; PhD program: yes vs. no) with PPW-R, PPW-T, PPW-S, and AS as the dependent variables shows no overall interaction effect for gender × rank: F(1, 661) = 1.17, p = .31, Wilks’s Λ = .99. However, as shown in Figure 3, follow-up contrast effect paired comparisons indicate that AS is significantly lower for female full professors, F(1, 664) = 4.001, p = .05; M_females = 4.71 versus M_males = 5.02, and female assistant professors, F(1, 664) = 3.98, p = .05; M_females = 4.52 versus M_males = 4.88, than for males, confirming both Hypotheses 2a1 and 2a2. Follow-up contrast effect paired comparisons indicate that PPW-S is significantly larger for female full professors, F(1, 664) = 6.04, p = .01; M_females = 4.75 versus M_males = 4.30, and female assistant professors, F(1, 664) = 5.81, p = .02; M_females = 4.85 versus M_males = 4.34, than for males, confirming both Hypotheses 2b1 and 2b2. Follow-up contrast effect paired comparisons indicate that PPW-T is not significantly larger for female full professors, F(1, 664) = 0.14, p = .71; M_females = 4.51 versus M_males = 4.49, not confirming Hypothesis 2c1 but it is higher for female assistant professors, F(1, 664) = 6.18, p = .01; M_females = 4.86 versus M_males = 4.39, than for males, confirming Hypothesis 2c2.²

Figure 3.

Academic satisfaction (Gender × Rank).

Hypothesis 3

Follow-up contrast effect paired comparisons indicate that in PhD-granting institutions, AS is significantly lower for female full professors, F(1, 664) = 3.81, p = .05; M_females = 4.60 versus M_males = 5.11, confirming Hypothesis 3a1 but it is not significantly different for female assistant professors, F(1, 664) = 1.89, p = .17; M_females = 4.50 versus M_males = 4.89, than for males, not confirming Hypothesis 3a2. Follow-up contrast effect paired comparisons show that in PhD-granting institutions, PPW-S is not significantly larger for female full professors, F(1, 664) = 3.20, p = .07; M_females = 4.78 versus M_males = 4.25, not supporting Hypothesis 3b1 and is significantly larger for female assistant professors, F(1, 664) = 4.73, p = .03; M_females = 5.13 versus M_males = 4.42, than for males, confirming Hypothesis 3b2. Follow-up contrast effect paired comparisons show that in PhD-granting institutions, PPW-T is not significantly larger for female full professors, F(1, 664) = 0.61, p = .44; M_females = 4.60 versus M_males = 4.39, not supporting Hypothesis 3c1 and is significantly larger for female assistant professors, F(1, 664) = 10.42, p = .00; M_females = 5.30 versus M_males = 4.33, than for males, confirming Hypothesis 3c2. Based on these results for full professors at PhD-granting institutions, we conducted another post hoc follow-up contrast effect paired comparison and findings indicate that female full professors have a significantly larger PPW-R than their male counterparts, F(1, 664) = 3.78, p = .05; M_females = 5.03 versus M_males = 4.45. Figure 4 and Table 2 provide the results for Hypothesis 3. Table 3 shows the final results for all of the hypotheses.

Figure 4.

Overall findings for academic satisfaction, PPW-service, and PPW-teaching (Gender × Rank × PhD).

Table 2.

Summary of Multivariate Analysis of Covariance Cell Means^a (Gender × Rank × PhD).

Gender	Female	Female	Male	Male	Female	Female	Male	Male	Female	Female	Male	Male
PhD program	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No
Rank	Assistant	Assistant	Assistant	Assistant	Assistant	Associate	Associate	Associate	Full	Full	Full	Full
PPW-research	4.88 (0.24)	4.31 (0.21)	4.31 (0.24)	4.46 (0.16)	4.53 (0.27)	4.47 (0.17)	4.52 (0.17)	4.60 (0.12)	5.01 (0.28)	4.68 (0.18)	4.53 (0.14)	4.70 (0.10)
PPW-service	5.13 (0.23)	4.56 (0.20)	4.43 (0.24)	4.27 (0.16)	4.73 (0.27)	4.74 (0.17)	4.61 (0.17)	4.61 (0.12)	4.88 (0.28)	4.71 (0.18)	4.24 (0.14)	4.36 (0.10)
PPW-teaching	5.31 (0.21)	4.44 (0.19)	4.32 (0.22)	4.45 (0.15)	4.94 (0.25)	4.55 (0.15)	4.83 (0.16)	4.59 (0.11)	4.64 (0.26)	4.41 (0.16)	4.38 (0.12)	4.51 (0.09)
Academic satisfaction	4.51 (0.20)	4.56 (0.18)	4.87 (0.21)	4.88 (0.14)	4.72 (0.24)	4.54 (0.14)	4.65 (0.15)	4.83 (0.11)	4.65 (0.24)	4.81 (0.15)	5.07 (0.12)	4.92 (0.09)

Note. PPW = perceived performance weights.

Mean (standard error).

Table 3.

Hypotheses With Results.

Main hypothesis	Subhypothesis	F	η_H2	M (Females)	M (Males)	Finding
Hypothesis 1: Gender
	Hypothesis 1a: Academic satisfaction	7.26*	.01	4.63	4.90	Hypothesis 1a, supported
	Hypothesis 1b: PPW-S	10.30**	.02	4.77	4.41	Hypothesis 1b, supported
	Hypothesis 1c: PPW-T	0.44	.00	4.60	4.53	Hypothesis 1b, not supported
Hypothesis 2: Gender, Rank
Hypothesis 2a: Academic Satisfaction
	Hypothesis 2a1: Academic satisfaction, full professors (profs)	4.00*	.01	4.71	5.02	Hypothesis 2a1, supported
	Hypothesis 2a2: Academic satisfaction, assistant profs	3.98*	.01	4.52	4.88	Hypothesis 2a2, supported
Hypothesis 2b: PPW-S
	Hypothesis 2b1: PPW-S, full profs	6.04*	.01	4.75	4.30	Hypothesis 2b1, supported
	Hypothesis 2b2: PPW-S, assistant profs	5.81*	.01	4.85	4.34	Hypothesis 2b2, supported
Hypothesis 2c: PPW-T
	Hypothesis 2c1: PPW-T, full profs	0.14	.00	4.51	4.49	Hypothesis 2c1, not supported
	Hypothesis 2c2: PPW-T, assistant profs	6.18**	.01	4.86	4.39	Hypothesis 2c2, supported
Hypothesis 3: Gender, Rank, PhD
Hypothesis 3a: Academic satisfaction
	Hypothesis 3a1: Academic satisfaction, full profs, PhD	3.81*	.01	4.60	5.11	Hypothesis 3a1, supported
	Hypothesis 3a2: Academic satisfaction, assistant profs, PhD	1.89	.00	4.50	4.89	Hypothesis 3a2, not supported
Hypothesis 3b: PPW-S
	Hypothesis 3b1: PPW-S, full profs, PhD	3.20	.01	4.78	4.25	Hypothesis 3b1, not supported
	Hypothesis 3b2: PPW-S, assistant profs, PhD	4.73*	.01	5.13	4.42	Hypothesis 3b2, supported
Hypothesis 3c: PPW-T
	Hypothesis 3c1: PPW-T, full profs, PhD	0.61	.00	4.60	4.39	Hypothesis 3c1, not supported
	Hypothesis 3c2: PPW-T, assistant profs, PhD	10.42**	.02	5.30	4.33	Hypothesis 3c2, supported

p ≤ .05. **p ≤ .01 (two-tailed).

Discussion

As shown in Table 3, for the Hypothesis 1, there are overall significant differences in AS (see Figure 3) and PPW-S between female and male professors regardless of their rank and whether their universities offer a PhD program. Honing in further, the findings for Hypothesis 2 explicate these relationships, finding that for female assistant professors, AS, PPW-S, and PPW-T are all significantly different than for their male counterparts. These findings are almost identical for female full professors, except that PPW-T is not found to be significantly different. Finally, for Hypothesis 3, female assistant professors in institutions with PhD programs do not have significantly lower AS but do have significantly different PPW-S and PPW-T than males in the same positions. For female full professors, AS is significantly lower than for male full professors. Figure 4 summarizes our findings, showing the significant differences for AS, PPW-S, and PPW-T. Focusing on the assistant professors (non-PhD-granting institutions), the findings for PPW-S (Panel B) and PPW-T (Panel C) alone indicate that for women, performance in those areas is higher than expected and provides lower return on investment. In turn, we surmise that the lower AS for women assistant professors (Panel A) is not coincidental and directly relates to service and teaching expectations, among other potential reasons. In PhD-granting institutions, female assistant professors also indicate significantly larger perceived service and teaching weights (PPW-S and PPW-T) than their male counterparts. For female full professors in both types of institutions (PhD-granting and not), AS is significantly lower; in non-PhD-granting institutions, PPW-S is also significantly different for female full professors.

The overall differences (see Figure 2) between female and male faculty for AS, PPW-T, and PPW-S provide the first clue that, due to different service and teaching expectations between genders, these areas of evaluation in academia remain subjective and less transparent for measurement purposes. At the critical stage of assistant professor, our findings show that women have less AS and feel that their service and teaching does not get properly rewarded. We did not hypothesize differences in PPW-R across genders because universities are more likely to clearly enunciate research expectations within and across disciplines. Even though these expectations may vary with different business disciplines and subdisciplines, impact factors, journal rankings, and citation counts tend to be an extremely salient and highly researched metric for research performance (e.g., Li et al., 2015; Theuβl et al., 2014). On the other hand, these types of third-party metrics are not readily available for service and teaching performance. The gender differences for satisfaction and service weight fall in line with previously discussed research, which indicates that due to higher service loads and other potential factors, women academics are less satisfied.

There are many possible explanations for our post hoc finding that PPW-R for full professors in PhD-granting institutions is significantly larger for female faculty than for males. One primary reason could be the relative invisibility and underrepresentation of women academics in high-level editorial positions in multiple fields which, due to the impacts of social networks and authorship (Rosenzweig, Grinstein, & Ofek, 2016), relates to lower likelihood of high impact and highly cited research for women (Pan & Zhang, 2014; Scharber, Pazurek, & Ouyang, 2017). In relation to this, King, Avery, Hebl, and Cortina (2018) find that systematic subjectivity in the academic review process gives rise to subtle biases in terms of both the authors who produce knowledge and the topics that ultimately get published. Secondly, according to the homophily principle, individuals interact with others who are similar to themselves with respect to gender, religion, age, and so on (McPherson, Smith-Lovin, & Cook, 2001). In addition, research shows that higher diversity leads to higher diversity; thus, if less women serve as editors, fewer will become editorial review board members, and eventually less will have publication opportunities in those journals (Potvin, Burdfield-Steel, Potvin, & Heap, 2018).

Last, our results show that gender differences at the full professor level are less prevalent in institutions with PhD programs when it comes to service and teaching weight. This would seem to suggest that power differences at the top are lower. However, on further post hoc analysis, results show that research weights for female full professors at doctoral institutions are significantly larger than for males.

Conclusions and Implications

Faculty Satisfaction and Retention

Most universities, including teaching and balanced ones, emphasize research productivity and utilize journal impact factors and citation counts as important metrics of faculty performance; research performance is also linked with higher salaries for faculty (Weeks, Rutherford, Boles, & Loe, 2014). Service rewards and better pay lead to greater job satisfaction, job performance, and lower employee turnover (Lee, Nam, Park, & Lee, 2006). Furthermore, from a workload perspective, role clarity is positively associated with job performance, while any role ambiguity and/or conflict will have a negative impact on job performance. In terms of work environment, the communications between management and employees, interactions among peers and even the physical work environment all influence job performance (Gu & Chi Sen Siu, 2009). Multiple scholars indicate that work environment, motivation, and satisfaction have a synergistic relationship with performance and productivity, both within academia (Kasper-Brauer & Leischnig, 2016; Nygaard, 2017) and within a classroom (Krishen, 2013).

Given the emphasis on research in business schools and the lower reported satisfaction of assistant and full professor women, one major implication of our research is that marketing department chairs should engage in periodic faculty satisfaction assessments. To retain faculty, administrative faculty in positions of power should also design reward and incentive systems that recognize not only research accomplishments but also service and teaching ones. Administrators should also increase transparency in terms of teaching and service assignments, by providing open documentation of this information; this type of open communication can aid in increasing perceptions of fairness and equity (Hanasono et al., 2019; Helgesson & Sjögren, 2019). Intradepartmental mentoring can improve faculty retention, increase all types of performance, and lower the detrimental effects of rejection sensitivity (Day & Porter, 2017). A supportive mentoring environment requires organizational support (e.g., rewarding faculty who participate), a knowledge sharing environment (e.g., brown bag lunches or colloquiums), and an honest feedback process (e.g., periodic assessments by administrators and faculty mentors; Tähtinen, Mainela, Nätti, & Saraniemi, 2011).

Departmental Leadership and Work Allocation

In addition to the erroneous assumption that by simply hiring women and faculty of color (or both, via intersectional faculty), universities are promoting a diverse environment, these institutions also underplay and overlook the critical role of department heads, who make approximately 80% of all administrative decisions (Carroll & Wolverton, 2004). According to Armenti (2004), these positions are primarily held by White males who are often complacent with gender inequity. In the limited research regarding the ethnic and gender balance of the marketing professoriate, Aggarwal, Rochford, and Vaidyanathan (2008) indicate that marketing department head positions are “typically headed by a White male who is a full professor and has been serving as a chair for the last 5.5 years” (p. 44). Neither Shepherd, Carley, and Stuart (2008) nor Honeycutt, Thelen, and Ford (2010) report the gender of the 132 and 109 marketing department chairs in their respective samples. As Beddoes and Schimpf (2018) suggest, most literature surrounding department heads is gender-blind (i.e., environments wherein the dominant majority maintain their privilege by denying that they are privileged) or assumes that definitions of fairness and collective good are not institutional and male-centric even when they are. Even in the rare occasions that women inhabit the role of a department head, (a) they are most often associate professors (Carroll & Wolverton, 2004); (b) the role is devalued, carries less power, and is considered service work (Bozeman, Fay, & Gaughan, 2013; Monroe, Ozyurt, Wrigley, & Alexander, 2008); and/or (c) they adapt their behavior and decisions to the cultural norms of the institution and face gender-based attributional ambiguity (Brower, Schwartz, & Jones, 2017). Women still only serve as chairs of business school departments approximately 22% of the time (Flynn, Cavanaugh, & Bilimoria, 2015). In fact, multiple studies indicate that the gender gaps in academia can be substantially lowered by appointing more female department chairs (Langan, 2019) and having a larger number of female full professors (Lee & Won, 2014).

Therefore, our findings have implications for faculty and administrators that hold managerial and decision-making positions within their institutions. Because of the significant gender, rank and institutional differences when it comes to teaching and service weightings (and to a lesser extent, research), faculty and administrators may require additional implicit bias training that can provide better cognitive awareness of inequities between the faculty they manage. Such awareness and consideration can lead to increased motivation, a better work environment, and an organizational culture that supports greater educational value.

Approaching Collegiality and Avoiding Mobbing

There is an obvious lack of women in positions of power in business schools; as such, their institutionalized masculine symbolic order perpetuates an environment wherein women faculty are often unwelcome, undermined, silenced, excluded, or objectified (Fotaki, 2013; Mitchell, 2018; Welde & Stepnick, 2014). This type of environment can lead to lower satisfaction and ultimately less motivation to advance into higher ranks in academia, in particular for female professors. Mobbing occurs when multiple individuals in an organization (e.g., a department) “gang up” against a single individual, often through subtle, powerful, and persistent actions (Leymann, 1990). Research indicates that nonsexual aggression (i.e., bullying and mobbing) in the workplace: (a) is more prevalently linked with women than men (Prevost & Hunt, 2018), (b) has a stronger negative effect on women’s job satisfaction than it does with men’s (Lapierre, Spector, & Leck, 2005), and (c) occurs more frequently to women from individuals with both more and less positional power (Lampman, Crew, Lowery, Tompkins, & Mulder, 2016; May & Tenzek, 2018). Mobbing and bullying in academia has been researched by multiple scholars, multiple disciplines, and throughout the world (e.g., Denny, 2014; Minibas-Poussard, 2018). A recent comprehensive literature review by Prevost and Hunt (2018) summarizes specific ways in which mobbing and bullying is enacted can include the following: (a) not recognizing meritorious accomplishments and underplaying professional competence, (b) increasing both administrative and teaching workload, (c) providing less resources for teaching and research, (d) exclusion from social circles and conversations, (e) interrupting or spreading rumors and gossip about a professor, and (f) acrimonious verbal behavior, such as yelling, gaslighting, interrupting, microaggressing, or silencing (Ahmad, Kalim, & Kaleem, 2017; Keashly & Neuman, 2010; May & Tenzek, 2018; Neuman, 2010; Wood, 2016). In the context of business and economics faculty, the most likely victims of mobbing are females between 31 and 50 years old and they mainly suffer from rumors, scrutiny, criticism, discounting of accomplishments, exclusion, and being ganged up against by a group formed by the bully (Raineri, Frear, & Edmonds, 2011).

Miles, Shepherd, Rose, and Dibben (2015) show that work satisfaction, mutual support/trust, equity/politics, and fairness of performance evaluations are all factors in the definition of collegiality for business school academics. Given our findings that female professors of all ranks have significantly lower AS, their intradepartmental experience of collegiality is also at risk. To counter potential collegiality issues experienced by female faculty in marketing departments, metrics-based data-driven assessments of meritorious accomplishments for research, service, and teaching should be implemented, rather than seniority and homophily as the most important drivers of rewards (Krishen & Petrescu, 2019).

Limitations and Future Research

Our research is limited by a sample that only considers gender, rank, and whether the institution is PhD-granting. Future research should address additional factors directly through another survey instrument of AACSB-accredited business schools that asks faculty about their experiences of second shift, mobbing, bullying, incivility, agency, and so on, using validated constructs from Gabriel, Butts, Yuan, Rosen, and Sliter (2017) and Minibas-Poussard (2018). There are also opportunities to examine the implications of faculty diversity and formal mentoring programs in future research. Based on our findings, our expectation is that there will be significant differences between faculty experiences of inequity, especially at the intersections of race, sexual orientation, gender, rank, and type of institution. Results of our study provide implications for practice as many institutions are digitizing academic performance such that administration has better access to tools for data-driven decision making. As such, department chairs and business school administrators can utilize faculty metrics, or key performance indicators, to level the playing field and provide clear comparative analytics for research, teaching, and service. Additionally, administrators should be able to understand that the value proposition of faculty is not “one size fits all” and may need to be negotiated to create a better fit of expectations, motivation, and incentives.

Future research can extend our findings in many ways, such as addressing some of the following questions:

Why do women faculty leave academic positions on their own versus due to tenure decisions? Is the exit rate consistent between rank, gender, ethnicity, sexual orientation, and intersections of them?

What is the ratio of female versus male business school department chairs? What is the length of service, and future career trajectory for those chairs in their institutions? How many female chairs move into higher levels of administrative responsibilities outside of their college? What insights might female chairs provide regarding subtle biases?

What is the current proportion of female editors, associate editors, and editorial review board members for all of the marketing journals? How do those numbers map to the topics and author genders in those journals?

Are there stories of mobbing and bullying in business schools that are shared? Are there retaliation-free mechanisms to share those stories? How might those stories be told using social media to help move academia forward in a positive way?

In comparison with other schools (e.g., life sciences, nursing, engineering, sociology), what are the objective numbers of female full professors, chaired positions, and endowed professorship positions in business schools? How do the subjective measures of professors in those positions, such as satisfaction, compare with other schools?

How does the intersectionality of academics affect gender and racial biases with regard to all of the aforementioned issues, particularly in business schools (Crenshaw, 1989; Kachen & LaTour, 2019)?

Footnotes

Appendix

Acknowledgements

The authors gratefully acknowledge the editors of this issue, Professors Victoria Crittenden, Cassandra Davis, and Rebeca Perren, for providing comments and insights regarding our article, as well as the reviewers of our article for helping us improve our contribution to the field.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Anjala S. Krishen

Notes

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