Distributive Justice in Higher Education:Perceptions of Administrators

Shawn M. Fitzgerald & Daniel Mahony &

Fashaad Crawford & Hope Bradley Hnat

# Springer Science+Business Media New York 2014

Abstract For the study we report here we used the theoretical framework of organizationaljustice to examine academic administrator’s perceptions of resource distribution decisions. Weasked deans, school directors, and department chairs in one midwestern state about their percep-tions of the fairness and likelihood of use of various distribution principles in scenarios involvingdistributions of compensation to faculty and resources to schools/departments. Differences basedon Carnegie classification and current position were examined. Overall, we found that participantsperceived compensating faculty members and allocating resources to departments based on thequality of teaching and impact on students was most fair, but they believed factors such as

Innov High EducDOI 10.1007/s10755-014-9287-2

ShawnM. Fitzgerald is Director of the School of Foundations, Leadership and Administration in the College ofEducation, Health, and Human Services at Kent State University. He received the B.A. from Lebanon ValleyCollege and the M.Ed. and Ph.D. from the University of Toledo. His research has focused on instrumentdevelopment, teaching statistics, and program evaluation.

Daniel F. Mahony is Dean and Professor in the College of Education, Health, and Human Services at Kent StateUniversity. He received the B.S. from Virginia Tech, the M.S. fromWest Virginia University, and the Ph.D. fromOhio State University. His research is focused on organizational justice across organizational types, sportconsumer behavior, and faculty recruitment. Email contact: dmahony@kent.edu

Fashaad Crawford is the Assistant Provost for Accreditation, Assessment, and Learning at Kent State University.He received the B.A. from South Carolina State University and theM.S. and Ph.D. from the University of Louisville.His research has focused on higher education administration, assessment, and student success.

Hope Bradley Hnat is the Director of Donor Relations for The Salvation Army. She received her B.A. inpsychology and M.A. in higher education administration from The University of Akron. Her research is focusedon organizational justice and fundraising.

S. M. Fitzgerald : D. Mahony (*)College of Education, Health, and Human Services,Kent State University,408 White Hall,Kent, Ohio 44242, USAe-mail: dmahony@kent.edu

F. CrawfordAssistant Provost for Accreditation, Assessment, and Learning,Kent State University,408 White Hall,Kent, Ohio 44242, USA

H. B. HnatThe Salvation Army,Akron, OH, USA

research productivity and funding secured were more likely to be used. While there were nodifferences based on current position, there were differences based on Carnegie classification withthe research universities indicating greater preference for and likelihood of using researchprinciples and non-research institutions indicating greater likelihood of using equality.

Key words distributive justice . fairness perceptions . resource distributions . facultycompensation

As access to resources in higher education continues to grow increasingly competitive, resourcedistribution decisions become more important. These distribution decisions can impact a highereducation institution and its employees in a variety of ways (Colquitt, 2001). This focus onresource distribution is not unique to higher education. There is a long history of research onorganizational justice, which focuses on examining distributions made in a variety of organi-zational settings, as well as the impact of those distribution decisions (Colquitt, Greenberg, &Zapata-Phelan, 2005). For example, researchers have found that perceptions of organizationaljustice impact variables such as job performance, organizational commitment, job satisfaction,turnover intentions, organizational citizenship behaviors, and trust (e.g., Colquitt, 2001;Cropanzano, Rupp, Mohler, & Schminke, 2001). Despite the long line of organizational justiceresearch, it has rarely been applied to higher education. The few studies that exist have generallyonly applied to specific decisions such as tenure and promotion (Ambrose & Cropanzano,2003) or unique areas of higher education such as intercollegiate athletics (e.g., Hums &Chelladurai, 1994; Mahony, Hums, & Riemer, 2002, 2005; Mahony & Pastore, 1998;Patrick, Mahony, & Petrosko, 2008). With our study we sought to expand the application ofthe organizational justice framework within higher education.

Resource Distribution in Higher Education

Most of the literature on higher education resource distribution has centered on state or systemwide processes (e.g., Banta, Rudolph, VanDyke, & Fisher, 1996; Liefner, 2003; Santos, 2007)while less attention has focused on institutional resource allocation processes (Koch, 1974;Casper & Henry, 2001). However, there has been some work in this area. Pfeffer and Salancik(1974) explored the effect of subunit power on resource allocations at a single university andfound measures of departmental power were significantly related to the proportion of resourcesreceived, even after controlling for workload of the department, national rank, and number offaculty members. Several years later, Hackman (1985) found internal resource allocations wereinfluenced by the congruency or centrality of a unit’s goals with those at the core of theinstitution. The focus on goals has often led to discussions about the relative priority placedby the institution on teaching and research. Santos (2007) conducted an analysis of internalresource distributions at 10 major public research universities. The results indicated teaching/instruction, and not research, was the primary priority for public research university resourceallocations. However, he also found that departments with more access to grants (e.g., engineer-ing) received larger allocations than those with less grant activity and that graduate educationwas rewarded more in these departments than undergraduate education, suggesting that theimpact of research productivity may be more complicated than the initial findings suggest.

More recently, Knight, Folkins, Hakel, and Kennel (2011) examined whether or not views ofacademic administrators on resource allocation fluctuated according to the discipline receivingthe funding. They surveyed academic administrators at doctoral-research universities regarding

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their resource allocation decisions and found that the discipline (hard/soft) impacted resourceallocation decisions. For example, academic administrators perceived hard-applied (e.g., me-chanical engineering) and hard-pure (e.g., physics) academic areas as having faculty memberswho are associated with greater research productivity, securing more external grant funding,and offering courses more aligned with market/workforce needs. Therefore, greater resourceswere more likely to be distributed to these areas in comparison to soft academic areas.

Research has also examined distributions to individual faculty members. In his nationalstudy on faculty salary distributions, Fairweather (2005) examined the relative importance ofteaching and research productivity on salaries. In his earlier studies, Fairweather (1996, 1997)had found that publishing more and teaching less resulted in higher faculty salaries acrossdifferent types of 4-year institutions. He suggested that this phenomenon was related to theemphasis on enhancing universities’ reputation through research productivity (Fairweather,1995). He defined teaching productivity in terms of the number of hours spent in theclassroom, use of collaborative instruction, and types of students taught. Research productivitywas based on refereed publications and service as a PI on an externally funded project. Whilethere were different findings in a few cases, Fairweather (2005) again found teaching more,particularly undergraduate students, was negatively related to pay while research productivityhad a positive impact. Moreover, these impacts were more likely to have increased than tohave decreased over time.

There are several important implications emerging from the prior higher education researchwhich lead to the current study. First, administrators should not expect teaching will be naturallyrewarded, even at institutions at which teaching is identified as a top priority (Fairweather, 2005).Moreover, the commonly espoused theory that good teaching and good research naturally gotogether is not well supported by the literature (Fairweather, 2002; Hattie & Marsh, 1996).Second, as has been found in other settings, the activities of bothmanagers and academics appearto be influenced by resource allocations in higher education (Liefner, 2003).

Taken together, research suggests that examinations of distribution processes are important.While prior research has made valuable contributions to our understanding of resource distri-bution, there is still much that is unknown. The variables used to assess the productivity andquality of both teaching and research have had to be defined by the researchers in these studies,and it is not always clear that they capture the variables decision makers believe are important.In addition, past research has made assumptions about the relative importance decision makersplace on teaching and research as opposed to asking them directly about the importance theyplace on these and other factors. Our study seeks to close these gaps in the literature.

Organizational Justice Research

One possible theoretical framework for examining resource distribution decisions and theirimpact in higher education is organizational justice, and our study focused on the distributivejustice aspect of organizational justice. Adams’ (1963, 1965) Equity Theory led to interest inthis area of research (Mahony, Hums, Andrew, & Dittmore, 2010). Adams believed individ-uals compare their ratio of outcomes to contributions to others’ ratios of outcomes tocontributions to determine if the outcomes distributed to them are fair. When the ratios areequal, they tend to believe these distributions are fair. However, if the ratios are unequal, theywill perceive the situation as unfair; and this perception will often impact their future behavioras they try to make the situation fair. The equity theory suggests that people believe that thosewho contribute the most should receive the greatest outcomes and that those who contributethe least should also receive the least.

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While this principle of equity (or contribution) is one means for determining distribution ofresources, it is not the only method people believe is fair. Deutsch (1975) said some personsmight perceive either equal or need based distributions as fair. Some scholars have alsosuggested that the use and preference among these three major distribution principles (i.e.,equity, equality, need) may be impacted by the type of organization making the distributions(e.g., Deutsch, 1975; Sheppard, Lewicki, & Minton, 1992). Therefore, researchers have foundthat it is important to examine distributive justice principles and sub-principles in variousorganization types in order to determine what is perceived to be most fair in each setting.

While definitions of equality tend to be relatively consistent (i.e., all groups are treated the samewhen making distribution decisions), definitions of need were not well understood until Mahonyet al. (2005) identified three definitions of need when examining intercollegiate athletic adminis-trators. In that study, respondents indicated the athletic teams with the greatest needs were thosethat (a) currently had fewer resources than other teams, (b) costs where naturally higher (e.g., moreathletes were needed in that sport, equipment costs were greater in that sport), or (c) they had tospend more money to compete with other teams (i.e., they needed money to be competitivelysuccessful). While these three characteristics, or sub-principles of need, were identified in a studyfocused on intercollegiate athletics, Mahony and his colleagues argued that they could be appliedto a variety of organizations, including the academic side of higher education.

Although definitions of need and equality are believed to be more consistent acrossorganizations, that is not as likely with definitions of equity (or contribution). Importantorganizational contributions vary based on the goals of the organization. Tornblom andJonsson (1985) were the first to attempt to identify sub-principles of equity: (a) productivity,(b) effort, and (c) ability. In other words, individuals or groups within an organization may beseen as being more worthy of receiving resources if they are more productive, give more effort,or have more ability than others. In their examination of intercollegiate athletics, Hums andChelladurai (1994) defined productivity in that setting as wins. They also added spectatorappeal, and Mahony et al. (2002) later added revenue production as another equity sub-principle in this setting.

Because sub-principles of equity vary across organizational types, (i.e., sub-principles incollege athletics were different than those in business), an important first step in distributivejustice research is to identify the key contributions individuals or groups can make to anorganization. Based on this premise, Bradley, Crawford, Fitzgerald, and Mahony (2013)conducted a qualitative study in which they interviewed deans to determine the importantcontributions in academia. They identified five possible contributions in their study: (a) quantityand quality of research publications, (b) external research funding, (c) quality of teaching, (d)impact on students, and (e) quality service. The study we report here builds on that work byexamining the key contributions that faculty member and departments or schools can make andthe ways these contributions may influence resource distributions in higher education.

Method

Data for this study were generated from a survey of deans and chairs/directors employed atpublic and private higher education institutions in one midwestern state.

Participants

The total number of respondents consisted of 126 administrators for a response rate of 10.52%.Based on the data from those who responded to the demographic questions, the majority of

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respondents were Caucasian (n = 102, 89%), male (n = 67, 61%) and ranged in age from 40 to 72(M = 55). Sixty percent (n = 68) were department chairs or directors while 40% (n = 46) indicatedthey were serving as a dean, assistant dean, or associate dean. Most were employed at publicinstitutions (n = 88, 75%) that were classified as either a research university (n = 43, 37%) ordoctoral/research intense university (n = 39, 34%). The number of years in higher educationranged from 10 to 43 with an average of just over 25 years. The total number of years as anacademic administrator varied from less than one full year to over 30 years (M = 9.5).

Questionnaire

The online questionnaire was composed of six sections, each constructed following guidelinesspecified by Dillman (2000) for questionnaire and survey development. The research teamreviewed the survey to assess both face and content validity. Sections of the 50-item surveyincluded questions focusing on demographic characteristics, compensation practices for fac-ulty members, resource distribution methods for schools/departments, organizational commit-ment, job satisfaction, and turnover intentions. Only three sections, demographic characteris-tics, compensation practices, and resource distribution methods, were analyzed for this study.

Compensation This section of the survey focused on principles for distributing compensationamong faculty members. Based on the work of Bradley et al. (2013), five sub-principles ofequity/contribution were examined: (a) quantity and quality of research publications, (b)external research funding, (c) quality of teaching, (d) impact on students, and (e) qualityservice. One item was used to examine equality (i.e., compensation would be distributedequally to all faculty members). Finally, two of the three sub-principles of need identified byMahony et al. (2005) were used to examine need: (a) need due to lack of resources and (b)need in order to be competitively successful. The third sub-principle of need, the naturally highcost of a program, did not apply in a compensation situation. Similar to prior research(Mahony et al., 2002), participants were asked to indicate the level of fairness and thelikelihood of using each method based on a 7-point Likert scale. When considering fairnessthe response choices ranged from “1” (Very unfair) to “7” (Very fair), and when consideringlikelihood of use response choices ranged from “1” (Very unlikely) to “7” (Very likely).

Resource distribution This section of the survey focused on principles for distributing re-sources among schools and departments in higher education. Based on the work of Bradleyet al. (2013), the same five items of the sub-principles of equity/contribution were examined.In addition, a sixth sub-principle of equity/contribution was added – (f) highest studentenrollment. While it was not mentioned specifically by the deans in the Bradley et al. study,those authors noted that the deans in that study focused more on faculty contributions thandepartment contributions. Further, previous studies suggested allocating resources according topure economic approaches (Johnson & Turner, 2009) such as student demand and enrollment(Casper & Henry, 2001).

To explore perceptions of faculty productivity and enrollment on resource distribution, oneitem was used to examine equality (i.e., compensation would be distributed equally to alldepartments). Finally, all three sub-principles of need identified by Mahony et al. (2005) wereused to examine need: (a) need due to lack of resources, (b) need in order to be competitivelysuccessful, and (c) need due to the high cost of the program. Again, participants were asked toindicate the extent to which they believed each method was fair or unfair and the likelihood ofusing each method based on the same 7-point Likert scales used for compensation.

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Demographic characteristics Demographic questions asked participants to indicate age, eth-nicity, gender, administrative appointment (dean/chair), Carnegie classification (research/non-research), type of university/college (public/private), number of years as an academic admin-istrator, and number of years in their current academic position. We examined differencesbased on Carnegie Classification and administrative appointment. We expected that theresearch institutions would perceive the research items were fairer and more likely to be used.We also expected that deans might differ from department chairs and school directors becauseof differences in the amount of control each had with regards to compensation and resourcedistribution decisions.

Procedures

A list of deans’ and chairs’ emails was developed based on reviews of public and privateuniversity and college websites. Before distributing the survey, we had received approval fromthe Institutional Review Board. Following standard protocol for online survey administrationsuggested by Dillman (2000), a pre-notice email invitation was sent to the distribution listasking for participation and providing an opportunity for any recipient to opt out of the study.Two weeks after the pre-notice email, the survey invitation was sent via an email with anexplanatory cover letter from members of the research team, followed by a “reminder” emailtwo weeks later. Based on data gathered from university and college websites there were 1,669positions at the chair, director or dean level. Of those, 271 did not have a contact nameassociated with a position or email address listed, 148 were associated with email addressesthat were no longer functional, and 53 asked to be removed from the survey leaving 1,197potential respondents. 126 responded to the survey for a response rate of 10.52%.

The lower response rate was likely related in part to a problem with the listserv used todistribute the survey. When sending the “reminder” email two weeks after the survey invitationemail, several respondents did not follow the directions for being removed from the listserv and,instead, responded to the entire listserv. The large number of unwanted emails may have led someto choose not to participate. However, it is important to note that no problems occurred during theinitial survey invitation email; and some still did respond as a result of the reminder email.Therefore, it is likely the low response rate was a result of using an online survey and commonresponse issues with the population for this study. Ameta-analysis conducted by Lozar-Manfreda,Bosnjak, Berzelak, Haas, and Vehovar (2008) revealed web survey response rates tended to beapproximately 10 percent lower than other survey approaches. Moreover, other researchers havefound that university administrators do not respond at a high rate. In fact, Knight et al. (2011) alsohad a response rate of less than 20% when examining university administrators, so the responserate in the current study appears not to be unusual for this population.

Given that the response rate for this study was lower than desired and thus susceptible topotential non-response bias, we assessed the potential for bias across four different demo-graphic variables–-gender, university research classification (i.e., research or non-research),university type (i.e., public or private), and administrator classification (i.e., dean or chair/director).To determine whether the proportion of responses in each of these demographicgroups in the sample differed from those observed in the population surveyed, we used a chi-square goodness-of-fit test. Analyses revealed no significant differences in the proportionsobserved in the sample compared to the population for gender, X2 (1, N = 110) = 0.45, p > .05,university classification, X2 (1, N = 102) = 0.13, p > .05, university type, X2 (1, N = 117) =1.01, p > .05, or administrator classification, X2 (1, N = 116) = 2.77, p > .05.

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Research Questions

We investigated the following research questions in this study:

Research question 1. What distribution principles and sub-principles do higher educationadministrators perceive as being most fair and most likely to be used when distributingcompensation to faculty?Research question 2. What distribution principles and sub-principles do higher educationadministrators perceive as being most fair and most likely to be used when distributingresources to departments/schools?Research question 3. Do perceptions of fairness and the likelihood of using differentcompensation methods differ by university Carnegie classification (Research/Non-Research)?Research question 4. Do perceptions of fairness and the likelihood of using differentresources distribution methods differ by university Carnegie classification (Research/Non-Research)?Research question 5. Do perceptions of fairness and the likelihood of using differentcompensation methods differ by university administrative position (Dean/Chair)?Research question 6. Do perceptions of fairness and the likelihood of using differentresources distribution methods differ by university administrative position (Dean/Chair)?

Statistical Analyses

A series of repeated measures ANOVAs were used to investigate the research questionsconsidered for this study. To address the first two research questions we used a set of foursimple, repeated-measures ANOVAs, using the ratings on each method considered as depen-dent variables. These analyses investigated differences in perceptions of fairness and thelikelihood of using various compensation and resources distribution methods for all respon-dents. Pairwise comparisons were carried out when statistically significant differences inresponse pattern were observed. In order to control for an increase in the type I error rate aBonferroni adjustment was used in performing all pairwise comparisons.

For questions 3 through 6, we applied a second series of repeated measures ANOVAs.These analyses were conducted using one between factor (classification) and one within factor(perceptions of fairness across compensation and resources distribution methods). Both maineffects for compensation method and resources distribution were considered, as well as theinteraction effect of method by Carnegie classification (questions 3 and 4) and administrativelevel (questions 5 and 6). When interactions were observed, only these effects were interpretedas the main effects would not fully describe the differences in the ratings observed. To interpretthe interaction effects, we followed with tests of simple main effects to detect where differ-ences in ratings were moderated by Carnegie classification and administrative level. We usedSPSS (2009) to analyze these data.

Results

Table 1 presents a summary of the means for the perceived fairness and likelihood of usingeach compensation practice for each group considered in the study. Table 2 presents a

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summary of the means for the perceived fairness and likelihood of using each resourcesdistribution practice for each group considered.

Research Question 1

Fairness of compensation method Statistically significant differences were observed whenconsidering perceptions of fairness across the different compensation methods, F (4.57,516.36) 39.16, p < 0.01. Compensating faculty members based on the quality of teachingwas perceived as most fair while respondents perceived equal distribution of compensation andcompensation based on faculty need (those paid less should receive more) as less fair than allother methods.

Likelihood of using compensation method When considering perceptions related to the like-lihood of using different compensation methods, statistically significant differences wereobserved, F ( 3.34, 380.71) 22.46, p < 0.01. Respondents perceived compensation based onthe quality and quantity of publications, research funding secured, and on competitive rates inthe discipline as being more likely while compensation based on faculty need (those paid lessshould receive more) was viewed as less likely than all others methods.

Research Question 2

Fairness of using resource distribution method Statistically significant differences were ob-served when considering perceptions of fairness across the different compensation methods, F(5.61, 637.76) 25.63, p < 0.01. Distributing resources based on the quality of teaching and the

Table 1 Perceptions of Fairness and Likelihood of using Various Compensation Practices for Faculty Membersby Total Sample, Position, and Carnegie Research Designation

Distributing compensation in accordance with: Total(M)

Deans(M)

Chairs(M)

Res.(M)

Non-Res. (M)

The quantity & quality of researchpublications produced

Fairness 4.77 4.84 4.64 5.01 4.06

Likelihood 4.50 4.71 4.33 5.09 3.18

The research fundingsecured Fairness 4.42 4.70 4.20 4.68 3.77

Likelihood 4.51 4.87 4.23 5.33 2.62

The quality of teaching Fairness 4.99 5.18 4.85 4.98 5.10

Likelihood 3.80 4.07 3.59 3.91 3.53

The impact faculty have on students Fairness 4.80 5.07 4.62 4.88 4.71

Likelihood 3.39 3.64 3.17 3.43 3.26

The service contributions made Fairness 4.57 4.86 4.42 4.58 4.77

Likelihood 3.25 3.51 2.94 3.25 3.12

An equal distribution to faculty members Fairness 2.90 3.00 2.82 2.73 3.29

Likelihood 3.17 2.76 3.32 2.72 4.12

The needs of the faculty (paid less receive more) Fairness 3.16 3.05 3.24 3.06 3.42

Likelihood 2.71 2.71 2.59 2.61 2.94

The competitive rates in the discipline Fairness 4.21 4.05 4.26 4.28 3.90

Likelihood 4.16 4.53 3.89 4.30 3.88

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impact that faculty members have on their students was perceived as most fair while respondentsperceived an equal distribution of resources to faculty members as less fair than all other methods.

Likelihood of using resource distribution method When considering perceptions related to thelikelihood of using different compensation methods, statistically significant differences wereobserved F (5.64, 614.83) 24.36, p < 0.01. Quantity and quality of research articles, researchfunding secured, needs due to high costs, needs to stay competitive, number of credit hours,and enrollment growth were all viewed more positively while distributing based on the servicecontributions made, an equal distribution across faculty members, and individual unit needs(those with less, need more), were viewed as less likely than all other methods.

Research Question 3

Fairness of compensation methods Both the main effect of method and the interaction effectof method by classification were significant, F (4.66, 508.46) 26.48, p < 0.01 and F (4.66,508.46) 3.91, p < 0.01, respectively. To interpret the interaction effect, we used tests of simplemain effects to detect where differences in ratings were moderated by Carnegie classification.

Table 2 Perceptions of Fairness and Likelihood of using Various Resources Distribution Practices by TotalSample, Position, and Carnegie Research Designation

Distributing resources in accordance with: Total(M)

Deans(M)

Chairs(M)

Res.(M)

Non-Res.(M)

The quantity & quality of researchpublications produced

Fairness 4.64 4.98 4.44 4.81 4.34

Likelihood 4.04 4.47 3.66 4.43 3.03

The research funding secured Fairness 4.24 4.53 4.05 4.31 4.16

Likelihood 4.30 4.67 4.03 4.83 3.03

The quality of teaching Fairness 5.15 5.48 4.92 5.07 5.37

Likelihood 3.40 3.56 3.28 3.42 3.41

The impact faculty have on students Fairness 4.91 5.23 4.70 4.85 5.09

Likelihood 3.30 3.49 3.15 3.34 3.25

The service contributions made Fairness 4.51 4.95 4.24 4.49 4.63

Likelihood 2.87 2.95 2.78 2.81 3.06

An equal distribution to all academic units Fairness 2.88 2.97 2.76 2.72 3.22

Likelihood 2.55 2.47 2.62 2.34 3.03

Needs –units that need most get most Fairness 3.97 4.05 3.82 3.88 4.16

Likelihood 2.91 3.02 2.88 2.77 3.25

Needs-units with high cost get most Fairness 4.46 4.47 4.42 4.23 4.88

Likelihood 4.02 4.05 4.03 3.84 4.47

Needs-most to units that need to staycompetitive

Fairness 4.46 4.42 4.44 4.27 4.81

Likelihood 3.90 4.19 3.80 3.95 3.88

The units with most credit hours get more Fairness 4.14 4.40 3.95 4.08 4.19

Likelihood 4.22 4.56 4.08 4.38 3.94

The units with most enrollment growthget more

Fairness 4.79 5.08 4.59 4.81 4.66

Likelihood 4.30 4.70 4.09 4.45 4.00

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Two simple main effects were observed. Differences existed in perceptions of fairness relatedto quantity and quality of research publications and external research funding, F (1, 113) =9.14, p < .01 and F (1, 113) = 9.75, p < .01 respectively. Respondents from researchinstitutions perceived distributing compensation in accordance with the quantity and qualityof research publications (M = 5.02) and the external research funding (M = 4.68) as being morefair than did respondents from non-research institutions (M = 4.12 andM = 3.71, respectively).

Likelihood of using compensation methods Both the main effect of method and the interactioneffect of method by classification were significant, F (3.83, 425.49) 10.81, p < 0.01 and F (3.83,425.49) 19.00, p < 0.01, respectively. To interpret the interaction effect we followed with tests ofsimple main effects to detect where differences in ratings were moderated by Carnegie classifica-tion. Three simple main effects were observed. Differences existed in perceptions of fairnessrelated to the quantity and quality of research publications, equal research funding, and equaldistribution to faculty members F (1, 113) = 26.91, p < .01, F (1, 113) = 70.94, and F (1, 113) =14.58, p < .01 respectively. Respondents from research institutions perceived distributing com-pensation in accordance with the quantity and quality of research publications (M = 5.04) andexternal research funding (M = 5.28) as being more likely than did respondents from non-researchinstitutions (M = 3.18 and M = 2.62, respectively). Respondents from research institutionsperceived distributing compensation equally across faculty (M = 2.70) as being less likely thandid respondents from non-research institutions (M = 4.12).

Research Question 4

Fairness of resource distribution methods Although the main effect of method was significant,F (6.01, 631.22) = 19.86, p < .01, the interaction effect of method by classification was not, F(6.01, 631.22) = 1.60, p > .05, so no further analysis was conducted.

Likelihood of using resource distribution methods Both the main effect of method and theinteraction effect of method by classification were significant,F (6.29, 673.26) 15.70, p < 0.01 andF (6.29, 673.26) 8.30, p < 0.01, respectively. To interpret the interaction effect we followed withtests of simple main effects to detect where differences in ratings were moderated by Carnegieclassification. Three simple main effects were observed. Differences existed when considering thelikelihood of using quantity and quality of research publications, F (1, 108) = 12.90, p < .01,external research funding,F (1, 108) = 25.33, p < .01, and equal distribution of resources to facultymembers, F (1, 108) = 4.96, p < .01. Respondents from research institutions perceived distributingcompensation in accordance with the quantity and quality of research publications (M = 4.43) andexternal research funding (M = 4.83) as being more likely than respondents from non-researchinstitutions (M = 3.12 and M = 3.06, respectively). Respondents from research institutionsperceived distributing compensation equally across faculty (M = 2.34) as being less likely thanrespondents from non-research institutions (M = 3.03).

Research Question 5

Fairness of compensation methods While the main effect of method was significant, F (4.71,508.69) 35.91, p < 0.01, the interaction effect of method by classification was not, F (4.71,508.69) 1.13, p > 0.05, so no further analysis was conducted.

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Likelihood of using compensation methods Again, the main effect of method was significant,F (3.34, 3.64.01) 22.70, p < 0.01 the interaction effect of method by classification was not, F(3.34, 3.64.01) 1.82, p > 0.05, so no further analysis was conducted.

Research Question 6

Fairness of resource distribution methods Although the main effect of method was significant,F (5.98, 621.96) = 24.36, p < .01, the interaction effect of method by classification was not, F(5.98, 621.96) = 0.81, p > .05, so no further analysis was conducted.

Likelihood of using resource distribution methods Although the main effect of method wassignificant, F (5.78, 612.94) = 25.21, p < .01, the interaction effect of method by classificationwas not, F (5.78, 612.94) = 1.61, p > .05, so no further analysis was conducted.

Discussion

The findings from this study have implications for both future research and college leaders. Whenexamining perceptions of fairness, respondents viewed distributing resources equally to facultymembers and departments/schools as less fair than other methods. In addition, distributingresources based on need was believed to be less fair when distributing compensation to the faculty.These findings are interesting for two reasons. First, distributions based on equality and need weregenerally perceived as being among the most fair distribution principles in the intercollegiateathletics studies (Hums & Chelladurai, 1994; Mahony, et al., 2002; Mahony, et al., 2005; Patrick,et al., 2008). Due to its competitive nature and history of disproportionate distribution of resources(Mahony & Pastore, 1998), one might predict intercollegiate athletics would be less likely toperceive these principles as fair, not more likely. Second, making distributions based on equality(e.g., at least a portion of raises being across the board, increasing budgets by a certain percentagefor all) does not appear to be unusual on the academic side. This is particularly true at universitieswith unionized faculty, which was the case for some of the universities in this study.

The distribution principles perceived as being most fair in both of these scenarios related toteaching. In the compensation scenario, quality of teaching was perceived as more fair than theother principles while in the department/school distribution scenario the quality of teaching andthe impact of faculty members on students were perceived as the most fair principles. Thestrong support for teaching across the institutions surveyed would seem to suggest that teachingis the most valued contribution for both faculty members and departments/schools. This wouldbe in conflict with much of the prior research (e.g., Fairweather, 1996, 1997, 2005).

However, in our study we found that there was a difference between what was perceived asbeing fair and what respondents indicated as being most likely to be used. In the facultycompensation scenario, the research principles (quantity and quality of research publicationsproduced and research funding secured) and need based on the competitive rates in thediscipline were identified as being more likely to be used. These same principles wereperceived as being more likely to be used in the second scenario along with need due to highcosts, credit hour production, and enrollment growth. These results are interesting for tworeasons. First, prior research that asked about both likelihood to be used and perceptions offairness found little difference in the ratings of the principles (Mahony et al, 2002). In other

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words, respondents generally indicated the principles they believed were fair were also likelyto be used. The current study is the first to find a clear difference in this pattern. Second, therespondents in this study appear to be in decision-making positions, yet they still believeddistributions are not being made based on the principles they believe are most fair. Becausethere were no differences in this pattern between the chairs/directors and deans, this raisesquestions about the degree to which both groups have control over the distribution ofcompensation and other resources.

There were fewer differences between perceptions of fairness and likelihood of use forthose principles rated lower. As was the case with fairness perceptions, distributing compen-sation and resources to departments based on need (those with less need more) and equalitywere generally perceived to be less likely. So, while there were differences between percep-tions and likelihood for those principles rated as fairer or more likely, there was generallygreater consistency for those rated lower.

While there were no differences between respondents based on position, there were differ-ences based on the Carnegie classification of their institution. Some of these differences wereexpected. In the compensation scenario, respondents from research institutions were morelikely to indicate distributions based on the quantity and quality of publications and externalresearch funding were both more fair and likely to be used. While they did not indicate theseprinciples were fairer when distributing resources to departments, they did indicate they weremore likely to be used. Overall, the research university respondents indicated stronger supportfor the research related principles, which was predictable. The other significant difference basedon Carnegie classificationwas that the non-research institutions indicated distributions based onequality were more likely to be used in both scenarios than did those at research institutions.

These results raise questions and have implications for both practice and future research. Ingeneral, there was stronger support for equity or contribution principles than equality and needbased principles, with the exception of need based on high costs or competition. While manyhave expressed concerns about the move toward more of a business approach in highereducation e.g., Fredman & Doughney, 2012; Katopes, 2009), the strong support for distribu-tions based on contribution suggest this is what is happening. Deutsch (1975) indicatedequality was used in organizations emphasizing positive social relations and a sense of“common fate” (Sheppard, et al., 1992) while need was more common where there was anemphasis on personal growth and the survival of group members. In contrast, Deutschsuggested that equity or contribution was more common when the goal was economicproductivity. The fact that administrators said equity principles were more likely to be usedsuggests that higher education is focused more on the latter than the former goal. One questionis whether this has always been the case or whether this is the result of changes over time (e.g.,decreased state funding). Further research would be needed to help answer this question.

The differences between perceptions of fairness and likelihood of use also have possibleimplications for practice and research. Prior research found that organizational justice percep-tions impact variables such as job performance, organizational commitment, job satisfaction,turnover intentions, organizational citizenship behaviors, and trust (e.g., Colquitt, 2001;Cropanzano, et al., 2001). It is reasonable to predict that inconsistencies between whatrespondents believe is fair and the principles being used would negatively impact thesevariables. This would be a particularly interesting case to examine in future research becausethe administrators are in positions that one would assume would have some input and powerwith regards to the distributions. The impact of feeling powerless may have a stronger impacton variables such as job satisfaction for those who are in leadership positions. It would also beinteresting to examine whether these inconsistencies exist for the faculty as well and thepossible impact of those inconsistencies. .

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Finally, research is needed to determine why those who appear to be in decision makingpositions (i.e., deans, department chairs, school directors) do not believe the principles beingused are those they believe are most fair. There may be at least two possible reasons for this.First, it is possible they are not actually making the decisions about resource distributions.Depending on the institution, they might have less impact on some of these distributiondecisions. This lack of control might exist for several reasons including (a) the centraladministration dictates the distribution of resources;, (b) the institutions have established goalsfor units and their leaders that “force” deans, department chairs, and school directors to makecertain distribution; and/or (c) there are agreements or policies in place reducing their decision-making flexibility, such as faculty union contracts or agreements with faculty members ordepartments/schools signed by previous administrators. They may also believe resourcedistributions are dictated by the market (i.e., they must reward research more becausecompeting institutions reward research more). Research would be needed to determine theextent to which these groups believe they have control over distributions in these two scenariosand the reasons for the lack of control if they believe that is the case. It is also important to notethat our study only examined a sample of administrators in one midwestern state in the UnitedStates. There may be regional or national differences in the amount of control individuals inthese roles have over resource distributions, so this could also be the focus of future research.

Second, it is possible that they rely more on variables which are easier to measure whenmaking distribution decisions. In general, respondents said the research variables were morelikely to be used even though the teaching related variables were considered to be among themost fair. This may be because research is perceived as easier to measure. In the Bradley et al.(2013) study, the comments of the deans would appear to support this. They often mentionedmore precision when measuring research (e.g., the number of articles published, quality ofjournals, research funding generated) than when talking about how they measured qualityteaching and impact on students. In fact, there has been variance in how teaching is measuredin the literature. For example, the measures of teaching productivity utilized by Fairweather(2005) were generally different than those identified by the deans in the study by Bradley andher colleagues. Hattie and Marsh (1996) also found that the quality of teaching was defined ina variety of ways in their review of past research.

Moreover, the finding in the current study that the non-research institutions indicatedgreater likelihood of use of equal distributions supports the theory that measuring teachingmay be more difficult. Because these institutions place less focus on research, it is notsurprising that they indicated less likelihood of using those principles. However, one wouldpredict a greater use of the teaching principles because of the heavy emphasis at theseinstitutions on teaching. Instead, the principle on which they were different was equality,which is also easy to measure. This inconsistency between the stated goals of these institutions,which often focus on teaching quality, and the low likelihood of making distributions based onteaching could be because the stated goals are not the real goals. However, it is also possiblethe reasons are more complex and have to deal with issues of measurement. Further researchwould be needed to determine how much impact ease of measurement, as opposed to trueorganizational goals, has on distributions.

Conclusion

Overall, the results of this study were another step in understanding organizational justice inhigher education and ultimately its impact on key organizational variables. The findings weredifferent in important ways from what has been found in prior research and raise a number of

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questions that should lead to further research on the perceptions of both higher educationadministrators and faculty members.

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