Journal of Organizational Behavior
J. Organiz. Behav. 24, 25–44 (2003)
Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/job.178
Predicting early career research
productivity: the case of management
faculty
IAN O. WILLIAMSON1* AND DANIEL M. CABLE2
1
University of Maryland, Robert H. Smith School of Business, College Park, MD 20742-1815, U.S.A.
University of North Carolina at Chapel Hill, The Kenan-Flagler Business School, Chapel Hill, NC
27599-3490, U.S.A.
2
Summary
We used a longitudinal design to examine the predictors of early career research productivity
for 152 management professors over the first six years of their career. Results revealed early
career research productivity to be a function of dissertation advisor research productivity, preappointment research productivity, and the research output of a faculty member’s academic
origin and academic placement. However, the effects of these predictors varied over time in
terms of strength. The findings are discussed in terms of guiding the evaluation and hiring of
new researchers in knowledge-based industries. Copyright # 2003 John Wiley & Sons, Ltd.
Introduction
There is growing agreement between scholars that the acquisition of high performing human assets can
provide firms with sustainable competitive advantages (Coff, 1997). To realize the competitive advantages provided by human assets, organizational decision makers must first identify accurate predictors
of employee performance that can be utilized to screen applicants (Wayne, Liden, Kraimer, & Graf,
1999). However, in most cases employers lack full information about job applicants’ abilities, making
it difficult to evaluate the probability that an applicant will be a productive employee (Coff, 1997).
Nowhere is the problem of talent identification more acute than in settings where the primary concern is knowledge creation, including such industries as biotechnology, information technology, management consulting, and academic universities. In these knowledge-based industries, the ability of
employees to create and disseminate high-quality original research reports has direct implications
for firms’ competitiveness, reputational capital, and ultimately their survival. For example, biotechnology, information technology and management consulting firms use research reports, commonly
referred to as ‘white papers,’ to promote their expertise, attract potential customers, and develop
intra-firm knowledge management centers (Hagel & Brown, 2001, Watson, 1998). Indeed, many
organizations adopt formal human resource programmes designed to encourage employees to generate
* Correspondence to: Ian O. Williamson, University of Maryland, Robert H. Smith School of Business, College Park, MD 207421815, U.S.A. E-mail: iwilliam@rhsmith.umd.edu
Copyright # 2003 John Wiley & Sons, Ltd.
Received 3 December 2001
Revised 15 July 2002
Accepted 27 September 2002
26
I. O. WILLIAMSON AND D. M. CABLE
original research. For example, American Management Systems, Inc (AMS), an international business
and information technology consulting firm, uses an associates programme to encourage consultants to
publish at least one white paper a year (Watson, 1998). Therefore, hiring employees who are more
motivated and able to publish research papers clearly would be valuable to these firms. Unfortunately,
the irregular and lagged nature of research innovation makes it difficult to predict which new employees have the greatest probability of making research breakthroughs.
The purpose of this paper is to identify predictors that can reduce uncertainty in the selection of
researchers. To accomplish this goal, we focused on the research productivity of a specific category
of knowledge workers: new business professors in management. We examined this labor segment for
several reasons. First, while some academic manuscript outlets differ from commercial white paper
outlets, many are quite parallel (e.g., both consultants and management professors publish in Harvard
Business Review and Personnel Psychology). Moreover, the analytical and theoretical skills needed to
examine research questions in both settings are very similar. Thus, understanding the predictors of
faculty research productivity may be informative to firms in other industries that value the creation
and dissemination of new research.
Second, like many other knowledge-intensive industries, business schools face intense pressures for
new hires to quickly become prolific researchers. Intense public scrutiny due to popular press rankings,
as well as competition from corporate universities, has increased competition between business
schools. A key component of a business school’s competitiveness in this environment is its ability
to acquire new faculty members who are capable of creating and disseminating original research
(Trieschmann, Dennis, Northcraft, & Niemi, 2000). Of course, many types of academic departments
and industries face similar levels of competition and demand for early research contributions, but an
advantage of focusing on one type of research is that it ensures comparability in terms of research outlets (i.e., a set journals that publish management research). Finally, a nascent research literature has
developed around management research productivity (Long, Bowers, Barnett, & White, 1998; Park &
Gordan, 1996), allowing us to integrate and extend past findings.
Examining the two prior studies (Long et al., 1998; Park & Gordan, 1996) that have examined the
predictors of management faculty research productivity reveals that existing knowledge about research
success can be enhanced in three ways. First, both studies have predicted research productivity using
few variables in a piecemeal fashion without considering the relative effects of several theoretically
relevant variables. For example, Long and colleagues (1998) did not examine individual level factors
(e.g., past research performance), while Park and Gordon (1996) did not examine organizational factors (e.g., department quality). As a result, we have limited empirical information to draw upon when
deciding how to weight information about researchers during the selection process. Recognizing this
limitation, both Long and colleagues (1998) and Park and Gordon (1996) suggest examining a more
comprehensive set of variables to delineate the relative importance of research productivity predictors,
thus providing more accurate information about research productivity.
Second, past research on career success suggests that individuals’ productivity is directly related to
the qualifications and abilities of their mentors (Kram, 1985). However, past studies have not examined
the relationship between mentor qualifications and early career research productivity. Given the importance of the student-dissertation advisor relationship in the context of academia (Green & Bauer,
1995), an examination of dissertation advisor qualifications should enhance our understanding of
the predictors of research productivity.
Finally, no research has examined how the predictors of research productivity may evolve over time,
highlighting the need for longitudinal research. Although Park and Gordon (1996) reported that strategy faculty research productivity varied widely over the course of their careers, research is needed to
examine whether some factors are more predictive immediately after entering an organization while
other factors gradually gain predictive validity.
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
EARLY CAREER RESEARCH PRODUCTIVITY
27
To address these limitations, the present paper builds on the work of Long and colleagues (1998) and
Park and Gordon (1996) by simultaneously examining the theory-based predictors of early career
research productivity, including dissertation advisor qualifications. By utilizing a longitudinal design,
we provide insight into how the predictors of research productivity evolve during the first six years of a
career. The results of this study should hold interest for employers who seek to hire individuals capable
of producing original research, for doctoral programmes attempting to develop effective researchers,
and for job seekers evaluating academic employment opportunities.
Theory and Hypotheses
Figure 1 provides a graphic overview of the variables and the relationships that comprise our model.
Drawing on sociology, psychology, and management theories, we hypothesize that four sets of predictors can be used to predict early career research productivity: (1) advisor qualifications, (2) preappointment productivity, (3) academic placement, and (4) academic origin. In general, Figure 1 suggests that these four sets of predictors can affect a new hire’s research productivity both directly and
indirectly. Thus, an individual’s academic advisor is important because he or she imparts research
values and knowledge that directly aid the student’s post-appointment research productivity. However,
as shown in Figure 1, an advisor also indirectly affects the individual’s early career productivity by
helping conduct research projects during graduate school and by helping place the individual into a
job, both of which in turn facilitate post-appointment productivity. Likewise, the quality of the university where an individual acquires his or her PhD can lead to greater pre-appointment productivity and
job placement, which in turn affect post-appointment productivity. Below we discuss the hypothesized
direct effects of these predictors on research productivity, followed by the indirect effects.
Figure 1. Hypothesized model of early career research productivity
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
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I. O. WILLIAMSON AND D. M. CABLE
Direct influences
Advisor qualifications
Studies of professionals’ careers suggest that an important predictor of early career productivity is the
mentoring that individuals receive from their supervisors and advisors (e.g., Scandura, 1992;
Scandura & Schrieshem, 1994). Specifically, advisors are thought to enhance the productivity of protégés by providing a variety of career-enhancing functions, such as coaching and assigning challenging
work assignments (Kram, 1983). Theoretically, the degree to which an advisor can successfully provide these career-enhancing functions to a protégé is largely dependent on the advisor’s own ability
level and accomplishments (Kram, 1985). In the context of academia, the student–dissertation advisor
relationship represents a formal mentoring relationship, such that dissertation advisors pass expertise
to doctoral students through direct training, providing feedback on manuscript drafts, counselling on
research agenda development, or helping protégés select appropriate research outlets for their work
(Green & Bauer, 1995). The more skilled and productive a dissertation advisor is, the more likely
he or she will imbue students with the research skills and values needed to be productive researchers
during the early portions of their careers. As shown in the Figure, this logic leads to Hypothesis 1:
Hypothesis 1: The research productivity of individuals’ dissertation advisors is positively related to
their post-appointment research productivity.
Pre-appointment productivity
According to behavioral consistency theory, the best predictor of employees’ future task productivity
is their past productivity at that specific task (Wernimont & Campbell, 1968). A person’s previous success at performing a task enhances his or her skill level and self-efficacy in that realm, increasing both
the desirability of pursing and the probability of competently repeating that behavior (Mael, 1991).
Thus, pre-appointment research productivity (i.e., graduate student publishing record) may be construed as a signal about research ability levels and goals, such that individuals who successfully publish journal articles or have conference papers accepted for presentations during their doctoral
programme should continue to be productive at these tasks over the first six years of their faculty career
(Park & Gordon, 1996; Rodgers & Maranto, 1989). Thus, we hypothesize:
Hypothesis 2: Pre-appointment research productivity will be positively related to post-appointment
research productivity.
Academic placement
Past studies of faculty research productivity have shown that faculty placement, or where individuals
obtain a job, may influence their research productivity (Long et al., 1998; Rodgers & Maranto, 1989).
One explanation for this finding is that various contextual attributes of an employing school provide
faculty members with ‘accumulated advantages’ that make it easier for them to be productive researchers (Long et al., 1998). Thus, when individuals join departments with productive faculty, their personal
productivity is likely to increase because an individual’s behavior is influenced by the colleagues that
make up his or her social setting (Salancik & Pfeffer, 1978). Specifically, newcomers who obtain positions in departments of active researchers should experience increased research productivity resulting
from colleagues who provide expectations, rewards, and ideas that stimulate productivity.
Holding departmental productivity constant, new faculty may also derive research advantages by
obtaining appointments in departments that have strong public reputations (Pfeffer, Leong, & Strehl,
1977). Public reputation refers to the evaluation of a department’s overall excellence and effectiveness
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
EARLY CAREER RESEARCH PRODUCTIVITY
29
by external constituents (Rodgers & Maranto, 1989). Theoretically, journal or conference acceptance
decisions may be influenced by a school’s public reputation because editors ascribe positive attributes
to individuals’ manuscripts based on their organizational affiliation (Pfeffer et al., 1977). For example,
the public reputation of a faculty member’s department might influence editors’ choices of reviewers,
interpretations of reviewer comments, and judgments about manuscript acceptance. Thus we hypothesize:
Hypothesis 3: The departmental scholarly output of individuals’ academic placements will have a
positive relationship with post-appointment research productivity.
Hypothesis 4: The public reputation of individuals’ academic placements will have a positive relationship with post-appointment research productivity.
Indirect influences
Advisor qualifications
As shown in Figure 1, in addition to directly influencing faculty research productivity, advisors may
also indirectly affect faculty productivity by influencing the pre-appointment research productivity of
their protégés. To the extent that advisors enhance technical skills and inculcate research values in their
protégés, it is logical that the protégés of prolific dissertation advisors will be productive while under
their direct tutelage (Kram, 1985). Therefore, we hypothesize:
Hypothesis 5: The research productivity of individuals’ dissertation advisors will be positively
related to pre-appointment research productivity.
We also expect dissertation advisor productivity to indirectly affect faculty productivity by influencing the quality of protégés’ academic placements. An important element of supervisor mentoring is
the sponsoring of protégés for desirable jobs (Kram, 1985). Since dissertation advisors write letters of
recommendation and contact universities concerning employment opportunities on behalf of their students, having a prolific advisor can influence the placement of a doctoral student (Cable & Murray,
1999). Therefore, we predict:
Hypothesis 6: The research productivity of individuals’ dissertation advisors will be positively
related to the quality of their academic placements, both in terms of (a) departmental scholarly output and (b) public reputation.
Pre-appointment productivity
We also expect pre-appointment productivity to indirectly affect post-appointment productivity by influencing the type of jobs that individuals receive. According to Merton’s (1973, p. 293) examination of
universalism, institutions of science work best when ‘recognition and esteem accrue . . . to those who
have made original contributions to the body of scientific knowledge.’ Because the most direct measure
of a researcher’s contribution to scientific knowledge is their research productivity, we expect that faculty
who develop strong research records during graduate school will be more likely to receive job opportunities at prolific research departments with positive public reputations (Cable & Murray, 1999).
Hypothesis 7: Individuals’ pre-appointment research productivity will be positively related to the
quality of their academic placements, both in terms of (a) departmental scholarly output and (b)
public reputation.
Copyright # 2003 John Wiley & Sons, Ltd.
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I. O. WILLIAMSON AND D. M. CABLE
Academic origin
The graduate programme that an individual attended may also provide accumulated advantages that
indirectly enhance research productivity. First, graduate programmes with high departmental scholarly
output and public reputations may provide research advantages that increase the pre-appointment publication and presentation success of their students, which in turn will impact post-appointment research
productivity. Compared with individuals from departments with low levels of scholarly output, individuals from graduate programmes with high levels of scholarly output may be more likely to receive
advanced research training and have a greater opportunity to join fruitful research projects by virtue of
being around scholars who are actively engaged in research (Long et al., 1998). This, in turn, may
increase individuals’ pre-appointment publications and presentations. In addition, individuals from
graduate programmes with high public reputations, as opposed to low public reputations, may have
a greater opportunity to meet and develop relationships with influential members of the professions
(e.g., frequently published researchers and editors) via research presentations and conferences hosted
by their school (Long et al., 1998). As a result, doctoral students at high public reputation schools are
likely to gain knowledge of and develop ties to the various gatekeepers of the profession, which may
influence the acceptance rates of their initial publication and presentation submissions. Therefore, we
predict that:
Hypothesis 8: The departmental scholarly output of an individual’s graduate programme will be
positively related to (a) pre-appointment publications and (b) pre-appointment presentations.
Hypothesis 9: The public reputation of an individual’s graduate programme will be positively
related to (a) pre-appointment publications and (b) pre-appointment presentations.
Second, we propose that individuals’ graduate programmes, both in terms of departmental scholarly
output and public reputation, will affect their academic placement and will therefore have an indirect
affect on their post-appointment research productivity. As noted by Long, Allison, and McGinnis
(1979: p. 816), ‘One of the most persistent findings in the study of stratification in science is the substantial correlation between the prestige of the university department which currently employs a scientist and the prestige of his (or her) doctoral department.’ One explanation for this finding is that
universities rely on the departmental productivity or public reputation of an individual’s graduate programme as a signal of his or her research ability (Long et al., 1979).
Hypothesis 10: The departmental scholarly output of individuals’ graduate programmes is positively related to individuals’ academic placements in terms of (a) departmental scholarly output
and (b) public reputation.
Hypothesis 11: The public reputation of individuals’ graduate programmes is positively related to
individuals’ academic placements in terms of (a) departmental scholarly output and (b) public
reputation.
Gender differences
The research productivity literature indicates consistent differences between male and female faculty,
such that men tend to produce greater quantities of publications then women (e.g., Over, 1982;
Zuckerman & Cole, 1975). Various factors have been offered to explain this finding, such as sex discrimination in the allocation of resources, career interruptions, and mentorship (Park & Gordon, 1996; Rodgers & Maranto, 1989). To control for possible gender effects in our model, we examined the effect of
protégé gender on post-appointment research productivity.
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
EARLY CAREER RESEARCH PRODUCTIVITY
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Organizational Context
The data used for this study consisted of information on 152 management faculty accepting their
first academic jobs upon completion of their PhD programme from 1987–1995. During this period
of time the job market for management doctoral students was fairly strong, thus qualified graduates
typically had options in terms of picking their academic affiliation. Data were limited to faculty
accepting positions at domestic universities with AACSB accredited doctoral programmes in management. During the time frame of the study 95 schools fit this description. Data collection was
limited to individuals hired by one of these 95 schools to account for research productivity differences between non-PhD programme and PhD programme institutions during this time frame (see
Park & Gordon, 1996 for more information). In total, faculty in our sample were employed by 67
different colleges and universities in 35 different states.
Method
The target sample for our study consisted of management faculty in their first jobs after finishing graduate school. Specifically, we studied faculty who in 1995 were working at management departments in
domestic American Assembly of Collegiate School of Business (AACSB) accredited business schools,
and who started their jobs during the period of 1987–1992. Past research has found that faculty hired
by institutions with doctoral programmes in management have significant higher levels of research
productivity than faculty hired by institutions without management doctoral programmes (Park &
Gordon, 1996). Thus, to control for doctoral programme effects, in our study we limited our sample
to those departments with doctoral programmes in management.
According to the AACSB Guide to Doctoral Programs in Business and Management (Soete, 1995), a
total of 95 American business schools offered doctoral degrees in management in 1995. The McGrawHill Directory of Management Faculty 1995–1996 (Hasselback, 1996) was used to ascertain which individuals at each of the 95 schools fit the specifications of the target sample. The McGraw-Hill Directory,
while not exhaustive, is one of the best available lists of US management faculty and has been used in
past research to identify management faculty (e.g., Park & Gordon, 1996). The directory identified 211
first-time assistant faculty members who accepted jobs between 1987 and 1992. However, missing or
unavailable data across all variables (e.g., advisor, graduate programme) resulted in a working sample
size of 152, 72 per cent of the faculty members with job start years between 1987 and 1992. For faculty
members that were not included in our study we collected data on their journal publication productivity
during the first six years of their career. Analysis of variance (ANOVA) results revealed that nonsampled faculty members did not differ significantly from sampled faculty members in terms of the
number of early career journal publications ( p > 0.18), suggesting that our sample was representative
of the target sample. The 152 faculty in our sample represented several areas of the management discipline, with 31 per cent identifying organizational behavior/organizational theory as their primary
research area, 25 per cent identifying themselves as strategy researchers, 15 per cent working in the area
of quantitative methods/management science, 10 per cent identifying themselves as human resource
management researchers, and the remaining 19 per cent conducting management research across the
areas of ethics, entrepreneurship, international management, and management information systems.
Copyright # 2003 John Wiley & Sons, Ltd.
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I. O. WILLIAMSON AND D. M. CABLE
Measures
Research productivity
Two measures of research productivity were used: (1) number of academic journal publications, and
(2) number of national Academy of Management (AOM) conference presentations. Following the procedures used by Park and Gordon (1996) and Long and colleagues (1998), the number of academic
journal publications for each faculty member was obtained by recording the total number of facultyauthored publications appearing in the premier management journals from 1983 to 1998. Consistent
with Cable and Murray (1999) our list of premier management publications consisted of the top 21
management journals identified by Gomez-Mejia and Balkin (1992). The Social Science Citation
Index (SSCI) and ABI/Inform (ProQuest Direct) databases were used to obtain the publication counts
for each faculty member by year. Only articles and research notes were counted as publications. Comments, book reviews, and editorials were not included. Each faculty publication was weighted for quality using the journal quality ratings provided by Gomez-Mejia and Balkin (1992). Gomez-Mejia and
Balkin (1992) reported that their ratings were strongly correlated to the 1990 Social Science Citation
Index (SSCI) impact factor (r ¼ 0.78) and Extejt and Smith’s (1990) subjective journal rankings
(r ¼ 0.86), suggesting that their ratings are valid measures of journal quality. The weights assigned
to each journal article along with the 1990 SSCI impact factors for each journal are provided in
Table 1. Table 1 also includes the 2001 SSCI impact factors for each journal, which are strongly correlated (r ¼ 0.88) with the 1990 SSCI impact factors. This suggests that the relative impact of the
selected management journals has not change much in the last decade.
Table 1. Set of management journals and publications
Journal name
Journal
quality ratinga
Academy of Management Journal
Strategic Management Journal
Journal of Management
Journal of Applied Psychology
Academy of Management Review
Management Science
Organizational Behavior & Human
Decision Processes
Journal of International Business Studies
Administrative Science Quarterly
Personnel Psychology
Journal of Organizational Behavior
Industrial and Labor Relations Review
Human Relations
Decision Science
Journal of Management Studies
Journal of Applied Behavioral Science
Industrial Relations
Harvard Business Review
Journal of Vocational Behavior
Psychological Bulletin
Journal of Occupational Psychology
1990 SSCI
2001 SSCI
impact factor impact factor
Number of
publications in journal
by faculty in sample
4.52
4.06
3.60
4.45
3.83
3.37
4.14
1.56
1.79
0.43
1.78
1.54
1.00
1.31
2.83
2.68
1.31
1.98
3.16
1.50
1.27
47
39
28
25
21
14
13
3.26
4.60
3.81
2.85
3.79
3.36
3.50
3.43
3.45
3.62
3.19
3.21
2.85
3.48
0.43
2.85
1.03
0.58
2.06
0.50
0.61
0.98
0.40
1.44
1.24
1.19
3.72
0.96
0.87
3.98
2.11
1.16
1.65
0.86
0.72
0.63
13
11
10
10
7
8
6
5
5
3
2
2
1
1
1.11
2.47
1.70
6.81
0.86
Total ¼ 271
a
Ratings taken from Gomez-Mejia and Balkin (1992).
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
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33
The annual national AOM meeting is the premier academic conference within the management discipline. While not as prestigious as journal publications, AOM conference presentations represent a
viable means of disseminating original research and have been shown to affect the academic placement
of management doctoral students (Cable & Murray, 1999). Presentation counts were obtained by counting the number of faculty-authored papers presented at the national AOM conference from 1983–1998.
For both journal publications and conference presentations, we were interested in faculty performance (a) prior to starting their first job and (b) after they started their first job. Pre-appointment publication productivity and pre-appointment presentation productivity were measured as the journal
publications and conference presentations by a faculty member prior to and including the year they
began working their first job. The job start year of each faculty member was obtained from the
McGraw-Hill Management Directory (Hasselback, 1996) or from schools’ web page documentation.
Post-appointment publication productivity and post-appointment presentation productivity were
measured by counting the number of journal publications and conference presentations by a faculty
member in the six years after the year they accepted their first academic job. We created measures of
both the first three years (years 1–3) and the second three years (years 4–6) of a faculty member’s
research productivity to examine the effect of the predictors over the course of a faculty member’s
career. The three- and six-year marks were adopted because most new faculty members face a critical
three-year review when their research trajectory is evaluated and a six-year tenure review when their
research productivity is an important factor in their tenure decisions. Due to skewness in the distributions of the pre- and post-appointment publication counts and pre- and post-appointment presentation
counts, a natural log transformation was performed on these measures for model testing.
Dissertation advisor research productivity
The Dissertation Abstracts Online (DAO) database was used to obtain the name of each faculty member’s dissertation advisor. The SSCI and ABI/Inform (ProQuest Direct) were then used to obtain
counts of the total number of advisor-authored publications that appeared in the top 21 management
journals (as identified by Gomez-Mejia & Balkin, 1992) during the 10 years prior to the year an advisor’s protégé started their job. Similar to the faculty publication variable, each of the advisors’ journal
publication was weighted for quality using the journal quality ratings provided by Gomez-Mejia and
Balkin (1992). If a faculty had two advisors we computed the average of the publication counts for
both advisors. In those cases where a dissertation advisor co-authored a publication with a faculty
member, the publication was included in the dissertation advisor’s productivity count if they had
the higher authorship position (i.e. first author), otherwise the publication was included in our measure
of faculty research productivity. Skewness in the distribution of advisor publication counts necessitated the use of a natural log transformation for model testing.
Academic placement
Two attributes of faculty’s academic placement were measured: departmental scholarly output and
department public reputation. Our measure of departmental scholarly output consisted of the average
cumulative number of journal articles published by a management department’s faculty over the 1987–
1995 period. Using the McGraw Directory of Management Faculty (Hasselback, 1996), the names of
each assistant, associate, and full professor who was employed in the management department of each
graduate school in 1995 was obtained. The SSCI and ABI/Inform Global were then used to gather
information about the cumulative number of publications each department’s faculty member had in
the 21 journals identified by Gomez-Mejia and Balkin (1992) during the period of 1987–1995. Consistent with past research (Howard, Cole, & Maxwell, 1987), the average number of departmental
faculty publications was determined by summing the total number of faculty publications and dividing
by the total number of faculty in a department. To avoid confounding the variable we did not include
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
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I. O. WILLIAMSON AND D. M. CABLE
the focal faculty member’s publication productivity (including any articles co-authored with department faculty) when compiling his or her department’s total faculty publications, nor was the faculty
member included in the total faculty count.
The Gourman Report (Gourman, 1996) rating was used to measure the public reputation of a faculty
member’s academic placement. The Gourman Report has been used to measure academic programme
reputation in past research (Cable & Murray, 1999; Gomez-Mejia & Balkin, 1992), and is presumably
the only numerical rating of virtually every graduate programme in the United States. Each school
receives a continuous overall rating from 1.0 to 5.0. Whenever possible, we used the Gourman Report
ratings for the degree granting institution’s business doctoral programme; if the business doctoral programme rating was not provided we used the Gourman rating of the overall graduate school. Although
Gourman ratings have been validated in past research (Cable & Murray, 1999), we provided additional
validation by examining the relationship between Gourman Report ratings, the three-year mean
GMAT scores of a school’s business PhD students (Soete, 1995), and the management department
rankings developed by Long and colleagues (1998) for each of the 95 AACSB accredited business
schools with doctoral programmes in management. The correlations between the Gourman Report ratings and these two indexes were 0.63 ( p < 0.001) and 0.70 ( p < 0.001) respectively, suggesting that
the Gourman Report is a reasonable indicator of a department’s public reputation.
Academic origin
Similar to academic placement, we measured both the scholarly output and the public reputation of a
faculty member’s academic origin (i.e., their graduate school). The identical methodology described
above to measure scholarly output of academic placement was also employed to measure the departmental scholarly output of a faculty member’s academic origin, and the 1996 Gourman Report (Gourman,
1996) was used to measure the public reputation of a university’s management department.
Results
The 152 faculty members comprising the sample published 285 papers in the premier management
journal set during the first six years of their academic job, for an average of 0.31 articles per year.
Several faculty coauthored papers with other members of the sample, thus only 271 distinct papers
were produced overall. Table 1 presents the number of articles published in each of the 21 journals
comprising the set of premier management journals.
To test the proposed relationships we estimated a covariance structural equations model using LISREL 8.3 (Jöreskog & Sörbom, 1999). The hypothesized model depicted in Figure 1 consisted of nine
latent endogenous variables and three latent exogenous variables each with one indicator assumed to
contain no measurement error. The means, standard deviations, and correlations among all variables
appear in Table 2. We assessed the overall fit of the model to the data with chi-square, the goodness-offit index (GFI), the adjusted goodness-of-fit index (AGFI), the comparative fit index (CFI), the
incremental fit index (IFI), the parsimony ratio (PRATIO), and the root mean square error of approximation (RMSEA). Chi-square statistics that are not statistically significant suggest that a model
adequately fits the data, while GFI, AGFI, CFI, and IFI scores at or above 0.90 are believed to indicate
acceptable fit (Medsker, Williams, & Holahan, 19941). For the RMSEA index, values below 0.08
1
Medsker and colleagues (1994) recommend evaluating a hypothesized model relative to plausible alternative models. We tested
three alternative models which did not significantly improve upon the hypothesized model. Due to space constraints only the
results of the hypothesized model are presented.
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
Mean
Copyright # 2003 John Wiley & Sons, Ltd.
2
3
4
(0.46)
0.09 (19.62)
0.02
0.09 (1.10)
0.05
0.01 0.27 (0.64)
0.02
0.19 0.09
0.03
0.01
0.37 0.25 0.05
0.10 0.07 0.10
0.52
0.01
0.03 0.09
0.24
0.09
0.20 0.03 0.05
0.03
0.26 0.07
0.15
0.03
0.25 0.00 0.02
0.05
0.27 0.11
0.10
1
6
7
8
9
10
11
12
(2.52)
0.24
(1.32)
0.03 0.08 (0.83)
0.23
0.16 0.48 (1.02)
0.37
0.35 0.06 0.26 (3.69)
0.32
0.39 0.17 0.34 0.18 (1.51)
0.21
0.28 0.08 0.23 0.25 0.43 (5.88)
0.19
0.40 0.07 0.29 0.23 0.53 0.50 (1.80)
5
Note: n ¼ 152.
The numbers in parentheses on the diagonal are standard deviations.
Correlations greater than 0.16 are significant at that 0.05 level.
a
Means and standard deviations calculated using untransformed data; natural log was used to determine correlations.
1. Gender (1 ¼ male)
0.69
2. Dissertation advisor productivitya
16.37
3. Academic origin departmental scholarly output
2.40
4. Academic origin public reputation (1–5)
4.46
5. Pre-appointment publicationsa
1.12
6. Pre-appointment presentationsa
0.99
7. Academic placement public reputation (1–5)
4.03
8. Academic placement departmental scholarly output 1.71
9. Post-appointment publications (years 1–3)a
2.30
10. Post-appointment presentations (years 1–3)a
1.33
11. Post-appointment publications (years 4–6)a
4.63
12. Post-appointment presentations (years 4–6)a
1.66
Variable
Table 2. Means, standard deviations and correlations between variables
EARLY CAREER RESEARCH PRODUCTIVITY
35
J. Organiz. Behav. 24, 25–44 (2003)
36
I. O. WILLIAMSON AND D. M. CABLE
are considered indicative of good fit (Hu & Bentler, 1999). A definitive cut-off point does not exist for
the PRATIO, however, the higher the score the greater the parsimony of the model (Mulaik, James,
VanAlstive, Bennett, Lind, & Stilwell, 1989). The chi-square for the hypothesized model was significant (2 ¼ [17, n ¼ 152] ¼ 35.35, p < 0.001), the AGFI was 0.84, and the PRATIO was 0.26; however,
the GFI was 0.97, the CFI was 0.96, the IFI was 0.96, and the RMSEA was 0.07 (90 per cent confidence
interval ¼ 0.04 to 0.12). All four of the latter values suggest that the hypothesized model adequately fit
the data. In addition, the chi-square difference test between the chi-square of the hypothesized model
and the null model was significant (2 ¼ 46, n ¼ 152) ¼ 354.80, p < 0.001), suggesting that the
hypothesized model provided a significantly better fit to the data than the null model.
Table 3 contains the maximum-likelihood parameter estimates, significance levels, and R2s for the
hypothesized model. First, we will present the results for the hypothesized direct relationships.
Hypothesis 1 predicted that dissertation advisor research productivity would be positively related to
both faculty post-appointment publication and presentation productivity. However, advisor research
productivity did not share a significant direct relationship with either faculty post-appointment publication or presentation productivity during years 1–3 or 4–6. Thus, Hypothesis 1 was not supported.
Consistent with Hypothesis 2, faculty pre-appointment presentations significantly predicted postappointment presentations in years 1–3 and 4–6 ( ¼ 0.27 and ¼ 0.17, respectively). Preappointment publication productivity shared a significant direct effect on post-appointment publication productivity in years 1–3 ( ¼ 0.27) but not years 4–6, providing partial support for Hypothesis 2.
In addition, pre-appointment publication productivity also significantly predicted post-appointment
presentations in years 1–3 ( ¼ 0.18) and pre-appointment presentations significantly predicted
post-appointment publications in years 1–3 ( ¼ 0.23).
The departmental scholarly output of a faculty member’s academic placement had a significant direct
effect on post-appointment presentation productivity in years 1–3 ( ¼ 0.20). However, department scholarly output did not significantly predict post-appointment publication productivity in years 1–3, nor did
it predict post-appointment publication or presentation productivity in years 4–6. Thus, Hypothesis 3 was
partially supported. The public reputation of faculty’s academic placement did not share a significant
relationship with post-appointment presentations or publications. Thus, Hypothesis 4 was not supported.
Next, we present the results of the hypothesized indirect relationships. Hypothesis 5, which predicted that dissertation advisor research productivity would be positively related to faculty preappointment publications and presentations, was supported ( ¼ 0.19 and ¼ 0.35, respectfully).
Advisor research productivity, however, was not significantly related to either the departmental scholarly output or the public reputation of faculty’s academic placement. Therefore, Hypotheses 6a and b
were not supported. Pre-appointment publications were significantly related to the departmental scholarly output of an individual’s academic placement ( ¼ 0.20), but pre-appointment presentations did
not predict departmental scholarly output. Thus, Hypothesis 7a was partially supported. Pre-appointment publications and presentations did not significantly predict the public reputation of an individual’s academic placement; therefore, Hypothesis 7b was not supported.
Hypotheses 8a and b predicted that departmental scholarly output of an individual’s graduate programme would be positively related to pre-appointment (a) publications and (b) presentations. Hypothesis 8a was not supported; however, graduate program scholarly output was significantly related to preappointment presentations ( ¼ 0.25), providing support for Hypothesis 8b. The public reputation of
an individual’s graduate programme was not significantly related to pre-appointment publications or
presentations. Thus, Hypotheses 9a and 9b were not supported.
Hypotheses 10a and b, that the departmental scholarly output of an individual’s graduate programme
would share a positive relationship with the (a) departmental scholarly output and (b) public reputation
of an individual’s academic placement, were not supported. On the other hand, the public reputation of
an individual’s graduate programme was significantly related to the departmental scholarly output and
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
Copyright # 2003 John Wiley & Sons, Ltd.
2
3
*p < 0.05.
Outcomes
1. Pre-appointment publications
2. Pre-appointment presentations
3. Academic placement public reputation
0.05 0.09
4. Academic placement departmental
0.20* 0.15
scholarly output
5. Post-appointment publications (years 1–3)
0.27* 0.23* 0.01
6. Post-appointment presentations (years 1–3) 0.18* 0.27* 0.11
7. Post-appointment publications (years 4–6)
0.01 0.06 0.01
8. Post-appointment presentations (years 4–6) 0.05 0.17* 0.05
9. Academic origin public reputation
R2
0.04 0.20
0.43
1
0.27
0.22
0.12
6
0.33*
0.40*
5
0.16
0.20*
0.09 0.12
0.14 0.06
0.41*
4
Endogenous variables
Beta matrix ()
0.23
7
0.01
0.12
0.43*
0.25*
9
0.35 0.08
8
Antecedents
Table 3. Maximum-likelihood parameter estimates for the hypothesized model of research productivity
0.01
0.06
0.02
0.03
Gender
0.07
0.13
0.12
0.09
0.19*
0.35*
0.04
0.06
Dissertation
advisor
productivity
0.27*
0.07
0.25*
0.02
0.03
Academic
origin scholarly
output
Exogenous variables
Gamma matrix ()
EARLY CAREER RESEARCH PRODUCTIVITY
37
J. Organiz. Behav. 24, 25–44 (2003)
38
I. O. WILLIAMSON AND D. M. CABLE
Figure 2. Significant path coefficients of hypothesized model
public reputation of an individual’s academic placement ( ¼ 0.25 and ¼ 0.43, respectively). Therefore, Hypotheses 11a and b were supported. Finally, in terms of an individual’s gender, there was no
significant relationship between gender and post-appointment publications or conference presentations
over years 1–3 or 4–6.
In summary, results suggest that advisor qualifications, pre-appointment productivity, academic placement, and academic origin all directly and/or indirectly influence faculty early career research productivity. Figure 2 provides a clear overview of the findings by depicting all of the statistically
significant path coefficients of the hypothesized model.
Because the ultimate outcome of interest in this study is post-appointment productivity, it is informative to examine the total (i.e., direct þ indirect) effects of each predictor on publications and presentations. Accordingly, Table 4 shows the standardized total effects of each predictor provided by
LISREL. It is interesting to note that the total effects of the predictors vary over the course of an individual’s early career. For example, pre-appointment publications and presentations had the largest total
effects on post appointment publications in years 1–3; however, advisor research productivity had the
largest total effect on publication productivity in years 4–6. Similarly, pre-appointment publications
had large significant total effects on post-appointment publication and conference presentation productive in years 1–3, but insignificant total effects in years 4–6.
Given that a unique contribution of our study is examining the system of relationships regarding new
faculty productivity, it is interesting to examine the total effects of the predictors on academic placement,
both in terms of public reputation and departmental scholarly output. Thus, Table 5 presents the standardized total effects of the predictors of academic placement. Interestingly, the public reputation of an
individual’s academic origin was the only variable with a significant total effect on academic placement
public reputation. The public reputation of an individual’s academic origin also had strong total effects
on the departmental scholarly output of their academic placement. Pre-appointment publications had a
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
EARLY CAREER RESEARCH PRODUCTIVITY
39
Table 4. Total effects of variables on post-appointment publications and post-appointment conference
presentations
Variables
Dissertation advisor research productivity
Pre-appointment publications
Pre-appointment presentations
Academic placement departmental scholarly output
Academic placement public reputation
Academic origin departmental scholarly output
Academic origin public reputation
Gender
Post-appointment
publications
Post-appointment
conference presentations
Years 1–3
Years 4–6
0.21*
0.30*
0.26*
0.16*
0.01
0.08*
0.01
0.01
0.25*
0.13
0.20*
0.18*
0.02
0.06*
0.03
0.06
Years 1–3
0.26*
0.23*
0.30*
0.24*
0.11
0.10*
0.07
0.06
Years 4–6
0.27*
0.09
0.33*
0.23*
0.01
0.09*
0.02
0.06
*p < 0.05.
Table 5. Total effects of variables on faculty academic placement
Variables
Dissertation advisor research productivity
Pre-appointment publications
Pre-appointment presentations
Academic origin departmental scholarly output
Academic origin public reputation
Academic placement
public reputation
0.07
0.03
0.03
0.11
0.53*
Academic placement departmental
scholarly output
0.03
0.20*
0.15
0.09
0.23*
*p < 0.05.
significant effect on academic placement scholarly output, but not on the public reputation of an individual’s placement. Advisor research productivity, pre-appointment presentations, and academic origin
scholarly output did not have significant total effects on an individual’s academic placement.
Discussion
In industries where competitiveness is linked to developing new knowledge, organizations must locate
and hire individuals who generate high research productivity. Although this selection process is difficult due to the subtle, unobservable traits that make individuals into great researchers, the present study
demonstrates that research productivity can be predicted with four theoretical sets of variables.
Specifically, results revealed that future research output can be predicted using: (1) dissertation advisor
qualifications, (2) graduate school productivity, (3), academic placement, and (4) academic origin.
By examining this set of predictors in the context of newly hired management professors, we were
able to extend a developing but limited literature on this topic. Thus, one key contribution of this study
is revealing the relative importance of advisor qualifications when predicting research productivity.
Results indicated that advisor productivity influenced faculty productivity indirectly, primarily
through greater publication records as a doctoral student. To illustrate the overall importance of advisor productivity on research productivity during the first six years of their employment, we divided our
sample into upper and lower halves based on advisors’ research productivity and compared the average
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I. O. WILLIAMSON AND D. M. CABLE
post-appointment research output of new hires in the resulting groups. Individuals who had an advisor
in the lower half of the sample had on average 2.49 presentations and a weighted publication score of
5.38. This was 1.32 fewer presentations and a weighted publication score 4.14 points lower than
faculty who were in the upper half of our sample in terms of advisor productivity ( p < 0.01 for both
differences). This represents a substantial difference in research output, given that the overall six-year
averages for the sample are 2.99 post-appointment presentations and a weighted publication score of
6.96. Thus, our results indicate that early career research productivity was greatly enhanced by studying under advisors who were prolific researchers. Interestingly, previous theoretical models of mentoring and research productivity have tended to not consider advisor qualifications. The findings of this
study suggest that the inclusion of this variable when developing models of professionals’ early career
productivity may enhance both literatures.
The scholarly output of individuals’ academic origin and academic placement were both important
predictors of research productivity, supporting the accumulated advantage explanation for why academic affiliation influences research productivity, and showing that management faculty benefit from
working in environments that allow them to interact with other successful researchers (Long et al.,
1998). We assume that these results generalize to non-academic research settings, such that joining
productive research laboratories/units encourages newcomers to be productive too, but future research
is necessary to confirm the relationship in other contexts.
Consistent with behavior consistency predictions, the research productivity of a graduate student was
a significant predictor of his or her early career research productivity as a faculty member. Thus, graduate
school productivity serves as a valid signal about individuals’ skills and motivation to continue their
research productivity after acquiring a job. As with the accumulative advantage finding discussed above,
it would be interesting for future research to examine the extent to which graduate school publications
and presentations predicts post-hire research productivity in commercial research settings.
Another novel finding of this study is that the predictors of research productivity vary over time. For
example, the total effects of pre-appointment publications and presentations on future research productivity were greatly diminished between years 1–3 and years 4–6. This finding suggests that post-hire
research behavior becomes less a function of initial success as individuals progress in their careers.
Conversely, the total effects of dissertation advisor productivity on individuals’ productivity increased
from years 1–3 to years 4–6. One logical explanation for this increased total effect is that the research
skills and values that advisors imbued in faculty members increased their research identities as doctoral students, which in turn affected research productivity later in their careers. Thus, the benefits of
having a skilled and productive advisor may continue to indirectly affect productivity even when the
direct interaction between a protégé and the supervisor decreases.
A final finding of interest is the insignificant affect of gender on the post-appointment productivity
of faculty members. One explanation that has been used by past researchers to explain gender differences in the performance of professionals is that the mentors of females and males provide different
levels of career functions. However, Ragins and McFarlin (1990), in their study of employees in
research and development firms, did not find any differences in the roles fulfilled by mentors across
male and female protégés. Consistent with their findings, we found an insignificant correlation
between gender and dissertation chair advisor research productivity (see Table 2). Thus, it is possible
that the early career productivity of male and female faculty did not differ because both groups had
equal access to highly qualified dissertation advisors.
Limitations and strengths
This study has limitations that should be acknowledged. First, we only examined one type of mentoring relationship—the dissertation advisor–student relationship. However, it is likely that individuals
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
EARLY CAREER RESEARCH PRODUCTIVITY
41
receive mentoring from people other than their advisor, including former instructors and colleagues
within their new job setting, and these relationships also may affect research productivity. Moreover,
while the degree to which an advisor can successfully provide career functions to a protégé is somewhat dependent on the advisor’s own qualifications (Kram, 1985), the nature of the interpersonal relationship shared by an advisor and a protégé may also influence the level of career-enhancement
provided by an advisor. Previous research has shown that the type and quality of the doctoral student–dissertation advisor relationship varies across participants (Wade-Benzoni & Rousseau,
1998—working paper). Thus, it would be useful for future research to examine whether the nature
of the interpersonal relationship between an advisor and their protégé moderates the relationship
between dissertation advisor qualifications and early career research productivity.
Next, our examination of the relationship between academic affiliation and research productivity
considered two of the attributes that have been theorized to influence faculty research productivity:
social context and public reputation. However, other aspects of management departments may also
influence research productivity, including organizational reward structures and organizational
resources (e.g., equipment, research funds). Future research could extend this study by examining
the relationships between research productivity and a more comprehensive set of workplace attributes.
Related to this point, future research could also examine additional predictors of academic placement.
In particular, social network theory suggests that individuals’ job opportunities are in part shaped by
their network ties and the ties of those with whom they associate (Granovetter, 1973). For example,
protégé’s with dissertation advisors who have extensive connections in the academy may have better
employment opportunities than protégés with poorly connected advisors, which in turn may influence
early career research productivity.
In this study we only examined research productivity in one industry (academia), and in one type of
department (management). This focus is useful in that it allows us to study an objective index of
research productivity through a common set of journals, and also allows us to build directly on past
research (Long et al., 1998; Park & Gordan, 1996). However, it would be interesting to confirm that a
similar set of theoretical variables predicts research productivity in other types of academic departments and schools (e.g., schools without doctoral programmes), as well as in commercialized research
settings (e.g., software engineering firms, biotechnology research laboratories, management consulting firms). With regard to advisors’ research productivity, for example, on one hand we would expect
similar pervasive effects in commercial settings because the advisor is so instrumental in developing a
protégé’s ability to conceive and operationalized innovative research ideas. On the other hand, the ability to publish innovative results in academic journals may constitute a different set of skills than the
more applied research productivity needed in industry. Thus, the four sets of theoretical predictors
examined in this paper may have different weights in terms of predicting applied versus academic
research productivity. It would also be valuable for future research to examine whether our theoretical
model is applicable in interdisciplinary departments (e.g., Stanford’s programme in Work, Technology,
and Organizations) and in international settings.
Finally, we only examined one type of individual difference in this study—past research performance.
Future research could also expand upon this study by examining other individual-level factors, such as
aptitude, previous course work, and motivation. An understanding of how these factors influence early
career research productivity could help organizations screen individuals during the recruitment process.
Implications
The finding that advisor qualifications significantly impact protégé productivity can be looked at in two
ways. First, this result suggests that skilled advisors can enhance an individual’s ability to acquire
Copyright # 2003 John Wiley & Sons, Ltd.
J. Organiz. Behav. 24, 25–44 (2003)
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I. O. WILLIAMSON AND D. M. CABLE
critical skills early in their careers, thereby increasing a protégé’s early career performance (Kram,
1995). In addition, given that advisors and protégés often possess a great deal of discretion when forming mentoring relationships, this finding can also be interpreted to suggest that highly productive
researchers attract better apprentices or perhaps ward off low-quality apprentices. Both interpretations
hold important implications for academic doctoral programmes. Given that the goal of many doctoral
programmes is to develop effective researchers, universities should employ selective criteria in determining the pool of faculty members from which doctoral students can select dissertation advisors. This
may increase the probability that doctoral candidates will receive high quality research training.
Furthermore, if prolific researchers are more skilled at identifying highly talented students then less
productive researchers, this practice will increase the likelihood that university resources are directed
towards those doctoral students with the greatest research potential.
Given the importance of research productivity to the competitiveness of firms in knowledge-intensive
industries, the findings of this study also hold important implications for organizations attempting to hire
productive researchers. In this study, we found that hiring decisions were heavily influenced by the public reputation of an individual’s academic origin, even though this factor was not predictive of future
research productivity. Conversely, hiring decisions were not affected by advisor productivity, which
had significant total effects on new hires’ research productivity in years 1–3 and years 4–6. Thus, it
appears that departments currently are using flawed criteria to hire new faculty, to the extent that they
desire research productivity, and results imply that departments should pay closer attention to information about the research productivity of job candidates’ dissertation advisors when evaluating candidate
quality. Although additional research is needed to confirm the generalizability of these results, our study
implies that non-academic industries also should place greater weight on applicants’ prior research productivity and advisor’s research productivity than the prestige of their university.
Finally, our study provides important information to job seekers in the academic labour market.
Despite the high correlation between academic placement scholarly output and public reputation
(r ¼ 0.48), only the departmental scholarly output of an individual’s academic placement predicted
their post-appointment productivity. These results suggest that job seekers should not undervalue
employment opportunities in productive departments that may not have the highest external reputation
ratings. In other words, job seekers who are motivated to be productive researchers should place more
weight on the productivity of a department’s faculty rather than the external prestige rating of the
department when making job choice decisions.
Acknowledgements
We thank Richard Blackburn, Ben Rosen, Ken Smith, and Marcus Stewart for helpful comments on
earlier drafts of the paper and Pedro Akl, and Eliot Williamson for their help with data collection. An
earlier version of this paper was presented in the Organizational Behavior Division of the 1999 Academy of Management Meeting in Chicago, IL, U.S.A.
Authors biographies
Ian O. Williamson (PhD, University of North Carolina, Chapel Hill) is an Assistant Professor of
Management at the Robert H. Smith School of Business at the University of Maryland—College Park.
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EARLY CAREER RESEARCH PRODUCTIVITY
43
His primary research interests include understanding how social network and institutional theories can
be used to complement traditional HRM perspectives. He is also interested in examining the recruitment and selection issues faced by small businesses and the use of information technology in HRM.
Daniel Cable (PhD, Cornell University) is an Associate Professor of Management at the KenanFlagler Business School at the University of North Carolina, Chapel Hill. He also likes to renovate
old houses with his wife. His current research interests include talent acquisition and retention, person–organization fit, the organizational entry process, organizational selection systems, job choice
decisions, and career success.
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