Business school doctoral programs and the future of business research

Abstract

We apply a neo-institutional theoretical lens to interpret the extent of any significant similarities or differences in doctoral programmes across business schools in Australia and New Zealand (ANZ). Overall, we characterise the state of doctoral education in business as lacking adequate funding, primarily attracting students with limited professional or industrial experience but having diverse approaches to the role of formal training as part of the doctoral programme. Although we view these findings as somewhat inevitable given institutional and isomorphic pressures, they are of concern if ANZ business schools are to produce research that is both rigorous and relevant beyond the academy. Comparisons across institutional groupings and discipline areas largely suggest relatively common approaches to doctoral programme design and administration across and within institutions.

JEL Classification: M00

Keywords

Business schools doctoral programmes neo-institutional theory research relevance research training

1. Introduction

The objective of this study is to survey the state of business school¹ doctoral programmes in Australia and New Zealand (ANZ) and determine whether there are substantive differences between university groupings and disciplines. Historically doctoral programmes in Australia and New Zealand have generally presented considerable diversity (Pearson et al., 2008; Usher, 2002) compared with those in the United States. However, there has been relatively little detailed analysis of how doctoral education in business is delivered in Australia and New Zealand and how it has evolved more recently. Indeed, there is only limited recent research of which we are aware on the state business school doctoral education worldwide (Corner and Pio, 2017; Grottke et al., 2013). Hence, it is possible that programmes have become increasingly homogeneous, a function of academic drift (Berdahl, 1985; Miller, 1975; Tight, 2015).

Our motivation stems from the critical foundation doctoral studies have in graduates’ careers, particularly if they pursue an academic career (Bedeian et al., 2010). For example, homogenisation of academic training can bring benefits, including more consistent research skills and expertise, thereby providing a basis for successful academic careers (Bedeian et al., 2010; Fairweather, 1993). However, homogenisation can also be associated with a disproportionate focus on high-ranking journals (Swanson et al., 2007), discouraging interdisciplinary research and research relevant to practice (Jackson, 2022). Consistent with the research preferences of business school leaders, this homogenisation can be an important determinant of who they hire and the opportunities they provide. More broadly, PhD studies can also play an important part in graduates’ outcomes should they pursue non-academic career pathways (Sharmini and Spronken-Smith, 2020).

We apply a neo-institutional theoretical lens (DiMaggio and Powell, 1983, 1991; Scott, 2001) to understand the reasons for any similarities or differences between attributes of doctoral programmes. Our approach is consistent with prior studies using neo-institutional theory to explain similarities in university programme characteristics and how these have evolved (Altbach, 2011; Morphew and Huisman, 2002; Taylor et al., 2013). The scope of doctoral programmes is considerable, so exploring practices that predominate or otherwise, with reference to isomorphic pressures, is an appropriate means of understanding the current state of business doctoral programmes in Australia and New Zealand (Donaldson and Petersen, 2007; Morphew and Huisman, 2002).

We obtain detailed data on multiple characteristics of ANZ business school doctoral programmes using a survey developed in conjunction with input from the Business Academic Research Directors’ Network (BARDsNet). ANZ doctoral programmes in the region are typically 3 to 4 years full-time, focusing on research training via a substantial proportion of thesis completion and a smaller coursework proportion. We examine multiple characteristics in detail, providing insight into potential trends and challenges. We focus on three key areas. While selective, they reflect areas of identified concern (see Section 2). First, we consider the programme structure and assessment. This incorporates the role of coursework versus research and the extent to which formalised assessment occurs concerning coursework and the research component (i.e. thesis). Second, we consider the career objectives and prior experience of doctoral students. Third, we examine the funding of doctoral programmes, including the provision of scholarships. At the same time, we test for differences between university groupings and across major discipline groups.

Our results suggest that while these programmes are subject to isomorphic pressures, to a minor extent coercive and a larger extent normative isomorphism, there has not been extensive academic drift towards substantial homogenisation. For example, while most programmes surveyed have formal stages related to coercive funding considerations, they are not dominated by coercive coursework, leading to diverse research abilities. Normative pressure appears to drive characteristics related to best practice, including supervisory panels, funding for networking and the requirement for external examination. However, we find several areas of concern, including research-centric doctoral programmes, which, through various isomorphic pressures, appears consistent with programmes in the United States but inconsistent with the balanced (i.e. teaching/research) workload models in ANZ, where it is common for new doctoral graduates to carry significant teaching loads. On the contrary, normative pressures have not pushed ANZ business schools to consistently focus on quantitative skills, thereby reducing the extent to which doctoral graduates from ANZ business schools can be expected to publish in top-tier publications.

Our research makes several contributions. First, it extends prior studies of university programmes (especially doctoral programmes), viewed through a neo-institutional framework. We are unaware of prior evidence of this type focused on doctoral education in ANZ business schools. We also provide novel evidence regarding the research training processes within ANZ business schools, thereby providing business school academics and leaders with insights into challenges they may need to address.² This contribution is timely given an ageing academic workforce and the impact of COVID-19, whereby many senior business school academics may elect to take attractive redundancy packages, thereby making the role of newly produced doctoral graduates more critical and their impact on business school practices more substantial.

In the following section, we review the major areas of concern identified regarding doctoral education in the business disciplines, globally and within Australia and New Zealand. These issues guide the design of our survey instrument, also described in Section 2. Section 3 presents the results and highlights identified differences between university groupings and/or discipline areas. Section 4 concludes with suggestions for developing doctoral education in Australian and New Zealand business schools.

2. Background and method

2.1. Background

There is evidence of sustained concerns about the structure and content of business school doctoral programmes. For example, frequent calls for a better understanding of the general and ethical values applicable to academic research, with Mitchell (2007), Berry (1989), Krueger (1991) and Trapnell et al. (2009) considering this issue across several business disciplines in the United States. At the same time, there is a strong tendency in certain parts of the world to emulate the United States, often characterised by their perceived prestigious institutions, with a strong component of formal research training, including the completion of core and field courses, as well as seminars and workshops (Krueger, 1991). Institutional theory predicts organisations duplicate what is perceived as ‘correct’ practices so they are viewed both internally and externally as legitimate (Meyer and Rowan, 1977; Scott, 1987). The acquisition of normatively defined practices is argued to be critical for survival, compared with efficiency-related practices (Fligstein, 2001; Meyer, 1980), and isomorphic pressures result, leading to the homogenisation of activities (in this case, homogeneous doctoral programmes). These isomorphic pressures reflect coercive, mimetic and normative pressures (DiMaggio and Powell, 1983).

As institutions seek legitimacy through the isomorphic pressures causing practice duplication, this can broadly cause concerns about the nature of doctoral programme offerings. It has also been argued that the relatively ‘structured’ and ‘formal’ process increases the tendency towards relatively homogeneous research by doctoral students and early career researchers (Fraser, 2014). Schwartz et al. (2005) provide evidence that US accounting doctoral students generally have low familiarity with anything other than traditional ‘premier’ journals. Whether a heavy focus on method and technique results in less than optimal development of broader critical thinking skills and ability to undertake independent and relevant research is subject to conflicting evidence (Hansen, 1991; McKiernan and Tsui, 2019; Sandhu et al., 2019). What follows below is a general overview of the elements of doctoral programmes, beyond structure and content considerations above, that have been suggested in prior evidence as most significant.

An important characteristic of doctoral programmes is the availability and quality of supervision. Not surprisingly, prior studies identify supervisors’ experience heavily influences supervisory style. Yet it is well understood that supervisory style needs to vary contingent on students’ needs relating to their personality, maturity, intellectual and emotional characteristics. Wright et al. (2007) highlight this issue, consistent with often diverse student cohorts in Australia. However, small supervisory pools limit flexibility. While the use of supervisory committees means there is likely to be more variability and adaptability in supervisory styles, the extent of supervisory committees in Australian and New Zealand doctoral programmes is unclear.

Varied feedback and networking opportunities are important determinants of student success. Mitchell (2007) demonstrates the importance of attendance and engagement at events, allowing students in US programmes to network, such as conferences and exchange programmes. Accordingly, we survey the extent to which students can access financial support to attend such events.

While our main focus is on the role of doctoral programmes as a means of research training, we recognise the importance of teaching. Business school faculty are typically employed on a balanced teaching, research and service model. Focusing on the marketing discipline in Australia, Boddy (2007) argues that focus on dissertation completion is inadequate preparation for teaching. This is consistent with Australian doctoral graduates’ heavy teaching loads. Supporting evidence is provided by McCoy and Milkman (2010), who find only half of doctoral candidates who were teaching while completing an economics doctorate in the United States and Canada completed teacher training. Johnston et al. (2014) found similar levels of training among marketing students in the United States, and although 53% of marketing doctoral candidates had formal teacher training, only 11% had credit recognition for this training. We, therefore, explore teaching experience.

Changes to doctoral student funding, for example, by the Australian government, have emphasised the importance of more structured and directive programmes and encouraged faster completion. In addition, doctoral programmes compete for funding with coursework programmes, which are seen as having significantly greater reputational effects (Bearden et al., 2000). Lengthy completion time is expected to be a concern in Australia and New Zealand, as government funding is tied to completion.

US-based evidence identifies direct and indirect financial support as among the most influential factors determining an individual’s choice to apply for doctoral programme admission (Fisher and Garrett, 1984; Stewart et al., 2008). Compared to other forms of tertiary study, doctoral programmes represent a long and sometimes uncertain pathway. Financial support through a mix of scholarship and university work (including teaching opportunities) improves the prospect of attracting doctoral students and the likelihood of completion. Accordingly, we view the extent of financial support provided as an important dimension to survey.

Student characteristics are also an important dimension of doctoral education. Gender balance in academia has remained a long-running concern across disciplines, including those in Australia (Everett, 1994; Flynn et al., 2017). With significantly improved mentoring and networking opportunities directed at addressing gender imbalances (Sandhu et al., 2019), it is important to understand the gender balance in doctoral studies, as this represents the future academic pipeline. Similarly, it is important to understand the mix between local and international students, as implications arising from differences in writing norms and national cultures have been noted, including in New Zealand, where there is a large proportion of international students (Corner and Pio, 2017). The Australian and New Zealand tertiary sector has attracted large cohorts of international students, and our survey considers how extensive international student enrolment is across different business disciplines.

Prospective students’ intrinsic interest in completing a doctoral degree is a key determinant of students’ intention to apply for doctoral studies (Osei, 2013). Prior studies in the United States show students who are ambitious, motivated, persistent, organised and intellectually curious are more likely to complete their doctoral studies and achieve better research outcomes (Grottke et al., 2013; Podsakoff et al., 2018; Smart and Conant, 1990; Stock et al., 2009). While measuring the extent to which students exhibit such characteristics is outside the scope of our study, the diversity of pathways taken by students before enrolling in a doctoral programme may reflect intrinsic interest. We, therefore, attempt to elicit information on students’ professional and educational backgrounds. Concerns about the broader relevance of doctoral research may also reflect doctoral students with a lack of prior industrial and/or professional experience and/or an inability to communicate research outcomes to non-academics.

2.2. Research questions

Our survey gathers relevant descriptive evidence on the programme characteristics, funding, student attributes, student numbers and employment destinations across doctoral programmes in Australian and New Zealand business schools. However, we are also interested in testing for significant differences across recognised university groupings. As previously discussed, there is a tendency for academic drift and homogenisation (Morphew and Huisman, 2002; Tight, 2015). Our testing for differences allows us to examine the extent to which this is occurring in Australia and New Zealand. Examining the differences across the areas we survey is important, as isomorphic pressures may operate with varying effects (Oliver, 1988). As previously detailed, to make sense of any homogeneity observed, we apply a neo-institutional theoretical lens, in particular, focusing on why any programme isomorphism has occurred with reference to cohesive, mimetic and normative pressures.

We define observable university groupings based on the national location (Australia or New Zealand) and then by two well-recognised groupings of Australian universities – the Group of Eight universities (Go8)³ and Australian Technology Network of Universities (ATN).⁴ There is a strong correlation between membership of one of these groupings and the assessment of research quality, as evidenced by successive Excellence for Research in Australia (ERA) assessments (Feng and Taylor, 2021), although even among these groups, there have been significant differences in the overall ranking of Business and Economics research quality. Nevertheless, Feng and Taylor (2021) identified the top six Australian business schools comprising five from Go8 institutions and one from the ATN. Accordingly, it is of interest to understand whether university groupings are related to the state of doctoral programmes or if there is homogenisation of programmes more broadly across the areas we examine. Hence, our first research question (RQ) is:

RQ1: Are doctoral programme characteristics, funding, student attributes, student numbers and employment destinations similar across observable university groupings?

We also recognise there may be discipline-specific differences, although isomorphic forces could be pervasive, resulting in little, if any, difference between disciplines (Scott, 2001). We define disciplinary groupings consistent with the primary Field of Research (FoR) codes used by the Australian Research Council (ARC), namely economics, accounting, finance, marketing and management. Based on our review of prior literature and personal observations of business school practices, we focus on testing for several differences across doctoral programmes based on discipline areas.⁵ First, consistent with concerns about the heavy focus on method and technique (Hansen, 1991; McKiernan and Tsui, 2019; Sandhu et al., 2019), we examine whether this is specific to particular discipline areas. Second, consistent with documented differences in writing norms and national culture (Corner and Pio, 2017), it is important to understand if such challenges are more likely in certain discipline areas, in line with students’ origination and language background. Third, the pathways students take before doctoral programme enrolment may have implications for student interest and their doctoral research relevance (Bearden et al., 2000; Perry and Zuber-Skerritt, 1994). Different discipline areas may attract different proportions of students from certain pathways, and consistent with this, differing numbers of students. Finally, the pathways doctoral graduates take post-completion may differ, in line with concerns associated with research relevance in some disciplines (Burgstahler, 2019; Kaplan, 2019). Hence, our second RQ is:

RQ2: Are doctoral programme characteristics, student attributes, student numbers and employment destinations similar across recognised business school disciplinary groupings?

2.3. Method

Our survey was structured consistent with the guidance from Dillman et al. (2014). To maximise responses, we used simple and consistent question scales. We did not randomise question order, as the survey was structured based on a logical flow, aiding ease of completion, developed in consultation with members of the Australian Business Deans’ Council (ABDC) and, especially, from multiple discussions at BARDsNet meetings. This group comprised 46 university member institutions across Australia and New Zealand (essentially all business schools in both countries). Each of the 46 member institutions received the online survey.

There were three follow-up reminders for survey completion over almost 18 months.⁶ The survey was not anonymous, allowing targeted reminders. We received 27 responses, providing a 58.70% response rate. It is noteworthy that participation rate was strong across different university groupings. The response rate was 55.26% and 75% for Australian and New Zealand universities, respectively. Among the Australian universities, the Go8 response rate was 62%, while all ATN institutions participated. As these two groups dominate the ERA ratings of business research, there is very strong coverage of institutions most likely to produce successful future researchers. The response rate for the Innovative Research Universities and Regional Universities Network groups was 50% and 40%, respectively. Although we would have liked all ANZ business schools to participate, the strong and generally representative response rate increases our confidence in making generalisations about the underlying process by which future business school academics are produced.

To check for non-response bias, we compared responses received early and late, splitting the responses based on the mid-point according to the date each survey response was received. Our comparison of means using the Mann–Whitney U test indicates differences in the mean responses across the variables are almost all insignificant. We also test for common method bias using Harman’s single-factor test, resulting in five factors with eigenvalues greater than one. The strongest factor explains 32.98% of the total variance, indicating common method bias is not present (Podsakoff et al., 2003).

To address RQ1, are doctoral programme characteristics, funding, student attributes, student numbers and employment destinations similar across observable university groupings (Go8/non-Go8 Australia institutions, ATN/non-ATN Australian institutions, and Australian and New Zealand institutions compared), we use the Wilcoxon Z-statistic, consistent with the non-parametric nature of our data. To address RQ2, are doctoral programme characteristics, student attributes, student numbers and employment destinations similar across recognised business school disciplinary groupings (economics, accounting, finance, marketing and management), we use the Friedman test. The Friedman test allows testing of differences across three or more related samples and is appropriate for non-parametric data. We report the Chi-square and associated asymptotic significance output from the Friedman test. All respondent institutions undertake research, to some degree, across all disciplinary groupings. Coupled with the descriptive statistics, we report the differences in Section 3 below. A summary of the significant differences we find across university and disciplinary grouping is reported in Appendices 1 and 2, respectively.⁷

3. Results and discussion

3.1. Programme characteristics

Table 1 summarises the programme characteristics of surveyed doctoral programmes. In Panel A, we summarise programme structural characteristics. Almost all programmes (92.6%) have formal stages, with no significant differences noted across university groupings. Government programme funding, based on completion, appears to be a powerful source of influence, causing coercive isomorphism towards more closely monitoring student progression with a view to completion. However, while this might suggest a high degree of programme formalisation and homogenisation, further analysis indicates this is not so, alleviating concerns about such homogenisation as noted in the United States (Fraser, 2014). For example, among the respondent business schools, only half (48.1%) have mandatory coursework. When examining differences across university groupings, we identify 61.9% of Australian institutions require coursework, significantly higher than New Zealand institutions where no coursework is required. The maximum formal component is one-third of the programme, likely reflecting government accreditation requirements in line with the Australian Qualifications Framework (AQF). On average, surveyed programmes have a little less than 20% of the doctoral programme directed to some form of formal coursework (17.7%). We do not find significant differences in the proportion of doctoral programmes directed towards coursework across university groupings.

Table 1.

Programme characteristics.

Panel A: Structure
	Min.	Max.	Mean	Median	SD
Formal stages (binary variable)	0.000	1.000	0.926	1.000	0.267
Mandatory course work (binary variable)	0.000	1.000	0.481	0.000	0.509
Course work in programmes with mandatory course work (percentage)	4.000	33.000	17.692	17.000	8.380
Mandatory PhD examination (binary variable)	0.000	1.000	0.111	0.000	0.320
Oral PhD examination (binary variable)	0.000	1.000	0.370	0.000	0.492
Panel B: Research method
Quantitative methods
Percentages	Min.	Max.	Mean	Median	SD
All	15.000	78.000	56.300	55.500	16.547
Accounting	8.000	100.000	57.813	60.000	19.790
Economics	35.000	100.000	72.063	77.500	22.089
Finance	20.000	100.000	68.688	67.500	25.848
Management	5.000	80.000	52.563	51.000	17.780
Marketing	8.000	100.000	56.750	55.500	19.591
Other	2.000	75.000	48.533	50.000	16.668
Qualitative methods
Percentages	Min.	Max.	Mean	Median	SD
All	20.000	78.000	43.750	49.000	15.828
Accounting	0.000	66.000	39.500	39.500	19.002
Economics	0.000	65.000	26.000	22.500	23.042
Finance	0.000	80.000	31.313	30.000	25.710
Management	25.000	97.000	49.563	49.500	17.424
Marketing	0.000	92.000	41.375	42.000	20.607
Other	25.000	96.000	53.933	50.000	16.867
Panel C: Supervision
	Min.	Max.	Mean	Median	SD
Faculty holding doctoral degrees (percentage)	58.000	99.000	86.615	90.000	9.835
Supervised by a committee (binary variable)	0.000	1.000	0.889	1.000	0.320
Panel D: Networking support
Percentage	Min.	Max.	Mean	Median	SD
Funding for candidates to attend conferences/workshops/PhD colloquiums (binary variable)	0.000	1.000	1.000	1.000	0.000
Is the funding to attend conferences/workshops/PhD colloquiums guaranteed or competitively determined (1 = guaranteed, 0 = competitively determined)	0.000	1.000	0.778	1.000	0.424
Panel E: Teaching opportunities
Percentage	Min.	Max.	Mean	Median	SD
Students who are teaching while completing their doctoral programme	10.000	90.000	41.818	39.000	22.371

The less formalised nature of doctoral programmes is also evident concerning examinations, with only 11.1% of programmes having a mandatory PhD examination (for example, field and/or comprehensive), while only around one-third include some form of oral PhD examination. However, all New Zealand doctoral programmes for which we received responses include oral examinations, a function of government requirements and, therefore, a form of coercive isomorphism, significantly more than the 19% of Australian institutions using such examinations. Otherwise, there are no other significant differences in examinations across the groupings. Collectively, outside the staged doctoral programme approach and oral PhD examinations in New Zealand, the structural characteristics of programmes vary widely across institutions. This suggests institutions largely determine structural characteristics based on their own managerial and academic judgement, and structural homogenisation is only occurring via coercive isomorphism.

In Panel B of Table 1, we summarise the primary research method (i.e. quantitative versus qualitative) and provide a discipline breakdown. The percentage of students primarily using quantitative methods is on average 56.3%, while those primarily using qualitative methods is 43.8%, with no significant variation across university groupings. However, this percentage varies widely across disciplines, with economics and finance having the highest percentage of students primarily using quantitative methods at 72.1% and 68.7% on average, respectively. This is likely a reflection of the normative isomorphic pressures in economics and finance disciplines, where such methods are widely regarded as more acceptable based on the interaction between academics and as reflected in journal publications. The accounting, management and marketing disciplines are more balanced, with percentages of 57.8, 52.6 and 56.8, respectively. Among the discipline areas, the highest percentage of students who are primarily using qualitative research methods is in management, although accounting and marketing are both around 40%, not very different from management. The Friedman test confirms significant differences across discipline areas relating to the percentage of students employing both quantitative and qualitative methods.

We note the vast majority of articles published in accounting and marketing journals ranked as A* by the ABDC (i.e. journals ranked in the top tier) publish predominantly, or even exclusively, quantitative research, consistent with methods familiar to US doctoral programme graduates (Schwartz et al., 2005). We would have expected such normalisation of the predominately acceptable method, quantitative, would have been reflected in the primary research method of doctoral students, however, this is not the case. It is possible such normative forces have not had a notable impact, largely due to lower publication pressure in Australia and New Zealand compared with the US tenure system (Miller et al., 2011). Given the quantitative focus of A* journals, our survey results suggest that many doctoral graduates from Australian and New Zealand business schools are unlikely to publish research in these outlets. However, the wider scope of methods used by doctoral students in the region means research more relevant to industry may follow.

We next consider the forms of supervision, namely capacity to supervise and the supervision form (individual supervisor or supervisory committee). The availability of suitably qualified supervisors indicates that students are more likely to find supervision in their research area of interest and identify an appropriate fit concerning mentoring style and student motivation skills. The importance of supervisor characteristics in US management and economics programmes is documented by Ford et al. (2006) and Stock et al. (2009), and we note in passing thesis completion typically accounts for a smaller proportion of the doctoral programme than in Australia and New Zealand. For the responding institutions, Panel C of Table 1 reports an average of 86.6% of faculty members hold doctoral degrees. However, the lowest percentage of faculty with doctoral qualifications among responding institutions is a little over half (58%). Panel C indicates that vast majority of business school doctoral programmes require students to be supervised by some form of committee. Only around one-tenth of programmes (11.1%) typically allow a single supervisor. This suggests that any characterisation of doctoral study as a somewhat ‘feudal’ servant–master arrangement is inconsistent with practice in Australia and New Zealand. Furthermore, we do not observe any significant differences across university groupings based on faculty holding doctorates and using a committee supervision structure. The lack of significant differences in supervisory qualification and composition suggests such practice is an accepted professional norm in line with programme quality expectations (Ford et al., 2006; Stock et al., 2009) and increases programme attractiveness. Furthermore, the importance of accreditation in Australia and New Zealand has grown substantially and likely has led to some coercion concerning minimum supervisory expectations.

Panel D of Table 1 summarises financial support directed towards networking. Every respondent university indicated they provide some form of specific funding for doctoral students to attend conferences, workshops and doctoral colloquiums. Moreover, a substantial percentage of funding is effectively ‘guaranteed’ to students, with a small portion competitively determined. Hence, it appears as a universal recognition and an accepted norm that doctoral students benefit from the opportunity to attend conferences, presenting their research and developing a network, consistent with the insignificant differences across university groupings based on networking support. This finding is encouraging in the context of supporting collective doctoral training continuation, including that offered by the Financial Research Network (FIRN) and the Accounting and Finance Australia and New Zealand (AFAANZ) doctoral courses. Such training also potentially fills a vital role given the absence of significant coursework in many individual programmes.

Given doctoral programmes are primarily directed at preparing students for a career in research and teaching, it is important to understand whether it is common for students to gain teaching experience. Panel E of Table 1 indicates, on average, a little less than half of doctoral students (41.8%) teach. Interestingly, a significantly higher proportion of students at Go8 institutions undertake teaching (66.8%) compared with non-Go8 Australian institutions (27.2%). No significant differences are found between ATN and non-ATN Australia institutions, and Australian and New Zealand institutions. The high proportion in some institutions, particularly Go8 institutions, of doctoral students engaged in teaching suggests it is important to consider the teaching-related training provided so they can build on their expertise during doctoral programme completion. On the contrary, the low proportion in some institutions, also teaching, raises questions as to their preparedness to teach when commencing academic careers and the extent to which their employer institutions need to consider the incentives for good teaching and relevant doctoral graduate teaching certifications (Doogar, 2003). Doctoral programmes are an accepted means of preparing students for academic careers; however, through various isomorphic pressures, programmes largely focus on research rather than teaching. While this may be appropriate in the United States, where the early-career academic workload is research-focused, such a model is problematic in Australia and New Zealand, where early-career academics typically have more balanced workloads.

3.2. Funding

Panel A and B of Table 2 summarises our exploration of funding. Using a strongly disagree to strongly agree (1–5) Likert-type scale, the average response to the statement ‘funding constrains our number of PhD students’ is 3.96, varying from a score of 2 (disagree) to 5 (strongly agree) and a standard deviation of the 1.020. On a strongly disagree to strongly agree (1–5) Likert-type scale, the average response to ‘we have too many PhD students in our program’ is 2.36, varying from 1 (strongly disagree) to 4 (agree) with a standard deviation of 0.70, indicating student numbers are not perceived as excessive in most institutions. The strong indication is funding constrains student numbers, with no significant differences across university groupings. With universities largely reliant on government funding, this appears to be acting as a coercive force limiting numbers. It appears universities would like to expand doctoral programmes and thereby research output, suggesting institutions should pursue further industry-funded engagement. Industry-funded engagement would have the added benefit of encouraging industry-relevant research.

Table 2.

Funding.

Panel A: Descriptive statistics
	Min.	Max.	Mean	Median	SD
Funding constrains our number of PhD students (Likert scale 1–5)	2.000	5.000	3.960	4.000	1.020
We have too many PhD students in our programme (Likert scale 1–5)	1.000	4.000	2.360	2.000	0.700
Students who complete their doctoral studies on time over the last 5 years (percentage)	11.000	94.000	64.375	70.500	22.335
Completing PhD full time (percentage)	38.000	100.000	70.792	75.000	14.747
Students who have completed a research masters and/or honours degrees (percentage)	2.000	100.000	76.522	92.000	32.284
Minimum number of examiners on each dissertation	1.000	3.000	2.259	2.000	0.526
Panel B: Likert scale point percentage
	Strongly disagree (1)	Disagree (2)	Agree nor disagree (3)	Agree (4)	Strongly agree (5)
Funding constrains our number of PhD students	0.000	16.000	4.000	48.000	32.000
We have too many PhD students in our programme	8.000	52.000	36.000	4.000	0.000
Panel C: Financial position
Percentage	Min.	Max.	Mean	Median	SD
Funded by competitive scholarships (e.g. university, APA or industry)	5.000	90.000	53.750	56.500	23.981
Funded by internal scholarships (e.g. teaching, research assistance and PhD packages)	0.000	48.000	14.900	11.000	14.119

APA: Australian Postgraduate Awards.

Consistent with the pressure of limited funding, responses indicate 64.4% of students complete their doctoral studies on time. Students at Australian institutions are significantly more likely to complete on time (68.4%) than their New Zealand counterparts (49%). Higher rates of on-time completion in Australia are likely the result of coercive government pressures whereby universities receive funding based on student graduation. In our sample, we also observe that a substantial number of doctoral students are completing their studies part-time. Panel A of Table 2 reports 70.8% of students are completing their PhD full-time, varying between 38.0% and 100.0% depending on the institution. From our university groupings, we find a significantly higher proportion of students completing their PhD full-time at New Zealand institutions (83%) compared with Australian students (67.6%). There is considerable variation across both countries and across university groupings, indicating study mode of students, whether full or part-time, is likely a function of individual institutional preferences, coupled with the students they attract.

Students who complete research studies before doctoral programme enrolment may also complete at a faster rate. On average, 76.5% of doctoral students have completed a research masters and/or honours degree. Although this varies widely across responding institutions, this is not associated with identifiable university groupings. The higher risk of non-completion for doctoral students without prior research studies is recognised, including the study by Stock et al. (2011) in the United States, where programmes are more course intensive and thereby, students without prior research studies are at less risk compared with students in Australia and New Zealand, where students typically receive less coursework training. While the percentage of students who have completed prior research studies varies widely, the average is high and likely a function of both normative pressure, based on shared knowledge of applicants’ chance of successfully completing doctoral studies, and coercive government forces, constraining funding if the students do not complete. Finally, Panel A of Table 2 reports common approaches to thesis examination. All surveyed institutions use external examiners, with common reliance on two or three examiners, and thereby no significant differences across university groupings. This indicates normative isomorphic pressure that external verification is completely accepted by business school academics, and absence would indicate a disconnect from the academic community.

Panel C of Table 2 reports the methods by which students primarily fund their candidature. Given earlier evidence of institutional funding limitations, it is not surprising that Panel C reveals only around half of enrolled students are typically funded by competitive scholarships, such as those provided by the university, government or industry. However, this percentage varies widely, ranging from 5% to 90%. We also find on average, an additional 14.9% of students are funded by internal scholarships related to teaching, research assistance or other activities. In general, it appears that a large proportion of students do not receive explicit funding and are dependent on other forms of financial support such as external employment and/or family assistance. On average, we find about a quarter of doctoral students live on campus, although this varies widely across institutions. Despite the variation observed in scholarship funding, there are no significant differences across university groupings. This may reflect scholarship determination based on individual student merit at each institution, rather than systematic differences in scholarships awarded across different institutions, driven by government funding constraints and limited industry engagement.

3.3. Student characteristics

Table 3 reports responses to questions regarding student characteristics. We find just over half (52.12%) of doctoral students are females. However, this varies widely across institutions, with a minimum to maximum female candidature of 25% to 78% and a standard deviation of 10.2%, although there are no significant differences across identifiable university groupings. These numbers are consistent with gender balance in the early career researcher pipeline, although some institutions’ cohort of doctoral candidates is far from gender-balanced. Given normative pressures within the sector and potential coercive regulatory pressures, the lack of gender balance in some institutions is surprising.

Table 3.

Student characteristics.

Panel A: Gender
Percentage	Min.	Max.	Mean	Median	SD
Female students	25.000	78.000	52.125	50.500	10.182
Panel B: Origination (local students)
Percentages	Min.	Max.	Mean	Median	SD
All	9.000	80.000	43.238	44.000	19.421
Accounting	4.000	100.00	43.294	30.000	28.541
Economics	3.000	100.00	39.941	30.000	25.459
Finance	9.000	80.000	38.824	30.000	20.601
Management	9.000	80.000	41.765	30.000	24.242
Marketing	9.000	94.000	42.313	30.000	25.811
Other	1.000	100.000	43.942	30.000	40.356
Panel C: Language background (English)
Percentages	Min.	Max.	Mean	Median	SD
All	7.000	80.000	46.408	40.000	18.353
Accounting	3.000	100.000	47.000	45.000	21.051
Economics	0.000	75.000	41.000	40.000	21.172
Finance	0.000	100.000	45.118	40.000	23.648
Management	8.000	83.000	47.222	45.000	20.704
Marketing	11.000	85.000	45.706	40.000	19.880
Other	3.000	87.000	48.438	45.000	21.049
Panel D: Industry background
Percentages	Min.	Max.	Mean	Median	SD
All	10.000	96.000	43.316	43.000	24.806
Accounting	0.000	100.000	39.889	45.000	31.728
Economics	0.000	100.000	39.333	34.000	28.357
Finance	5.000	100.000	40.722	41.500	27.915
Management	10.000	100.000	49.167	49.500	27.045
Marketing	0.000	87.000	39.667	49.500	25.796
Other	0.000	100.000	47.313	49.500	28.535
Panel E: Academic background
Percentages	Min.	Max.	Mean	Median	SD
All	10.000	94.000	38.100	33.500	22.110
Accounting	5.000	100.000	42.056	32.000	31.004
Economics	8.000	100.000	37.000	24.000	30.236
Finance	5.000	94.000	34.222	27.500	25.655
Management	0.000	94.000	39.389	31.000	26.951
Marketing	10.000	100.000	43.412	37.000	30.877
Other	10.000	94.000	39.438	30.000	24.787
Panel F: Age
Percentages	Min.	Max.	Mean	Median	SD
Candidate age	24.000	49.000	33.280	32.000	6.045
Panel G: Acceptance rates
Percentages	Min.	Max.	Mean	Median	SD
All universities	5.000	70.000	26.346	20.000	20.363
Australian universities	5.000	70.000	27.048	20.000	19.996
Go8	5.000	25.000	13.200	10.000	8.871
Non-Go8 (Australian universities)	9.000	70.000	31.375	27.500	20.656
New Zealand universities	10.000	66.000	23.400	11.000	24.183

We also consider the extent to which doctoral students are sourced locally versus overseas. Panel B of Table 3 shows an average of 43.2% of doctoral students are local students, varying widely across institutions from 9% to 80% with a standard deviation of 19.4%, although there are no significant differences across university groupings. When we examine this question across specific disciplines, we observe only small insignificant variations. The high numbers of international students are not surprising given the fees charged, which reduces the coercive impacts of government funding. However, it also presents potential challenges associated with those from non-English speaking backgrounds. Panel C of Table 3 reports only 46.4% of PhD students come from English-speaking backgrounds, and once again, we observe no statistically significant variation across the disciplinary areas (confirmed by the Friedman test) or between identifiable university groupings. Such a high proportion of non-English background students has previously been recognised by Corner and Pio (2017) in the New Zealand context as a challenge for effectively delivering doctoral programmes, given different writing norms and academia perceptions. Given the large number of international students in Australia and New Zealand, we expect this challenge to continue and could be made worse by pandemic-induced isolation.

Further evidence on the background of doctoral students is reported in Panels D and E of Table 3. On average, 43.3% of students have industry experience, varying from 10% to 96%, with a standard deviation of 24.8%. Students from industry comprise, on average, between 39.3% and 40.7% of candidates in accounting, economics, finance and marketing. However, industry candidates comprise 49.2% of candidates in management, which is significantly higher than other discipline groupings. This difference may reflect greater intrinsic interest of industry-based students in the management discipline, who are thus prepared to come back to university. It may also reflect a preference among candidates from industry to undertake doctoral studies in a discipline where qualitative research methods are common. Regardless, higher proportions of students with an industry background would likely improve the research relevance. Thus, the low proportion of industry candidates, particularly in some institutions, and lower proportions across some disciplines is a concern. The high proportions of students not from industry is likely a function of the relatively high numbers of such students in the prospective student pool, coercive pressure to accept these students for funding and research output reasons, and limited funding in some cases to attract those with industry experience through scholarships.

Panel E of Table 3 indicates, on average, 38.1% of students have prior academic experience, varying widely from 10% to 94%. The extent to which students come from an academic background within their discipline varies, although not significantly, comprising 43.4% of students in marketing, 42.1% in management, 39.4% in accounting, 37.0% in economics and 34.2% among finance candidates. The lower proportion of candidates with an academic background is likely a function of the coercive pressures in business schools to hire full-time academics who have completed their PhD in line with accreditation requirements. Some candidates may have prior experience through casual research assistant and teaching positions; however, it is more common to undertake such positions while completing doctoral studies.

The average candidate age in our sample is 33.28, varying widely from 24 to 49 with a standard deviation of 6.05, as reported in Table 3 Panel F. This variation in age reflects a student cohort ranging from recent undergraduate coursework graduates to those with significant industry experience and does not vary significantly based on university groupings. Based on average age, doctoral candidates potentially have a little more than 10 years of industry experience following undergraduate studies, although the extent to which this time period also reflects other post-graduate study rather than non-academic career paths is not known. The higher proportion of candidates lacking industry experience suggests many candidates have completed other post-graduate studies, such as masters programmes. Once again, the ability of such candidates with limited experience to identify RQs relevant to industry remains a concern.

We next consider acceptance rates. Acceptance rates provide a basic insight into the level of demand to undertake doctoral studies. Panel G of Table 3 reports these results. On average, 26.4% of applicants are accepted into doctoral programmes, varying widely from 5% to 70%. Given the average acceptance rates are below 30%, there appears to be relatively rigorous selection processes. Based on our university groupings, Go8 institutions have significantly lower acceptance rates than non-Go8 Australian universities. This could be a function of normative pressures to identify as part of the Go8 group with agreement on a higher standard of potential applicants or simply a function of the larger volume of applicants due to perceived higher quality programmes.

3.4. Student numbers

Doctoral candidate numbers are summarised in Table 4. The average number in each institution was 15.0 in accounting, 20.1 in economics, 14.2 in finance, 30.5 in management and 15.0 in marketing, with the Friedman test indicating significant differences across disciplines. The Wilcoxon test indicates management has significantly higher numbers than all other disciplines. This is unsurprising given the wide scope of research topics in management.

Table 4.

Students numbers.

Panel A: All universities
Discipline	Min.	Max.	Mean	Median	SD
All	6.000	366.000	113.870	120.000	80.864
Accounting	1.000	42.000	15.000	10.500	12.344
Economics	0.000	101.000	20.091	15.000	23.191
Finance	0.000	39.000	14.238	10.000	12.864
Management	1.000	82.000	30.454	30.000	20.423
Marketing	1.000	35.000	15.048	16.000	9.997
Other	1.000	150.000	31.222	14.500	36.480
Panel B: Australian universities
Discipline	Min.	Max.	Mean	Median	SD
All	6.000	366.000	119.333	127.000	89.640
Accounting	1.000	42.000	15.118	11.000	13.181
Economics	0.000	101.000	21.882	15.000	25.913
Finance	0.000	39.000	16.688	12.500	13.812
Management	1.000	82.000	30.588	30.000	21.680
Marketing	1.000	35.000	15.625	16.000	10.972
Other	1.000	150.000	34.429	14.500	40.574
Panel C: Go8
Discipline	Min.	Max.	Mean	Median	SD
All	91.000	249.000	161.600	151.00	56.787
Accounting	3.000	24.000	12.800	13.000	7.759
Economics	0.000	63.000	22.600	20.000	26.054
Finance	12.000	37.000	28.600	33.000	9.965
Management	29.000	82.000	40.800	30.000	23.080
Marketing	11.000	30.000	18.600	16.000	7.127
Other	16.000	81.000	47.750	47.000	28.593
Panel D: Non-Go8 (Australian universities)
Discipline	Min.	Max.	Mean	Median	SD
All	6.000	366.000	103.077	79.000	93.321
Accounting	1.000	42.000	16.083	10.500	15.078
Economics	1.000	101.000	21.583	13.500	27.010
Finance	0.000	39.000	11.273	10.000	11.967
Management	1.000	73.000	26.333	25.000	20.562
Marketing	1.000	35.000	14.273	10.000	12.402
Other	1.000	150.000	29.100	11.000	44.665
Panel E: New Zealand universities
Discipline	Min.	Max.	Mean	Median	SD
All	43.000	122.000	94.200	112.000	34.586
Accounting	6.000	30.000	14.600	10.000	10.237
Economics	4.000	23.000	14.000	15.000	8.803
Finance	3.000	12.000	6.400	6.000	3.362
Management	15.000	60.000	30.000	23.000	17.593
Marketing	5.000	22.000	13.200	12.000	6.535
Other	4.000	33.000	20.000	21.500	13.832

We find significantly higher numbers of students completing finance doctoral studies at Go8 compared with non-Go8 institutions. This possibly reflects the prestige and high-ranking publications in finance studies, aligned with normative pressure in Go8 institutions to maintain their identity as leading research institutions. In contrast, there are significantly higher numbers of accounting and management students at ATN compared to non-ATN Australian institutions. This could reflect the more practice-based nature of accounting and management and, therefore, normative pressure on ATN institutions to maintain their identity as leaders in practice-related research and thereby engage with such practice, although this is difficult to say given the broad range of research topics these disciplines encompass. No other differences across university groupings are noted. When account is taken of the relatively large number of business schools, even allowing for the large number of students who do not take up employment in the university sector (see Section 3.5 below), it would appear there is a relatively substantial pipeline of new academics.

3.5. Employment destinations

To understand immediate graduate outcomes, we survey institutions concerning graduate pathways. On average, 53.1% of graduates go to academic employment destinations, varying widely from 15% to 90% with a standard deviation of 20.9%, as reported in Panel A of Table 5. The Friedman test confirms the proportion of students going to an academic employment destination varies significantly, however, no significant one-to-one differences are found using the Wilcoxon test. The discipline where the highest percentage of graduates go to an academic destination is accounting (62.0%), followed by marketing (55.7%), management (55.4%), economics (52.9%) and finally finance (49.9%), although again, these percentages vary widely across institutions. These percentages do not differ significantly across university groupings. Although we are reluctant to over-extrapolate, the fact accounting doctoral programmes have the highest academic employment destination rate is also consistent with recent criticisms that accounting research is of little relevance to the profession, as shown by Burgstahler (2019) and Kaplan (2019) in the United States. Of course, whether this reflects the way doctoral programmes operate, the background of the doctoral students (e.g. lack of prior professional/industrial experience), succumbing to normative pressures to identify as part of an academic rather than practice-based discipline, or some other factor, is not clear.

Table 5.

Employment destinations.

Panel A: Academic
Percentage	Min.	Max.	Mean	Median	SD
All	15.000	90.000	53.111	54.000	20.942
Accounting	15.000	100.000	62.000	67.000	25.011
Economics	5.000	90.000	52.933	65.000	23.945
Finance	2.000	90.000	49.867	50.000	23.883
Management	15.000	90.000	55.400	55.000	19.946
Marketing	15.000	90.000	55.667	60.000	19.606
Other	15.000	90.000	50.875	50.000	21.685
Panel B: Industry
Percentage	Min.	Max.	Mean	Median	SD
All	8.000	76.000	32.765	26.000	19.344
Accounting	0.000	76.000	28.071	25.000	21.935
Economics	10.000	88.000	35.643	25.500	24.149
Finance	0.000	92.000	38.143	30.000	25.264
Management	10.000	76.000	34.857	28.000	17.999
Marketing	0.000	76.000	32.714	28.000	19.660
Other	10.000	76.000	39.267	30.000	20.130
Panel C: Government
Percentage	Min.	Max.	Mean	Median	SD
All	0.000	31.000	11.000	10.000	9.097
Accounting	0.000	30.000	9.308	10.000	8.807
Economics	0.000	50.000	13.929	10.000	13.499
Finance	0.000	30.000	10.538	10.000	8.743
Management	0.000	30.000	9.385	10.000	8.372
Marketing	0.000	30.000	8.231	6.000	9.038
Other	0.000	30.000	12.643	10.000	8.949

Given our findings that a large proportion of doctoral graduates do not go to academic positions, we further examine alternative employment destinations, with industry and government destinations reported in Table 5, Panels B and C, respectively. Of course, as with all employment destination responses, these figures are dependent in several cases on estimations sourced by the respondents. On average, 32.8% and 11.0% of graduates go to industry and government employment destinations, respectively. The discipline where the highest percentage go to industry is finance (38.1%), followed by economics (35.6%), management (34.9%), marketing (32.7%) and finally, accounting (28.1%), however, these differences are not significant based on the Friedman test. The discipline where the highest percentage of graduates go to government employment destinations is economics (13.9%), followed by finance (10.5%), management (9.4%), accounting (9.3%) and marketing (8.2%), however again, these differences are not significant. Interestingly, the proportion of management students at Go8 institutions going on to industry employment is less than half that of other institutions. In contrast, there is a significantly higher proportion of students going to industry employment across accounting, economics, finance and marketing at ATN compared to non-ATN Australian institutions. These differences appear in line with the normative pressures in both types of institutions and the stakeholders they interact with; Go8 institutions generally focus on high-ranking research, while ATN institutions are more concerned with work readiness outcomes. No other significant differences are found across the university groupings. Overall, these findings suggest that research relevance is more likely to be considered in ATN institutions than in that of Go8 institutions, given the difference in graduate pathways. However, it also must be acknowledged that graduates from Go8 institutions are more likely to find opportunities to stay within academia.

4. Conclusion

Given concerns about future trends and challenges in Australian and New Zealand business schools, we conduct a detailed survey of Australian and New Zealand business school doctoral programmes. We apply a neo-institutional theoretical lens to make sense of the underlying reasons for the state of these doctoral programmes and the degree of observable homogeneity. In general, our survey of doctoral programmes suggests that institutional normative isomorphism largely explains similarities in the key characteristics observed across different university groups and discipline areas, going well beyond the superficial role of coercive pressures (Scott, 2008).

There are many positive aspects of business school doctoral programmes in Australia and New Zealand. The combination of homogeneous and heterogeneous characteristics suggests Australian and New Zealand universities are subject to isomorphic pressures that have varying effects on doctor programme attributes (Oliver, 1988) and which have not led to extensive academic drift and programme replication throughout the region. While the majority of programmes have formal stages, likely relating to coercive funding considerations, they are generally not dominated by coursework or one research method, thereby potentially contributing to heterogeneity in research output and abilities of graduates. Students appear to receive support via supervisory panels (rather than single supervisors), funding to develop their professional network, illustrating recognition of best practice and normative isomorphism in action. However, there appears only limited opportunity to receive scholarships and living support. Furthermore, teaching opportunities vary widely while completing doctoral studies, and it is encouraging to see that significantly higher numbers of students from Go8 institutions are provided with teaching opportunities. Limited teaching opportunities in some institutions is potentially concerning, a reflection of the research-centred nature of doctoral programmes and not the balanced workload models in Australia and New Zealand.

Not surprisingly, our survey reveals the majority of graduates take up academic positions upon completion, consistent with the lack of candidate industry experience, limited industry funding and the universal academic orientation of doctoral programmes. However, with the decline in international student numbers and associated funding, the number of positions available for the foreseeable future may be greatly diminished. A higher proportion of graduates may need to find employment in industry and government, which could be problematic given concerns over research relevance and, consequently, the degree to which non-academic employers value doctoral graduates. We suggest pathways into doctoral programmes need to change substantially, and greater encouragement is needed for those with industry experience to enter programmes, thereby promoting industry-relevant research projects. Of course, the concerns associated with the ad hoc nature of funding also need to be acknowledged. Attracting a higher proportion of candidates with greater industry experience will be difficult in the absence of a financial model supporting such students.

Although our results suggest some diversity in the extent to which Australian and New Zealand business schools prepare doctoral students to address the challenges in producing quality research seen as relevant beyond the academy, there is nevertheless a high degree of commonality around most of the issues. Funding constraints, limited pre-doctoral study experience and pressure to gain teaching experience are relatively common problems in Australian and New Zealand business school doctoral programmes. While there seems to be common acceptance of the need for external examination to verify satisfactory research achievement, we are surprised at the reluctance to adopt a more formalised training in research methods, despite an apparent enthusiasm for progressive assessment/stages. We are, likewise, concerned at the large proportion of doctoral students who see their future as being in qualitative research, despite the high percentage of top-tier research journals in business disciplines having a quantitative focus. The absence of training in quantitative research methods likely limits the extent to which research will be publishable in many of the leading outlets. It seems normative isomorphic pressures concerning research method and focus on high-ranking publications have not taken hold in Australian and New Zealand business schools. This may also have negative implications for future assessments of research quality where quality is implicitly or explicitly linked to the most highly ranked journals.

It is also noteworthy that few doctoral students in business schools have substantive professional or industrial experience, although it should be noted that Go8 institutions appear more discerning in selecting applicants with lower acceptance rates. Hence, even where students receive sufficient research training, their ability to produce academically rigorous research may not be matched by an understanding of (or even an ability to recognise) important RQs relevant beyond the academy (Burgstahler, 2019; Kaplan, 2019). The importance of conducting research, which is relevant to industry, the professions and policy-making more broadly, is likely becoming more important (Jackson, 2022). In addition, there is likely to be an increasing demand to incorporate relevant research into industry-focused curriculum (i.e. in teaching). The characteristics of a typical doctoral student, which we document, suggests caution is warranted in believing business research is of increasing relevance beyond the academy.

A potential limitation of this study is it reports on the state of doctoral programmes pre-COVID-19. Changes in the operating models of business schools are likely, and this may, in turn, lead to significant changes in their doctoral programmes. We suggest that understanding how such changes occur and their implications for teaching and research in the business disciplines will be crucial in predicting the quality and relevance of research (and teaching) in Australian and New Zealand business schools. We also suggest some broader evaluation of the quality of doctoral education is warranted. In the manner of existing evaluation of research quality (i.e. ERA assessments), a potentially important starting point would be to have some record of the publication outcomes of doctoral programme graduates.

Footnotes

Appendix

Appendix 2.

Summary of significant differences across discipline areas.

	Accounting			Economics			Finance			Management			Marketing
	Mean	Median	SD	Mean	Median	SD	Mean	Median	SD	Mean	Median	SD	Mean	Median	SD
Student numbers	15.000	10.500	12.344	20.091	15.000	23.191	14.238	10.000	12.864	30.455	30.000	20.423	15.048	16.000	9.997
Quantitative research method	57.813	60.000	19.790	72.063	77.500	22.089	68.688	67.500	25.848	52.563	51.000	17.780	56.750	55.500	19.591
Qualitative research method	39.500	39.500	19.0002	26.000	22.500	23.042	31.313	30.000	25.710	49.563	49.500	17.424	41.375	42.000	20.607
Academic employment destination	62.000	67.000	25.011	52.933	65.000	23.945	49.867	50.000	23.883	55.400	55.000	19.946	55.667	60.000	19.606

									Chi-square			Asymptotic significance
Student numbers									27.780			0.000
Quantitative research method									13.373			0.010
Qualitative research method									18.535			0.001
Academic employment destination									9.600			0.048

Acknowledgements

We acknowledge the suggestions of the editor, Andrew Jackson, and two anonymous reviewers. We also appreciate the support of many past and present Deans and Associate Deans-Research, in enabling the administration of our survey. We also appreciate the feedback of attendees at meetings of the ABDC, meetings of the Business Academic Research Directors’ Network (BARDSNet) and our UTS colleagues.

Final transcript accepted 19 August 2022 by Andrew Jackson (Editor-in-Chief ).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support for this research was provided by the Australian Business Deans’ Council (ABDC) and UTS Business School. However, the views expressed are solely those of the authors.

ORCID iD

James Wakefield

Notes

References

Altbach

(2011) The past, present, and future of the research university. Economic and Political Weekly 46: 65–73.

Bearden

Ellen

Netemeyer

(2000) Challenges and prospects facing doctoral education in marketing. Marketing Education Review 10: 1–14.

Bedeian

Cavazos

Hunt

, et al. (2010) Doctoral degree prestige and the academic marketplace: A study of career mobility within the management discipline. Academy of Management Learning & Education 9: 11–25.

Berdahl

(1985) Strategy and government: US State systems and institutional role and mission. International Journal of Institutional Management in Higher Education 9: 301–307.

Berry

(1989) Becoming a marketing academician: A strategic career planning seminar for doctoral students. Journal of Marketing Education 11: 2–6.

Boddy

(2007) Academia marketing myopia and the cult of the PhD. Marketing Intelligence & Planning 25: 217–228.

Burgstahler

(2019) Promoting research relevance. Accounting Horizons 33: 1–2.

Corner

Pio

(2017) Supervising international students’ theses and dissertations. Academy of Management Learning & Education 16: 23–38.

Dillman

Smyth

Christian

(2014) Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method. Hoboken, NJ: John Wiley & Sons.

10.

DiMaggio

Powell

(1983) The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review 48: 147–160.

11.

DiMaggio

Powell

(1991) The iron cage revisited. In: Powell

DiMaggio

(eds) The New Institutionalism in Organizational Analysis. Chicago, IL: The University of Chicago Press, pp. 63–82.

12.

Donaldson

Petersen

(2007) Cohort doctoral preparation programs: Neo-institutional perspectives. Connexions module: m14518. Available at: https://core.ac.uk/download/pdf/19135756.pdf

13.

Doogar

(2003) What should accounting doctoral programs focus on? An economic perspective. In: Schwartz

Ketz

(eds) Advances in Accounting Education Teaching and Curriculum Innovations. Bingley: Emerald Group Publishing, pp. 199–209.

14.

Everett

(1994) Sex, rank and qualifications at Australian universities. Australian Journal of Management 19: 159–175.

15.

Fairweather

(1993) Faculty reward structures: Toward institutional and professional homogenization. Research in Higher Education 34: 603–623.

16.

Feng

Taylor

(2021) How excellent is research in Australian business schools? Lessons from past ERA assessments. UTS working paper, University of Technology Sydney (UTS), Broadway, NSW, Australia.

17.

Fisher

Garrett

(1984) The marketing educator shortage: A supply side perspective. Journal of Marketing Education 6: 7–13.

18.

Fligstein

(2001) The Architecture of Markets. Princeton, NJ: Princeton University Press.

19.

Flynn

Cavanagh

Bilimoria

(2017) Gender equality in business schools: The elephant in the room. In: Flynn

Haynes

Kilgour

(eds) Integrating Gender Equality into Business and Management Education. London: Routledge, pp. 26–54.

20.

Ford

Duncan

Bedeian

, et al. (2006) People, places, and life transitions: Consequential experiences in the lives of management laureates. Academy of Management Learning & Education 5: 408–421.

21.

Fraser

(2014) Position paper: Defeating the ‘paradigm wars’ in accounting: A mixed-methods approach is needed in the education of PhD scholars. International Journal of Multiple Research Approaches 8: 49–62.

22.

Grottke

Pelger

Schmiedeberg

(2013) Firm or faculty? Evidence on characteristics of German-speaking accounting PhD students and their career preferences. Accounting Education 22: 66–84.

23.

Hansen

(1991) The education and training of economics doctorates: Major findings of the executive secretary of the American Economic Association’s commission on graduate education in economics. Journal of Economic Literature 29: 1054–1087.

24.

Jackson

(2022) A call for policy relevant research. Australian Journal of Management 47: 399–400.

25.

Johnston

Keller

Linnhoff

(2014) Mentoring in doctoral programs and preparedness of early career marketing educators. Academy of Educational Leadership Journal 18: 15–22.

26.

Kaplan

(2019) Reverse the curse of the top-5. Accounting Horizons 33: 17–24.

27.

Krueger

(1991) Report of the commission on graduate education in economics. Journal of Economic Literature 29: 1035–1053.

28.

McCoy

Milkman

(2010) Do recent PhD economists feel prepared to teach economics? The Journal of Economic Education 41: 211–215.

29.

McKiernan

Tsui

(2019) Responsible management research: A senior scholar legacy in doctoral education. Academy of Management Learning & Education 18: 310–313.

30.

Meyer

(1980) Institutional and Technical Sources of Organizational Structure Explaining the Structure of Educational Organizations. Stanford, CA: Stanford University.

31.

Meyer

Rowan

(1977) Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology 83: 340–363.

32.

Miller

Taylor

Bedeian

(2011) Publish or perish: Academic life as management faculty live it. Career Development International 16: 422–445.

33.

Miller

Jr (1975) Evaluation and political reality. New Directions for Institutional Research 1975: 47–54.

34.

Mitchell

(2007) The academic life: Realistic changes needed for business school students and faculty. Academy of Management Learning & Education 6: 236–251.

35.

Morphew

Huisman

(2002) Using institutional theory to reframe research on academic drift. Higher Education in Europe 27: 491–506.

36.

Oliver

(1988) The collective strategy framework: An application to competing predictions of isomorphism. Administrative Science Quarterly 33: 543–561.

37.

Osei

(2013) The dissertation process in obtaining philosopher doctorate in business administration. American International Journal of Contemporary Research 3: 106–112.

38.

Pearson

Evans

Macauley

(2008) Growth and diversity in doctoral education: Assessing the Australian experience. Higher Education 55: 357–372.

39.

Perry

Zuber-Skerritt

(1994) Doctorates by action research for senior practising managers. Management Learning 25: 341–364.

40.

Podsakoff

MacKenzie

Lee

J-Y

, et al. (2003) Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88: 879–903.

41.

Podsakoff

Mishra

, et al. (2018) Can early-career scholars conduct impactful research? Playing ‘small ball’ versus ‘swinging for the fences’. Academy of Management Learning & Education 17: 496–531.

42.

Sandhu

Perera

Sardeshmukh

(2019) Charted courses and meandering trails: Crafting success and impact as business school academics. Academy of Management Learning & Education 18: 153–185.

43.

Schwartz

Williams

(2005) US doctoral students’ familiarity with accounting journals: Insights into the structure of the US academy. Critical Perspectives on Accounting 16: 327–348.

44.

Scott

(1987) The adolescence of institutional theory. Administrative Science Quarterly 32: 493–511.

45.

Scott

(2001) Institutions and Organizations. 2nd ed. Thousand Oaks, CA: SAGE.

46.

Scott

(2008) Approaching adulthood: The maturing of institutional theory. Theory and Society 37: 427–442.

47.

Sharmini

Spronken-Smith

(2020) The PhD – Is it out of alignment? Higher Education Research & Development 39: 821–833.

48.

Smart

Conant

(1990) Marketing dissertations: Profiling the successful thesis candidate. Journal of Marketing Education 12: 2–8.

49.

Stewart

Williamson

King

Jr (2008) Who wants to be a business PhD? Exploring minority entry into the faculty ‘pipeline’. Academy of Management Learning & Education 7: 42–55.

50.

Stock

Finegan

Siegfried

(2009) Completing an economics PhD in five years. American Economic Review 99: 624–629.

51.

Stock

Siegfried

Finegan

(2011) Completion rates and time-to-degree in economics PhD programs (with comments by David Colander, N. Gregory Mankiw, Melissa P. McInerney, James M. Poterba). American Economic Review 101: 176–188.

52.

Swanson

Wolfe

Zardkoohi

(2007) Concentration in publishing at top-tier business journals: Evidence and potential explanations. Contemporary Accounting Research 24: 1255–1289.

53.

Taylor

Webber

Jacobs

(2013) Institutional research in light of internationalization, growth, and competition. New Directions for Institutional Research 2013: 5–22.

54.

Tight

(2015) Theory development and application in higher education research: The case of academic drift. Journal of Educational Administration and History 47: 84–99.

55.

Trapnell

Mero

Williams

, et al. (2009) The accounting doctoral shortage: Time for a new model. Issues in Accounting Education 24: 427–432.

56.

Usher

(2002) A diversity of doctorates: Fitness for the knowledge economy? Higher Education Research & Development 21: 143–153.

57.

Wright

Murray

Geale

(2007) A phenomenographic study of what it means to supervise doctoral students. Academy of Management Learning & Education 6: 458–474.