Higher Education

, Volume 64, Issue 1, pp 41–58 | Cite as

Academic dissatisfaction, managerial change and neo-liberalism



This paper examines perceptions by academics of their work in the Australian state of Victoria, and places such perceptions within the context of international and Australian debates on the academic profession. A 2010 survey conducted by the National Tertiary Education Union in Victoria was analysed in light of the literature on academic work satisfaction and on corporatised managerial practice (“managerialism”). The analysis is also placed in the context of neo-liberalism, defined as a more marketised provision combined with increased pro-market state regulation. Factor analysis was used to reduce 18 items we hypothesised as drivers of work satisfaction to four factors: managerial culture, workloads, work status and self-perceived productivity. Regression models show the relative effects of these factors on two items measuring work satisfaction. This analysis is complemented by discursive analysis of open-ended responses. We found that satisfaction among academics was low and decreasing compared to a previous survey, and that management culture was the most important driver. Concern with workloads also drove dissatisfaction, although academics seem happy to be more productive if they have control over their work and develop in their jobs. Work status had little effect. In the open-ended responses the more dissatisfied academics tended to contrast a marketised present to a collegial past. While respondents seem to conflate all recent managerial change with marketisation, we pose a crucial question: whether the need for more professional management needs to be congruent with marketising policy directions.


Management Managerialism Neo-liberalism Australia Work satisfaction 

Introduction and background

In an internationally comparative sense, Australian academics generally do not appear to be satisfied with their work, and appear unhappy with their senior managements in particular. Coates et al. (2009) indicate that Australian academics have the second lowest work satisfaction scores of those from the 18 diverse countries surveyed in the Changing Academic Profession study, more satisfied only than those in the UK (and equal with those in Portugal and China). This study also shows that negative attitudes to university managements among academics were the third worst in Australia, more negative only in the UK and Hong Kong (Coates et al. 2010). This article seeks to contribute to the international discussion on academic work life by exploring what appears to be particularly troubling levels of dis-satisfaction and discontent in Australia. The research is part out of a multi-industry project that aims to explore the nature and causes of work (dis)satisfaction.1 Firstly we briefly outline the scope of higher education and the history of academic work in Australia and particularly in the state of Victoria where the research took place. We then consider recent research into academic labour, particularly discussions around the rise of “managerialist” practice in public sector work relations, as well as the general nature of work satisfaction and changes thereto in regard to broad developments in political economy that have been analysed in terms of the rise of “neo-liberalism”. Thirdly, in light of the previously discussed contexts, we examine and discuss our original data. These consist of responses from academics in universities in the Australian state of Victorian to the second of the National Tertiary Education Union (NTEU)’s bi-annual surveys of staff attitudes (conducted in December 2009 to January 2010). We particularly question whether a focus on managerial practice per se is adequate in explaining the state of academic work satisfaction.

There has been ongoing change in Australian academic work life thoughout the post-Second World War period, from a rather elite and ad hoc vocation in the direction of a most formalised, qualified and research-focused profession as social and economic needs changed. PhDs were offered from the immediate post-war period, research became a focus from the 1950s and a requirement from the 1960s and departmental life became more formalised and democratic in the 1970s (for institutional histories charting such change see Blainey 1957 and Foster and Varghese 1996).

However, change to academic work has been particularly dramatic in the past two decades, that is since the period of the reforms into higher education launched in 1987 by then Labor education minister John Dawkins, which marked a shift towards non-public funding and a market orientation (Lacy and Sheehan 1997). A further set of changes followed the election of the conservative Howard government in 1996, exacerbating real funding cuts initiated by the previous government and furthering change to management practice and institutional purpose (National Tertiary Education Union 2007).

An aspect of the set of recent changes in higher education in Australia has been the substantial growth in participation. In Australia in 2009 (the latest full year for which figures are available) there were 39 universities, 37 of which are public institutions, and were also 75 private and other providers (chiefly public colleges of technical and further education) which were both accredited to teach higher education and reported their student numbers to the relevant national authority,2 with a total of 1,134,866 enrolled. This represents an increase in student numbers of 22% since 2003. Victoria, the second most populous of the eight states and territories and the focus of this study, has eight public universities and 22 other institutions involved in higher education with 294,318 students, or 26% of the national total (Department of Education Employment and Workplace Relations 2006, 2011).

Higher education in Victoria is taught in all of the “four tiers” of tertiary education, hierarchially stratified by positional value, as posited by Moodie (2009a) as categorising global tertiary education: world research universities, selecting universities, recruiting universities and vocational institutes. As discussed further below we have selected out survey participants from universities as such, and these participants represent all eight Victorian universities which cover not just the three global types but also the five historially constituted university types in Australia (Moodie 2009b): the oldest, most elite and most research intensive “Group of Eight”; universities that developed out of mainly larger and older institutes of technology located in central business districts of state capitals; universities established in leafy outer suburbs in the 1960s and 1970s to service baby boomers; former colleges of advanced education that became universities as part of the Dawkins reforms; and a group of newer universities with their main activity centered in a rural town or region.

A number of Australian studies into academic labour have stressed the rapid and continuous change of the past two decades and have situated the process of change within a general turn in the management of public institutions under a rubric of “managerialism”. Anderson defines managerialism as crucially involving “incorporation of approaches, systems, and techniques commonly found in the private sector, to the management and conduct of the public sector” (2006: 578). She further argues that it involves “more muscular management style, an emphasis on particular forms of accountability, the development of a market-orientation, a focus on securing non-government funding, and increased concern with issues of efficiency and economy”, implemented through “performance management schemes, quality assurance mechanisms, the restructuring of academic departments, and the implementation of budgetary devolution” (2008: 251–252). Managerialism is used in a similar sense by Lyons and Ingersoll (2010), by Winter and Sarros (2002a, b) and by Winter et al. (2000). A perhaps more benign synonym for managerialism appears to be the term “New Public Management”, cited by Bellamy et al. (2003: 14) who give a flavour of the language used that suggests entrepreneurial, corporatised practice: “mission statements, quality, strategies, performance measures, key performance indicators, targets, profiles and market segments are but a few of the concepts that now seem commonplace in university discourse.” McInnis (1999) charts the key results of institutional restructure, funding cuts and changes to management practice on academic work roles from 1993 to 1999: mean working hours increased from 47.7 to 49.2 h per week; the proportion of academics able to pursue their academic interests fell from 66 to 53%, and time spent on administration increased from 6.4 to 8.4 h per week. These trends appeared to have continued into the following decade with staff-student ratios increasing from 12.9 in 1990 to 19.8 by 2008 (Universities Australia 2010). During this period academics have lost some of the control they previously had over their work to management (Lyons and Ingersoll 2010), a trend also noted in Britain (Bryson 2004).

It is crucial however, to situate such practice within broader change in political economy, and how such change has affected higher education and intellectual production as well as work satisfaction across the economy. Many previous studies, such as those on managerialism cited above, allude to such broader processes, without making explicit the contextualisation we feel is important for proper understanding of industrial relations within higher education. In fact one substantial New Zealand study altogether discounts broader social contexts for the dissatisfaction it identifies, claiming, “Ultimately, it is the individual managers and faculty who must assume responsibility for shaping their role and academic work profile” (Houston et al. 2006: 28).

The set of practices that have come to be termed managerialism appears to be related to the rise to hegemony of neo-liberal ideas. Neo-liberals advocate a return to the ideas of neo-classical economics such as a thorough-going individualism and the inherent efficiency of the marketised provision of most if not all goods and services. Key texts appearing in the period of the initial ascendency of this current were Hayek (1976) and Friedman and Friedman (1980). Harvey (2005) argues that the rise of neo-liberalism was a result of the breakdown of the consensus that had dominated the capitalist world in the post Second World War period, consisting of considerable state ownership, expanding welfare systems, and cooperative models of industrial relations. The limits to the growth potential of this model, which increasingly reduced the corporate share of national income, appeared to have been reached by the end of the 1960s, leading to a series of recessions through the 1970s and early 1980s. In this context the ideas of the previously marginal current of neo-liberal economists and thinkers became attractive to capital, in terms of the need to drive productivity growth. However, while classical liberalism advocated a minimalist state aloof from economic interactions, in line with a representation of markets as a natural outcome of innate human qualities, neo-liberalism appears comfortable with an interventionist state, regulating in many fields to promote and maintain private ownership, markets and competition: “The era of neo-liberalism is also the golden age of regulation”, with new regulatory regimes including the enforced marketisation and corporatisation of the public provision of services (Levi-Faur and Jordana 2005: 6).

This set of processes provide the context to the waves of restructuring (re-regulations), real funding cuts, increases in academic workloads and stress and the turn to managerialist discourse and practice referred to above. With increasingly reliance on student fees the traditional focus of universities of maximising status now exists alongside pressures to maximise fee income (the latter driver being more imperative the lower the status of a university), with UK and Australian universities, although still overwhelmingly public institutions, becoming leading players in a new international market for student load (Marginson 2006). The labour of academics occurs in the context not just of managerialist practice and discourse in relation to work relations per se, but also one in which students are increasingly positioned as consumers and customers who should be most concerned with maximising their individual competitive advantage, as opposed to being positioned as scholars or rounded citizens (Brule 2004; Symes 1999). In terms of the regulatory nature of neo-liberalism, Waitere et al. (2011) stress that performance-based research funding in universities, which they see as an outcome of neo-liberal change via managerialist practice, has lead to greatly increased state regulation of academic life, discussing how New Zealand academics must justify their research outputs to compete for funding and gain individual rankings. While they point to positives in performance-based research funding in a more coherent organisation of research, they argue that the negatives are more significant: they cite the stress and depression an individual ranking downgrade can cause, and argue that competitiveness, short-term thinking, hubris and game-playing are rewarded and collaborative, critical, creative and long-term work can suffer.

Some see more of a balance between the positives and negatives in the changes to academic work life of the past two decades. Harman and Meek (2007) argue, using the results of a range of surveys of Australian academjics taken between 1977 and 2002, that shifts towards new forms of managements and towards a more entrepenurial approach have had contradictory effects. They concur with what they see as a dominant view that there has been negative impacts in terms of workloads, worsening morale and disillusionment. However, they see high levels of collaborative work and of engagment with government agencies and the private sector as signs of succesful transition to the new environment. They thus tend to see the prevalence of the latter types of engagement as contradicting commonly expressed views about how increased roles for government and business and marketisation generally can be counter to academic freedom, when these two results are not necessraily contradictory: some academics may be operating in a more “entrepeneurial” way because they have to to, not because they want to or think it is a better way to organise research and teaching.

In considering the impact of neo-liberalism on work life, the concept of work satisfaction is key. Green (2006) argues that, while feelings of well-being and satisfaction at work are socially and historically constructed, there are valid measures of these concepts, particularly when such feelings change through time. Further, he presents evidence from a range of surveys in varied industrialised countries indicating that satisfaction has fallen through the 1990s and into the 2000s, despite increasing real incomes. The main evidence for causal effects on satisfaction comes from sets of similar questions in workplace surveys in the UK in 1992 and 2001. Multivariate analysis shows that the fall in satisfaction is explained most by increasing work intensification and a fall in workers’ discretion over their work. While this evidence of causality from two surveys in a single national context is limited, it does supports the contention that the neo-liberal era has entailed attempts to increase managerial control for the purposes of enforced productivity increases.

Past studies on academic labour have stressed the contradictory nature of academic work perception and work satisfaction in the twenty-first century. Academics have been found from large scale questionnaires to be relatively happy with the intrinsic nature of their work, such as autonomy and flexibility, while unhappy with extrinsic aspects of reward, promotion and recognition (Houston et al. 2006). They often feel committed to their work and institution, while feeling this effort is reciprocated by management with increasing workloads and lack of respect (Winter and Sarros 2002a; Winter et al. 2000). Winter and Sarros have also noted a “value conflict” between “traditional academic cultures” and “modernising corporate culture” (2002b: 121). From a number of interviews across institutions and disciplines Anderson (2006, 2008) finds that academics are unhappy with managerialism but rather than being crushed by new cultures and practices generally find ways to work around or resist the most unappealing aspects.

In this study we aim to further develop the analysis of academic work satisfaction. The quantitative part of the evidence presented here seeks to model underlying factors behind the responses to two questions in the above-mentioned survey that endeavoured to capture how academics were thinking about this subject. The two questions were:
  1. 1.

    “I have a higher degree of work satisfaction now than I did 2–5 years ago”;

  2. 2.

    “I would like to stay at this institution even if I were offered a decent job elsewhere.”


The first question speaks of a change in sentiment. This is pertinent given the relative nature of satisfaction argued for by Green (2006). The second is more “point in time”, and it is a question often included in organisational climate surveys as a behavioural proxy for the sentiment work (dis)satisfaction (Gaither et al 2007; Shaver 2003).


All data presented here are from the National Tertiary Education Union (NTEU) Victorian Division’s second bi-annual online survey about the state of tertiary education in Victoria. The survey was designed to provide information to the union about significant issues for staff in the sector. The 2009–2010 survey builds on a 2006–2007 survey. Over time it will provide for comparisons between universities and analyses of changes in attitudes. The survey was open to all staff in higher and vocational education institutions in the state, whether union members or not, from 30 November 2009 to 2031 January 2010. The union contacted employees of universities and vocational institutions by email and directed them to the survey site with assurance of confidentiality.3

This paper focuses on academics in higher education (universities and higher education divisions of the five dual-sector universities in Victoria). Hence data for administrative and professional staff and staff in technical and further (vocational) education and adult and community education are excluded. We have excluded those teaching higher education in these less traditional sectors to focus the analysis and keep its presentation within reasonable bounds. For these reasons we have also abstracted from the differences between the university types referred to in the introductory section, and these simplifications should be borne in mind. Also excluded here, by reason of question 1 in the introduction, are responses from academics with less than 2 years experience at their institutions. We also extract responses only for the 14 attitudinal questions and six demographic questions in the survey hypothesised as relating to work satisfaction, as discussed in the following section. Some attitudinal questions are point-in-time responses and some represent change in sentiments over a 2–5 year period. All attitudinal data are on a five-point Likert scale, from ‘strongly agree’ (=1) to ‘strongly disagree’ (=5). There were also two open-ended questions used for qualitative analysis as discussed below. A total of 1,414 academics from eight institutions with more than 2 years experience at their current institution completed the online survey validly.

A caveat upon the NTEU survey data is that respondents are not randomly selected: They self-select from the pool of recipients of an email from the NTEU. All members receive an email and reminders, as do a substantial proportion of non-members on institutional email lists. Indeed, 34.2% of respondents are non-members. We do not claim that it is a wholly representative sample of Victorian higher education academics, however, as we did not find any effect from the union membership variable and as our results are broadly in line with those of many of the studies cited here we do not think there is any systematic bias in our sample either.


In this paper we present a statistical analysis complemented by an examination of qualitative data. For the former we set out to find common factors, via factor analysis, which could form a regression model that explain a substantial amount of work (dis)satisfaction. We firstly examined the frequencies of each response category of our two dependent variable question, as presented at Fig. 1 in the following section, with a presentation of the results from similar questions from the 2006–2007 NTEU survey shown at Fig. 2 for comparison.

Based on our examination of the literature on academic work satisfaction and the restructuring and marketisation of the sector, as discussed above, we then selected 20 question variables as hypothesised drivers of (dis)satisfaction relating to management culture, work load and intensity and changes therein, work-life balance, work quality, changes to the quality of educational provision and to the “bottom-line” focus of universities and demographic variables. The data reproduced at Table 1 in the following section summarise the responses to the 14 attitudinal questions. The demographic variables classify gender, length of service at current institution, form of employment (casual, fixed term or continuing), salary classification, part-time versus full-time employment and union membership.4 The responses indicate a high degree of correlation between many items.5 Hence it was valid to use factor analysis. This is a statistical procedure whereby a number of items such as questionnaire responses are reduced to a smaller number of factors, within which items correlate relatively highly, and between which items do not correlate as highly. The purpose is to identify underlying structures that are evident in items that we hypothesise are related before conducting the analysis. The common factors therefore need to make conceptual sense as well as be empirically valid. There are several forms of factor analysis, and we found principal component analysis produced the clearest factors. The factor analysis procedure can assign a score for each respondent for each factor produced, calculated from how high the respondent scores on each item in the factor (note gender and union membership are not included in analyses below, as they did not “load” with other variables in a common factor in any clear way, leaving a total of 18 variables). We can then use regression analysis, which produces equations modelling how dependent variables change as a number of independent variables change, to find models of the relative contribution of each of these factors in explaining a dependent variable.

We produced three regression equations altogether. We firstly produced one with each of the two satisfaction variables (“satisfaction change” and “stay-go”) as dependents. Regression models numerical relationships, so it should be noted that we are treating the ordinal 5-point Likert scale responses (“strongly agree” to “strongly disagree”) as if they were scale variables (1–5). Then we used principal components analysis to reduce “satisfaction change” and “stay-go” to a single factor score and used this score as a dependent in a third linear regression. This enables us to check for differences in results with the first two regressions as a check on the validity of operationalising a common underlying work satisfaction through these two dependent variables.

We note that the regression analyses are not intended for sophisticated prediction but to understand underlying influences better. Hence the most important statistics for us are not R 2 results (which shows the predictive strength of the overall regression model) per se but whether the model fit is statistically significant and, consequently, which of the factors are significant and more influential. That is, the key figures from the regression results are the standardised beta coefficients, which show the relative influence of each factor, independent of (controlling for) the other factors.

Following a number of studies in the area that have used a triangulated approach, combining quantitative and qualitative methods (Winter and Sarros 2002a; Houston et al. 2006), we complemented the statistical analysis with an examination of the responses to two open ended questions: “Do you have any comments about higher education sector”, and, “What are the three major concerns/issues you have right now about your employment or your workplace?” To gain a sample of responses to these, the participants were sorted by combined satisfaction factor (obtained as discussed above), the scores were divided into three equal ranges and 20 responses (of those that had made some comment for either question) were randomly selected from both the high satisfaction group (of 194 out 1,414 cases) and low satisfaction group (consisting of 551 cases). These were examined to determine any systematic differences in how respondents constructed their evaluations of their industry and workplace.


We firstly present some descriptive results indicating the overall nature of respondents’ satisfaction. Figure 1 below summarises responses to the two attitudinal questions, which we will treat as dependent variables in the analyses in subsequent sections. They offer slightly different results but the same assessment. The proportion of academic respondents expressing overall satisfaction (combining the “agree” and “strongly agree” responses) is relatively low (less than 30% on both indicators), while the proportion expressing overall dissatisfaction is relatively high (42% on the “stay-go” indicator and 59% on the “change indicator”). These results are consistent with those from the 2006–2007 NTEU survey, which used a somewhat different question to capture change in satisfaction, although suggesting perhaps a decline in the proportion satisfied and an increase in the proportion dissatisfied: Overall agreement with the “stay-go” variable fell from 32% in 2006–2007 to 27% in 2009–2010, with overall disagreement rising slightly from 41 to 42%.

Table 1 summarises responses to the 14 attitudinal questions, as discussed in the preceding section, that are treated as factors contributing to work (dis)satisfaction.

We can see from Table 1 an overall trend towards dissatisfaction with many aspects of academic work life: for example, there is only 22% overall agreement with the statement of confidence in senior management, with 61% overall disagreement, and only 14% overall agreement with the statement on sufficient staffing, compared with 74% overall disagreement.
Fig. 1

NTEU survey work ‘satisfaction’ variables 2009–2010 (percent)

Fig. 2

NTEU survey work ‘satisfaction’ variables 2006–2007 (percent)

Table 1

Academics’ attitudes to their institutions and work, frequency (and percent)


Strongly agree


Not sure


Strongly disagree


I have confidence in the ability of senior management at my institution

29 (2.1)

284 (20.1)

242 (17.2)

439 (30.9)

419 (29.7)

1410 (100.0)

Change is handled well at my institution

19 (1.3)

190 (13.5)

186 (13.2)

544 (38.5)

473 (33.5)

1412 (100.0)

I am consulted before decisions that affect me are made

29 (2.1)

227 (16.1)

127 (9.0)

550 (38.9)

481 (34.0)

1414 (100.0)

I have adequate control over the work I do

69 (4.9)

562 (39.9)

134 (9.5)

457 (32.5)

186 (13.2)

1408 (100.0)

I feel valued as a staff member at my institution

63 (4.5)

384 (27.3)

237 (16.8)

398 (28.3)

326 (23.1)

1406 (100.0)

There are sufficient staff in my workplace to get the work done effectively

16 (1.1)

184 (13.2)

157 (10.7)

582 (41.2)

461 (32.6)

1395 (100.0)

I can maintain a good balance between work and other aspects of my life

40 (2.8)

388 (27.6)

192 (13.7)

532 (37.6)

254 (18.0)

1406 (100.0)

I regularly work additional hours for which I am not compensated

614 (43.9)

562 (40.2)

76 (5.4)

109 (7.8)

37 (2.6)

1398 (100.0)

I work faster than I did 2–5 years ago

159 (11.2)

593 (41.9)

320 (22.9)

268 (19.2)

59 (4.2)

1399 (100.0)

I work harder (or more intensively) than I did 2–5 years ago

359 (25.6)

695 (49.5)

199 (14.2)

135 (9.6)

17 (1.2)

1405 (100.0)

My workload is more now than it was 2–5 years ago

422 (29.9)

583 (41.3)

197 (14.0)

185 (13.1)

23 (1.6)

1410 (100.0)

I feel that the quality of my individual work has improved over the last 2–5 years

111 (8.0)

641 (45.3)

310 (22.2)

276 (19.8)

57 (4.1)

1395 (100.0)

Universities provide a better standard of education now than they did 2–5 years ago

18 (1.3)

126 (8.9)

400 (28.3)

552 (39.1)

316 (22.4)

1412 (100.0)

My institution is more focused on ‘the bottom line’ than on outcomes for students

389 (27.5)

536 (38.0)

186 (13.2)

242 (17.1)

59 (4.2)

1412 (100.0)

Data reduction

Data reduction, as described in the first part of this section, was carried out on the variables in Table 1, together with the demographic variables form of employment (continuing, fixed term, casual), part-time or full-time status, length of service with institution, and salary classification. This delivered four factors. Together these combined factors accounted for a substantial 55.8% of total variation in all of these variables (it was found that gender and union membership added little to the factor model and did not load with other variables in any clear way). Table 2 reproduces the rotated component matrix, which shows the extent to which each underlying factor correlates with each variable (component scores of greater than 0.4 are shown in bold, a standard way of indicating if some variables contribute substantially more to each factor than other variables and consequently whether this factor makes sense as a structure underlying these more substantially contributing variables).
Table 2

Rotated component matrix for factors underlying the independent variables







Universities provide a better standard of education now than they did 2–5 years ago





My institution is more focused on ‘the bottom line’ than on outcomes for students





I have confidence in the ability of senior management at my institution





Change is handled well at my institution





I am consulted before decisions that affect me are made





I have adequate control over the work I do





I work faster than I did 2–5 years ago





I feel valued as a staff member at my institution





My workload is more now than it was 2–5 years ago





I can maintain a good balance between work and other aspects of my life





I work harder (or more intensively) than I did 2–5 years ago





There are sufficient staff in my workplace to get the work done effectively





I feel that the quality of my individual work has improved over the last 2–5 years





I regularly work additional hours for which I am not compensated





What is your salary classification?





What is your form of employment?





How long have you worked for your current employer?





Do you work full-time or part-time?





Extraction method: Principal component analysis. Rotation method: Varimax with kaiser normalization. Factor scores above 0.4 shown in bold

We can see from Table 2 that variables which substantially contribute to the first factor are those relating to educational quality, the ‘bottom line’ focus of institutions, confidence in management, change management, consultation with and valuing of staff, control over work and staffing levels. It seems valid then to posit an underlying theme related to organisational and managerial practice and broad policy approach (which we call MC for management culture). The second factor, mainly consisting of variables relating to workloads, work-life balance, work intensity and staffing levels, seems to deal with concerns about workloads (and is called WL). The third, combining forms of employment, length of service and position and little else, clearly concerns the individual’s working status (IS). The fourth is an interesting factor that combines work quality and speed, so would seem to relate to self-perception of productivity (PR). If we call each of the dependent variables WS for work satisfaction we can then describe three linear regression models (that is, modelling of change in a dependent variable as a straight line defined by how a number of independent variables change):
$$ {\text{WS}}_{1 - 3} = {\text{ x}}_{1} {\text{MC }} + {\text{ x}}_{2} {\text{WL }} + {\text{ x}}_{3} {\text{IS }} + {\text{ x}}_{4} {\text{PR}} . $$
where WS1 is the stay-go variable, WS2 is change in satisfaction variable and the variable WS3 is the factor score we generated representing both stay-go and change in satisfaction,6 and x1–4 for each equation are the constants that represent the relative influence of each factor. Below the results of our regression modelling are shown, with all results pertaining to significance if not otherwise defined being reported at the α = 0.05 level (that is, we are at least 95% confident of the results).

Model for the stay-go variable

Table 3 gives the results for the stay-go variable. The model is statistically significant (p < 0.001) and explains 36% of the variation in the stay-go variable (R 2 = 0.36; F = 154.48). The significant factors are management and culture, workload and productivity, with the relative influence falling most heavily, we see from the standardised coefficients, with management and culture followed, with a little more than one quarter of this contribution, by workload. Individual work status does not add independently to the model (that is, in addition to any influence expressed through the other factors).
Table 3

Linear regression model for the stay-go variable


Unstandardised coefficients

Standardised coefficients












Management culture factor






Workload factor






Individual status factor






Productivity factor






Dependent variable: I would like to stay at this institution even if I was offered a decent job elsewhere

Model for the satisfaction change variable

Table 4 gives the results for the change in work satisfaction variable. The model is significant and explains 42% of the variation in the satisfaction change variable (R 2 = 0.42, F = 254.47, p < 0.001). As with the regression model for the stay-go variable, the significant factors are management and culture, workload and productivity, with the relative influence falling most heavily with management and culture followed by workload. Here individual work status adds a little to the model, although in terms of standardised co-efficients this contribution is less than half that of workload and productivity and barely one-eighth that of management culture.
Table 4

Linear regression model for change in work satisfaction


Unstandardised coefficients

Standardised coefficients












Management culture factor






Workload factor






Individual status factor






Productivity factor






Dependent variable: I have a higher degree of work satisfaction now than I did 2–5 years ago

Factor score underlying stay-go and change in work satisfaction

Table 5 gives the results for the factor score underlying both the stay-go change in work satisfaction variables, derived in the manner explained in the first part of this section. This overall model is again significant and explains 55% of the variation in the combined factor score (R 2 = 0.55; F = 338.98, p < 0.001). Again the significant factors are management and culture, workload and productivity, with the relative influence again falling most heavily with management and culture followed, at a little under a third of the contribution, by workload. Individual work status here is not quite significant (at the α = 0.05 level), and would not add much if it was.
Table 5

Linear regression model for factor score underlying stay-go and change in work satisfaction


Unstandardised coefficients

Standardised coefficients












Management culture factor






Workload factor






Individual status factor






Productivity factor






Dependent variable: Combined satisfaction factor

Representations of satisfaction and the sector

As noted above, we also aimed to qualitatively gauge the conceptions and meanings that underlay differing levels of work satisfaction among survey respondents by analysing responses to two open-ended questions: “Do you have any comments about higher education sector”, and “What are the three major concerns/issues you have right now about your employment or your workplace?” As discussed, the responses were sorted by combined satisfaction factor, the scores were divided into three equal ranges and 20 responses (of those that had made some comment for either question) were randomly selected from both the highest and lowest range.

The respondents with scores in the low satisfaction band showed a particular propensity to cite what was seen as the managerialist and profit-seeking nature of contemporary universities as a major concern. In six cases out of the 20, respondents used a form of construction Coffey and Atkinson (1996: 107) call “contrastive rhetoric”, meaning a normative comparison between two states, often used in narratives intended to impart a lesson. That is, they contrasted the present state of higher education with what was viewed as a preferable state. These examples were:
  • “The failure to provide adequate resources/priority to quality teaching and research. The managerialist culture”.

  • “Put the focus back on education and stop treating staff like shop assistants in a retail environment”.

  • “The focus is far too much on money and bottom line outcomes rather than actual education”.

  • “How collegial universities have been turned into corporations with managerialism and dictatorial practices the dominant mode of operation.”

  • “It has been truly sad watching the working conditions of staff continue to be eroded (some of which are only now being clawed back) and to see the shift in Universities being places of education to ones of profit margins and the eternal chase for the international dollar at the expense of all else”.

  • “It seems to me that the higher education sector has deteriorated enormously over the last 10 years in particular and despite public rhetoric it is largely to do with the university repositioning itself as an income generating machine rather than intellectual capital”.

Such academics appear to represent their work situation as bound up with a narrative of negative change in which quality education is contrasted with marketisation and managerialism. Among the smaller group with high satisfaction, there was a similar comment, although it was the only comment specifically critical of managerialism or neo-liberalism:
  • “Senior management driven by economic rationalist values and practices destructive to pedagogy”.

There seemed in this highly satisfied group a tendency to be more concerned with individual rather than workplace or industry wide ramifications of problems, with problems identified such as:
  • “I would like to focus on my research more, rather than undergrad teaching”.

  • “Being able to achieve the goals I have set”

  • “Access to superannuation scheme”

This small sample supports the main finding from the statistical analysis, that lower reported satisfaction is most strongly related to a broad concern with management culture, particularly an adoption of what respondents appear to define as both neo-liberal and managerialist approach. The open-ended responses further suggested a tendency to highlight this concern with a preference for what is seen as a more collegial, less-profit-driven sector, and in three cases out of six of those with lower satisfaction explicitly showing a preference for the sector that existed in the past.

Discussion and conclusions

The summary of our data shows that the distribution of satisfaction among Victorian academics is skewed towards the low end, a situation that appears to have worsened from the time of the previous NTEU survey. As can be seen from the analytic results, the most important factor influencing work satisfaction—as measured by willingness to stay at an institution, self-perception of change in satisfaction and the calculated factor underlying these two measures—appears to be linked perceptions of management culture and policy direction. This factor contributed more than twice as much, in terms of standardised coefficients, as any other factor in each of the three regression models presented above. The main driver of dissatisfaction among Victorian academics is a set of related concerns with management ability, change management practices, lack of consultation, control over work, institutional staffing levels and a focus on profit over educational standards. The open-ended comments reported above appear to support these results.

These results differ somewhat from previous studies, as cited above, which located dissatisfaction in extrinsic aspects of the job of broad management attitude towards faculty, contrasted with relative satisfaction with the autonomy and flexibility of academic labour: we found a definite discontent about perceived loss of control, linked with unhappiness with management and the broad direction of institutions and the sector generally. As noted in the introduction, past studies have tended to give little context beyond the organisational sphere (managerialism). The broad concerns found in our management culture factor, and the comments by some (albeit a small sample) of the more dissatisfied academics, suggests that general discontent with neo-liberal change across the economic and social spheres is a driver of work dissatisfaction among academics.

We argued earlier that a root cause of the neo-liberal turn was a drive to increase productivity. Our results show some interesting complexities regarding work intensification. In our regression models a factor identified as concern with increasing workloads has an impact on satisfaction, in a negative direction, albeit with less than half of the coefficients of the management culture factor in each of the three equations. A finding that might seem somewhat contradictory to the effect of workloads is the significant positive effect that the factor related to speed and quality, identified as self-perception of productivity, has on work satisfaction. This finding bears out that found by Gough et al. (2010: 10) in relation to the work of nurses. They initially and unexpectedly found that increasing job satisfaction was associated with increasing work effort and increasing speed of work. However, further analysis showed that measures of speed and effort were actually mediating a relationship between measures of job growth (increasing skills, responsibility, influence and interest) and job satisfaction. This statistical relationship was supported by comments in interviews. In general nurses do not mind and even like working harder and faster if they are “growing” in the job. We also found that measures of individual status had a (small) positive effect on satisfaction. These results for academics appear to bear out the relationships between work intensity and “job growth” found for nurses. As noted in the introduction, this study arose out of a multi-industry project that aims to explore whether productivity gains can be accommodated with fairness at work. Our results suggest that academics do not like the forcible piling on of workloads but will happily be more productive if they have control over their work and develop in their jobs.

Is it possible however, to better harness the undoubtedly high work motivation of academics without the bracing disciplines of marketised competition and managerial control, unpopular among many? Some of our respondents at least appear to represent the neo-liberal turn as it has affected higher education as a narrative of change from a wholly positive past to a wholly bleak present. There is a danger here in idealising the past, a return to which is not likely to be possible or even desirable in the context of a much larger and more diverse sector. Bryson (2004) refers to perceptions by some discontented British academics of, as he puts it, a “golden age” of the “gentlemanly scholar”, and such elitist notions are unlikely to be much of a popular answer to neo-liberalism. Here it may help to unpack the apparent congruence between recent change in managerial practice and neo-liberal policy. That is, academics may experience and report in surveys such as ours policy change and all recent managerial practice change as one and the same thing, when this does not have to be the case.

Coates et al. (2009: 31) argue that reducing recent managerial change to a singular negative managerialism, or “point[ing] to executives as the root of all evil”, misses the necessity of change to a system that was previously characterised by an amateurish, ad hoc approach to management. They point out that vital issues such as improving staffing levels, addressing concerns with casualisation and generally making the profession more attractive will requite a more professional and systematic approach to management. On the other hand it is hard to see though how the changes they call for will be possible without linking better management to substantial policy change, such as increased public funding and a less marketised and competitive environment generally, because, as they report, increasing student to staff ratios and casualisation have followed decreased public funding and, as we among others have found, marketisation and competitiveness are not attractive for many academics. We may generalise from the point made by Waitere et al. (2011) cited above that a more coherent and explicit approach to research management is welcome, even if the pressures towards individualist, competitive and short-term approaches might not be. That is, moves to improve management and accountability, which may entail more regulation, does not necessarily entail a neo-liberal policy approach, just because the two processes have moved in tandem in recent decades. It was noted above that Coates et al. (2009) found that UK academics report the lowest and Australian academics the next lowest relative satisfaction levels (along with Portugal and China) in the 18-country 2007 Changing Academic Profession survey, noting that the higher education sectors in these two countries have undergone particularly significant change. It might also be suggested more generally that in these two countries the turn from a social-democratic to a neo-liberal model was particularly wrenching and thoroughgoing, compared to for example the United States (where social-democratic practice was less established) or continental Europe (where neo-liberalism has been less thoroughgoing). As also noted above, another finding of the CAP study was that Australian academics had the third most negative attitude to management. Coates et al. (2010) discern a “paradox” in that this discontent with management exists alongside what other research suggests is a sensitivity to academic mission by middle and upper management. A similar paradox seems to be evident in the findings of Winefield et al. (2008) who measured aspects of work stress including job satisfaction and trust in senior management for staff at 17 Australian univerities in 2000 and again in 2003–2004. The high level of stress and low levels of satisfaction revealed in 2000 led participating institutions to introduce measure to reduce stress and increase morale. The latter survey showed a number of improvements for general staff including in commitment, perceptions of autonomy and procedural fairness and trust in senior management but only in the area of increased job involvement for academic staff. Apparent efforts by management not being met by trust from academics may be expalainable by the general argument here that “management” is to some extent a proxy for broader political-economic and sectoral change that many academics do not like. It would be useful to undertake further comparative research that could better distinguish between the effects of managerial change, policy change and broad economic change on the work life and satisfaction of academics.

There appears to be a major disconnect between the views and practices of contemporary university management and governments, and the satisfaction of academic staff. While many higher education teaching and research staff appear happy to work more productively, most appear to see a lack of a clear pedagogical and intellectual rather than profit-driven aim to their labours. There is a broad feeling that marketisation has not delivered the promised freedom and flexibility, but further bureaucratism and control, as well as increasing pressures to work harder, supporting Green’s (2006) arguments about the two main drivers of decreasing work satisfaction under neo-liberalism being workloads and perceived loss of control. Many well-intentioned efforts by university managements may be undermined by these general trends.


  1. 1.

    This is a collaborative research project entitled Work and Social Cohesion Under Globalisation, supported by the Australian Research Council (ARC), within which a focus on work satisfaction is part of a more general aim to examine how demands for innovation and productivity gains can be reconciled with fairness in five industries (tourism, health, information and communications technologies and automotive parts as well as higher education).

  2. 2.

    The exact extent of the small but burgeoning sector of private providers and public technical colleges involved in higher education, part of an increasing marketisation of higher education discussed below, is unclear, as the reporting of student and staff data for non-university provision only became mandatory in 2010 with figures not available until 2012.

  3. 3.

    A personal communication from a colleague who was an NTEU union official through the period that these surveys were undertaken indicates that their results have not been published previously, although they were used in briefings to university managements and to inform union collective bargaining teams.

  4. 4.

    In order to allow each of these variable to be included in a factor analysis, as described below, the following were coded as numerical, ordinal variables: form of employment, that is casual, fixed term and continuing were recoded 1, 2 and 3 in terms of increasing job security; academic salary classifications A through E were recoded as numbers 1 through 5. Part-time versus full-time employment, union membership versus non-membership and gender were coded as dummy variables. Note the latter two were found to have no significant effects.

  5. 5.

    We will not reproduce the correlations here. Most were mutually correlated positively or negatively at the 0.01 significance level.

  6. 6.

    We will not reproduce here the details of this score, save to say that it accounts for a very substantial 75 per cent of the variance of WS1 and WS2 and that Bartlett’s test is not significant at the α = 0.01 level, which indicates a strong probability that there are significant relationships between the variables.



The authors wish to thank the industry partners and participating colleagues and institutions in the Australian Research Council Linkage Project, Work and Social Cohesion Under Globalisation, of which this paper is a part. Particular thanks are due to the Victorian Division of the NTEU, a project partner, for making available the data for this paper. Its communications and campaigns officer Alex White deserves special mention. The second-named author discloses an interest as the immediate past honorary president of the NTEU in Victoria. The authors acknowledge the assistance of Richard Gough, Victoria University, in formulating the conceptual direction of this paper. We also thank Leo Goedegebuure, University of Melbourne, and two anonymous reviewers, all of whom made very useful comments on earlier drafts of the paper.


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.LH Martin Institute of Higher Education Leadership and ManagementUniversity of MelbourneCarltonAustralia
  2. 2.Centre for Strategic Economic StudiesVictoria UniversityMelbourneAustralia

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