The questionnaires were distributed electronically and, after some follow-up, 24 responses were received in 2006, 24 responses were received in 2005 and 25 responses were received in 2004. This represents a response from about 60 per cent of the universities. A number of universities, however, have no IS discipline group, so the effective response rate is more than 80 per cent (of the 30 or so IS groups) and can therefore be claimed to be representative of the population of IS groups as a whole. There is a mix of titles (most commonly schools, but also departments and other titles), but hereafter the groupings will be referred to as schools. The discipline titles of these schools of the 24 respondents in 2006 were 50 per cent (12 respondents) IS, 25 per cent information technology (IT) and 25 per cent other titles. Furthermore, 14 of these schools were in a business/commerce faculty, seven in an IT faculty and three in a mix of others.

Academic staff levels are shown in Table 11.1 and indicate a 2006 mean of 16.3 total academic staff in IS schools, with a reduction in size evident from 2004 and 2005. This is consistent with the reduction in IS student numbers during this period. Table 11.2 shows a breakdown into staff categories and highlights the low number of senior staff (levels D and E) and research-only staff (research fellows) in each school.

The overall view is that there is a mix of names and locations for IS schools, but the majority are medium-sized groups with IS in the name and reside in a business/commerce faculty where they can maintain a close association with the areas of application of IS.

Staff research activity levels are shown in Table 11.3 and indicate that in 2006 the majority (mean 83.7 per cent) of staff were doing some research although only about half of these were research active according to the strict Department of Education, Science and Training (DEST) definition (mean 41 per cent). Just more than half (mean 57.5 per cent) have PhDs and a further quarter are doing PhDs (mean 23.6 per cent). Just more than one-third (mean 37.6 per cent) are supervising PhDs and one-quarter (mean 25 per cent) have supervised a PhD to completion. It can be seen that although the proportions of staff doing some research and those considered DEST research-active have remained about the same, there has been an increase in the number of staff with PhDs and in supervision in the period 2004–06.

Doctoral student numbers are shown in Table 11.4 and it can be seen that the mean number of doctoral students and the mean number of PhD completions per school have remained much the same since 2004. The results indicate that in 2006 the mean number of full-time equivalent (FTE) PhD students in each school was 11.5 (7.8 full-time and half of 7.4 part-time), while the mean number of PhD graduations per school in the previous year was 1.4. With that many PhD students, there would be an expectation of three to four graduates per annum (based on a target of 3.5 FTE years for completion of a PhD), but the real completion rate is less than half that. This signals a throughput problem, which might exist because of variable-quality supervision practices (within schools and across the sector) and a lack of adequate resources, which needs to be addressed.

Respondents were asked to indicate the topics of research interest in the past, present and future, and responses for the 2006 survey are summarised in Table 11.5 below, sorted by future topic of interest. The results demonstrate the substantial interest in research on IS management and strategy and the organisational implications of IS and IT, IS adoption/diffusion, electronic commerce and knowledge management, with almost all groups indicating an interest in these areas. In addition, interest is strong in topics such as IS development and business modelling, mobile commerce and the theoretical underpinnings of IS. On the other hand, specific topics and technical issues such as computer and network applications and computer-supported cooperative work (CSCW)/groupware are relatively less popular. It should be pointed out, however, that the table reveals how many groups are interested in these topics and does not show how large these groups are. So, further research is needed at the individual researcher level.

The respondents were asked also to indicate the usual unit of analysis of their research. In the 2006 survey this was the organisation (22 responses), groups/teams (19), clusters of organisations (19), industry (16), processes/tasks (15), individuals (14), national economy/society (eight) and world economy/society (three). Clearly, researchers focused most on organisations and the people within them, and significantly less on studying IS at the national or global levels. This could represent an opportunity to collaborate with other researchers (for example, economists) to investigate the impact of IS and information technologies on Australia’s economy and its links with the region and globally. In terms of a research paradigm, responses revealed dominance of the positivist paradigm (in 71 per cent of schools), but the interpretivist paradigm was also used often (54 per cent). The survey data confirmed a growing recognition that IS researchers in Australia did conduct research based on non-positivist research paradigms. Few mentioned any significant emphasis on research using a critical paradigm, which was also the case at the international level (Mingers 2001).

When asked to indicate the specific research methods used, the responses revealed that the full range of research methods were being applied by IS researchers (see Table 11.6 below, sorted by the research method used most often). The most popular method is the survey, but also popular are positivist and interpretive case studies, and design science. This balanced application of paradigm and method is perhaps an indicator that Australian IS researchers are more like their European than their North American counterparts. Arnott and Pervan (2005) found that, in published research in decision support systems, North American journals were overwhelmingly positivist whereas European journals were more balanced on paradigm and method. Again, these data are at a school level, so a study of individual researchers is needed to reveal the true extent of usage of the different methods.

Respondents in the 2006 survey indicated clearly that the primary beneficiaries of their research were other IS academics (20), managers (17) and IS professionals (15 responses), followed distantly by end users/workers (seven), policymakers (six) and people in general (zero). This might again show that we (IS researchers) are not taking up the opportunity to influence governments and society, and it could be a major reason for the apparent lack of recognition of IS as a discipline by some government agencies. Respondents indicated that, where it occurred, most research collaboration occurred with IS colleagues within that particular academic group. Clearly, there is a need to widen the collaboration net nationally and internationally, which could help to increase quality, and with practitioners, which increases relevance and provides opportunities for funding—for example, the Australian Research Council (ARC) Linkage grants. It could also serve to enhance the impact of IS research, which might be an advantage in the research quality-assurance mechanism that will replace the proposed Research Quality Framework (RQF), once developed. The planned RQF was abandoned in December 2007 by the new Labor government.

School research output is shown in Table 11.7 and indicates that in 2006 schools generated a mean of about 52 publications, 34 of which were conference papers, 11 journal papers and a small number of other types. It can be seen that there has been a substantial increase in the mean number of publications in the period 2002–05. The largest increase has been in conference papers, although the number of journal papers has also increased.

Research performance per staff member is shown in Table 11.8 and indicates that in 2005 the mean output per academic staff member was 2.6 publications per annum and the mean grant income per academic staff member was about $17 800 per annum. It can be seen that there has been a substantial increase in publications and grant income since 2002, although the rate of increase has decreased substantially and the differences between 2004 means and 2005 means are very small. Further, Tables 11.7 and 11.8 reveal that the mean number of journal papers (of any type—there was no assessment of journal quality) per IS academic is much less than one per annum. Follow-up investigation would be required to determine publication rates in tier-one and tier-two journals, but it is certain to be even lower. This would have severely limited the chances of IS research groups achieving a high rating in the proposed RQF process—thus constraining IS research funding.

Research grant income per school is shown in Table 11.9 and indicates that in 2005 the mean grant income was more than $300 000 per annum. The amount of research grant income varied considerably between the groups, with a few groups doing very well in gaining funds from external sources, but most having to depend on internal university resources. The main source of research grant income in 2006 was from the ARC (Linkage and Discovery grants), although substantial research income was also generated from collaborative research centres (CRCs), industry contracts and internal university resources. It can be seen that although the total research income increased significantly after 2002, it has remained much the same throughout 2003–05. Generally, these figures compare poorly with other disciplines, including computer science and computer engineering.

Table 11.10 shows a comparison of several research variables with significantly different means across university categories. The university categories are based on those of Marginson and Considine (2000) and provide a useful means of comparing research performance. The categories are defined as follows (Marginson and Considine 2000:15–16):

It is clear from Table 11.10 that the mean size of IS schools in each of the categories is very similar. The Sandstone/Redbrick and Unitech categories have, however, significantly greater mean numbers of professors, mean numbers of DEST research-active staff, mean numbers of doctoral students, mean numbers of papers in refereed journals and refereed conferences, mean numbers of publications per staff member, mean total amounts of grant income and mean grant incomes per staff member. This is consistent with the research-intensive nature of universities in the Sandstone/Redbrick category and the historical location of IS schools within the Unitech universities.

The final part of the survey allowed each respondent to suggest the three main strengths, weaknesses, opportunities and threats (SWOT) for the IS discipline research; a summary of the most frequently cited issues in the 2006 survey is provided in Table 11.11. In total, more than 150 ideas were generated in the SWOT and the top five in each category are presented here.

The respondents clearly believe there is strength in our diversity and relevance. Diversity was indicated in types of research undertaken, the research approaches taken (and the underlying epistemology) and in the breadth of experience most IS researchers brought with them from their background in IS practice and their grounding in practitioner activity. These strengths in diversity and relevance need to be nurtured and exploited.

Key weaknesses are the lack of relevance and identity and poor funding (relative to computer science/computer engineering), which is associated with other weaknesses such as the lack of a research culture in Australian business and lack of recognition from funding agencies such as the ARC. These and other research focus and training issues need to be overcome.

The respondents clearly recognise that there are numerous opportunities of which we should attempt to take advantage. In this, collaboration (with industry, international colleagues and other Australian universities) is the key. In addition and as indicated earlier, the opportunity exists for IS to increase its profile and recognition by conducting research on societal and economic issues, which might influence government policy.

While industry collaboration was seen as an opportunity, it could also be a threat if proper linkages were not built. Research impact will be critical in any research quality-assurance mechanism. Perhaps the greatest threats to IS research in Australian universities lie in the lack of recognition of IS as a discipline and its location in the academic structure, the falling numbers and excessive teaching loads in most schools and the career and financial opportunities outside academia.