apmrn workshop, fuzhou, may 29th,...

APMRN Workshop, Fuzhou, May 29th, 2007

Where will all the researchers go? Training, networks and mobility of scientists in the Asia Pacific region.

Tim Turpin, Centre for Industry and Innovation Studies, University of Western Sydney ,

<[email protected]>

Jane Marceau, University of Technology, Sydney <[email protected]>

Richard Woolley, Centre for Industry and Innovation Studies, University of Western Sydney <[email protected]>

Stephen Hill, University of Wollongong, Australia

Abstract

This paper reports on a project that investigates patterns of research training, career trajectories and science network formation from a sample of over 10,000 scientists from 16 countries. Our study provides insights into how two kinds of networks are formed and sustained: on the one hand, through ‘virtual’ co-location in a transnational science-based diaspora and on the other hand, through ‘on-site’ engagement, notably during post-doctoral work, visiting fellowships and sabbatical sojourns. As ‘organisational arrangements involving universities, governments and industry deepen in developing economies, opportunities for international collaboration both through virtual and on-site collaboration are expanded. ______________________________ Acknowledgements: The project from which this paper was developed carried out with support from the Australian Research Council and UNESCO through an ARC Linkage Project. The authors wish to acknowledge the support provided by the ARC and UNESCO and the ongoing support and encouragement from the UNESCO, Jakarta Office.

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Where will all the researchers go? Scientists as innovation personnel as the basis of intra-regional ‘Triple-Helix’ arrangements in developing economies in Asia

Background Thirty years ago, the US House of Representatives tabled a detailed report on the impact of the brain drain on the place of science and technology in American international relations (U.S. House of Representatives 1977). Their report showed that between 1962 and 1966 more than 45% of engineers and natural scientists accepted by the US as immigrants were from India and China. By the late 1970s, however, a downward trend in the inflow of scientists and engineers to the United States was evident (U.S. House of Representatives 1977: 1279). Since the mid-1970s the world of scientific training and careers has changed dramatically. In 1989, for example, the opening of the Iron Curtain resulted in a huge increase in the outflow of scientific personnel from the former Soviet countries, notably to Israel. A number of studies since the 1980s have shown how the immigration of scientists and engineers from developing countries to the United States, Israel, Canada and Great Britain contributed to the growth of scientific and innovative capacity in the North (Arocena and Sutz 2006). In the Asian region, China’s move from a centrally-controlled to a market-driven economy led to the formulation and implementation of new science and technology policies through the 1980s (Harvie and Turpin 1997). The resulting growth of research and training institutions and their contribution to industrial production through the 1980s and 1990s was dramatic (Zhang 2007). This was largely due to reforms that encouraged the movement of scientists from the public sector to newly established special economic zones and rapidly growing township village enterprises (Turpin and Garrett-Jones 1996).These transfers of personnel, at a very local level, paralleled global mobility and the consolidation of science intensive knowledge networks. International institutions, including universities and transnational corporations built on and further contributed to these networks. In recent years, India, struggling to build its scientific capacity through the 1960s and 70s, has emerged as a global leader in the IT and software sectors and as a major international player in the production and design of pharmaceuticals (Krishna 2007). Both China and India are now attracting significant global investments in R&D from the world’s largest corporations. A recent study (Doz et al.) has shown that, over the next decade, the world’s large business R&D spenders plan to place 75% of new R&D investments in these two rapidly expanding economies. Already many transnational corporations are planning to move to India and/or recruit scientific personnel from India. Cisco Systems has decided that 20 per cent of its top talent should be in India by 2012 and IBM’s Vice President refers to India and China as the world’s ‘…two biggest pools of high-value skills, which we want to leverage’ (quoted in Giridharadas 2007). In the race for scientific and technological personnel as innovation experts who make a valuable contribution to a nation’s innovation and production systems there are two marked trends. The first is that less-developed countries in Asia and Latin America, as elsewhere, are losing science and technology-trained personnel and are much

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concerned about the erosion of their hard-won scientific capability through an international brain-drain (Mulla 2005; Kapur and McHale 2005). The second is the creation of transnational innovation networks made up of local and expatriate scientists and known as Distributed Knowledge Networks (OECD, 2001), or as others have defined them in the migration literature, as, Diaspora Knowledge Networks – in both cases (DKNs). These new networks, centred in developed countries but linking developing ones, have the potential to contribute to solving some of the many issues confronting both poorer and richer countries (Meyer and Wattiaux, 2006; Mahroun et al. 2006). As Meyer and Wattiaux have put it, the conceptual definition and growing empirical analyses through DKNs have:

…subverted the traditional ‘brain drain’ migration outflow into a ‘brain gain’ skills circulation by converting the loss of human resources into a remote although accessible asset of expanded networks (Meyer and Wattiaux 2006: 5).

Empirical studies of the functioning of these distributed knowledge networks have so far focused primarily on networks in the Americas (Meyer and Brown 1999, Meyer 2005) and Africa (Meyer et al. 2001). A key observation is that diasporas of scientific and technological personnel may create positive externalities that boost the innovative capacity of developing countries by providing readily accessible new knowledge, ideas and skills. Stein et al, for example, have argued that knowledge networks contribute to innovation and international learning by producing new knowledge through trandisciplinary research on problems as they are experienced across international boundaries and operational knowledge, as they put it, acquired through context-bound interactions across various sectors. Their case study analyses thus emphasise the dissemination of knowledge through networks and contributions that carry global knowledge into local contexts (Stein et al, 2001:4). This new localism in science, as we have called it elsewhere, reflects a global transformation of the social relations in the production of knowledge through networks (Hill and Turpin 1995). Such networks tend to have concentrated centres in what can be described as ‘knowledge-hubs’. Many firms in both countries that were essentially dependent on universities or research institutions during their formative period are now becoming more global and less dependent on local institutions. In China for example, a recent study by Ramirez and Dickenson (2007) has shown how the Zhongguancun Science Park has become far less reliant on its university and research institute antecedents than during its formative years depending instead, for knowledge and specialist expertise, on a set of global scientific and industrial networks. The authors expressed surprise that respondents did not rate universities highly as a source of knowledge. However, their study reveals the importance of key scientific personnel as they travel around the world anchoring their work to global knowledge networks. One of the entrepreneur respondents to the Ramirez and Dickenson study commenting on the importance of alumni networks referred to the ‘… importance of the “Tsinghua entrepreneurial group” formed in Silicon Valley around the millennium, most of whose members have now returned to Beijing’ ( Ramirez and Dickenson 2006, 35). Institutions, generally speaking, stay put but scientists and their knowledge are very much on the move (see also Dente, 2007).

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Our recent large scale study of the training and careers of scientists and technological personnel in the Asian region addresses questions concerning the formation of such knowledge networks, their location and interactions (see Appendix A). This paper presents some of the findings from that study. We focus on the impact of research training at doctoral and post-doctoral levels for individual decisions about where to pursue a career in science and technology, most importantly about whether to go ‘home’ or not and if going home when to do so. The study’s results suggest that nations should take deliberate steps to ensure that the Asian region’s fast-growing ‘diaspora’ of science and technological personnel benefits all. The smaller and les developed countries may also benefit from the mobility of their best and brightest innovation personnel. At present, it is not clear that they can so benefit. As Arocena and Sutz, for example, have suggested, knowledge diasporas may serve only countries that already have well established national innovation systems (2006) which may not be the case for developing nations. In order to develop new policies that can be used to create well-functioning intra-regional or broader international scientific and technological knowledge networks, policymakers need to understand how such networks emerge, the factors motivating the movement of knowledge personnel who can create the networks and the push-pull factors that are likely to influence future patterns of international mobility. We present data which could underpin such new policies and hence the creation of integrated intra-regional Triple Helix arrangements. This paper thus reports on a project, carried out in collaboration with UNESCO, and designed to reveal patterns of research training, career trajectories and science network formation from more than 10,000 scientists from 16 countries and 21 nationalities. It is the first attempt in the Asian region to systematically examine the patterns of migration of S&T personnel and to inform debates about the capacity of different nations to capture expertise through the creation of international networks. National and transnational networks in the Asian region The countries of Asia constitute a mosaic of contrasting multi-layered economies. The mosaic includes two ‘giant’ developing economies (China and India), several industrialised or developed economies (Japan, Singapore and South Korea), some emerging economies, notably Malaysia, Thailand and the Philippines, and the developing economies of Indonesia, Vietnam, Pakistan and Sri Lanka. Almost all countries in the region are presently reassessing their public science, technology and innovation policies with a view to building sustainable national innovation capabilities. What happens to their scientists is thus of critical interest. Embedded in the initiatives underway are some emerging contradictions. First, when viewed at the regional level, many national science and technology policies appear to be internally (nationally) focused, often in reaction to earlier neglect of local needs in the push for businesses to develop export markets (Turpin & Krishna, 2007). As governments reassess and redirect their S&T resources towards pressing domestic concerns, they may risk weakening their links to the international science and technology networks that push global innovation, although the same policies may also encourage the creation of new and more local S&T niches in some countries. In many

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countries, new policy and business demands for local technology development compete for resources and attention with those for local involvement in evolving global developments. Growth in numbers of S&T personnel in both India and China since the 1980s has been impressive. In China during the single decade from 1992 to 2002, the proportion of enrolled tertiary students per 10,000 people increased from 18.6 to 70.3. S&T funding in China during the same period increased from USD 6.7 billion to USD 35.5 billion (Zhang, 2007). In India, the number of engineering degree-holders increased five fold in little more than a decade, from 185,400 in 1980 to 1,011,000 in 2004. Numbers of scientists in training also grew, with the number of science postgraduate degree holders increasing from 139,200 in 1970 to 795,600 in 2004 (Krishna, 2007). In both India and China there is growing evidence that a ‘Triple Helix’ (Etzkowitz and Leydesdorff, 1997) of government policymakers, industrial firms and universities is driving the growing demand for S&T personnel. The rapid increase in domestic institutional capacity will provide large numbers of new entrants to their S&T labour market but it seems likely to be insufficient to meet demand. Many of the smaller developing economies in the region may well thus face external demands for their new scientists. The brain drain thus developed may hit these countries hard while the brain gain will advantage their larger or more developed neighbours further. While interaction between two elements of the Triple Helix, universities and industry, facilitated by governments in the Asian region, deepens it is important to know whether the scientific capacity, mobility and endeavour apparent in individual nations are matched by an increased capacity for all national players within the region to capture the associated social and economic benefit. The nature and pace of economic transformation in Asian economies vary considerably from place to place but we know little about how scientists across the region contribute, in different contexts, to social and industrial development. The growth in scientific output from the Asian region Scientific output from the Asia region has increased dramatically since the 1980s while the overall number of scientific publications by US authors has remained practically unchanged. Since 1998, contributions from Chinese researchers have more than doubled. Over the same period, publications by scientists in Singapore and Thailand each increased by 70%, those by Koreans by 60% and those by scientists from the Philippines by 30%. The increase in scientific publications by scientists in Asia parallels a significant growth in research training and hence scientific capacity apparent around the region. The number of doctoral degrees awarded by Asian universities doubled in the 1990s, increasing from 10,000 in 1990 to nearly 20,000 in 1997. In China, the number of science and engineering degrees awarded by Chinese universities rose fivefold, from 1000 in 1990 to over 5000 in 1997 (Johnston et al. 2000)). The growing higher education capacity in Asia evident in these few figures opened new regional cross-border pathways for higher education and students were quick to

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take advantage of new possibilities. Between 1990 and 1995, for example, the number of Japanese students studying in China increased from 806 to 8,500. In Taiwan, the number of foreign students grew from 4000 in the late 1980s to nearly 6000 in the mid-1990s (Bohm et al. 2003). In the Asian region, scientists are thus becoming increasingly mobile, first through their training experiences and then potentially throughout their careers. Scientific collaboration through international networks can occur in two ways; on the one hand, through ‘virtual’ co-location in a transnational science-based diaspora (Meyer at al. 2006) and, on the other hand, through ‘on-site’ engagement, notably during post-doctoral work, visiting fellowships and sabbatical sojourns. As industry and university interactions deepen in developing countries, opportunities for international collaboration through both mechanisms expand. Our study provides insights into how the two kinds of networks are formed and sustained through physical mobility between countries at different stages of careers in the region. The remainder of this paper is directed toward indicating how and why particular collaborative patterns have emerged and their implications for future mobility. The paper concludes by considering the S&T human resource implications for the giant economies of China and India as well as the smaller players in the region. The emergence of collaboration: our survey of 10,000 Asian scientists. The sample for our survey was drawn by identifying researchers who had published in SCI-coded journals between 2003 and 2005 and had an institutional base located in the Asian region. An initial sample was constructed to reflect the proportion of SCI publications according to location. A questionnaire was emailed to potential respondents asking about their research training experiences, post-doctoral work, countries of professional activity, research networks and countries preferred for future work. We received 10,132 usable responses. Patterns of mobility and networks Table 1 summarises the patterns of regional movement of scientists from when they first undertook research training, their later employment, the location of international networks and most important collaboration(s) and preferred future work locations. The data are aggregated for seven mobility variables according to location. Data are not cross- tabulated in this table but are presented so as to show the comparative representation of each location for each variable. Thus, it can be seen, for example, that 16% of the sample were Indian nationals but that India was slightly under-represented as place of research degree (15%), significantly under-represented as place of post-doctoral training (6%), similarly under-represented as a node in international research networks (4%), further underrepresented in most important collaborations (3%) and highly under-represented as a choice of location for future research (1%). Japan, on the other hand, was over-represented as a place selected for preparing a research degree (15%), under-represented as location of post-doctoral training (9%), slightly over-represented as a place of current work (14%) and

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somewhat under-represented for participation in international networks and important collaborations. The general summary data presented here suggest that five countries drive choices of research training location and network creation: the USA, the UK, Australia, Germany and Japan. The data suggest a close relationship between selection of location for undertaking research degree and place of current work and between place of post-doctoral training and participation in current research networks. The probable explanation for this is that, as research engagement intensifies, new networks are developed and existing ones consolidated. It is likely that as the ‘pulling capacity’ of countries such as the US, Germany, Japan, the UK and Australia (each for slightly different reasons as discussed later) continues, these centres will attract scientific talent from other parts of the world. However, as we argue below, there are returnees and these bring with them new networks for sustained scientific interaction across national and organisational boundaries. The following section extends the analysis by exploring in more detail the links developed by groups of respondents who are nationals of selected countries. Patterns of training, networks and mobility for selected countries The patterns of training, networks and mobility shown by respondents in five countries were analysed to explore any differences between the large but still emerging economies of India and China and the experiences of the more industrialised Asian economies of Japan, the Republic of Korea and Australia. Australia was included for this part of the analysis because of its historical and linguistic links to countries such as the US, the UK and Canada but its geographic location in the Asian region. Data for each of these countries are shown in Tables 2-6. Indian experiences of research training, networks and mobility The pathways taken by Indian nationals are shown in Table 2. Outside India, the US was the main single research-training location, followed by the UK. Post-doctoral training was a far more international experience, with nearly 30% of Indian respondents undertaking their post-doctoral education in the US and only 31% undertaking it in their home country. Germany, Canada and the UK and Japan represented the other main locations. The pattern of current work location reflects that of initial research training locations (PhD and Masters Research) suggesting that a large proportion of young scientists stay in or return to India (88%) when they enter the labour force. Locations where respondents currently work show a pattern similar to location of research degree. In short, this suggests early ‘stayers’ remain at home. Those who have worked elsewhere were concentrated mainly in the US, Germany, the UK and Japan. International research networks, on the other hand, reflect post-doctoral choices, suggesting a consolidation effect as research intensity and networks develop together. Location of ‘most important collaboration’ shows further concentrations in the US and Germany. Preferences for countries of future activity also seem to consolidate

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post-doctoral experiences. However, while networks and collaboration are concentrated around five main locations choices for a preferred work location are concentrated in two countries: the US and Australia. The high response rate of respondents choosing Australia as their preferred future work location perhaps represent a bias among this sample toward the location of the study which was carried out from Australia. Chinese experiences of research training, networks and mobility Table 3 presents the same data for Chinese nationals. A higher proportion of Chinese students completed their research degree in another location than did their Indian counterparts but location choices were more evenly spread across several countries, including Japan, the USA and Singapore and, to a lesser extent, the UK. Post-doctoral students were concentrated in the USA and Japan, with Singapore, France, Germany, Canada, Hong Kong and the UK hosting most of the Chinese post-doctoral population as a whole. A slightly higher proportion of Chinese than Indians were currently working internationally, mainly in the US, Japan and Singapore. A very large proportion, however, just under 82%, still worked in China. Location of most work shows increasing proportions of Chinese in Japan, Germany, the UK and the US. As in the Indian sample, the place of current work of the Chinese also reflects the location where research degree was attained while, again in a manner similar to the Indian experience, Chinese participation in research networks reflects the choices of location made for post-doctoral work. Location of most important collaboration shows increasing proportions for Germany, HK, and the US reflecting the importance of these countries for Chinese scientists. Chinese respondents also showed a strong preference for Australia as a future work location, although a preference well behind that for the USA (39%). Japanese experiences of research training, networks and mobility The experiences of Japanese scientists are shown in Table 4. This group is the ‘stay at homes’, both for their research degree and their current place of work; more so than any of the other sub-groups discussed here. Where they went abroad, they focused heavily on North America for their post-doctoral work, with almost half (47%) of those going overseas moving to the US and a further 5% choosing Canada. This too is reflected in place of most work. Germany and the UK are the other main choices. The same foci are again evident in the location of network participation. A high proportion of Japanese nationals have worked in the US, a much higher ratio than the other national groups (with the exception of Korea) and one again consistent with post-doctoral education choices. The place of choice for future work by the Japanese is also mainly the USA, followed by Australia. Other choices included France, China and Germany. Korean experiences of research training, networks and mobility

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The case of Korea seems to be an exception to the patterns described above (see Table 5). Their patterns of work, networks are the most concentrated, of all groups, in the US. A relatively high proportion of Koreans (39%) completed their research degree out of the country, mostly in the US. This proportion is considerably higher than that for any of the other national groups. The overseas choice for work location, however, does not last at entry to post-doctoral training and the labour market. Like the Japanese, the Koreans are a ‘return to home’ group once they have their PhDs. Among the Koreans that did undertake post-doctoral study overseas, nearly two thirds went to the US, a preference also seen in choice of place for work, research network participation, most important collaboration and future professional activity (Australia is again over-represented in the last choice). In other words, there seem to be two distinct Korean patterns; one where a student goes overseas for a research degree and then returns home and one where, once overseas at doctoral level, young scientists choose to stay not only for post-doctoral study but also for a good part of their professional careers in science and technology. The US and Japan continue to provide the focus for networks and collaboration. Australian experiences of research training, networks and mobility Patterns of study and work choices among Australians lie between those of the Koreans and those of nationals of the other countries in terms of location of research degree. More than three quarters completed their doctorates in Australia. But their overseas work locations are most concentrated on the UK and the USA, although compared with the other national groups, Australians are much more likely to complete their post doctoral work at home (43%). While Australians are somewhat more inclined than the other groups to complete their research degrees overseas, they are more likely than the Chinese to be working back at home but less so than their Indian, Japanese or Korean counterparts. Location of network, like the other groups, and consistent with place of international work, are most concentrated in the US and UK, So too are most important collaborations but they are generally more widely spread across other countries than the other national groups. Networks with Japan are comparatively less for the Australian sample. ASEAN experiences of training, networks and mobility The Asian region is diverse in terms of countries and their size and level of development. We now explore the experiences of some of the smaller and less developed countries in the region. The ASEAN bloc comprises 10 countries, some of which are industrially developed and comparatively wealthy such as Singapore and Brunei. Others are large and struggling with processes of development, such as Indonesia and the Philippines. Others are comparatively small and economically struggling, such as Cambodia and Lao PDR. Our study had 707 respondents from ASEAN countries. This number included 97 from Singapore, 140 from Malaysia, 49 from the Philippines, 189 from Thailand, 38 from Indonesia, 30 from Vietnam and 12 from Cambodia, Lao PDR, Brunei and Myanmar together. Our study is therefore heavily weighted toward the more scientifically developed group of Singapore, Malaysia, Thailand and, to a lesser extent, the Philippines.

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The ASEAN responses reflect a strong outward movement for research degree preparation, directed toward the UK, the USA (by far the most common destination), Australia and Japan. As with our other groups, an even greater proportion went overseas for post-doctoral study, with 80 per cent completing their studies in a place outside the ASEAN region. Unlike some of our other groups, however a high proportion of ASEAN scientists appear to return to work in the ASEAN region, although not necessarily in their countries of origin The research networks thus built, reflecting post-doctoral study location, also make Australia and the USA preferred countries for future work. The strong preference for a future career in Australia probably reflects Australia’s geographic position in the region, although we cannot rule out some response bias here. Reasons for moving Making a move first to study overseas and then perhaps to pursue a career outside one’s home country is an important decision and one that has many implications of a financial and cultural kind. We therefore asked about factors motivating this choice. Respondents were asked to indicate their reason for potentially moving to another location. The reasons selected were cross-tabulated with location of preferred location. The results focused on those countries most selected are shown in Table 8. Although the numbers in some cells are small at this disaggregated level they suggest different reasons for moving to various countries. Singapore and Canada, for example, seem to offer a greater pull for increased salary opportunities. Canada and the UK appear as more favoured destinations when scientists are seeking to move to another location primarily for general lifestyle reasons. Although the numbers are too small to draw any strong conclusion China suggests a location for business and commercial opportunities. Of the 2462 respondents who identified another global location in which they would like to work the largest group selected as their reason for wanting to move as ‘continuing with collaboration in my field’ (32%). This indicates a strong motivation to consolidate existing networks. The next most noted motivating factors were: to gain access to better research infrastructure (21%); and equally, to be part of a scientific community or intellectual climate (21%) These three factors combined suggest strong pull factors from areas where there is a well established ‘knowledge centre’. It is not surprising therefore, that the US continues to generate a strong pull factor attracting overseas scientists. These responses were explored in more detail by contrasting, Indian, Chinese and ASEAN responses to this question. The data are presented in Tables 9, 10 and 11. Each of these groups continued to nominate the same three main reasons, with some minor variations. For the Chinese, the US, Australia and the UK were preferred destinations: the US and Germany the preferred locations for infrastructure; the UK and Australia most nominated for collaboration; and Germany predominating for intellectual climate. For the Indians the US, Australia, Germany ad the UK were preferred locations: the US, UK and Germany for infrastructure; Germany and Australia for collaboration; and the US and German for the intellectual climate. The ASEAN group presented some variation with respect to seeking higher salaries and

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moving to an organisation with more prestige or simply seeking to move as an alternative to working in their current location. This suggests perhaps a higher dissatisfaction with the organisational structures operating in the smaller economies. Is age a factor in deciding where to move? This possibility was explored through the preferences of two national groups: the Chinese and Indians. Data for each group were aggregated and cross tabulated according to four age groupings and selected countries of choice for future work (Tables 12 and 13). For the Chinese there were two main preferred destinations: the US and Australia These two choices were followed, with much smaller numbers, by Germany and the UK. Younger Chinese scientists were less likely to nominate Australia as their choice for future work and more likely to nominate the US. The Indian group also favoured the US and Australia, but a higher proportion nominated Germany Japan and the UK., particularly among the younger groups. Does this mean the Indian group is becoming more mobile and more widely dispersed? Interestingly a recent report by Dente (2007) drew attention to the growing scientific networks between India and Germany, both at an institutional level as well as between science specialists. In summary, it appears that a desire to consolidate work with colleagues in the context of a high level of technical research infrastructure and support underpin the main reasons for mobility. The data suggest that the process is inherently self-reinforcing; as the research experience intensifies through post doctoral research so too does the formation of scientific networks. As these develop further their continuation and further deepening becomes a powerful motivational factor. Mobility of scientists within the business sector Knowledge networks draw on knowledge produced in public sector institutes, locally and globally. They also draw on knowledge and expertise located in business sector firms and organisations. The preceding sections described the mobility of scientists working in both public and private sectors. The following sections describe patterns of mobility of our respondents working outside the public sector. Table 14 presents data on respondents from both sectors. The business sector sub-sample provided 750 respondents (7% of the total sample). The proportion in the business sector varied across the 11 countries shown in Table 14 from 4% for China to over 12% for New Zealand and Australia. The higher proportion for New Zealand possibly reflects the restructure of the New Zealand research system into Crown Institutes and in Australia perhaps to the growing significance of Cooperative Research Centres. Within the business sector sub sample the largest numbers (in terms of nationality) were from Japan, Australia, India and Korea. In terms of location of acquiring research degree and current place of work, most were located in Japan and Australia, followed by India and Korea. There seems to be a great consistency for this group across these three variables. Most networks, however, were concentrated in the US,

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with the UK also figuring as an important location. This pattern is also reflected in loocation of most important collaboration. Members of the business sub-sample therefore are a group of ‘stayers’ or ‘returnees’ but with strong collaborative networks with the US and the UK. Table 15 presents the data according to the length of time working in the business sector for the sample as a whole. Over 3000 respondents had worked for ‘some time’ in the business sector. Longer-term employees in business were dominated by the Japanese (48% for 20 years or more). Shorter term employment in business (1-5 years) was more equally distributed but concentrated mostly among Chinese, Australians, Indians and Koreans. The mid-range length of business employment (6-20 years) was made up primarily of Japanese and Koreans, followed by Australians. To some extent this reflects the different age structure in the sample, with Chinese weighted toward the younger age groups and the Japanese weighted more toward the older age groups. However, the data also suggest the growing importance of the high tech business sector reported widely in both China and India (see for example Dente, 2007). Discussion and conclusion The evidence presented above shows that Japan and Korea both have high return rates (compared to other countries) from among their overseas scientists. Comparatively good opportunities at home in these countries for scientists’ career choices are clearly factors at play. Growing R&D investments in India and China, particularly in the increasingly sophisticated special economic zones are likely to also provide growing opportunities for careers. They will also provide a growing focus for collaboration through DKNs. As scientific engagement increases through post-doctoral studies and research sabbaticals, it is likely that scientific mobility and on-site collaboration in these areas will also increase. As international activities expand, they will offer new opportunities for both doctoral research and post-doctoral training. Sophisticated research infrastructure and the opportunities to collaborate with world class researchers are important factors pulling scientists to particular areas, including home countries in the region. To some extent differences in mobility patterns may be linked to field of research. We plan to discuss that aspect of location choices of our scientific and technological personnel in a later paper. What future for science in the less developed countries? The growth of the large economies of India and China makes it likely that some of the smaller and less developed countries in the Asian region will find it difficult to retain scientists within their own systems or to gain access to new knowledge through DKNs. The diaspora does not necessarily mean that the ‘losing’ countries will have no benefit whatsoever from their investment in the scientific education of their young people. As Mahroun et al. (2006) have suggested, there is potential for developing countries to capture some benefit from their professionals abroad, beyond simply receiving remittances. Using the example of the health care professions, they suggest that

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sending and receiving countries could benefit by supporting links between senders and receivers in formalised development programmes. The general thrust of this position is compelling but may require special policy initiatives if maximum use is to be made of the opportunities. These initiatives may be taken by the countries concerned and/or by international aid agencies assisting the countries of the region. Thus, for example, the data presented in this paper on scientists suggest at least one way forward. Post-doctoral studies offer important network building opportunities. The location in which post-doctoral training is received is formative both in terms of where scientists eventually work and where their long term networks reside. A study of post-doctoral fellowships awarded to Australian scientists in the early 1990s drew attention to the importance of these awards in steering future career options (Marceau and Preston 1997). Countries themselves, perhaps in collaboration with others, may be able to devise career structures which enable their best and brightest who may be tempted to remain overseas after finishing their training to return for regular periods and teach or undertake specific projects at ‘home’. Returning graduates of this kind bring with them much needed tacit knowledge about new scientific methods, equipment and promising areas of enquiry. Properly supported at home they can quickly make significant contribution. The study by Marceau and Preston showed, for example, how important this inflow of new information could be even in the context of Australian science. It also showed how in at least one institution senior professors had long term strategies for maximising both the chances of their graduates going to the best places in their fields overseas and returning home from overseas. These senior scientists then rapidly integrated the knowledge returnees brought with them into the work of the labs to which they returned. Science careers in all smaller countries urgently need to be rethought so that access can be ensured to the best centres overseas without the home countries losing out; much science can be undertaken through access to equipment and centres of excellence for periods and then followed through elsewhere. This kind of approach makes returning much less of a ‘once and for all’ decision and introduces flexibility for the scientific and technological personnel concerned. International development efforts also could be usefully re-directed in similar ways. They could, for example, introduce post-doctoral awards for top young scientists to be taken up in targeted locations around the world. The location should vary according to the national scientific strength and research priorities of the various sending countries. The selections should be strategic, with the logic of building on existing or emerging strengths by locating specialists closer to the centre of regional knowledge hubs. Many policy makers may feel this is a risky option, one likely to further the loss of national talent from developing countries because it might potentially lead to a geographic ‘brain loss’. Our view is that this approach should be seen as complementary to other development strategies that seek to build local scientific infrastructure and research management capacity. Our evidence shows that the ‘stayers’ ie those who complete their research training at home, are more inclined to stay at home. It is those who extend their research intensity further, through post-doctoral fellowships for example, who are more inclined to move. Members of this group are closer to the heart of global research networks; their potential to act as contributors to scientific capacity at home could be significant.

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Spatial proximity is not necessarily the same as organisational proximity. The growing sophistication of information and communication technologies has opened the way for the growth of knowledge networks ‘based upon spatially dispersed’ interaction through distributed knowledge networks (OECD, 2001: 21). These networks can be the basis of intra-regional or broader international knowledge exchange mechanisms. Indeed, it is the combination of organisational proximity and spatially dispersed interaction that characterises the development of ‘knowledge hubs’ in various parts of the world (TIAC, 2002). These hubs are not simply links between research institutes or universities and industry but are emerging clusters of education, training and research organisations whose members act together, develop strong linkages to industry and improve R&D infrastructure. They depend on permeable international boundaries which should be a growing and enduring feature of the scientific landscape in Asia if all countries there are to benefit from the expertise of the scientific and technological personnel they produce and can ‘borrow’. The kinds of international research training and career paths that we have described in this paper are potentially the beginning of powerful and successful intra-regional organisational arrangements which transcend national boundaries and enable the weaker countries to benefit from the capacities of others in their area. In turn, this approach will enable the smaller countries in turn to contribute more quickly in their specialised areas.

Table1: Countries of research training, post doc, current work, international networks and preferred future location (all respondents)

Location

Nationals

%

Research Degree

%

Post doc

%

Location

of current work

%

Location of most work *

%

Location of main

networks *

%

Most

important collaboration

%

Preferred

future location for work

%

Australia 1047 10.2 883 9.9 319 7.1 1121 11.1 1399 8.9 1269 7.0 580

6.3 663 21.8

Canada 126 1.2 147 1.6 223 5 119 1.2 463 2.9 538 3.0 294

3.2 148 4.9China 1650 16 1176 13.1 257 5.7 1403 13.9 1522 9.7 1197 6.6 523

5.7 84 2.8

France 127 1.2 148 1.7 111 2.5 72 0.7 360 2.3 651 3.6 339

3.7 85 2.8Germany `197 1.9 192 2.1 240 5.3 169 1.7 639 4.1 1101 6.1 572 6.2 165 5.4Hong Kong 50 0.5 55 0.6 32 0.7 114 1.1 180 1.1 177 1.0 118 1.3 23 0.8India 1680 16.3 1311 14.6 254 5.7 1492 14.8 1563 9.9 750 4.2 304

3.3 23 0.8

Japan 1331 12.9 1337 14.9 411 9.2 1395 13.8 1669 10.6 1756 9.7 847

9.2 154 5.1Korea 771 7.5 448 5 122 2.7 777 7.7 755 4.8 461 2.6 201

2.2 33 1.1

Malaysia 158 1.5 48 0.5 5 0.1 133 1.3 136 0.9 111 0.6 47 0.5 18 0.6Netherlands 63 0.6 70 0.8 47 1 50 0.5 128 0.8 208 1.2 109

1.2 22 0.7

New Zealand 315 3.1 216 2.4 74 1.6 368 3.7 423 2.7 280 1.6 137

1.5 30 1Pakistan 101 1 36 0.4 4 0.1 83 0.8 77 0.5 59 0.3 20

0.2 3 0.1

Philippines 55 0.5 26 0.3 2 0 51 0.5 70 0.4 58 0.3 30

0.3 2 0.1Russian Fed. 72 0.7 98 1.1 29 0.6 35 0.3 99 0.6 125 0.7 80

0.9 4 0.1

Singapore 115 1.1 112 1.2 54 1.2 285 2.8 294 1.9 265 1.5 124

1.3 51 1.7Chinese Taipei

431 4.2 159 1.8 68 1.5 425 4.2 366 2.3 230 1.3101

1.1

14 0.5

Thailand 217 2.1 69 0.8 17 0.4 226 2.2 230 1.5 173 1.0 77 0.8 11 0.4UK 247 2.4 801 8.9 315 7 223 2.2 974 6.2 1618 9.0 747

8.1 183 6

USA 530 5.1 1180 13.2 1512 33.7 744 7.4 2829 18.0 4918 27.3 2904

31.4 1001 32.9Other 1019 9.9 451 5 390 8.7 795 7.9 1549 9.9 2077 11.5 1095

11.8 321 10.6

Total 10302 100 8963 100 4486 100 10,080 100 15725 100.0 18022 100.0 9249 100.0 3038 100 Source: Asian scientists mobility survey 2005/6 * = sum of two choices

15

Table 2: Scientists’ research backgrounds, networks and potential movement: Indian nationals

Location

Research Degree

%

Post doc

%

Location

of current work

%


%

Location of main network

*

%

Location of most


Future location

preference

%

Australia 10 0.7 12 1.6 9 0.5 33 1.3 71 2.6 30 2.2

174 20.6

Canada 10 0.7 32 4.2 7 0.4 49 1.9 73 2.7 40 3.0 32 3.8China 0 0 1 0.1 0 0 5 0.2 23 0.9 11 0.8 6 0.7France 1 0.1 21 2.7 6 0.4 42 1.7 115 4.3 58 4.3

21 2.5

Germany 2 0.1 63 8.2 9 5 147 5.8 263 9.8 164 12.2 63 7.5Hong Kong 0 0 0 0 1 0.1 1 0.0 1 0.0 2 0.1 1 0.1India 1269 85.9 241 31.3 1459 88.2 1486 58.6 600 22.2 222 16.5 7 0.8Japan 6 0.4 33 4.3 6 0.4 66 2.6 153 5.7 72 5.4

48 5.7

Korea 1 0.1 13 1.7 11 0.7 28 1.1 29 1.1 18 1.3 10 1.2Malaysia 0 0 0 0 8 0.5 5 0.2 15 0.6 6 0.4

9 1.1

Netherlands 4 0.3 8 1.1 2 0.1 14 0.6 32 1.2 16 1.2 4 0.5New Zealand 2 0.1 2 0.3 2 0.1 4 0.2 5 0.2 4 0.3

3 0.4

Pakistan 0 0 0 0 0 0 0 0.0 1 0.0 0 0.0

0 0Philippines 0 0 1 0.1 0 0 1 0.0 2 0.1 0 0.0

0 0

Russian Fed. 2 0.1 2 0.32 1 0.1 5 0.2 10 0.4 11 0.8

0 0Singapore 6 0.4 1 0.1 26 1.6 20 0.8 27 1.0 8 0.6 21 2.5Chinese Taipei 0 0 6 0.8 7 0.4 8 0.3 12 0.4 7 0.5

3 0.4

Thailand 0 0 0 0 0 0 5 0.2 7 0.3 2 0.1

1 0.1UK 31 2.1 46 6 6 0.4 116 4.6 255 9.5 118 8.8

48 5.7

USA 100 6.8 226 29.4 47 2.8 351 13.8 721 26.7 381 28.3

307 36.3Other 34 2.3 62 8.1 47 2.8 156 6.1 292 10.8 175 13.0 87 10.3Total 1478 100 770 100 1654 100 2537 100.0 2697 100.0 1345 100.0 845 100

Source: Asian scientists mobility survey 2005/6 * = sum of two choices

16

Table 3: Scientists’ research backgrounds, networks and potential movement: Chinese nationals

Location

Research Degree

%

Post doc

%

Location of current work

%

Location of most work

*

%

Location of main

networks *

%

Most

important collaborati

on

%

Future location

preference

%

Australia 8 0.6 7 1.1 16 1 35 1.5 100 3.6 51 3.5 169 24.6Canada 9 0.6 27 4.1 13 0.8 58 2.4 104 3.8 62 4.2 30 4.4China 1136 78.5 239 36.7 1337 81.8 1338 56.0 649 23.6 215 14.6 223 3.3France 12 0.8 30 4.6 5 0.3 45 1.9 84 3.1 46 3.1 11 1.6Germany 18 1.2 32 4.9 13 0.8 108 4.5 181 6.6 107 7.3 45 6.6Hong Kong 27 1.9 21 3.2 28 1.7 84 3.5 98 3.6 71 4.8 13 1.9India 0 0 0 0 0 0 1 0.0 5 0.2 4 0.3 1 0.1Japan 54 3.7 69 10.6 51 3.1 151 6.3 247 9.0 139 9.5 20 2.9Korea 5 0.3 11 1.7 6 0.4 25 1.0 34 1.2 21 1.4 0 0Malaysia 1 0.1 0 0 0 0 1 0.0 2 0.1 2 0.1 0 0Netherlands 6 0.4 6 0.9 2 0.1 10 0.4 34 1.2 15 1.0 4 0.6New Zealand 0 0 2 0.3 5 0.3 7 0.3 6 0.2 4 0.3 1 0.1Pakistan 0 0 0 0 0 0 0 0.0 0 0.0 1 0.1 0 0Philippines 0 0 0 0 0 0 0 0.0 2 0.1 2 0.1 0 0Russian Fed. 4 0.3 0 0 0 0 7 0.3 14 0.5 12 0.8 0 0Singapore 40 2.8 29 4.4 52 3.2 5 0.2 76 2.8 39 2.7 6 0.9Chinese Taipei 1 0.1 1 0.2 2 0.1 5 0.2 5 0.2 3 0.2 0 0Thailand 0 0 1 0.2 1 0.1 3 0.1 4 0.1 0 0.0 0 0UK 22 1.5 20 3.1 11 0.7 83 3.5 180 6.6 88 6.0 31 4.5USA 52 3.6 102 15.6 75 4.6 216 9.0 700 25.5 444 30.2 266 38.7Other 52 3.6 55 8.4 18 1.1 140 5.9 223 8.1 144 9.8 67 9.8Total 1447 100 652 100 1635 100 2389 100.0 2748 100 1470 100.0 687 100


17

Table 4: Scientists’ research backgrounds, networks and potential movement: Japanese nationals

Location

Location of

Research Degree

%

Location of Post

doc %

Location of

current work

%


%

Location of main

network *

%

Location of most


%

Preferred future

Location

%

Australia 0 0 7 1.2 4 0.3 19 1.0 79 3.4 32 2.7

42 17.6

Canada 2 0.2 31 5.4 3 0.2 54 2.7 63 2.7 34 2.9

7 2.9China 0 0 2 0.3 1 0.1 11 0.6 113 4.9 75 6.3

12 5

France 1 0.1 0 0 0 0 32 1.6 96 4.2 50 4.2

16 6.7Germany 1 0.1 21 3.6 5 0.4 62 3.2 170 7.4 73 6.1

11 4.6

Hong Kong 0 0 0 0 0 0 0 0.0 1 0.0 0 0.0

0 0India 0 0 2 0.3 0 0 0 0.0 14 0.6 7 0.6

2 0.8

Japan 1124 96 177 30.6 1233 95.5 1061 53.9 348 15.2 85 7.1

7 2.9Korea 1 0.1 2 0.3 2 0.2 1 0.1 82 3.6 31 2.6

4 1.7

Malaysia 0 0 0 0 1 0.1 3 0.2 5 0.2 4 0.3

0 0Netherlands 0 0 2 0.3 0 0 18 0.9 25 1.1 16 1.3

2 0.8

New Zealand 0 0 2 0.3 1 0.1 5 0.3 6 0.3 4 0.3

4 1.7Pakistan 0 0 0 0 0 0 0 0.0 0 0.0 0 0.0

0 0

Philippines 0 0 0 0 1 0.1 0 0.0 3 0.1 2 0.2

1 0.4Russia 0 0 0 0 0 0 3 0.2 27 1.2 18 1.5

0 0

Singapore 0 0 0 0 1 0.1 1 0.1 5 0.2 4 0.3

2 0.8Chinese Taipei 0 0 1 0.2 1 0.1 3 0.2 10 0.4 3 0.3

4 1.7

Thailand 0 0 0 0 0 0 6 0.3 28 1.2 16 1.3

2 0.8UK 8 0.7 20 3.5 1 0.1 76 3.9 167 7.3 65 5.5

6 2.5

USA 26 2.2 276 47.7 24 1.9 537 27.3 839 36.5 536 45.1

93 38.9Other 8 0.7 33 5.7 13 1 105 5.3 228 9.9 134 11.3

24 10

Total 1171 100 579 100 1291 100 1967 100.0 2297 100.0 1189 100.0 239 100Source: Asian scientists mobility survey 2005/6 * = sum of two choices

18

Table 5: Scientists’ research backgrounds, networks and potential movement: Korean nationals

Location

Location of

Research Degree

%

Location of Post

doc

%

Location of

current work

%


%

Location of main

networks *

%

Location of most


%

Preferred future

location

%

Australia 6 0.9 9 2.4 2 0.3 16 1.3 40 3.0 15 2.2

42 16.8

Canada 6 0.9 13 3.5 0 0 26 2.2 34 2.5 15 2.2

19 7.6China 0 0 0 0 0 0 6 0.5 42 3.1 19 2.7 14 5.6France 7 1.1 4 1.1 0 0 13 1.1 27 2.0 15 2.2

8 3.2

Germany 8 1.2 14 3.7 3 0.4 25 2.1 54 4.0 19 2.7 7 2.8Hong Kong 0 0 0 0 1 0.1 2 0.2 2 0.1 2 0.3

1 0.4

India 0 0 0 0 0 0 0 0.0 8 0.6 8 1.2 2 0.8Japan 33 5 25 6.7 7 1 74 6.2 293 21.7 113 16.3

15 6

Korea 406 61.2 73 19.5 681 92.9 611 51.4 185 13.7 46 6.6

6 2.4Malaysia 0 0 0 0 0 0 1 0.1 0 0.0 1 0.1

0 0

Netherlands 0 0 1 0.3 1 0.1 3 0.3 5 0.4 4 0.6 3 1.2New Zealand 1 0.2 0 0 1 0.1 1 0.1 3 0.2 0 0.0

3 1.2

Pakistan 0 0 0 0 0 0 0 0.0 0 0.0 0 0.0

0 0Philippines 0 0 0 0 0 0 0 0.0 2 0.1 0 0.0

1 0.4

Russia 0 0 1 0.3 0 0 1 0.1 8 0.6 7 1.0

0 0Singapore 0 0 0 0 0 0 0 0.0 0 0.0 0 0.0

5 2

Chinese Taipei 0 0 0 0 0 0 2 0.2 4 0.3 3 0.4

1 0.4Thailand 0 0 0 0 0 0 0 0.0 0 0.0 0 0.0

0 0

UK 8 1.2 8 2.1 1 0.1 14 1.2 41 3.0 19 2.7

8 3.2USA 183 27.6 219 58.4 30 4.1 372 31.3 531 39.3 367 52.8

104 41.6

Other 5 0.8 8 2.1 6 0.8 21 1.8 73 5.4 42 6.0 11 4.4Total 663 100 375 100 733 100 1188 100.0 1352 100.0 695 100.0 250 100


19

Table 6. Scientists’ research backgrounds, networks and potential movement: Australian nationals

Location

Location of

Research Degree

Location of

current work %


%

Location of main

networks*

%

Location of most


%

Preferred future

location

%

Location of Post

doc % %

Australia 707 76.8 203 42.6 878 85.5 904 55.6 382 20.1 121 12.6

26 18.6

Canada 12 1.3 33 6.9 5 0.5 55 3.4 72 3.8 41 4.3

2 1.4China 2 0.2 0 0 4 0.4 20 1.2 47 2.5 32 3.3

4 2.9

France 2 0.2 8 1.7 0 0 18 1.1 64 3.4 35 3.7

6 4.3Germany 2 0.2 12 2.5 5 0.5 33 2.0 75 4.0 42 4.4 3 2.1Hong Kong 2 0.2 2 0.4 4 0.4 10 0.6 11 0.6 8 0.8

2 1.4

India 4 0.4 2 0.4 0 0 9 0.6 11 0.6 5 0.5

2 1.4Japan 1 0.1 7 1.5 8 0.8 17 1.0 49 2.6 29 3.0

4 2.9

Korea 0 0 0 0 2 0.2 1 0.1 11 0.6 4 0.4

0 0Malaysia 0 0 0 0 1 0.1 4 0.2 10 0.5 2 0.2

1 0.7

Netherlands 1 0.1 1 0.2 1 0.1 6 0.4 22 1.2 15 1.6 1 0.7New Zealand 17 1.8 5 1.1 18 1.8 45 2.8 49 2.6 31 3.2

2 1.4

Pakistan 0 0 0 0 0 0 1 0.1 5 0.3 3 0.3

0 0Philippines 1 0.1 0 0 2 0.2 4 0.2 3 0.2 2 0.2

0 0

Russia 12 1.3 1 0.2 0 0 10 0.6 9 0.5 5 0.5

0 0Singapore 0 0 1 0.2 12 1.2 12 0.7 16 0.8 7 0.7

1 0.7

Chinese Taipei 0 0 0 0 1 0.1 1 0.1 3 0.2 1 0.1

0 0Thailand 0 0 0 0 1 0.1 4 0.2 15 0.8 2 0.2

2 1.4

UK 93 10.1 59 12.4 30 2.9 152 9.4 294 15.5 141 14.7 22 15.7USA 38 4.1 111 23.3 33 3.2 193 11.9 525 27.7 294 30.7

30 21.4

Other 26 2.8 31 6.5 22 2.1 126 7.8 224 11.8 137 14.3

32 22.9Total 920 100 476 100 1027 100 1625 100.0 1897 100.0 957 100.0 140 100


20

Table 7. ASEAN countries nationals by location of research training, networks and preferred locations for future work

Location

Research Degree

%

Post doc

%

Current work

%

Location of most work*

%

Location of main research network*

%

Preferred location

%

ASEAN

191 34.4 34 19.8 539 87.8 400 72.6 212 19.7 12 6.5Australia 46 8.3 8 4.7 16 2.6 23 4.2 76 7.1 49 26.6 Canada 13 2.3 6 3.5 3 0.5 4 0.7 25 2.3 12 6.5 China 2 0.4 1 0.6 1 0.2 2 0.4 28 2.6 2 1.1 France 7 1.3 5 2.9 1 0.2 5 0.9 30 2.8 1 0.5 Germany 0 0 7 4.1 1 0.2 3 0.5 33 3.1 6 3.3 Hong Kong 0 0 0 0 1 0.2 1 0.2 6 0.6 0 India 2 0.4 1 0.6 1 0.2 2 0.4 4 0.4 0 0 Japan 42 7.6 21 12.2 13 2.1 28 5.1 148 13.7 20 10.9 Korea 3 0.5 8 4.7 7 1.1 6 1.1 23 2.1 2 1.1 Netherlands 2 0.4 0 0 0 0 1 0.2 15 1.4 0 0 New Zealand 5 0.9 0 0 2 0.3 3 0.5 9 0.8 3 1.6 Russian Fed 4 0.7 2 1.2 0 0 3 0.5 3 0.3 0 0 Chinese Taipei 1 0.2 0 0 4 0.7 2 0.4 9 0.8 0 0 UK 99 17.8 10 5.8 3 0.5 27 4.9 132 12.2 16 8.7 USA 90 16.2 50 29.1 7 1.1 31 5.6 238 22.1 49 26.6 Other 48 8.6 19 11 15 2.4 10 1.8 87 8.1 24 13Total 555 100 172 100 614 100 551 100 1078 100.0 184 100


21

Table 8. Reason for seeking to move job by Location with 49+ selections.

Location

To earn increased salary or

other financial rewards

To be part of a

scientific community

or intellectual

climate

To gain access to adequate longer-

term research funding

To continue with

collaboration in my field

To access better research support

& technical infrastructure

To move to an

organisation with greater

prestige

To move to another

location

To be able to publish the results

of my work

To commercialize

my intellectual property

Other Total

Australia

28 137 56 220 115 16 29 8 9 37 655

% 4.3

20.9 8.5 33.6 17.6 2.4 4.4 1.2 1.4 5.6 100.0 Canada 11 28 8 43 25 0 16 0 3 11 145

% 7.6 19.3 5.5 29.7 17.2 0.0 11.0

0.0 2.1 7.6 100.0 China 2 7 10 29 12 1 6 3 4 7 81

% 2.5 8.6 12.3 35.8 14.8 1.2 7.4 3.7 4.9 8.6 100.0 France 0 18 4 33 10 1 4 2 1 3 76

% 0.0 23.7 5.3 43.4 13.2 1.3 5.3 2.6 1.3 3.9 100.0Germany 14 35 3 55 42 2 3 5 1 1 161% 8.7 21.7 1.9 34.2 26.1 1.2 1.9 3.1 0.6 0.6 100.0

Japan 6 22 11 64 28 3 3 2 2 6 147% 4.1 15.0 7.5 43.5 19.0 2.0 2.0 1.4 1.4 4.1 100.0Singapore

9 8 3 13 9 2 1 1 0 3 49

% 18.4 16.3 6.1 26.5 18.4 4.1 2.0

2.0

0.0 6.1

100.0UK 8 43 16 53 30 9 8 2 2 10 181% 4.4 23.8 8.8 29.3 16.6 5.0 4.4 1.1 1.1 5.5 100.0

USA 58 208 50 278 244 45 22 12 12 38 967% 6.0 21.5 5.2 28.7 25.2 4.7 2.3 1.2 1.2 3.9 100.0Total 136 506 161

788 515 79 92 35 34 116 2462

% 5.5 20.6 6.5 32.0 20.9 3.2 3.7 1.4 1.4 4.7 100.0Source: Asian scientists mobility survey 2005/6

22

Table 9. China: Preferred Location move and reasons for wanting to move

Location



To be part of a scientific community

or intellectual

climate



To work with collaborators

in my specialization

To access better

research support and

technical infrastructure

To move to an


prestige

To move to another

location

To be able to publish the results

of my work

To commercialize my intellectual

property

Other Total

Australia 7 27 24 66 27 6 1 2 1 3 164 Australia % 4.3 16.5 14.6 40.2 16.5 3.7 0.6 1.2 0.6 1.8 100.0 Canada 2 7 2 9 6 0 3 0 0 0 29 China 0 4 2 4 4 1 6 1 0 1 23 France 0 4 1 2 2 0 1 0 0 0 10 Germany 5 12 0 13 12 1 0 2 0 0 45 Germany % 11.1 26.7 0.0 28.9 26.7 2.2 0.0 4.4 0.0 0.0 100.0 Hong Kong 1 0 1 5 5 1 0 0 0 0 13 India 0 0 0 0 0 0 0 1 0 0 1 Japan 2 4 2 7 5 0 0 0 0 0 20 Korea 0 0 1 1 1 0 0 0 0 0 3 Malaysia 0 0 0 0 0 0 0 0 0 0 0 Netherlands 1 0 0 1 2 0 0 0 0 0 4 New Zealand 0 1 0 0 0 0 0 0 0 0 1 Pakistan 0 0 0 0 0 0 0 0 0 0 0 Philippines 0 0 0 0 0 0 0 0 0 0 0 Russia 0 0 0 0 0 0 0 0 0 0 0 Singapore 2 0 0 2 1 1 0 0 0 0 6 Chinese Taipei 0 0 0 0 0 0 0 0 0 0 0 Thailand 0 0 0 0 0 0 0 0 0 0 0 UK 2 5 1 15 4 2 0 1 0 0 30 UK % 6.7 16.7 3.3 50.0 13.3 6.7 0.0 3.3 0.0 0.0 100.0 USA 15 40 16 81 67 12 1 3 3 7 259 USA % 5.8 15.4 6.2 31.3 25.9 4.6 0.4 1.2 1.2 2.7 100.0 Other 2 10 4 111 31 2 2 0 0 1 60Total 39 114 54 232 163 26 14 10 4 12 668 Total % 5.8 17.1 8.1 34.7 24.4 3.9 2.1 1.5 0.6 1.8 100.0

Source: Asian scientists mobility survey 2005/6

23

Table 10. India: Preferred Location move and reasons for wanting to move.

Location



To be part of a


or intellectual

climate



To work with collaborators

in my specialization

To access better research support & tech infrastructure

To move to an


prestige

To move to

another location

To be able to publish

the results of my work

To commercialize


Other Total

Australia 8 44 7 64 42 3 0 0 3 3 174 Australia % 4.6 25.3 4.0 36.8 24.1 1.7 0.0 0.0 1.7 1.7 100.0 Canada 0 8 1 16 3 0 1 0 1 2 32 China 0 0 1 3 2 0 0 0 0 0 6 France 0 5 0 11 4 0 0 0 0 0 20 Germany 2 16 1 23 16 0 1 1 1 0 61 Germany % 3.3 26.2 1.6 37.7 26.2 0.0 1.6 1.6 1.6 0.0 100.0 Hong Kong 0 0 1 0 0 0 0 0 0 0 1 India 0 0 0 0 0 1 0 0 0 6 7 Japan 1 9 0 24 10 0 1 0 0 1 46 Korea 1 0 0 3 0 0 0 1 0 1 6 Malaysia 1 0 0 4 3 0 0 0 0 1 9 Netherlands 0 1 0 2 0 0 1 0 0 0 4 New Zealand 0 2 0 0 0 1 0 0 0 0 3 Pakistan 0 0 0 0 0 0 0 0 0 0 0 Philippines 0 0 0 0 0 0 0 0 0 0 0 Russia 0 0 0 0 0 0 0 0 0 0 0 Singapore 4 6 1 5 4 0 0 0 0 0 20 Chinese Taipei 0 1 0 2 0 0 0 0 0 0 3 Thailand 1 0 0 0 0 0 0 0 0 0 1 UK 0 12 2 10 14 2 2 0 0 2 47 UK % 0.0 25.5 4.3 21.3 29.8 4.3 4.3 0.0 0.0 4.3 100.0 USA 11 83 11 57 89 6 3 0 5 3 296 USA % 3.7 28.0 3.7 19.3 30.1 2.0 1.0 0.0 1.7 1.0 100.0 Other 3 11 7 21 14 0 1 0 1 2 66Total 32 198 32 245 201 13 10 2 11 21 802 Total % 4.0 24.7 4.0 30.5 25.1 1.6 1.2 0.2 1.4 2.6 100.0


24

Table 11. ASEAN: Reasons for wanting to move

Location



To be part of a


or intellectual

climate

To gain access to adequate longer-term

research funding

To continue with

collaboration in my field

To access better research

support & technical

infrastructure

To move to an


prestige

To move to

another location

To be able to publish

the results of my work

To commercialize


Other Total

ASEAN 12 42 10 50 37 12 15 8 1 10 197 ASEAN % 6.1 21.3 5.1 25.4 18.8 6.1 7.6 4.1 0.5 5.1 100.0


25

Table 12: China national scientists’ preferred location option by age

Age Group Preferred

future location >29 % 30-39 % 40-49 % 50+ %

Australia 19

17.0 84 25.7 51 25.9 15 29.4Canada 4 3.6 16 4.9 7 3.6 3 5.9China 0 0.0 15 4.6 8 4.1 0 0.0France 1 0.9 5 1.5 5 2.5 0 0.0Germany 6 5.4 26 8.0 10 5.1 3 5.9Hong Kong 4 3.6 4 1.2 1 0.5 4 7.8India 0 0.0 0 0.0 1 0.5 0 0.0Japan 4 3.6 7 2.1 8 4.1 1 2.0Korea 1 0.9 1 0.3 0 0.0 1 2.0Malaysia 0 0.0 0 0.0 0 0.0 0 0.0Netherlands 2 1.8 2 0.6 0 0.0 0 0.0New Zealand 0 0.0 0 0.0 1 0.5 0 0.0Pakistan 0 0.0 0 0.0 0 0.0 0 0.0Philippines 0 0.0 0 0.0 0 0.0 0 0.0Russia 0 0.0 0 0.0 0 0.0 0 0.0Singapore 4 3.6 1 0.3 1 0.5 0 0.0Chinese Taipei 0 0.0 0 0.0 0 0.0 0 0.0Thailand 0 0.0 0 0.0 0 0.0 0 0.0UK 3 2.7 17 5.2 9 4.6 2 3.9USA 54 48.2 125 38.2 66 33.5 21 41.2Other 10 8.9 24 7.3 29 14.7 1 2.0Total 112 100.0 327 100.0 197 100.0 51 100.0


26

Table13 : Indian national scientists’ preferred location option by age

Age Group

Location >29 % 30-39 % 40-49 % 50+ %

Australia

6 10.2 48 18.4 73 24.7 47 23.4Canada 3 5.1 9 3.4 13 4.4 7 3.5China 0 0.0 3 1.1 0 0.0 3 1.5France 3 5.1 5 1.9 8 2.7 5 2.5Germany 7 11.9 28 10.7 18 6.1 10 5.0Hong Kong

0 0.0 0 0.0 1 0.3 0 0.0

India 2 3.4 4 1.5 1 0.3 0 0.0Japan 0 0.0 15 5.7 20 6.8 13 6.5Korea 0 0.0 2 0.8 3 1.0 5 2.5Malaysia 0 0.0 2 0.8 3 1.0 4 2.0Netherlands 0 0.0 2 0.8 1 0.3 1 0.5New Zealand

1 1.7 1 0.4 0 0.0 1 0.5

Pakistan 0 0.0 0 0.0 0 0.0 0 0.0Philippines

0 0.0 0 0.0 0 0.0 0 0.0

Russia 0 0.0 0 0.0 0 0.0 0 0.0Singapore 4 6.8 7 2.7 6 2.0 4 2.0Chinese Taipei

0 0.0 1 0.4 0 0.0 2 1.0

Thailand

0 0.0 0 0.0 1 0.3 0 0.0UK 3 5.1 17 6.5 13 4.4 15 7.5USA 26 44.1 99 37.9 108 36.5 71 35.3Other 4 6.8 18 6.9 27 9.1 13 6.5Total 59 100.0 261 100.0 296 100.0 201 100.0


27

Table 14: Business sector scientists, location of current work, networks and important collaboration

Location

Nationality of all

respondents

% currently working in the business sector

Nationality of all those working in

business sector (%)

Location of

research degree

%

Location of current

work

%

Location of main

networks*

%

Location of most


%

Australia

1047 11.6 (n=121)

16.1 96 14.9 126

17.0 117

8.9 51 7.5Canada 126 5.6 (n=7) 0.9 10 1.6 4 0.5 36 2.7 25 3.7China 1650 3.6 (n=60) 8.0 44 6.8 49 6.6 65 5.0 34 5.0Germany 197 9.6 (n=19) 2.5 12 1.9 11 1.5 59 4.5 30 4.4India 1680 5.8 (n=97) 12.9 73 11.3 84 11.3 63 4.8 33 4.9Japan 1331 12.1 (n=162)

21.6 140

21.7 171

23.0 127

9.7 57 8.4

Korea 771 8.6 (n=66) 8.8 44 6.8 67 9.0 49 3.7 19 2.8New Zealand 315 12.7 (n=40)

5.3 27 4.2 49 6.6 32 2.4 8 1.2

Singapore 115 10.4 (n=12) 1.6 11 1.7 30

4.0 31 2.4 15 2.2UK 247 6.9 (n=17)

2.3 49 7.6 8 1.1 111 8.5 52 7.6

USA 530 7.2 (n=38) 5.1 64 9.9 57 7.7 396 30.2 241 35.4Other 1019 10.9 (n=111) 14.8 74 11.5 86 11.6 224 17.1 115 16.9Total 10302 7.3 (n=750) 100.0 644 100.0 742 100.0 1310 100.0 680 100.0

Source: Asian Scientists Survey 2005. * Totals = sum of two choices.

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Table 15: Scientists working in business by selected location of current work and years of work in business

Location of current work

Never worked

in business

%

1-5 years

%

5-10 years

%

11-20 years

%

20 + years

%

Total worked

in business

%

Australia 735 10.4 239 12.4 67 15.0 43 13.8 16 11.3 365 12.9Canada 85 1.2 26 1.4 4 0.9 0 0.0 2 1.4 32 1.1China 1033 14.7 246 12.8 58 13.0 15 4.8 7 5.0 326 11.6France 92 1.3 15 0.8 2 0.4 4 1.3 0 0.0 21 0.7Germany 124 1.8 32 1.7 2 0.4 5 1.6 3 2.1 42 1.5Hong Kong 78 1.1 30 1.6 3 0.7 0 0.0 0 0.0 33 1.2India 1200 17.1 195 10.1 27 6.0 24 7.7 9 6.4 255 9.0Japan 961 13.7 179 9.3 72 16.1 89 28.6 68 48.2 408 14.5Korea 434 6.2 194 10.1 62 13.9 51 16.4 14 9.9 321 11.4New Zealand 235 3.3 87 4.5 24 5.4 15 4.8 3 2.1 129 4.6Singapore 156 2.2 95 4.9 22 4.9 9 2.9 0 0.0 126 4.5UK 154 2.2 43 2.2 14 3.1 5 1.6 2 1.4 64 2.3USA 487 6.9 188 9.8 27 6.0 20 6.4 10 7.1 245 8.7Other 1263 17.9 354 18.4 63 14.1 31 10.0 7 5.0 455 16.1Total 7037 100.0 1923 100.0 447 100.0 311 100.0 141 100.0 2822 100.0

Source: Asian Scientists Survey 2005.

References: Arocena R. and J. Sutz (2006) ‘Brain Drain and Innovation Systems in the South’, International Journal of Muoticultural Societies, Vol. 8 (1): 43-60. Bohm, A, D. Davis, D., Meares, and D. Pearce (2003) Global Student Mobility, IDP, Sydney. Dente, Karen (2007) ‘Scientists on the Move’ in Cell (129) April 6, 2007 pp 15-17. Etzkowitz, Henry and Loet Leydesdorff (1997) Universities and the Global Knowledge Economy: a triple helix of university-industry-government relations, Pinter: London. Giridhardaras, Anand ( 2007) India’s edge goes beyond outsourcing ‘ New York Times, April 4th . 2007. Harvie, Charles and Tim Turpin (1997) ‘China’s Market Rforms and Its New Forms of Scientific and Business Alliance’, in C. A. Tisdell and J. C. H. Chai (eds) China’s Economic Growth and Transition: Macroeconomic, Environmental and Social/Regional Dimensions, New York: Nova Science Publishers. Hill Stephen C. and Tim Turpin, ‘Cultures in Collision: The Emergence of a New Localism in Academic Research’, Chapter 7 in Marilyn Strathern (ed.), The Uses of Knowledge: Global and Local Relations. The Reshaping of Anthropology, Volume 1 - Shifting Contexts, Routledge, London, 1995. Johnston J., A. Rapoport and M. Regets (2000) ‘US Graduate Education’ in Graduate Education Reform in Europe, Asia and the Americas and International Mobility of Scientists and Engineers, National Science Foundation, Washington. Kapur, Devesh and John McHale (2005) ‘Give us your Best and Brightest: The Global Hunt for Talent and its Impact on the Developing World’, Centre for Global Development, Washington DC. Krishna, V.V. (2007) Dynamics in the sectoral system of innovation: Indian experience in software, biotechnology and pharmaceuticals’ in Tim Turpin and V.V. Krishna (eds) Policy and the Diffusion of Knowledge: Understanding the Dynamics of Innovation Systems in the Asia Pacific, Edward Elgar: Cheltenham ( forthcoming) Mahroum, Sami and Paul De Guchteneire (2006) Transnational Knowledge Through Diaspora Networks (editorial) International Journal of Multicultural Societies, Vol. 8 (1): 1-3. Meyer, John-Baptiste (2001) Network approaches versus brain drain lessons from the diaspora’. International Migration 39 (5) Special Issue 1, 99-110.. Marceau, Jane and Hugh Preston (1997) ‘Nurturing national talent: the Australian Research Council’s Fellowship Scheme’ Prometheus 15(1): 41-54

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Meyer, John-Baptiste and Jean-Paul Wattiaux (2006) ‘Diaspora Knowledge Networks: Vanishing Doubts and Increasing Evidence, International Journal of Multicultural Societies, Vol. 8 (1), 4-24. Mullan Fitzhugh (2005) ‘The metrics of the physician Brain Drain in The New England Journal of Medicine, 353 (17) 1810-1818. OECD, Cities and Regions in the New Learning Economy, OECD, Paris 2001 Stein, Janice Gross, Richard Stren, Joy Fitzgibbon and Melissa MacLean (2001) Networks of Knowledge: collaborative innovation in international learning, University of Toronto Press: Toronto. TIAC (2002) The Organisation of Knowledge: Optimising the Role of Universities in a Western Australian‘Knowledge Hub, Western Australian Technology and Industry Advisory Council: Perth Turpin, Tim and Sam Garrett-Jones (1996) ‘Innovation Networks in Australia and China in Henry Etzkowitz and Loet Leydesdorff (eds. ) Universities and the Global Knowledge Economy: a triple helix of university-industry-government relations, Pinter, London. Turpin, T. (2000), Science and technology Policies in Asia-Pacific Economies: implications for regional knowledge systems and social transformation, CAPSTRANS-CEDA Policy paper Series No. 3, CEDA Information paper No. 70, Committee for Economic Development of Australia, Sydney. US House of Representatives (1977) Science, Technology, and American Diplomacy: an extended study of the interaction of science and technology with United States foreign policy Volume II, US Government Printing Office, Washington. Zhang, Jing (2007) ‘The dynamics of China’s national innovation system: resources, capabilities and linkages’ in Tim Turpin and V.V. Krishna (eds) Policy and the Diffusion of Knowledge: Understanding the Dynamics of Innovation Systems in the Asia Pacific, Edward Elgar: Cheltenham ( forthcoming)

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Appendix 1 Methodological note on the Scientists Survey In 2004, the SCI included a separate field for email addresses of authors in its online database. The researchers downloaded the author, institutional address and email address fields of all papers with at least author from the 22 countries shown in Table A in Appendix 1 to this paper. This information was collated according to the global location of the lead author. Following this procedure a process of sorting was carried out to remove duplicates and compile a final list (n≅110,000). Information describing the researchers, the funding of the research and contacts for enquiries and for ethics matters were provided on an introductory page, along with a personalised id and password for logging into the survey. This page was provided in Chinese, English and Japanese. Although the fact that the survey itself was in English was explained in the invitation email, a significant number (n≅2,800) of those who accessed the Chinese or Japanese information page prior to accessing their survey dropped out prior to commencing the survey. This was likely due both to language issues and to those who were curious about the survey content accessing the questionnaire without intending to participate. This is supported by the fact that virtually all those who started the survey completed it in full.

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