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Record W4415779364 · doi:10.1111/deve.70004

The Four Talent Giants: National Strategies for Human Resource Development Across Japan, Australia, China, and India. By Gi‐WookShin, Stanford, <scp>CA:</scp> Stanford University Press, 2025. xv + 324 pp. <scp>US</scp> $140 HC. <scp>ISBN:</scp> 978‐1‐50‐364266‐9

2025· article· en· W4415779364 on OpenAlexaboutno aff
Anthony P. D’Costa

Bibliographic record

VenueThe Developing Economies · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsHuman resourcesSalientPortfolioTalent developmentTalent managementField (mathematics)ProductivityNarrative

Abstract

fetched live from OpenAlex

Gi-Wook Shin has written an excellent book on talent development strategies. Using four countries—Japan, Australia, China, and India—the book compares talent strategies dynamically. The book has eight chapters, beginning with a brief justification for the choice of the four countries in the region, followed by an analytical framework in Chapter 2 based on “talent portfolio theory” (TPT). Chapters 3–6 cover the four countries in great detail, capturing the salient dynamics of the TPT operating over time in each of these countries. Chapter 7 assesses the TPT framework, whereas the final chapter draws some lessons and policy implications of talent portfolios and their strategic management. Shin's book is noteworthy for three key reasons: First, he has developed a novel framework to analyze the development and the international movement of talent and their mobilization by governments for national economic and technological development. Second, he covers an important region of the world that has significant players in talent portfolios and offers wide-ranging experiences for talent strategy. And third, it is a timely publication when anti-immigrant sentiments are running high. He has skillfully marshaled a wealth of data, including field interviews in these countries, to produce a coherent narrative of global talent. Broadly equated to “human resources” (p. 2), talent has been defined as tertiary educated, skilled workers (p. 1), mostly technical professionals or science, technology, engineering, and mathematics (STEM) students (p. 7). This talent is an important contributor to the ecosystem of business, company startups, economic development, higher education, research and development, and innovation at both the national and global levels. His TPT framework (p. 21–28) has allowed him to carve out a niche in a crowded international migration literature and offer policy directions for national talent strategies. The TPT framework, borrowed from finance theory, suggests that to benefit from the returns to human capital, a country should have a portfolio of talent that integrates the national and international stocks and flows of “brain power.” There are four distinct yet overlapping dimensions of this portfolio, which Shin calls the four Bs: brain train, brain gain, brain circulation, and brain linkage (p. 28). The First B refers to the national education system (brain train), especially tertiary, technical education. Each of the four countries exhibits unique experiences, but they also share their success in establishing a talent “infrastructure” that has served these countries well at different time periods for their economic development. The Second B, brain gain, is the process by which talent is secured. A country could attract foreign talent through an expanding economy and commercial opportunities, and incentivize the return of nationals (brain gain) who have emigrated as students or working professionals (initial brain drain). I interpret brain gain not as a one-time gain of foreign talent by countries but as a process by which talent also moves seamlessly between two places. For example, Australia, through international recruitment of talent by business enterprises, universities, and governments (by easing visa regulations for employment), could attract Australians and non-Australians from overseas permanently or temporarily (brain gain). The temporary flows lead into or overlap with the Third B—namely, brain circulation. This overlap has been found to be very strong for the US where foreign (say Indian) talent resides permanently or visits India temporarily to conduct professional business for the US market (D'Costa 2008, 72). The ability of talent to circulate between sending and receiving countries is made possible by an overseas talent diaspora that is mostly permanent but has members that freely move for new commercial ventures, knowledge sharing, offshoring activities, and so on. This diaspora (stock) that grows over time with inflows of foreign talent allows for circulation (temporary and in some cases permanent outflows) on the assumption that sending countries are now experiencing economic growth and diversification with technological change. This dynamic of circulation leads to the Fourth B—namely, brain linkages. The diaspora links business enterprises in both receiving and sending countries and facilitates tapping into social capital, professional networks, and epistemic communities for securing and sharing commercial, technological, and policy information. China and India have utilized these linkages for national development. India's highly successful export-oriented software sector can be partly attributed to the governance structure resulting from bridging by the US-based Indian professional talent diaspora (D'Costa 2025a). Managing and coordinating the 4Bs is tricky. China and India are sending countries but both have experienced return talent. Just like Australia, they have gained some of the talent back via their diasporas. Australia's talent portfolio has changed toward brain gain, some circulation, and linkages. However, the draconian pandemic policy in 2020 of evicting foreign students and the subsequent reduction in foreign student visas for housing-related concerns means that Australia's talent portfolio will need to be readjusted. Japan is an outlier. It has largely a home-trained talent, including many Nobel laureates in the sciences, with very limited international mobility—outward or inward. There are good reasons for this (see Chapter 3). I attribute this limited engagement with the world economy to “institutional stickiness,” which results from limited English-language competence, particular Japanese ways of conducting business, the importance of Japanese social protocols, and risk-averse behavior to interact with the unfamiliar non-Japanese institutions (D'Costa 2016, Chapter 7). Lacking a strong talent diaspora, brain gain, and international linkages within limits are the best options for Japan to address its slow economic growth, aging population, and labor shortages. The second attractive attribute of Shin's book is the choice of countries/regions. China and India have had high rates of economic growth since the 1990s. They have contributed to the reduction of global poverty by lifting up hundreds of millions of impoverished people and are projected to be part of the ongoing structural shift of the world economy, away from the US and Europe. Although they differ on most socioeconomic and geopolitical dimensions, Shin, using his TPT framework, shows that they share the successful creation of a talent infrastructure that “trains brains” at home. With globalization this initial building block of a talent portfolio has morphed into an overseas brain bank (diaspora) from which they have gained circulating talent and forged transnational linkages. The choice of Japan and less-studied Australia adds nuances to the country mix. Japan like South Korea is ethnically homogeneous. Both in their varying ways industrialized rapidly since World War II, and both developed an effective system of universal education as well as a tertiary education system for their industrialization and economic development aspirations. More Korean students went abroad than Japanese. Although immigration-reluctant Japan has been studied extensively due to demographic shifts and labor shortages, Australia has drawn less attention because it has already established itself as an immigrant-friendly country. This could be due to its small size and its geographic remoteness. Australia has more in common with the Anglophone countries such as the US and UK and has a long legacy of “white” immigration. But as Shin persuasively demonstrates, Australia has managed its talent portfolio by moving away from the “white-only Australia” policy to embracing multiculturalism (p. 76–82), especially from Asia to diversify its talent and address its economic and human resource needs. By not enforcing an assimilationist model, Australia offers a successful example of how to adjust its talent portfolio approach. The third noteworthy reason for Shin's work is the timeliness of its publication. While Shin's work recognizes the importance of immigration policies, it did not anticipate the recent aggressive anti-immigrant swing in the US with the America First policy. As long-standing patterns, composition, and direction of talent mobility are expected to be disrupted, the TPT framework will need reworking since the US is a major host for foreign talent. It will be no longer about rebalancing the talent portfolio alone but also about which receiving countries will enthusiastically accommodate and economically interact with foreign talent. Aging societies such as Japan with shortages of skilled human resources must by necessity readjust their brain train and brain gain mechanisms. But these strategies could be derailed should anti-foreigner views become popular, undermining an already difficult task of attracting foreign talent despite its very successful “Cool Japan” campaign. Immigration restrictions imply that India's massive brain train infrastructure must be rebalanced in favor of the domestic economy. New technologies such as artificial intelligence and the recent hike of the US H-1B visa application fee to US$100,000 will add further stress for India's ambitious young job seekers (D'Costa 2026). Indian professionals may have to be reoriented toward the local economy and non-US markets such as Canada, Australia, Singapore, Japan, and selectively Europe. The signing of various economic partnership agreements, especially with Japan, may offer India some additional options. Notwithstanding the global competition for talent, rebalancing and diversifying talent portfolios in a changing world will be challenging. Can governments have the foresight and the political capacity to begin the rebalancing process now to find a new equilibrium of the 4Bs in the future? For future research, Shin's TPT framework could be heuristically useful by incorporating inequality in the analysis. As the Indian case illustrates, educational inequality leads to differential opportunities and international mobility for the few (D'Costa 2025b), whereas the successful Indian diaspora with the highest education and income among all ethnic communities in the US adds to inequality in the host economy; it could also trigger anti-immigrant sentiments. Rebalancing inequality at home could be an extension of the TPT framework that could also avoid future geopolitical and political risks. Gi-Wook Shin's skillfully argued book will inspire students and scholars to rethink talent migration, education inequality, and the future of Asian economic development. The author declares no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.249
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
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