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Is China a Global Leader in Research and Development?

Research and Development (R&D) is the backbone of innovation. It supports the development of new products and services, which have the potential to touch all aspects of modern life in the ways that personal computers and smartphones have and that artificial intelligence and robotics are expected to in the near future. In a global community built on technology, how countries leverage their R&D efforts has a profound impact on their economic prosperity and the quality of life enjoyed by their citizens.

China has leaned on its manufacturing prowess for decades to support economic development, but it is increasingly seeking to contend with countries whose economies are deeply rooted in innovation-based growth. China has made considerable progress in establishing itself as a pioneer in emerging industries and its leaders are increasingly looking toward innovation as a driver of its economic growth.

R&D Spending Around the World

Decades of rapid economic growth have enabled Chinese leaders to dedicate more resources to R&D. According to the Organization for Economic Co-Operation and Development (OECD), China’s R&D spending accounted for just 0.72 percent of its GDP in 1991. At the time, China’s economy was the 10th largest in the world, just behind Canada, which contributed 1.53 percent of its GDP to R&D in the same year. Economic leaders during the early 1990s, such as the US and Japan, averaged higher R&D to GDP ratios, at 2.5 and 2.7 percent, respectively.

By 2015, China’s R&D expenditure had surged to 2.06 percent of its GDP. This shift was propelled in part by government measures. For instance, China’s 12th Five Year Plan (2010 – 2015) set an R&D spending target of 2.2 percent of GDP by 2015, a mark it narrowly missed by 0.14 percent. Beijing has since renewed its support for R&D through the 13th Five Year Plan (2015 – 2020) , which targeted spending 2.5 percent of GDP on R&D by 2020. China’s spending on R&D continues to grow, but likely fell short of  the 2.5 percent goal in 2020. According to the OECD, China’s R&D expenditure reached 2.14 percent of GDP in 2018, and Chinese government figures show R&D spending at 2.23 percent of GDP in 2019.

While China may narrowly miss these goals, China’s nominal spending on R&D is rapidly growing. China’s R&D expenditure witnessed a more than 35-fold increase from 1991 to 2018 – from $13.1 billion to $462.6 billion. In 2018, China spent as much on R&D as the next four countries – Japan, Germany, South Korea, and France – combined, and China’s spending accounted for nearly one-quarter of global R&D expenditure. 1 Chinese R&D spending still lagged that of the US by nearly $89 billion in 2018, but the gap between the two countries is rapidly narrowing.

Breaking Down the Sources of R&D Financing

The OECD delineates four sources of R&D financing: business, government, foreign funding from the rest of the world (ROW), and other national-level sources. In developed economies, business typically finances a substantial portion of R&D initiatives. The average amount of R&D financed by business in OECD countries was 62.5 percent in 2018. Japan, South Korea, and Taiwan all had ratios well over 75 percent. 2

This trend is mirrored in China, with its businesses financing 76.6 percent ($354.4 billion) of the country’s gross expenditure on R&D in 2018. However, this high concentration of business financing has not always been the case. In 1994, business contributed only 32.4 percent of China’s R&D spending. This uptick can partially be attributed to the growing number of Chinese enterprises. According to the World Bank, the number of domestic listed companies in China more than tripled from 1,086 in 2000 to 3,777 in 2019.

However, analyzing trends in business funding is muddled by the importance of state-owned enterprises (SOEs) in the Chinese economy. SOEs are subject to orders from “government officials functioning as representatives of ownership,” which in some cases makes the R&D initiatives financed by SOEs akin to government funding. SOEs also have preferential access to bank loans from China’s state-owned banks, which reduces the cost of borrowing and provides SOEs with stronger financial backing compared to private companies. Unlike their counterparts in the United States and Europe, which commonly rely on venture capital to finance R&D, private firms in China often fund their own innovation efforts, which further widens the financing gap.

Analyzing trends in business funding is muddled by the importance of state-owned enterprises (SOEs) in the Chinese economy.

In contrast to financing from business, direct funding from the government is on the decline. From 2000 to 2018, the percent of R&D financed by the government in China dropped from 33.4 percent to 20.2 percent. This places China on a level comparable to the United States (23 percent) and South Korea (20.5 percent), but significantly below that of Mexico (76.9 percent) and Russia (67 percent).

This trend, however, may soon shift as Beijing works to implement policies aimed at increasing government-led innovation. In 2015, Beijing launched “ Made in China 2025 ,” a plan to increase manufacturing capability and technological innovation within key industries. As part of this push, 901 government guidance funds were launched with the goal of raising $347 billion to help lessen the burden on Chinese firms of financing R&D. Lucrative tax breaks are also being provided to firms to further incentivize investment in R&D.

As a result of domestic restrictions that limit inbound investment flows from overseas, R&D paid for by ROW represented only a small fraction of China’s R&D financing in 2018 (0.36 percent). This rate is much less than that of the United States (7.3 percent), but is on par with other countries in East Asia, including South Korea (1.9 percent) and Japan (0.6 percent). Importantly, these figures do not capture the role of R&D centers operated by multinational corporations. For instance, data from China’s Ministry of Commerce show that as of October 2020 MNCs had established 477 R&D centers in Shanghai alone.

How China utilizes its R&D financing

It is also necessary to consider the users of R&D financing, as those conducting R&D are not always the same as those funding such endeavors. The OECD delineates four main users of R&D funds: government, business, higher education institutions, and private non-profits. The amount of R&D performed by each of these actors varies considerably by country. In the case of China, the share of R&D conducted by nonprofits is practically nonexistent. The other three users are analyzed below.

Over the last several decades, Beijing has worked to boost the role of business enterprises in driving innovation forward. This effort has seen the transfer of government research capacities to SOEs. For example, in 1999, over 11,000 government laboratories were transferred to SOEs as part of an effort to better connect manufacturers with innovation centers. Moves such as these have contributed to the marked growth in the amount of R&D pursued by Chinese firms. In 1991, a mere 39.8 percent of all R&D in China was performed by business enterprises. By 2018, that number had soared to 77.4 percent, which was greater than that of both the United States (72.6 percent) and the average for OECD economies (70.6 percent). 3

Similar to the issue of distinguishing the sources of R&D funding, SOEs complicate how Chinese firms utilize R&D. According to China’s National Bureau of Statistics , R&D spending by SOEs and companies with mixed ownership made up 67.6 percent of enterprise R&D expenditure in 2019. Private enterprises, meanwhile, only constituted 32.3 percent.

Nonetheless, private firms are playing an increasingly important role. Since 2011, the percentage of R&D performed by private companies increased by 16.6 percentage points. 4 In 2019, privately owned Chinese technology giant Huawei invested $19.3 billion in R&D. This accounted for about 6 percent of China’s national total and surpassed the total amount of R&D spending that took place in 25 of China’s 31 provinces and regions. This shift could prove promising for China. Some research has shown that when compared to SOEs, private companies dedicate higher portions of their revenue to R&D and often yield higher returns on investment.

China’s spending on R&D for spacecraft manufacturing skyrocketed from $22.6 million in 2000 to $386.6 million in 2016. Learn more about the importance of R&D to achieving China’s ambitions in space.

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Expenditures by the Chinese government stood at 15.2 percent of total R&D usage in 2018. This ratio is similar to that of advanced economies, such as the United States (10.4 percent) and Germany (13.5 percent), but significantly lower than that of Russia (32 percent) and Mexico (34.4 percent). In nominal terms, the Chinese government spent $70.2 billion in 2018, more than any other country in the world. 5 Government-driven expenditure has contributed to the development of highly visible technological advancements, particularly those made by the China National Space Administration. The Tiangong-2 space station and the “Micius” quantum satellite – the first of its kind – are just two such examples. More recently, China’s Chang’e 4 lander became the first spacecraft to land on the far side of the moon.

Institutions of higher education perform only a small portion of China’s R&D – about 7.4 percent of the total in 2018. This is considerably less than that of Japan (11.6  percent), Germany (17.6 percent), and Finland (25.2  percent). Several factors are at play when considering the role of academic institutions in China. The country’s restrictions on intellectual freedom, coupled with a focus on the graduate employment rate over scientific output, have impeded innovation within China’s universities.

President Xi Jinping specifically called on China to “strengthen basic research, and make major breakthroughs in pioneering basic research and groundbreaking . . . innovations” in his speech at the 19 th Party Congress.

China also lacks well-established linkages between businesses and universities, which significantly limits knowledge transfers. Although this relationship is difficult to quantify, Times Higher Education examined how universities collaborate with industry on research, and noted that in 2016 over “6 percent of US publications [were] joint efforts between the academy and industry, compared with just 2.7 percent in China.”

Additional insight can be gleaned by considering the industries targeted by R&D initiatives. Official government figures show that the manufacturing of electronics, including computers and communication equipment, attract the most funding from government, business, and academic institutions – totaling some $35.4 billion in 2019.

This focus on information and communication technology has helped pave the way for breakthroughs like the Sunway Taihu Light, the world’s fourth-fastest supercomputer in 2020. It has also led to commercial success in niche markets. Chinese drone manufacturer DJI, for instance, is reported to control up to 74 percent of the global drone market. Huawei has emerged as one the leading companies working on next generation mobile communications technology, including the roll-out of 5G networks, which are expected to be 50-100 times faster than 4G.

China is also a leader in surveillance technology, with Hangzhou Hikvision Digital Technology controlling over 20 percent of the global market share. Its newer products, such as the DeepinView Camera, are purportedly outfitted with facial recognition capabilities that can not only identify known individuals, but also estimate the age, ethnicity, and gender of unrecognized persons. Hikvision products have been exported to a number of countries, including the UK and the US , where they have reportedly been put to use by private enterprises and local governments . 6

China’s R&D priorities

Research and development can also be distinguished by its desired outputs into three areas: basic, applied, and experimental development research. Definitions for these areas are outlined in the table below.

Beijing has consistently poured the largest share of its R&D resources into experimental development, averaging roughly 80 percent from 2000 to 2019. According to an OECD report, this has contributed to a growing output from “ engineering-oriented domains ,” which has made it easier for manufacturers to quickly adapt products and services to the domestic market. China’s preference for experimental development research far outstrips that of other leading economies. Innovation powerhouses like the United States and Japan devoted just over 62 percent of R&D on experimental development research.

Conversely, China’s R&D spending on basic and applied research, which are critical to the development of new scientific ideas and cutting-edge technologies, proportionally lags that of other major powers. Basic research in China averaged around 5 percent of total R&D expenditure between 2000 to 2018, while the share of applied research dropped from 17 percent to 11.1 percent. Over the same period, the US poured 17.3 percent of its R&D funding into basic research and 20.4 percent into applied research. In nominal terms, China’s basic and applied expenditure was $77.1 billion in 2018, more than that of South Korea ($34.5 billion) and Japan ($54.7 billion), but less than half that of the US ($200.5 billion).

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China’s Research Evaluation Reform: What are the Consequences for Global Science?

• Published: 30 April 2022
• Volume 60 , pages 329–347, ( 2022 )

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• Fei Shu 1 , 2 ,
• Sichen Liu 1 &
• Vincent Larivière   ORCID: orcid.org/0000-0002-2733-0689 2 , 3  

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In the 1990s, China created a research evaluation system based on publications indexed in the Science Citation Index (SCI) and on the Journal Impact Factor. Such system helped the country become the largest contributor to the scientific literature and increased the position of Chinese universities in international rankings. Although the system had been criticized by many because of its adverse effects, the policy reform for research evaluation crawled until the breakout of the COVID-19 pandemic, which accidently accelerates the process of policy reform. This paper highlights the background and principles of this reform, provides evidence of its effects, and discusses the implications for global science.

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Introduction

In parallel with the exponential growth of its economy, China’s emergence in science and technology has had a far-reaching impact on global science. In 2017, China has surpassed the US and became the largest source country in terms of the number of scholarly papers (National Science Board 2018 ), and its R&D expenditures are almost on par with those of the US (543 vs. 582 billion USD in 2018) (UNESCO Institute for Statistics 2018 ). Such growth in international research output can be associated with the implementation of China’s national strategy of science and education, in which science, technology and education are given priority in the national development plan (National People’s Congress of the People’s Republic of China 2007 ). The key elements of the national strategy include the increasing investment in R&D and promotion of internationalisation of research (Marginson 2021 ). It is also partly attributed to the creation of a SCI-based research evaluation system, favoring publications indexed by the Science Citation Index (SCI). Since the 1990s, the number of such international publications as well as other related bibliometric indicators (e.g. Journal Impact Factors (JIF), Essential Science Indicators (ESI), etc.) have been overweighed in research evaluation, tenure assessment, funding application as well as performance salaries in China (Quan et al. 2017 ; Shu et al. 2020a ) to develop China’s leadership in global science.

In China, SCI-based indicators are applied to research evaluations at both individual and institutional levels. However, they have been criticized for their negative effects on academic integrity (Quan et al. 2017 ; Tang 2019 ) and national knowledge dissemination (Chu et al. 2015 ; Duan et al. 2015 ; W. Li et al. 2015 ; C.-e. Liu 2018 ; Yanyang Liu et al. 2003 ; X. Wang 2012 ; Jiping Zhang 2019 ; Zhu 2020 ; Zou and Zhang 2017 ) for several years. A policy reform against indicator-based research evaluation has also been called for a long time (L. Zhang and Sivertsen 2020 ). As early as 2011, Ministry of Education (MoE) issued a document regarding the change of research evaluation in social sciences and humanities (Ministry of Education of China 2011 ). The policy reform even gained the attention from China’s leaders; in 2016, China’s Chairman Xi ( 2016 ) asked Chinese scientists to “publish papers on homeland”. As a response in 2018, MoE, Ministry of Science and Technology of China (MoST), Ministry of Human Resource and Social Security (MoHRSS), Chinese Academy of Science (CAS), and Chinese Academy of Engineering (CAE) issued a joint document asking universities and research institutes not to abusively use indicators relative to papers, titles, ranks, degrees and awards (Ministry of Education of China 2018 ). However, significant changes were not observed in China’s research evaluation system, and SCI-based indicators have still been abundantly used.

Perhaps unexpectedly, a real change to the SCI-based evaluation system was triggered by the outbreak of the COVID-19 pandemic, when Chinese researchers prioritized publication of findings on the new coronavirus in international journals (Huang et al. 2020 ; Q. Li et al. 2020 ) rather than national journals, which would have helped disseminating them to those who were fighting the pandemic (Ministry of Science and Technology of China 2020a ). The publication of these two articles aroused public anger and was accused of delaying the control of the pandemic (An 2020 ; Du 2020 ; Qin 2020 ). In response to this (H. Li 2020 ; Yan Liu 2020 ), MoST and MoE issued two official documents in February 2020 that aim to reshape scholarly communication and research evaluation in China (Ministry of Education of China and Ministry of Science and Technology of China 2020a , b ; Ministry of Science and Technology of China 2020b ), which attempt to overcome the abusive use of SCI-based indicators on research evaluation (Quan et al. 2017 ; Shu et al. 2020a ) and build a new scientific research evaluation system.

As the largest contributor, China publishes almost one fourth of scientific literature and one fifth of international collaboration (ISTIC 2020 ). The possible impact of China’s research evaluation reform on global science has been of concern (Mallapaty 2020 ). In this study, we highlight the principles of policy reform as well as their background, and analyze the possible implications for global science.

Policy Reform

The two documents issued by MoE and MoST contain seven major measures, which can be divided into three aspects of scholarly communication and research evaluation as shown in Table 1 .

Farewell to the SCI

SCI-based indicators were introduced in the 1990s when the country initiated its ambious plan Footnote 1 to embrace the global science. Nanjing University was the first university to use SCI papers for research evaluation, and topped China’s university rankings afterwards. SCI-based indicators then spread across the country, as research administrators regarded them as a solution to increase China’s share of international publications (Qiu and Ji 2003 ). Many Chinese scholars also believed that SCI-based indicators were fairer than peer review, which was considered to be biased by personal relationship and seniority in China (Shi and Rao 2010 ).

In order to promote university research, three national programs (i.e., Project 211, Project 985, and Double First Class) have been initiated one by one since the 1990s. These programs provide substantial financial support to a small group of selected universities, and one key admission requirement is the number of international publications (Shu et al. 2020b ). To encourage scholars to publish internationally and improve their rankings, Chinese universities apply the SCI-based indicators that have, since then, been considered as the gold standard in China’s research evaluation. SCI papers became mandatory requirements for doctoral degrees, faculty hiring and promotion, funding applications, and university rankings. Publishing in a subset of SCI-indexed elite journals leads to major research funding, as well as additional rewards, such as promotion from assistant to full professor, appointment as Chair or Dean, and even to university president (Shu et al. 2020a ). Cash-per-publication policies have also been widespread, leading to additional revenues of up to 1 million CNY per paper (150,000USD) (Quan et al. 2017 ).

The strong pressures to publish in SCI journals may lead to the effect of goal displacement (Frey et al. 2013 ; Osterloh and Frey 2014 ) which the Chinese government became acutely aware of at the outbreak of the pandemic. The purpose of research for some Chinese institutions and scholars is not to advance knowledge, but rather to improve their rankings and indicators, even at the cost of research integrity (Tang 2019 ). Indeed, over the last two decaces, along with the growing number of international publications from China, cases of academic misconduct (plagiarism, academic dishonesty, ghostwritten papers, fake peer review, etc.) have also increased (Jia 2017 ; Hvistendahl 2013 ). The scale of adacemic misconduct cases evolved from individual cases to “paper mills” (Chawla 2020 ; Else and Van Noorden 2021 ). In this context, it is not surprising that the number of China’s retracted papers has been increasing in the past two decades, and China has the largest number of retracted papers, contributing to 24% of all retracted papers (490/2,061) in 2020, followed by the US (122) and Iran (79) as reported by Web of Science (Figure 1 ). Figure 1 also shows that the share of China’s retractions to all retractions across the world has been higher than the share of China’s publications to all publications worldwide since 2004.

Number and share of China’s publications and retractions indexed by the Web of Science (2000–2020)

Priority to National Journals

SCI-based evaluation policies have created incentives for Chinese scholars to publish their research in international journals rather than in national journals (Zou and Zhang 2017 ; C.-e. Liu 2018 ). In China, however, international journals are less accessible than national Chinese journals due to the paywalls and language (Schiermeier 2018 ). As a result, dissemination of findings to the international scientific community comes at the expense of the national Chinese community (Larivière et al. 2020 ), and this was clearly observed at the outbreak of the pandemic, when Chinese scholars disseminated their findings on human-to-human transmission of coronavirus internationally rather than nationally. Local health practitioners were not informed by their colleagues, but aware of such a crucial finding from the paper (Q. Li et al. 2020 ) published in the New England Journal of Medicine (Du 2020 ; Qin 2020 ; Wuhan Municipal Health Commission 2020 ).

Since the end of World War II, dissemination of science has been dominated by English, leading to a corresponding decrease for other languages (Larivière and Warren 2019 ). This was also observed for papers published in Chinese, as the number of national publications indexed by China Scientific and Technical Papers and Citation Database (CSTPCD) Footnote 2 started to decrease in 2010 (Figure 2 ). In some disciplines such as Condensed Matter Physics, Applied Mathematics, or Crystallography and Electrochemistry, Chinese scholars even give up publishing papers in local Chinese journals (Shu et al. 2019 ). Some Chinese scholars argue that publishing internationally prevents knowledge dissemination through national journals (Zou and Zhang 2017 ; C.-e. Liu 2018 ). Indeed, in 2019, Chinese researchers have published more papers internationally than they have nationally for the first time.

Number of national and international publications in China (1995-2019) (National Bureau of Statistics of China 1996 –2019)

This can also be observed at the ownership shares of international journals: while Chinese researchers contribute to about 25% of international literature, less than 2% of these international journals are owned by Chinese publishers (ISTIC 2020 ). Such imbalance has been noted by China’s leaders, with Chairman Xi requesting that scientists publish nationally (Xi 2016 ). As a response (Ministry of Science and Technology of China 2020a ), the reform gives emphasis to national scholarly communication by requiring researchers to publish at least one third of their papers in national journals.

Restrictions to Open Access Publishing

Despite limited access to subscription journals (Schiermeier 2018 ), open access (OA) publishing remains controversial in China. Papers published in OA journals are often valued less as those published in subscription journals, and are even excluded from research evaluations. This can be attributed to the perception that OA journals are predatory and perform very little peer review (Li 2006 ; Xu et al. 2018 ; Liu and Huang 2007 ).

Despite this perception, the percentage of Chinese papers published in Gold OA journals has been increasing from 4.9% in 2008 to 30.0% in 2020 in the dimensions.ai database. This percentage is higher than that of the United States (20.5%) and the United Kingdom (21.5%), on a par with that of Japan (30.4%), but remains lower than that of Brazil (55.3%), which publishes mainly in the non-APC journals indexed by its national platform, SciELO. China is, however, among the countries with the lower share of hybrid OA (around 2%), which suggests that paying APCs in subscription journals is not rewarded. The main reason for Chinese scholars to choose OA journals is not research impact or global reach, but whether the journal is indexed by WoS (Xu et al. 2020 ). Commercial publishers have taken advantage of such focus on WoS, and created low quality journals with nominal or no peer review and quick acceptance (Xia et al. 2017 ). For example, IvySpring International Publisher, an Australian OA publisher, has four journals indexed by WoS; almost two thirds of papers published in 2018 were contributed by Chinese authors.

As most OA journals are published outside China, it is believed that a large amount of research funding is lost through APCs (Liu 2018 ). A list of APCs (in 2018) of all OA journals indexed by Web of Science was collected and built in this study. The number of APC paid, and APC revenue generated were calculated on the basis of first affiliated institution in the byline and regular APC rate. Although the APCs are normally billed to the corresponding authors, Chinese scholars only can receive the reimbursement of APC payments when their affiliated institutions are ranked first in the byline. In 2018, the 89,165 OA papers (Gold and Hybrid OA indexed by WoS) published by Chinese institutions as the first affiliated institution incurred around 165 million USD APCs as calculated. Springer Nature generated more than 33 million USD revenue from APCs in China, followed by MDPI (29 million USD), Frontiers (15 million USD) and Hindawi (15 million USD), which focus on the OA publishing (Figure 3 ).

Publishers’ share of China’s OA publishing (2018)

Since the 1990s, the number of international papers indexed by SCI has been applied to research evaluation in China to increase the international visibility of China’s research (Gong and Qu 2010 ; Quan et al. 2017 ). In addition to the research evaluation policies, monetary incentives and performance bonus are also used to encourage Chinese scholars to publish SCI papers (Peng 2011 ; Quan et al. 2017 ; Shu et al. 2020a ), eventually forming a SCI-based research evaluation system in which SCI-based indicators become the most important criterion in tenure assessment, funding application, university ranking and other research assessment activities (Quan et al. 2017 ; Zhao and Ma 2019 ; Shu et al. 2020a ). As a result, Chinese scholars, especially in Natural Sciences, are required to publish SCI papers for their tenure and promotion as university and research institutes rely on such SCI-based indicators for their ranking and funding records (Shu et al. 2020a ; Wang and Li 2015 ).

Although the SCI-based research evaluation system partly contributes to China’s rise in global science, the abusive use of SCI-based indicators in research evaluation has been criticized for a long time since international publications only do not adequately represent China’s research activities (Guan and He 2005 ; Shu et al. 2019 ; Jin and Rousseau 2004 ; Jin et al. 2002 ; Liang and Wu 2001 ; Moed 2002 ; Zhou and Leydesdorff 2007 ). Some scholars even point out that the increase of international publications may come at the expense of dissemination of research to local Chinese communities (Zou and Zhang 2017 ; Xu 2020 ; Liu 2018 ), considering many international publications are less accessible in China because of the paywalls and language barriers. Indeed, the number of local national publications in China has been declining in the past decade as Chinese scholars have published more international publications than local national publications since 2019 (ISTIC 2021 ).

In addition, the SCI-based research evaluation brings a negative goal displacement effect (Frey et al. 2013 ; Osterloh and Frey 2014 ) as the purpose of publishing for some Chinese scholars is not to advance and disseminate knowledge but to complete the research evaluation and receive monetary awards (Quan et al. 2017 ), forming a different reward system of science (Merton 1973 , 1957 ). Furthermore, with the growth of the number of international publications, the number of academic misconducts such as plagiarism, paper mills, fake peer review and so on have also been increasing in China, which seriously affects China’s academic reputation (Hu et al. 2019 ; Tang 2019 ).

Although a science policy reform regarding the SCI-based research evaluation has been called for several years, the SCI-based indicators are still favored by research administration. China’s research evaluation policy is trapped in a dilemma of antinomy (Zhou and Zhang 2017 )—some official documents against the use of SCI-based indicators were issued while some research programs using SCI-based indicators were still promoted (Zhao and Ma 2019 ).

Implications

The new policy by MoST and MoE aims to create a rebalance contributing to global science and supporting national interests. This will not only affect Chinese scholars but the international research community, as China is the largest source contributor to scientific literature. However, no immediate changes to Chinese researchers’ dissemination practices have been noticed over the last eighteen months as Chinese scholars published 590,649 papers indexed by WoS in 2020, reaching its historical high.

What are the Alternative Research Evaluation Criteria?

Although both MoST and MoE intend to say farewell to SCI-based evaluation, they did not reveal how to achieve this beyond general principles. The two ministries delegated this responsibility to provincial departments, which have to design new evaluation systems based on those principles. Considering the top-down administration model in China that officials get used to implementing the policies and executing the orders from the top, it is hard to imagine that the provincial departments could formulate any detailed policies regarding the new evaluation system in a short term. In the following 12 months, all 31 provincial divisions (including 22 provinces, 4 municipalities and 5 autonomous regions) answered the call from MoST and MoE, but in different ways. According to the documents collected in this study, 16 Provincial Departments of Science and Technology issued their corresponding documents while the rest only forwarded the two official documents of MoST and MoE. Furthermore, these 16 new provincial documents do not reveal any alternatives to the SCI, and simply quote the statements made by MoST and MoE.

Indeed, Chinese scholars pointed out the impossibility of finding an alternative in a short term (L. Yu 2020 ), considering the SCI-based research evaluation system has deep roots in China. MoST and MoE emphasize that the future of research evaluation lies in peer review. However, peer review in China is also very controversial, given the strong influence of guanxi (personal relationships) (Shi and Rao 2010 ). Along those lines, given its time and resource consuming aspect, it is difficult to complete a large amount of research evaluations through peer review only (Bornmann 2011 ).

The Voice of the Silent Majority

MoST is responsible for coordinating science and technology activities, whereas MoE administrates universities, which are responsible for most research conducted in the country (83.5% of monographs and 75.5% of journal articles) (National Bureau of Statistics of China 2019 ). National research institutes and funding agencies are affiliated to MoST while MoE operates national research programs such as Project 211, Project 985, and Double First-Class, which provide substantial financial support to a small group of selected universities. Thus, in such dual administration, the policy reform needs to be coordinated by both MoST and MoE.

However, that does not seem to be the case. For instance, the MoE does not seem to push the policy as much as the MoST. On the contrary, MoE keeps promoting the Double First-Class program, which uses WoS/ESI indicators as a key criterion for admission (Chen and Qiu 2019 ; G. Zhao and Ma 2019 ). Recently, MoE issued two documents regarding research evaluation in social sciences and humanities (Ministry of Education of China 2020 ) and university tenure assessment (Ministry of Human Resources and Social Security and Ministry of Education of China 2021 ). Those did not contain anything new, and simply restated the measures announced in February 2020. Indeed, some universities have already figured out how to deal with the prohibition—they replaced direct cash-per-publication by a score assigned to each individual SCI paper… a score that could be converted into salary at the end of the year (Quan et al. 2017 ). Since the documents issued by MoST and MoE only prohibit direct cash awards for individual publications, universities or research institutes can use indirect monetary awards instead. Thus, we are far from a revolutionary change in the research evaluation practices of Chinese universities.

Global Leadership

In the 1990s, China launched an ambitious plan (Central Committee of the Communist Party of China and State Council of China 1995 ) for global leadership in science. One may consider the plan to be successful, as the country is now the largest contributor to research papers worldwide. China intends to expand its leadership to academic publishing. The purpose of the new China Science and Technology Journal Excellence Action Plan (CSTJEAP) is not only to encourage Chinese scientists to publish papers in national journals, but also to make their national journals more global.

CSTJEAP will not prevent Chinese researchers from publishing in top international journals. However, it aims to restrict publication in those with less impact, especially Gold and Hybrid OA journals with APCs. For example, we may no longer see many Chinese papers in the Czech Journal of Genetics and Plant Breeding (an OA journal indexed by WoS), in which more than half of papers published in 2018 came from Chinese authors. Indeed, those 89,165 China’s OA papers (either Gold or Hybrid OA) were published in 2,638 journals indexed by WoS in 2018; as Table 2 shows, only 335 and 913 journals were respectively included in Quartile 1 of Chinese Academy of Science Journal Partition (CASJP) and Journal Citation Report (JCR) that are used to define the high-quality journals in China. It means that the vast majority of OA papers (between 58,769 and 83,961) are ineligible to be high quality publications (HQPs) for the reimbursement of APCs under the new policy. This may also lead to a decrease of 14.1–20.3% in OA publications worldwide.

Uncertain Future

More than 30 years ago, China opened its doors to the West and embraced the international society; since then, China’s economy has experienced a tremendous growth and has become the fastest growing economy in the world. As a rising power, China created tensions challenging the existing international order (Kim and Gates 2015 ; Punnoose and Vinodan 2019 ), controlled and dominated by Western countries. Under the leadership of Chairman Xi, China has adopted an increasingly ambitious strategy pursuing global leadership not only in politics and economics but also in science, which will influence China’s science policies in the future.

In Chinese perspectives, although China is the largest contributor to global science, its power of discourse (Foucault 1971 ) in academia is still limited as the international scholarly communication system is controlled by Western countries in terms of academic journals, professional association, and academic norms (Zhang 2012 ; Liang 2014 ; Wang 2011 ). It is believed that the Western-centrism (Hobson 2012 ) exists in global science (especially in social sciences) as research topics, paradigms, methodologies, and evaluation are dominated by Western countries through their control over international scholarly communication venues as well as their peer-review process (Yu and Qiu 2021 ; Zhang 2016 ; Wang 2011 ). Some scholars even argue that Western countries use scholarly communication to disseminate Western culture, value and ideology for the purpose of politics (Jiang 2018 ; Xie 2014 ; Zhao 2020 ).

With the increase of the global share of scientific literature, Chinese scholars attempt to convert their roles in global science, from participants to leaders; sharing and gaining the power of academic discourse is considered as the prerequisite (Zhang 2016 ; Xu 2020 ; Zhang 2012 ; Shen 2016 ; Hu 2013 ). One example is that IEEE had to drop its ban on using Huawei scientists as reviewers under the pressure amid boycott from China’s academia (Mervis 2019 ; IEEE 2019 ). Indeed, Academic Discourse Power has become a popular research and news topic in China in the past decade (Figure 4 ). Some proposals suggest building a new global scholarly communication system including China-owned English journals, self-reliant citation index, and a database indexing English abstracts of Chinese papers (Wu and Tong 2017 ; Zhou 2012 ; Zhang and Zhen 2017 ; Fang 2020 ; Lu 2018 ), which was adopted in the two official documents by MoST and MoE.

Number of Chinese Publications Regarding Academic Discourse Power from CNKI (2011–2020)

Recently, China released its 14th five-year social and economic development plan, which identifies scholarly communication as an approach disseminating China’s culture, beliefs and values, and emphasises more self-reliance rather than international collaboration in science and technology development (Government of People's Republic of China 2021 ). The plan mentions the proposal building a national scholarly communication system in response to Chairman Xi’s call to “publish papers on homeland” (Xi 2016 ). Although these long term goals will not come into effect immediately, even be replaced by other strategies in the next five-year plan, they create uncertainty for the future of global science considering the possible conflict between the rising power and traditional powers in science.

China’s future involvement in international collaboration is another uncertain consequence to global science. In the past decades, China has been promoting international collaborations through various mobility funding initiatives (Quan et al. 2019 ). The China Scholarship Council, administrated by MoE, annually funds almost 20,000 Chinese scholars for a 6–12-month international stay as visiting scholars (Wu 2017 ), while National Natural Science Foundation of China (NSFC), administrated by MoST, offers funding for foreign researchers to encourage international collaboration (Yuan et al. 2018 ). As Figure 5 shows, the number of international collaboration papers (indexed by WoS) in China has been increasing in the past two decades; however, the ratio of international collaboration papers to all international papers decreased in 2019 and 2020. We are not sure whether the decrease is attributed to the policy reform or due to the pandemic when international mobility was strictly limited (Lee and Haupt 2021 ).

International Collaboration Publications in China (2000–2020)

Two years into the pandemic, the documents issued by MoST and MoE appear more like a communication exercise to appease public anger than the start of a strong policy reform. With the top-down administration model based on the centralized Chinese government, the SCI-based evaluation system was promoted from the top (e.g., MoST, MoE, etc.) and followed by the bottom (e.g., universities, research institutes, etc.). Thus, the MoST and MoE should not shirk their responsibilities and create ambiguous and non-transparent policies (Qi 2017 ; Shu et al. 2020b ) when promoting the policy reform. For example, MoE should reconstruct the Double First Class program that is highly based on ESI indicators (Chen and Qiu 2019 ; Zhao and Ma 2019 ); MSFC, administrated by MoST, should give national publications the same weight as international publications when evaluating funding applications. Chinese universities and research institutes need to receive a clear and consistent signal that the policy reform is not only an armchair strategist.

Indeed, many negative effects don’t originate from the nature of the SCI-based indicators but come from the administrative purpose of research evaluation, which contributed many “beautiful” numbers in terms of the number of publications and rankings rather than real advancement of knowledge. China’s scientific administration should be aware that a successful research evaluation system should be completely merit-based; and the policy reform should start from the top.

In July 2021, the General Office of the State Council of China ( 2021 ) issued another new document providing the principles for designing a new research evaluation system in science and technology, which duplicates most contents of previous documents. Unfortunately, a detailed proposal regarding the new research evaluation system is still missing.

Data availability

Not applicable.

Code availability

Although the first Chinese scientific development plan (Project 863) started in 1986, the milestone of China’s scientific development is Xiaoping Deng’s (China’s former leader) declaration “Science and technology are primary productive forces” in 1988, which has guided China’s scientific development in several decades. In 1993, China legislated the first version of the Law of the People's Republic of China on Science and Technology Progress; in 1995, China initiated the national strategy of “invigorating China through the development of science and education”. As a result, Project 211 and Project 985 were launched in 1995 and 1998 respectively.

CSTPCD, developed by the Institute of Scientific and Technical Information of China (ISTIC) in 1987, indexes more than 2,000 national scientific journals for the purpose of research evaluation of China’s scientists and engineers. The number of papers indexed by CSTPCD and number of Chinese papers indexed by SCI, representing national and international publications respectively, are reported in annual Statistical Data of China’s S&T Papers , and included in the China Statistical Yearbook .

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Shu, F., Liu, S. & Larivière, V. China’s Research Evaluation Reform: What are the Consequences for Global Science?. Minerva 60 , 329–347 (2022). https://doi.org/10.1007/s11024-022-09468-7

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New focus on basic research in china's advancement in science and technology.

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Mu-ming Poo, New focus on basic research in China's advancement in science and technology, National Science Review , Volume 9, Issue 2, February 2022, nwac014, https://doi.org/10.1093/nsr/nwac014

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On 1 January 2022, a new version of the Law on China's Science and Technology (S&T) Advancement (‘科学技术进步法’) went into effect. This is the second revision of the Law, which was first implemented on 1 October 1993. The current revision is marked by extensive changes and additions that reflect China's rapid S&T development over recent decades and many new challenges facing China today. Many articles in the Law are elaborated with detailed descriptions of new strategies and plans for S&T advancements that are commensurate with China's economic prowess. Promotion of basic research stands out as one of the main goals for the future.

In the opening chapter on general provisions of the Law, four directions of future S&T advancement are laid out: exploring the world's scientific frontiers, meeting economic challenges, addressing major domestic needs and promoting people's health. These aim at economic and social progress together with sustainable development. Four pillars of the nation's strategic S&T force are defined: national laboratories, national research and development (R&D) institutions, top research universities and leading S&T enterprises. These pillars will provide leadership and support for innovation in the key areas and targeted directions of S&T. The Law sets the agenda for achieving a highly efficient, synergistic and open national innovation system, perfecting a healthy socialist market economy system that fully realizes market-directed and government-assisted S&T resource allocation, optimizing the sustainable flow of innovation elements and elevating systemic capability and efficiency with regard to achieving progress in targeted areas.

The government's support for basic research is highlighted in the second chapter of the Law. The principle is to combine the serving of the country's needs with free S&T exploration, via planning and the stable support of three types of research—major areas of basic science, frontier technology and public welfare technology. The Law stipulates a gradual increase in the government's contribution to overall S&T funding (with an increment higher than that of regular expenditure), a gradual increase in the percentage of GDP devoted to R&D, and a gradual elevation of the proportion of basic research funding within the total R&D expenditure. It also calls for industry's investment in basic research and society's contributions via gifts, donations and private foundation funding, with the government's financial support and tax benefits promised.

Complementing the support for basic research, the Law calls for a reform in the education system that links theoretical with practical education, and cultivates innovative capability, critical thinking and the spirit of pursuing truth based on facts. It also emphasizes the role of higher education institutions in scientific research, technological development and social services, as well as in cultivating high-level specialists with social responsibility, an innovative spirit and practical capabilities. New policies for cultivating S&T talents are detailed in the Law, and include elevating their social status, ensuring they have the appropriate environment for innovative activity (with appropriate evaluation criteria and incentives) and protecting their intellectual rights.

The foundation of basic research is ‘free exploration’, a recurring theme in the Law and many recent governmental pronouncements. This requires substantial reform in the S&T management system and institutional evaluation mechanism, in order to encourage and provide room for free S&T pursuits. Notably, there is a prominent emphasis on the fact that basic research needs to be guided by the goal of meeting the country's needs. This appears to be quite different from the notion held by many researchers that basic research entails free exploration without being influenced by predetermined goals, and that its outcome is often unexpected and serendipitous. But in fact, exploratory research as basic as pure mathematics and astronomy are often goal directed. Exploratory research is far from an aimless random walk, and major breakthroughs are often propelled by the desire to reach the goal of solving major S&T problems.

Impressive progress has been made in many S&T fields in China over recent decades, as reflected by the rapid rise in the total number and impact of research publications. However, the results of many basic research studies were limited to the stage ‘proof of principle’, and ended with publications in high-profile journals. The practical use of original concepts, on the other hand, requires a series of incremental advances in basic research and technical improvement that are less glorious and sometimes more difficult to achieve. There has been much recent attention, in the Chinese research community, on China's need to achieve ‘0 to 1’ breakthroughs, i.e. groundbreaking discoveries and inventions that result in paradigm shifts in various fields of S&T. Yet, equally important is the arduous task of ‘1 to 100’ advances that could truly bring practical benefits to society. By emphasizing goal-directed basic research, the new Law points to a well-defined new horizon for S&T advancement in China.

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The  Cornell China Center  (CCC) has announced six new grant awards, totaling $140,000, to support research by Cornell faculty teams partnering with researchers in China.

Focused on building solutions to meet the United Nations’ sustainable development goals for China and the world, the 2021 awards include four joint seed fund grants to expand collaborations between Cornell researchers and counterparts at Zhejiang University in Hangzhou and two China Innovation Grants.

CCC-funded research thrived in the past year, despite the COVID-19 crisis and logistical challenges the far-flung teams faced – from international travel bans to the 12-hour time difference. The center made 13 awards in 2020, including joint seed funding to five Cornell teams partnering with Shanghai Jiao Tong University.

CCC research teams found ways to collaborate virtually and adapt their work to meet the moment. K. Max Zhang , professor of mechanical and aerospace engineering in the College of Engineering, is leading a CCC-funded project team to develop a cost-effective air-quality system for Chinese cities. When COVID-19 lockdowns began in China, his team recognized an opportunity: They analyzed the air-quality impacts from January to April 2020 for six megacities with different lockdown durations.

Using machine learning techniques to evaluate this “naturally controlled experiment,” they found that the lockdown reduced ambient NO2 concentrations by 36% to 53% during the most restrictive periods.

“Data doesn’t mean information automatically – you have to extract and make sense of it. That’s a challenge, and that’s what we’re working on,” Zhang said. “The CCC grant has been crucial in providing the resources for collaborating with our partners in China.”

“It is encouraging to see project teams adapt effectively during COVID times,” said Ying Hua, CCC’s director. “We are also happy to see our grants supporting Cornell students’ continued participation in research during a time with significant challenges.”

Throughout the pandemic, CCC has linked the Ithaca campus with researchers, students and alumni in China. With more than 1,000 Cornell students studying in China during the past academic year, CCC’s Beijing office welcomed students enrolled in Study Away and learning remotely for in-person and hybrid career information sessions, academic talks and gatherings with Cornell alumni.

Delivering effective online education is the opportune focus of a project funded by CCC in 2019. The research team has tested a variety of strategies to increase student retention and engagement in massive open-enrollment courses for environmental education professional development.

Research associate Yue Li says that the grant’s focus on cross-disciplinary research has given their team a fresh perspective on how to reach learners: “I’m from the Department of Natural Resources and the Environment, and our collaborators are from information science and education, so this is the first time we have had this kind of  interdisciplinary collaboration – which is really valuable.”

With course participants across 50 countries, the team has found that students in China benefit from the encouragement of facilitated study groups. Li says the team is extending the successful collaboration into further research using different interventions to motivate participants to take environmental actions beyond the course.

Four seed fund grants in the 2021 cycle support partnerships between Cornell and Zhejiang University, with each university funding its own researchers:

• Improving Seed Yield and Stress Tolerance in Rice through Natural Variations of a Novel Lipid Binding Protein: Jian Hua , plant biology, College of Agriculture and Life Sciences, and Yajing Guan (ZJU).
• In Silico Nanosafety Assessment for Promoting Nano-Enabled Strategies in Agricultural Production: Dan Luo , biological and environmental engineering, CALS, and Fang Cheng (ZJU).
• Making Inclusive Finance More Digital and Greener: Big Data Evidence from China: Yongmiao Hong , statistics and data science, Cornell Ann S. Bowers College of Computing and Information Science, and Xingguo Luo (ZJU).
• Regulating the Crystallographic Orientation of Zinc Metal for Advanced Aqueous Zinc Batteries: Lynden Archer , chemical and biomolecular engineering, College of Engineering, and Yingying Lu (ZJU).

Two innovation grants will launch large-scale collaborative research: Cornell-Southern China-Macau International Cooperative Functional Food Groups – Rui Hai Liu , food science, CALS; and Practical Approaches to the Control of Ichthyophthiriasis in Asian Aquaculture –  Theodore Clark , microbiology and immunology, College of Veterinary Medicine.

Sheri Englund is associate director of communication for Global Cornell. Priya Pradhan ’22 is a writing intern for Global Cornell.

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Forty years of business research in China: a critical reflection and projection

• Ji-Ye Mao 1  

Frontiers of Business Research in China volume  12 , Article number:  24 ( 2018 ) Cite this article

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Indigenous business research has largely mirrored the economic growth in China over the past 40 years, which has reached a critical juncture. It is, therefore, important to take stock of the past progress to identify critical success factors and remaining challenges, in searching for paths to the next leap forward. To this end, this commentary will first review the key milestones in indigenous business research over the past four decades. Then it will highlight two paradoxes, namely, the lack of indigenous theories despite the phenomenal growth of Chinese firms, and the growing divergence between scientific rigor and low relevance to practice, which will need to be addressed in the future. Lastly, several predications and suggestions will be offered.

This year marks the 40th anniversary of China’s reform and opening up commenced in late 1978, which has fundamentally transformed the nation and lifted it out of poverty to a large extent. After four decades of phenomenal growth, the nation has reached a critical junction, and is now searching for both new directions and drivers for the next round of growth, while trying to steer away from the middle income trap. Despite the phenomenal growth in the past, there are structural problems in the economy that are difficult and painful to resolve after low hanging fruits have been picked up. However, it is also clear that the old path of growth is no longer sustainable, and a new mode of growth is overdue.

In many ways, progress in business research in China has mirrored the growth pattern of the Chinese economy, and registered an equally impressive growth curve. Whereas the economic success is widely known to the world as reflected in not only all kinds of statistics but also everyday living, few have a reasonable grasp of the nature and extent of progress in business research in China, nor the remaining challenges and opportunities. China has emerged as a top producer of business research papers in both quantity and influence measured in citations (Li 2015 ). Whereas the notion of empirical business research was entirely alien to Chinese researchers till late 1980s, it is now firmly entrenched in the academia. Similar to the current state of the economy, business research in China also needs another round of transformation, in order to establish its own identity and to make greater contributions to the global community of business researchers.

It is against such a backdrop that this commentary is composed with a threefold purpose. First, it will briefly take stock of the transformation of business research from nearly nonexistence to a flourishing state demonstrated by both the quantity and quality of publications. Second and third, it will identify key challenges and contradictions, and to speculate on future directions.

An overview of the past progress

Business research in China has made remarkable strides over the past four decades. Whereas it is important to take stock, neither is it desirable nor feasible to present a complete historical review of the development process in this commentary. Instead, it shall present a brief overview only, while highlighting several key milestones as the background for the critical reflection to follow.

In a comprehensive review of business research in China over the period between 1978 to 2008 based on a survey of senior Chinese scholars in the field, Su and Liu ( 2009 ) identified 55 important milestones and divided the development history of business research in China into three stages, the awareness stage (1978–1986), formation stage (1987–1996), and rapid development stage (since 1997). During the awareness stage, the importance of business research was gradually recognized by the state, firms, and academia. However, previously there was no real research on market-oriented modern organizations beyond isolated exploration on productivity enhancement, because enterprises followed executive orders from the state as part of the planned economy. Hardly was there any indigenous management research based on generally adopted research methodologies by Western researchers, be it empirical or mathematical. Research at that time was largely translating Western textbooks and preparing lecture notes.

During the formation stage, business research gained formal recognition by major stakeholders, and was institutionalized, especially after Deng Xiaoping’s famous tour in southern China, where he called for greater degrees of adamant reform and opening up in the spring of 1992. This was a landmark event in modern Chinese history, which jump-started the then stagnating reform and accelerated the pace of transformation in all sectors including science and technology development. Gradually, business research was recognized as an academic discipline by the state authorities. In particular, the management sciences division of the national Natural Science Foundation of China (NSFC) was promoted to a full-fledged department as other recognized disciplines in 1996, 10 years after the diversion’s establishment from the very beginning of the NSFC. The first MBA programs were also launched in several universities on a trial basis in 1990, which stimulated business research and created the need for researchers.

Lastly, since 1997 business research as an academic discipline entered a stage of rapid growth. Two events significantly shaped the subsequent development in particular. First, through its newly formed Management Sciences Department, Footnote 1 the NSFC became the primary source of funding to business researchers and provided the largest research grants on average to scientists on a competitive basis. The success rate has always been under 20%, and used to be much lower hovering above the 10% mark, and thus a grant from NSFC carried high esteem. Applications were subjected to a peer review process, which weighed heavily the soundness of the research methodology and scientific rigor in particular. The influence of the NSFC was partly reflected in the funding for papers published in English language journals. According to a report by the Management Science Department of the NSFC (Li, 2015 ), in 2009 among the papers authored by Chinese mainland-based researchers and were indexed by the Web of Science (WoS), 37% of them were funded by the NSFC, far ahead of under 8% funded by the Ministry of Education, the second largest source of research funding. These two ratios rose to 47% and 15%, respectively, in 2013, while the rest were funded by the third to the fifth largest national funding sources including the Ministry of Science and Technology, and the Ministry of Human Resources and Social Security of China. 66% of the highly cited papers were funded by NSFC in 2013. Clearly, NSFC has established its position as the primary funding source for business research in China. Second, also during this stage, Professor Anne Tsui, organized a series of workshops on empirical business research methodology at the Hong Kong University of Science and Technology, from 1999 to 2002. The workshops rightfully targeted junior faculty in Chinese universities, and each trained dozens of junior researchers, who later became academic leaders in their own institute and respective research field.

Paradox 1: Business success vs. lack of indigenous theories

As a result of the rapid growth of Chinese economy over the past four decades, the number of Chinese companies in the global Fortune 500 has reached 115 in 2017, including 109 based in Chinese mainland and Chinese Hong Kong (Fortune, 2017 ). Not only in size but also in quality and innovation have Chinese companies managed to grow. China is leading the world or among the frontrunners in e-commerce, mobile payment, sharing economy, artificial intelligence, 3D printing, and pilotless planes. The top four e-commerce giants BATJ (an acronym to refer to Baidu, Alibaba, Tencent, and JD.com , and especially Alibaba and Tencent) are powering new business models in the name of New Retail, which refers to the combination of omni-channels (online and offline), socialization in addition to merely retail transactions, and the use of big data to personalize consumer experiences. However, no well-known management tool, method, concept, or theory has emerged from best practices of Chinese firms, let alone anything generalizable and adopted beyond a single company. In contrast, during the late 1980s and later, when the success of Japanese firms produced new manufacturing methodologies such as lean manufacturing, the Kanban system, just-in-time inventory management, popularized by the Toyota Production System.

It begs the question of how have the Chinese firms achieved the phenomenal growth? Is there a distinctive growth model or winning formula for corporate China? Or is Chinese firms’ success largely due to the large size of the domestic market protected by a unique institutional environment, and the so-called population dividend and latecomer advantage? Alternatively, is it because indigenous research has turned a blind eye to the best practices of Chinese firms? My personal view is that the past success of Chinese firms was largely attributable to the shortage economy featured in the early stage of reform and opening up and lasted till earl 2010s when the economy has maintained a high growth rate. There was a huge demand from consumers for any product of reasonable quality and price. In other words, just riding the rising tides was good enough for corporate China. Moreover, it is likely because that Chinese firms have been playing a catch up game, and achieved success simply by adopting well-established Western managerial processes and methods and sometimes creatively adapting these to the local context. As an anecdote, a former colleague of mine and a long-time senior advisor to Huawei, widely considered the most successful Chinese firm, believed that the most important success factor of Huawei was continuously adopting Western management processes and methodologies such as the Integrated Product Development process of IBM. To date, the best-known new to the world and originated from China method, “ Rendanheyi ,” which means to align every employee to customer requirements in order to produce quality product to satisfy customer needs, is a methodology proposed by Haier’s supreme leader Mr. Zhang Ruimin. However, it has hardly been studied by Chinese researchers, nor was it widely adopted beyond Haier. Therefore, there exists hardly any evidence of its effectiveness, let alone theorizing around the method.

Paradox 2: Divergence between research rigor and relevance

According to the same report by the Management Science Department of the NSFC (Li, 2015 ), in 2004, Chinese researchers published only 682 papers referenced in the SCI/SSCI (WoS) databases, which could be considered an indicator of quality, and this number rose to 5288 after an impressive 6.8 fold increase in 2013 only after that of the US and the UK, 19,221 and 7063, respectively. More importantly, the number of citations per paper, which is often taken as a measure of quality and influence, by Chinese researchers in the SCI/SSCI databases is ranked the second in the world, only after that of the Netherlands. In fact, two Chinese business schools have broken into the top 100 in the world in the University of Texas at Dallas list of top 24 business research journals. All of these indicate that business research by Chinese scientists has achieved an acceptable degree of methodological maturity and scientific rigor.

However, the practical impact of the business research has been minimal. Part of the reason is that junior researchers in the top-tier business schools are hired from overseas with solid training to produce high quality research, but the research support and culture are not always up to the standard in the elite research schools in the US. Promotion and other incentives disproportionally favor research excellence, i.e., publications are preferred by peers who also prefer rigor to relevance. In contrast with the past, at least some of the earlier generations of business faculty have worked closely with the industry, e.g., the well-known Six Gentlemen for Huawei, i.e., the six professors from Renmin University of China, who advised Huawei and helped its success in its early years. However, by and large, few faculty hired over the past two decades are focused on applied research or choose to closely engage the business world. Many researchers have taken notice of this disturbing fact that research papers are increasingly more methodologically rigorous, but less and less relevant to practice, to the extent that research papers are neither targeting practitioners, nor are they used in classroom teaching. For many researchers, publication is just for the sake of it, and this situation is due for a change.

Regrettably, existing research papers on business administration in China virtually show no signs of indigenous characteristics (Tsui and Zhang 2011 ). As a result, no adequate progress has been made to address the criticisms on Chinese or Asian management research in general, such as the lack of self-confidence (Meyer 2006 ), weaknesses in theory development or relevance for management practices (White 2002 ), and heavily utilizing existing management theories but rarely proposing new theories (Tsui, 2009 ).

Despite the two paradoxes and challenges discussed earlier, a quantum leap has been made in business research in China. It is because scientific rigor must be established first, which was needed the most over the past 40 years, i.e., addressing the primary weakness head-on. In other words, the past success has laid a solid foundation for the future. Rigor will remain the most important issue for the years ahead. In the past, the effort was well spent on catching up the methodology of organizational research. Therefore, Chinese researchers should stick to the winning-formula and keep pursuing methodological rigor continuously.

Future directions

Next, this commentary will conclude with several suggestions for ways to move forward, and some practical advice.

First, it could be highly promising for Chinese researchers to address questions that target indigenous management problems. Unfortunately, not enough has been done in this regard. In a review of 270 empirical research papers related to Chinese contexts published in six top-tier general management journals in the world over the previous three decades till 2010 and Management and Organization Review (MOR) from its launch in 2005 to 2010, Jia et al. ( 2012 ) found that only 10 of the 270 featured some degree of Chinese contextualization in their concepts or constructs, relationships, and the logics underlying the relationships. A key conclusion was that Chinese-context-centered studies only offered three new concepts, market transition, network capitalism, and guanxi , though they have re-conceptualized concepts such as trust, citizenship behavior, and emotional intelligence. However, the Chinese context has failed to contribute new theoretical logics, except for Confucianism and related concepts such as guanxi , face, wulun , renqing , and traditionality. Interestingly, Li and Tsui ( 2002 ) showed that impactful studies (measured by citations) tend to have strong indigenous features, which means contextual factors are the key in theory-building as independent variables or moderators.

Not only is contextualized research theoretically important, but also increasingly feasible and practical. Whereas China has emerged as the world factory, it has also become the largest laboratory for organization research. Given the fast pace and magnitude of changes in Chinese firms, many interesting phenomena are amplified and intensified, and thus could be easier to observe. For example, the continuous reform and associated frequent policy changes combined with the technology advance and globalization, the operating environment for Chinese firms are particularly dynamic, which make it ideal for advancing theories on dynamic capabilities, and strategic transformation. A personal anecdotal example is what I have observed from my own research on IT outsourcing. Whereas most existing research on offshore IT outsourcing adopted a client perspective because the research was conducted by researchers in the West, I had access to Chinese IT vendors only when I started my research in this area in 2004 in China. This limitation was turned into an opportunity that allowed me to fill a gap in the literature from a vendor’s perspective (Jarvenpaa and Mao 2008 ) and to complement the existing research. Similar opportunities exist in areas that China is on the leading edge such as e-commerce, 3D printing, pilotless plains, AI applications, and shared economies. Chinese researchers have an opportunity to make unique contributions in these areas to the global management community.

Moreover, from a practical perspective, it is also important to contextualize business research. Situated in a unique political, social, and cultural environment, Chinese firms have to overcome numerous unique challenges. In particular, given the size of the Chinese economy, Chinese researchers shoulder a heavy responsibility to help domestic firms with their research, and thus must pay attention to critical issues of practical importance to the development of these firms. They should not simply recycle Western theories and turn a blind eye to critical issues faced by Chinese companies, though it might make sense for researchers in a small nation or region to overlook local issues. It is the responsibility of Chinese researchers to conduct research that is relevant to the local practice. Through solving real management problems, useful theories can be developed. Therefore, more effort should be directed to local management issues, which could also yield high return. As an increasing number of companies are operating on the global stage and becoming multinational, critical issues to Chinese firms can be highly relevant and of interest to firms in other emerging economies as well as the developed world. As a popular Chinese saying suggests, the more national, the more international.

Second, Chinese researchers should ask theoretically important questions in their research, which is the prerequisite for any high impact research and highly regarded by researchers as part of the current paradigm of research. To this end, indigenous research must engage in a dialogue with the mainstream literature and frontiers of business research in the world, to identify a major gap or weaknesses in the extant research. After all, any research contribution is an extension or revision of the existing theories.

Third, there is a growing need to embrace the diversity in research methods. Whereas traditional empirical research has primarily used questionnaire-based survey data, today it is increasingly more important to extend the traditional data collection to the macro end or the micro end, i.e., big data or case-based rich data. In particularly, qualitative research, which tends to be case-based (Eisenhardt 1989 ; Eisenhardt and Graebner 2007 ) for inductive theory development has gained more traction in recent years (Mao and Su 2016 ) because of case studies’ advantages in creating new discoveries and new insights. The comparative advantages of qualitative research are important for theory-building that is grounded in complex real-world problems. Case studies and inductive qualitative research in general can be expected to be used more widely to address the issues identified by Tsui ( 2009 ), “research in Chinese management has exploited existing questions, theories, constructs, and methods developed in the Western context. Lagging are exploratory studies to address questions relevant to Chinese firms and to develop theories that offer meaningful explanations of Chinese phenomena” (p. 1).

Meanwhile, the arrival of the big data era has also provided exciting opportunities for collecting massive high quality data, as Chinese firms such as China Mobile, China Life, Alibaba, and Tencent, possess the largest databases in the world. Again, Chinese researchers have an advantages because they are closer to the big data sources than their Western colleagues, and research collaboration between local and overseas researchers can yield high quality publications in top-tier journals.

Fourth and lastly, the past progress in business research can be attributed to international collaboration, as over 50% of the top-tier journals published in management sciences with funding from NSFC involved collaboration with co-authors affiliated with overseas institutions (Li 2015 ). International collaboration brought in not only methodological rigor, but also experience in theorizing, which takes a long career to develop, given that empirical research in business administration began only in the mid-1990s. A casual observation of the top-tier journal publications by Chinese mainland-based researchers, the majority of whom have a doctoral degree overseas, reveals that they are usually the result of international collaboration with more established overseas co-authors. A complementary strength of the local researchers is their close engagement with the frontline innovation and best-practices by Chinese companies, while their overseas collaborators are more experienced with the revision and publication process. It is safe to expect that international collaboration will remain important. The biennial conference of the International Association for Chinese Management Research (IACMR) has been instrumental in promoting the engagement between local Chinese researchers and those overseas. Therefore, in the future Chinese business researchers have both the need and means to extend the scope and deepen the depth of international collaboration.

In essence, it is all about adopting scientific rigor, i.e., to tell the Chinese stories with an international language. Clearly indigenous business research is poised to make the next leap forward. This journal, Frontiers of Business Research in China , which is also a by-product of the reform and opening up, is committed to becoming a premier outlet for high quality business research with strong implications for management in China.

Conclusions

In sum, over the past four decades, business research in China has completed a full circle of spiral climb by adopting international standards and scientific rigor in methodology. This has laid a solid foundation for the next round of climbing. It also is important to identify the critical success factors of the past success, and how to leverage the past success. This research commentary reviews the key milestones in indigenous business research over the past four decades to commemorate the 40th anniversary of the reform and opening up in China. It also highlights two paradoxes, i.e., the lack of indigenous theories despite the phenomenal growth of Chinese firms, and the growing divergence between scientific rigor and low relevance to practice, which will need to be addressed in the future. Lastly, several predications and suggestions are offered to address the two paradoxes. First, more effort should be directed to local management issues. A particularly fruitful future avenue would be to contextualize research, i.e., to more closely examine unique challenges and issues faced by indigenous Chinese companies while staying more relevant to the local businesses. Second, indigenous research must engage in a dialogue with the mainstream literature and frontiers of business research in the world so that important research questions can be asked and theoretical contributions can be made. Third, there is a growing need to embrace the diversity in research methods such as qualitative research and big-data based approaches. Fourth and lastly, Chinese business researchers should extend the scope and deepen the depth of international collaboration, which was a critical success factor in the past.

The department covers three narrower disciplines of management sciences, including operations research, business administration, and public administration and managerial economics. The term management sciences will be used with the same meaning subsequently.

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Acknowledgements

The author would like to acknowledge the funding from the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities (Project No. 10JJD630012).

This study was supported by the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities (Project No. 10JJD630012).

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Mao, JY. Forty years of business research in China: a critical reflection and projection. Front. Bus. Res. China 12 , 24 (2018). https://doi.org/10.1186/s11782-018-0045-7

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H UANG FEIRUO was once a respected scientist who studied ways to make pigs gain weight more quickly. He ran government-funded research projects at Huazhong Agricultural University in the central city of Wuhan. But last month 11 of his graduate students accused him of plagiarising the work of other academics and fabricating data. He had also, they said, put pressure on them to fake their own research. On February 6th the university announced that it had fired Mr Huang and retracted some of his work.

Scientific fraud is all too common in China. Bad incentives are a big part of the problem. Chinese universities typically reward researchers with promotions and funding based on the quantity of papers they publish, not the quality. That has got results. In 2017, for the first time, China published more scientific papers than any other country. It has kept the top spot ever since. But while some of the research has been cutting-edge, much has been dodgy.

The scale of the problem is hard to measure, as fraudulent work often goes unnoticed. But it is useful to look at retractions, or when a scientific journal withdraws a study, usually due to suspicions of research misconduct. Papers from China have the fourth-highest retraction rate in the world, according to Nature , a journal (see chart). In a database of some 50,000 retracted studies compiled by Crossref, an American non-profit, and Retraction Watch, a blog, about 46% are from China.

Many of the fishy papers are probably written, for a fee, by “paper mills”. These outfits often plagiarise real research, changing a few details. Some fakes are obvious, says Elisabeth Bik, a microbiologist who specialises in rooting them out. She found a Chinese paper on prostate cancer, for instance, which claimed that more than half of the patients studied were women. Only men have prostate glands. Other fakes look more convincing and might pollute a field of research. So some scientists simply refuse to peer review work from China, says Ms Bik.

The government, which hopes to turn China into a scientific superpower, is trying to crack down on fake research. In recent years it has fined hundreds of misbehaving scientists and barred them from public funding. In January the Ministry of Education launched a fresh campaign, demanding that universities investigate every retracted paper written by their faculty. Many authors welcome such toughness. Authorities should use harsh penalties to “purify” the pursuit of science, says a researcher at a hospital in Beijing.

But punishment alone will not fix the problem, says Shu Fei of Hangzhou Dianzi University. He believes universities should stop rewarding researchers just for publishing lots of papers. In 2020 the government released guidelines to this effect. Still, little has changed, says Mr Shu. Part of the problem, he suspects, is that university leaders are government officials (rather than academics). So they are good at chasing numerical targets, but bad at fostering good science, which is hard to quantify.

The example set by Mr Huang’s graduate students is encouraging, at least. On social media many Chinese people have applauded them for taking a stand, at the risk of damaging their own academic careers. But there is much work still to be done. In an online survey published last year, over a quarter of Chinese graduate medical students considered it acceptable to fabricate some data or results. ■

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Center for Security and Emerging Technology

Translation, research report on governance modernization in the digital age: practice and prospects for the application of large models in the government domain (2023), 数字时代治理现代化研究报告——大模型在政务领域应用的实践及前景（2023年）.

Read our translation of a report by a Chinese state-run think tank that describes how the Chinese government and foreign governments are using large AI models.

The following report by a Chinese state-run think tank describes how the Chinese government and foreign governments are using large AI models. The authors list more than 50 large models developed by Chinese tech companies that provincial and local governments in China have deployed for various purposes, and provide four brief case studies. While these AI systems have the potential to improve Chinese local governments’ provision of public services, the focus of many of these governments on early detection and suppression of social disturbances suggests that these AI models are being used to enhance and intensify China’s surveillance state.

An archived version of the Chinese source text is available online at:    https://perma.cc/8SYR-Z2LN

Currently, large generative artificial intelligence (AI) models have become a focus and hot topic for all different people. Large models such as ChatGPT and Bard are a leap forward in AI technology and represent the transition of AI technology from perceiving and understanding the world to creating the world. The government domain involves a large volume of content production and human-to-human interaction. It is highly aligned with the high-level information collection, text summary, and intelligent interaction capabilities of generative AI large models. This field is fertile ground for the future application of generative AI large models.

Since the emergence of large model tools, countries around the world have explored the possibility of applying new technologies in government governance, promoting the formation of a wave of digital government reforms with intelligentization (智能化) as their main feature. In terms of the scope of application , the application of large models in the government domain has been widely explored. Eighteen countries or regions, including the United States, the UK, Australia, Canada, Singapore, Japan, and South Korea, have applied large models in government affairs management, covering 13 specific scenarios in the 5 major fields of government internal office work, government information disclosure, government service provision, optimization of people’s livelihood (民生) services, and national defense and aerospace. In terms of application depth , the awareness and utilization rate of large models in the government domain have reached a high level in some countries. The Roland Berger consulting firm predicts that, provided they receive ample applications, large models are expected to reduce operating costs in the public service industry by 1.8%. In terms of deployment and promotion , countries and regions such as Singapore, Japan, and the United States are at the forefront in practice. They have promoted the transition from local and dispersed exploration to integrated applications and have made overall arrangements for deployment methods, data processing, and other aspects.

In order to make good use of the “double-edged sword” of large model technology, countries are actively promoting organizational, talent, and technological changes to adapt to new governance challenges, while accelerating the application of large models in the government domain at the same time . Since 2023, South Korea, Singapore, the United States, the UK, Australia, New Zealand, Japan, Canada, and Denmark have successively issued interim guidelines for the use of generative AI by government agencies (civil servants). They are working to avoid technical risks and promote the compliance of applications by clarifying usage principles, framing the scopes of scenarios, and establishing regulatory norms. However, because the technology is still in the stage of rapid development, ambiguity still exists in governance policies: First, a complete risk governance framework for government application of AI technology has not yet been formed. Second, scenario categorization and grading, and end-to-end supervision specifications are relatively rough and cannot achieve full coverage of new technology application behaviors.

In China, the application of large models in the government domain is still in its initial exploratory stage. According to statistics, there are at least 56 large model vendors in China that have deployed products in the government domain. Of these, 15 vendors including Baidu (百度), Beijing Knowledge Atlas Technology Co., Ltd. (Zhipu AI; 智谱华章), iFlytek (科大讯飞), SenseTime (商汤科技), the Institute of Automation of the Chinese Academy of Sciences (CAS Institute of Automation; 中国科学院自动化研究所), Alibaba Cloud (阿里云), 360, and Kunlun Tech (昆仑万维) have registered large model products. Localities including Beijing, Shanghai, Hangzhou, and Shenzhen have introduced policies to promote the implementation of large model applications in the government domain. Government hotlines, intelligent customer service, urban governance, healthcare, and education are key implementation directions. With the rapid development of large generative AI models, it is expected that, in the future, related technologies will be widely applied in the construction of smart cities and the provision of government services in various places, becoming a powerful force promoting a new round of governance transformation. Government agencies need to strengthen forward-looking deployment, proactively respond to the opportunities and challenges brought by new technological changes, develop a full understanding of large model technology from multiple levels, including strategy, business, organization, and risk, accelerate explorations into the feasible paths for the development and application of large government models suitable for China, and accelerate the modernization of government governance.

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Why the Pandemic Probably Started in a Lab, in 5 Key Points

By Alina Chan

Dr. Chan is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “Viral: The Search for the Origin of Covid-19.”

This article has been updated to reflect news developments.

On Monday, Dr. Anthony Fauci returned to the halls of Congress and testified before the House subcommittee investigating the Covid-19 pandemic. He was questioned about several topics related to the government’s handling of Covid-19, including how the National Institute of Allergy and Infectious Diseases, which he directed until retiring in 2022, supported risky virus work at a Chinese institute whose research may have caused the pandemic.

For more than four years, reflexive partisan politics have derailed the search for the truth about a catastrophe that has touched us all. It has been estimated that at least 25 million people around the world have died because of Covid-19, with over a million of those deaths in the United States.

Although how the pandemic started has been hotly debated, a growing volume of evidence — gleaned from public records released under the Freedom of Information Act, digital sleuthing through online databases, scientific papers analyzing the virus and its spread, and leaks from within the U.S. government — suggests that the pandemic most likely occurred because a virus escaped from a research lab in Wuhan, China. If so, it would be the most costly accident in the history of science.

Here’s what we now know:

1 The SARS-like virus that caused the pandemic emerged in Wuhan, the city where the world’s foremost research lab for SARS-like viruses is located.

• At the Wuhan Institute of Virology, a team of scientists had been hunting for SARS-like viruses for over a decade, led by Shi Zhengli.
• Their research showed that the viruses most similar to SARS‑CoV‑2, the virus that caused the pandemic, circulate in bats that live r oughly 1,000 miles away from Wuhan. Scientists from Dr. Shi’s team traveled repeatedly to Yunnan province to collect these viruses and had expanded their search to Southeast Asia. Bats in other parts of China have not been found to carry viruses that are as closely related to SARS-CoV-2.

The closest known relatives to SARS-CoV-2 were found in southwestern China and in Laos.

Large cities

Mine in Yunnan province

Cave in Laos

South China Sea

The closest known relatives to SARS-CoV-2

were found in southwestern China and in Laos.

philippines

The closest known relatives to SARS-CoV-2 were found

in southwestern China and Laos.

Sources: Sarah Temmam et al., Nature; SimpleMaps

Note: Cities shown have a population of at least 200,000.

There are hundreds of large cities in China and Southeast Asia.

There are hundreds of large cities in China

and Southeast Asia.

The pandemic started roughly 1,000 miles away, in Wuhan, home to the world’s foremost SARS-like virus research lab.

The pandemic started roughly 1,000 miles away,

in Wuhan, home to the world’s foremost SARS-like virus research lab.

The pandemic started roughly 1,000 miles away, in Wuhan,

home to the world’s foremost SARS-like virus research lab.

• Even at hot spots where these viruses exist naturally near the cave bats of southwestern China and Southeast Asia, the scientists argued, as recently as 2019 , that bat coronavirus spillover into humans is rare .
• When the Covid-19 outbreak was detected, Dr. Shi initially wondered if the novel coronavirus had come from her laboratory , saying she had never expected such an outbreak to occur in Wuhan.
• The SARS‑CoV‑2 virus is exceptionally contagious and can jump from species to species like wildfire . Yet it left no known trace of infection at its source or anywhere along what would have been a thousand-mile journey before emerging in Wuhan.

2 The year before the outbreak, the Wuhan institute, working with U.S. partners, had proposed creating viruses with SARS‑CoV‑2’s defining feature.

• Dr. Shi’s group was fascinated by how coronaviruses jump from species to species. To find viruses, they took samples from bats and other animals , as well as from sick people living near animals carrying these viruses or associated with the wildlife trade. Much of this work was conducted in partnership with the EcoHealth Alliance, a U.S.-based scientific organization that, since 2002, has been awarded over $80 million in federal funding to research the risks of emerging infectious diseases.
• The laboratory pursued risky research that resulted in viruses becoming more infectious : Coronaviruses were grown from samples from infected animals and genetically reconstructed and recombined to create new viruses unknown in nature. These new viruses were passed through cells from bats, pigs, primates and humans and were used to infect civets and humanized mice (mice modified with human genes). In essence, this process forced these viruses to adapt to new host species, and the viruses with mutations that allowed them to thrive emerged as victors.
• By 2019, Dr. Shi’s group had published a database describing more than 22,000 collected wildlife samples. But external access was shut off in the fall of 2019, and the database was not shared with American collaborators even after the pandemic started , when such a rich virus collection would have been most useful in tracking the origin of SARS‑CoV‑2. It remains unclear whether the Wuhan institute possessed a precursor of the pandemic virus.
• In 2021, The Intercept published a leaked 2018 grant proposal for a research project named Defuse , which had been written as a collaboration between EcoHealth, the Wuhan institute and Ralph Baric at the University of North Carolina, who had been on the cutting edge of coronavirus research for years. The proposal described plans to create viruses strikingly similar to SARS‑CoV‑2.
• Coronaviruses bear their name because their surface is studded with protein spikes, like a spiky crown, which they use to enter animal cells. T he Defuse project proposed to search for and create SARS-like viruses carrying spikes with a unique feature: a furin cleavage site — the same feature that enhances SARS‑CoV‑2’s infectiousness in humans, making it capable of causing a pandemic. Defuse was never funded by the United States . However, in his testimony on Monday, Dr. Fauci explained that the Wuhan institute would not need to rely on U.S. funding to pursue research independently.

The Wuhan lab ran risky experiments to learn about how SARS-like viruses might infect humans.

1. Collect SARS-like viruses from bats and other wild animals, as well as from people exposed to them.

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of human cells.

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of

human cells.

In Defuse, the scientists proposed to add a furin cleavage site to the spike protein.

3. Create new coronaviruses by inserting spike proteins or other features that could make the viruses more infectious in humans.

4. Infect human cells, civets and humanized mice with the new coronaviruses, to determine how dangerous they might be.

• While it’s possible that the furin cleavage site could have evolved naturally (as seen in some distantly related coronaviruses), out of the hundreds of SARS-like viruses cataloged by scientists, SARS‑CoV‑2 is the only one known to possess a furin cleavage site in its spike. And the genetic data suggest that the virus had only recently gained the furin cleavage site before it started the pandemic.
• Ultimately, a never-before-seen SARS-like virus with a newly introduced furin cleavage site, matching the description in the Wuhan institute’s Defuse proposal, caused an outbreak in Wuhan less than two years after the proposal was drafted.
• When the Wuhan scientists published their seminal paper about Covid-19 as the pandemic roared to life in 2020, they did not mention the virus’s furin cleavage site — a feature they should have been on the lookout for, according to their own grant proposal, and a feature quickly recognized by other scientists.
• Worse still, as the pandemic raged, their American collaborators failed to publicly reveal the existence of the Defuse proposal. The president of EcoHealth, Peter Daszak, recently admitted to Congress that he doesn’t know about virus samples collected by the Wuhan institute after 2015 and never asked the lab’s scientists if they had started the work described in Defuse. In May, citing failures in EcoHealth’s monitoring of risky experiments conducted at the Wuhan lab, the Biden administration suspended all federal funding for the organization and Dr. Daszak, and initiated proceedings to bar them from receiving future grants. In his testimony on Monday, Dr. Fauci said that he supported the decision to suspend and bar EcoHealth.
• Separately, Dr. Baric described the competitive dynamic between his research group and the institute when he told Congress that the Wuhan scientists would probably not have shared their most interesting newly discovered viruses with him . Documents and email correspondence between the institute and Dr. Baric are still being withheld from the public while their release is fiercely contested in litigation.
• In the end, American partners very likely knew of only a fraction of the research done in Wuhan. According to U.S. intelligence sources, some of the institute’s virus research was classified or conducted with or on behalf of the Chinese military . In the congressional hearing on Monday, Dr. Fauci repeatedly acknowledged the lack of visibility into experiments conducted at the Wuhan institute, saying, “None of us can know everything that’s going on in China, or in Wuhan, or what have you. And that’s the reason why — I say today, and I’ve said at the T.I.,” referring to his transcribed interview with the subcommittee, “I keep an open mind as to what the origin is.”

3 The Wuhan lab pursued this type of work under low biosafety conditions that could not have contained an airborne virus as infectious as SARS‑CoV‑2.

• Labs working with live viruses generally operate at one of four biosafety levels (known in ascending order of stringency as BSL-1, 2, 3 and 4) that describe the work practices that are considered sufficiently safe depending on the characteristics of each pathogen. The Wuhan institute’s scientists worked with SARS-like viruses under inappropriately low biosafety conditions .

In the United States, virologists generally use stricter Biosafety Level 3 protocols when working with SARS-like viruses.

Biosafety cabinets prevent

viral particles from escaping.

Viral particles

Personal respirators provide

a second layer of defense against breathing in the virus.

DIRECT CONTACT

Gloves prevent skin contact.

Disposable wraparound

gowns cover much of the rest of the body.

Personal respirators provide a second layer of defense against breathing in the virus.

Disposable wraparound gowns

cover much of the rest of the body.

Note: ​​Biosafety levels are not internationally standardized, and some countries use more permissive protocols than others.

The Wuhan lab had been regularly working with SARS-like viruses under Biosafety Level 2 conditions, which could not prevent a highly infectious virus like SARS-CoV-2 from escaping.

Some work is done in the open air, and masks are not required.

Less protective equipment provides more opportunities

for contamination.

Some work is done in the open air,

and masks are not required.

Less protective equipment provides more opportunities for contamination.

• In one experiment, Dr. Shi’s group genetically engineered an unexpectedly deadly SARS-like virus (not closely related to SARS‑CoV‑2) that exhibited a 10,000-fold increase in the quantity of virus in the lungs and brains of humanized mice . Wuhan institute scientists handled these live viruses at low biosafet y levels , including BSL-2.
• Even the much more stringent containment at BSL-3 cannot fully prevent SARS‑CoV‑2 from escaping . Two years into the pandemic, the virus infected a scientist in a BSL-3 laboratory in Taiwan, which was, at the time, a zero-Covid country. The scientist had been vaccinated and was tested only after losing the sense of smell. By then, more than 100 close contacts had been exposed. Human error is a source of exposure even at the highest biosafety levels , and the risks are much greater for scientists working with infectious pathogens at low biosafety.
• An early draft of the Defuse proposal stated that the Wuhan lab would do their virus work at BSL-2 to make it “highly cost-effective.” Dr. Baric added a note to the draft highlighting the importance of using BSL-3 to contain SARS-like viruses that could infect human cells, writing that “U.S. researchers will likely freak out.” Years later, after SARS‑CoV‑2 had killed millions, Dr. Baric wrote to Dr. Daszak : “I have no doubt that they followed state determined rules and did the work under BSL-2. Yes China has the right to set their own policy. You believe this was appropriate containment if you want but don’t expect me to believe it. Moreover, don’t insult my intelligence by trying to feed me this load of BS.”
• SARS‑CoV‑2 is a stealthy virus that transmits effectively through the air, causes a range of symptoms similar to those of other common respiratory diseases and can be spread by infected people before symptoms even appear. If the virus had escaped from a BSL-2 laboratory in 2019, the leak most likely would have gone undetected until too late.
• One alarming detail — leaked to The Wall Street Journal and confirmed by current and former U.S. government officials — is that scientists on Dr. Shi’s team fell ill with Covid-like symptoms in the fall of 2019 . One of the scientists had been named in the Defuse proposal as the person in charge of virus discovery work. The scientists denied having been sick .

4 The hypothesis that Covid-19 came from an animal at the Huanan Seafood Market in Wuhan is not supported by strong evidence.

• In December 2019, Chinese investigators assumed the outbreak had started at a centrally located market frequented by thousands of visitors daily. This bias in their search for early cases meant that cases unlinked to or located far away from the market would very likely have been missed. To make things worse, the Chinese authorities blocked the reporting of early cases not linked to the market and, claiming biosafety precautions, ordered the destruction of patient samples on January 3, 2020, making it nearly impossible to see the complete picture of the earliest Covid-19 cases. Information about dozens of early cases from November and December 2019 remains inaccessible.
• A pair of papers published in Science in 2022 made the best case for SARS‑CoV‑2 having emerged naturally from human-animal contact at the Wuhan market by focusing on a map of the early cases and asserting that the virus had jumped from animals into humans twice at the market in 2019. More recently, the two papers have been countered by other virologists and scientists who convincingly demonstrate that the available market evidence does not distinguish between a human superspreader event and a natural spillover at the market.
• Furthermore, the existing genetic and early case data show that all known Covid-19 cases probably stem from a single introduction of SARS‑CoV‑2 into people, and the outbreak at the Wuhan market probably happened after the virus had already been circulating in humans.

An analysis of SARS-CoV-2’s evolutionary tree shows how the virus evolved as it started to spread through humans.

SARS-COV-2 Viruses closest

to bat coronaviruses

more mutations

Source: Lv et al., Virus Evolution (2024) , as reproduced by Jesse Bloom

The viruses that infected people linked to the market were most likely not the earliest form of the virus that started the pandemic.

• Not a single infected animal has ever been confirmed at the market or in its supply chain. Without good evidence that the pandemic started at the Huanan Seafood Market, the fact that the virus emerged in Wuhan points squarely at its unique SARS-like virus laboratory.

5 Key evidence that would be expected if the virus had emerged from the wildlife trade is still missing.

In previous outbreaks of coronaviruses, scientists were able to demonstrate natural origin by collecting multiple pieces of evidence linking infected humans to infected animals.

Infected animals

Earliest known

cases exposed to

live animals

Antibody evidence

of animals and

animal traders having

been infected

Ancestral variants

of the virus found in

Documented trade

of host animals

between the area

where bats carry

closely related viruses

and the outbreak site

Infected animals found

Earliest known cases exposed to live animals

Antibody evidence of animals and animal

traders having been infected

Ancestral variants of the virus found in animals

Documented trade of host animals

between the area where bats carry closely

related viruses and the outbreak site

For SARS-CoV-2, these same key pieces of evidence are still missing , more than four years after the virus emerged.

For SARS-CoV-2, these same key pieces of evidence are still missing ,

more than four years after the virus emerged.

• Despite the intense search trained on the animal trade and people linked to the market, investigators have not reported finding any animals infected with SARS‑CoV‑2 that had not been infected by humans. Yet, infected animal sources and other connective pieces of evidence were found for the earlier SARS and MERS outbreaks as quickly as within a few days, despite the less advanced viral forensic technologies of two decades ago.
• Even though Wuhan is the home base of virus hunters with world-leading expertise in tracking novel SARS-like viruses, investigators have either failed to collect or report key evidence that would be expected if Covid-19 emerged from the wildlife trade . For example, investigators have not determined that the earliest known cases had exposure to intermediate host animals before falling ill. No antibody evidence shows that animal traders in Wuhan are regularly exposed to SARS-like viruses, as would be expected in such situations.
• With today’s technology, scientists can detect how respiratory viruses — including SARS, MERS and the flu — circulate in animals while making repeated attempts to jump across species . Thankfully, these variants usually fail to transmit well after crossing over to a new species and tend to die off after a small number of infections. In contrast, virologists and other scientists agree that SARS‑CoV‑2 required little to no adaptation to spread rapidly in humans and other animals . The virus appears to have succeeded in causing a pandemic upon its only detected jump into humans.

The pandemic could have been caused by any of hundreds of virus species, at any of tens of thousands of wildlife markets, in any of thousands of cities, and in any year. But it was a SARS-like coronavirus with a unique furin cleavage site that emerged in Wuhan, less than two years after scientists, sometimes working under inadequate biosafety conditions, proposed collecting and creating viruses of that same design.

While several natural spillover scenarios remain plausible, and we still don’t know enough about the full extent of virus research conducted at the Wuhan institute by Dr. Shi’s team and other researchers, a laboratory accident is the most parsimonious explanation of how the pandemic began.

Given what we now know, investigators should follow their strongest leads and subpoena all exchanges between the Wuhan scientists and their international partners, including unpublished research proposals, manuscripts, data and commercial orders. In particular, exchanges from 2018 and 2019 — the critical two years before the emergence of Covid-19 — are very likely to be illuminating (and require no cooperation from the Chinese government to acquire), yet they remain beyond the public’s view more than four years after the pandemic began.

Whether the pandemic started on a lab bench or in a market stall, it is undeniable that U.S. federal funding helped to build an unprecedented collection of SARS-like viruses at the Wuhan institute, as well as contributing to research that enhanced them . Advocates and funders of the institute’s research, including Dr. Fauci, should cooperate with the investigation to help identify and close the loopholes that allowed such dangerous work to occur. The world must not continue to bear the intolerable risks of research with the potential to cause pandemics .

A successful investigation of the pandemic’s root cause would have the power to break a decades-long scientific impasse on pathogen research safety, determining how governments will spend billions of dollars to prevent future pandemics. A credible investigation would also deter future acts of negligence and deceit by demonstrating that it is indeed possible to be held accountable for causing a viral pandemic. Last but not least, people of all nations need to see their leaders — and especially, their scientists — heading the charge to find out what caused this world-shaking event. Restoring public trust in science and government leadership requires it.

A thorough investigation by the U.S. government could unearth more evidence while spurring whistleblowers to find their courage and seek their moment of opportunity. It would also show the world that U.S. leaders and scientists are not afraid of what the truth behind the pandemic may be.

More on how the pandemic may have started

Where Did the Coronavirus Come From? What We Already Know Is Troubling.

Even if the coronavirus did not emerge from a lab, the groundwork for a potential disaster had been laid for years, and learning its lessons is essential to preventing others.

By Zeynep Tufekci

Why Does Bad Science on Covid’s Origin Get Hyped?

If the raccoon dog was a smoking gun, it fired blanks.

By David Wallace-Wells

A Plea for Making Virus Research Safer

A way forward for lab safety.

By Jesse Bloom

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

Follow the New York Times Opinion section on Facebook , Instagram , TikTok , WhatsApp , X and Threads .

Alina Chan ( @ayjchan ) is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “ Viral : The Search for the Origin of Covid-19.” She was a member of the Pathogens Project , which the Bulletin of the Atomic Scientists organized to generate new thinking on responsible, high-risk pathogen research.

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The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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Globally, Biden Receives Higher Ratings Than Trump

• 1. Views of the U.S.

Table of Contents

• Views of the U.S.
• Confidence in Biden, Trump and other world leaders
• Differences by ideology, age and gender
• 2. Confidence in Joe Biden
• 3. Confidence in Donald Trump
• 4. Comparing confidence in Macron, Putin and Xi to ratings of Biden and Trump
• Biden’s handling of global economic problems
• Biden’s handling of climate change
• Biden’s handling of China
• Biden’s handling of the Russia-Ukraine war
• Biden’s handling of the Israel-Hamas war
• 6. Is U.S. democracy a good example to follow?
• Appendix A: Favorability of the United States since 2000
• Appendix B: Confidence in the U.S. president since 2001
• Acknowledgments
• About Pew Research Center’s Spring 2024 Global Attitudes Survey

Overall, views of the U.S. are more positive than negative across the 34 countries surveyed. A median of 54% hold a favorable opinion of the U.S., while a median of 31% have an unfavorable opinion.

Poles are most likely to evaluate the U.S. positively: 86% hold a favorable view, though this share has declined 7 percentage points since last year. Half or more express a positive view in Hungary, Italy and the UK. In the other European countries surveyed, views of the U.S. are roughly split. 

In the Asia-Pacific region, 70% or more rate the U.S. positively in Japan, the Philippines, South Korea and Thailand. In contrast, half or more see the U.S. unfavorably in Australia, Malaysia and Singapore.

The U.S. receives the lowest ratings of the survey in Tunisia and Turkey, where 80% or more have a negative opinion. Roughly three-quarters of Israelis have a positive view of the U.S.

Publics in the sub-Saharan African and Latin American countries surveyed tend to view the U.S. favorably. 

Opinions of the U.S. have grown less positive among some notable allies since last year. For example, 40% of Australians now hold a positive view of the U.S., compared with 52% in 2023. Ratings of the U.S. are also down among several key NATO allies.

Positive ratings have also declined in Tunisia, where we last surveyed in 2019. Then, 33% of adults viewed the U.S. favorably, compared with only 9% today.

In Turkey, which gives the second-lowest ratings of the U.S. in the survey, views have been consistently negative since we first started polling there in 2002.

In Chile, Colombia, Ghana and Peru, the share with a positive view of the U.S. has increased since we last asked this question in 2017. We have seen a similar increase in many other countries since 2017 – during the first year of Trump’s presidency – despite declines in the last couple years.

Views of the U.S. have also become slightly more positive since last year in two countries: Roughly half of adults in Hungary (52%) now have a positive view of the U.S., compared with 44% last year. In Kenya, where President William Ruto’s recent visit to the U.S. was announced right before fieldwork began, more have a favorable view of the U.S. today than in 2023 (78% vs. 71%).

Read Appendix A  for views of the U.S. from 2000 to now.

Ideological and age differences

In many countries, people on the ideological right and adults under 35 are more likely than others to rate the U.S. positively.

Canada is a good example of the ideological divide: A majority of adults who place themselves on the right (66%) have a favorable opinion of the U.S., compared with only 37% of those on the left.

The age gap in positive views of the U.S. is seen in Canada, Hungary, India, Singapore, South Africa, South Korea, Sri Lanka, Thailand, Turkey and the Latin American countries surveyed. In Turkey, as an example, 29% of adults under 35 rate the U.S. favorably, compared with only 7% of those ages 50 and older.

In Australia, Israel and Sweden, the age pattern is reversed: For example, 85% of older Israelis and 72% of younger Israelis have a positive assessment of the U.S.

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• NATURE INDEX
• 09 August 2023

Mapping China’s shifting research collaboration

China’s rapid rise in global science was an established trend, but the past few years — especially since the COVID-19 pandemic hit in 2020 — have seen new patterns emerging. International collaboration has fallen with some nations and research strengths are being spread among more Chinese institutions.

Close partners

China’s strongest partners after the United States (see ‘Out of favour’) all increased their collaborative output with China between 2019 and 2022, but some recorded a dip in 2021. Singapore replaced Japan in 2021 as China’s fifth strongest collaborative partner.

Source: Nature Index. Data analysis by Bo Wu. Infographic by Simon Baker, Bec Crew and Tanner Maxwell.

Out of favour

The United States’ most productive partnership is with China, however their collaborative output has dropped by 15% since 2020. A similar trend is seen for Canada, China’s seventh largest collaborative partner, with a 13% drop since its 2020 peak.

Lion’s share

From 2015 to 2021, China’s growing Share in the Nature Index seems to have added to total global Share. In 2022, however, there was a significant drop in Share from the rest of the world, meaning that China’s research is taking up a higher proportion of total global Share.

Local talent

China’s Share per Count, which measures the ratio of China-affiliated authors to each publication, increased significantly between 2020 and 2022 — a sign that the country’s high-quality research is becoming more homegrown. COVID-19 restrictions on cross-border collaborations are likely to have been a factor.

Quality clusters

The 10 leading Chinese institutions in 2022 accounted for one-third of China’s Share in the Nature Index, down from the 46% contribution made by the same institutions in 2015. In other nations, research concentration among the leading institutions in 2022 has stayed broadly the same.

Nature 620 , S9 (2023)

doi: https://doi.org/10.1038/d41586-023-02161-z

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Evergrande’s NEV unit plunges on China’s order to refund US$262 million in state subsidies

• The Guangzhou-based carmaker was ordered to return 1.9 billion yuan (US$261.9 million) in state subsidies, according to a statement

China Evergrande New Energy Vehicle Group (NEV) plunged by the most in nearly three years, after the Chinese government ordered the unit of China Evergrande Group to return all its state subsidies, adding to the financial woes of the world’s most indebted developer.

Evergrande NEV’s shares plunged by as much as 26.7 per cent in recent trading to 31.5 Hong Kong cents in the city’s stock market, the lowest intraday level in almost a month.

The Guangzhou-based carmaker was ordered to return 1.9 billion yuan (US$261.9 million) it had received as subsidies from various local authorities because it failed to meet its contractual obligations, according to an overnight statement to the Hong Kong stock exchange.

The company failed to fulfil its obligation to set up a headquarters, and did not meet its production and sales goals, causing a local authority to terminate its April 2019 agreement with Evergrande NEV, according to the statement, which did not identify the authority.

Evergrande NEV has to return the subsidies within 15 days of the notice, or risk losing its assets, including the equipment, factory building and the land allocated to build its car assembly, the statement said.

A refund could “have a material impact on the financial position and operations” of Evergrande NEV or each of the relevant subsidiaries, the carmaker said, adding that it will apply for an administrative review on this decision.

A subsidiary of the carmaker in Tianjin received a separate order to stop producing and selling electric cars, according to a separate statement. Evergrande NEV said it has “actively rectified the issues after the inspection” and intends to appeal against the stop-work order.