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It Takes Two (or More) to Tango

India's coolaborative research

By Dr. Anand Kulkarni

Collaboration, both at home and abroad, in research is one of the keys to success through sharing knowledge, leveraging complementary capabilities, diffusing risk and cost and linking with the world’s “best and the brightest” to solve complex challenges confronting humankind. The Royal Society in the U.K highlights the growing importance of a multi-polar scientific world with widely dispersed research hubs, and with collaboration being critical (Royal Society 2011).

This article looks at the research performance of Indian Institutions [1], especially their collaborative effort, drawing on the comprehensive SciVal database. We benchmark India’s performance against other BRICS countries and the emerging CIVETS- Columbia, Indonesia, Egypt, Turkey and South Africa. Note the “V” for Vietnam is missing as data is unavailable. The U.S is also included as it is still the global benchmark for research endeavour.

Between 2010 and 2015, India produced 644,981 scholarly outputs, which as a proportion of worldwide output was 4%.

India fared well, therefore, in terms of overall papers produced but decidedly short of the global “publication powerhouses” in China and the U.S with 2,533,169 and 3,673,223 or 15.9% and 23% of global publications respectively.

Of further interest is India’s collaborative effort as shown in Table 1. India follows a similar path to that of other countries in terms of having a higher share of internationally collaborative papers than domestic collaboration at 17% and 8.2% respectively. Like most of the countries that we consider, Indian researchers are reaching out to counterparts abroad rather than at home. China (and to a lesser extent Turkey) are exceptions to this, with a stronger domestic collaborative focus, which possibly points to the strong investments China has made in research, science and technology to build the foundational capabilities and connections at home.

A Case of India's Collaborative Research Efforts

India’s international collaborative efforts exceed those of domestic efforts | Photo Courtesy: Pixabay

Table 1: Scholarly Outputs 2010-2015 (all fields)

Number of outputs International Collaboration (%) Domestic Collaboration (%) Institutional Collaboration (%) Academic-corporate collaboration (%)
India 644,981 17% 8.2% 67.6% 0.8%
China 2,533,169 16.9% 20.1% 58.6% 1.5%
Brazil 359,858 26.8% 25.4% 42% 1.2%
Russian Federation 288,427 27.8% 13.4% 43.0% 1.2%
South Africa 96,783 44.2% 7.8% 28.6% 1.4%
Colombia 40,068 46.4% 7.8% 36.5% 0.8%
Indonesia 27,226 47.1% 3.4% 39.6% 0.9%
Egypt 79,394 43.9% 12.0% 31.1% 0.8%
Turkey 223,330 19.8% 20.8% 47.7% 0.7%
U.S 3,673,223 29.7% 19.3% 33.5% 3.1%
Source: SciVal accessed on 7th June 2016

What is also true though is that India’s overall collaborative effort at 25% (both domestic and international) is lower than all other countries without exception including emerging CIVET nations. Indians seem reluctant to break out of their silos and jointly work with others at home or abroad compared to other nations.  What reinforces this is that India has the highest proportion of institutional collaboration of all countries that we consider i.e., Indian researchers collaborate within their own institutions rather than look outward.

There is an absence of a strong functioning innovation and research “eco-system” in India unlike in other countries (see for example, Mathew 2010). Ideally such a system would link constituent actors in a cohesive and coordinated manner, build connections between knowledge development and diffusion and ensure compatibility of objectives across the system.  The absence of compatible objectives is reflected in, for example, a mismatch between public sector driven research and commercial application.

There is also the issue perhaps that research has simply not been a concerted national priority. For example, Gross Expenditure (GERD) on research as a share of GDP is 0.8%, ranking India at a moderate 42nd in the world (out of 141) on this indicator in the Global Innovation Ranking, compared to China which has a GERD/GDP of 2.1% and is ranked 17th on this indicator (Global Innovation Index 2015).

Further reinforcing our argument is India’s weak position in academic-corporate collaboration, those more applied, commercially oriented fields of endeavour, as shown in Table 1.

Collaboration by Field

Table 2 looks at the composition of India’s research outputs between 2010 and 2015 in comparison with China. The first point is that India’s top 5 are dwarfed in volume of output by their Chinese counterparts. (Table 3). Second, however, the top 5 fields are broadly similar for both countries. However, China has a very significant output in materials science, not reflected in the Indian experience. One would expect that this reflect’s China’s strength in manufacturing, and its aspiration to move up the industrial value chain. Further, it should be noted that although not in its “top 5”, chemistry is a very sizeable output for China at 308,655 papers between 2010 and 2015, more than 3.5 times India’s output in this field. For 3 of the top 5 outputs in the tables below, China is more internationally collaborative than India, reflecting the fact that in the “big ticket” fields, Chinese researchers are more likely to reach out to the rest of the world than India.

Table 2: India’s Top 5 Scholarly Outputs by Field 2010-2015

Number of publications % International collaboration % National collaboration
Medicine 146,427 17.1% 6.1%
Engineering 129,813 14.5% 9.3%
Computer Science 91,191 13.3% 7.1%
Chemistry 88,291 20.3% 11.2%
Physics and Astronomy 85,211 26.5% 13.9%
Source: SciVal accessed on 7th June 2016

Table 3: China’s Top 5 Scholarly Outputs by Field 2010-2015

Number of publications % International Collaboration % National Collaboration
Medicine 415,682 20.9% 16.3%
Physics and Astronomy 381,065 18.2% 24.0%
Materials Science 388, 840 16% 23%
Engineering 934,289 11.5% 18.4%
Computer Science 413, 215 17.1% 18%
Source: SciVal accessed on 7th June 2016

Also of importance is China’s strong performance in computer science, an area that one does not always naturally associate with China. Is this an emerging threat to India’s supposed dominance in this field? Is India’s focus on computer science too much at the lower end of the value chain where research is not a core element? Or does India perform technologically advanced capabilities without taking the research route? These and other questions will pose challenges for India as it seeks to further develop its industrial capabilities in computer science, and attempts to deal with competition from China. Correspondingly, despite its dominance in pharmaceuticals (albeit largely through generic drugs), research into pharmacology, toxicology and pharmaceuticals does not make the top 5 in India.

Another interesting factor is that neither country figures prominently in arts and humanities outputs. While recognising that industries of the future will rely heavily on STEM (science, technology, engineering and mathematics), there is an emerging view that nations should not ignore STEAM (STEM plus Arts) as the arts provide other important dimensions including lateral thinking, creativity and alternative perspectives and ways of approaching problems.

Research Impact

Just concentrating on scholarly outputs does not give an accurate picture of the impact of these publications. One measure of impact is published outputs which are cited in patents. This gives some sense of the extent to which publications are reflected in the early process of commercialisation of research.

On this score, drawing on the SciVal database, it is noteworthy that India fares reasonably well (2212 outputs cited in patents between 2010 and 2015), although again short of the powerhouses China (9263) and the U.S (37,229) by a long way, but ahead of all the other countries that we consider.

So, on balance India does derive some value for its research but its volume of outputs and its levels of collaborative interaction require considerable attention.


So what should Indian policy makers and researchers look to do? Firstly, to build, maintain and strengthen the research eco-system by providing incentives (and disincentives not to) to collaborate. One such mechanism could be to free up mobility between researchers in institutions and academia and re-visit hiring policy in academic institutions to recruit people from various backgrounds. Secondly, to invest more heavily in research and development including focusing on collaborative research which links the interests of the nation as a whole with commercial aims. Third is to connect Indian researchers even more into growing and critical research networks leveraging India’s large diaspora abroad. Fourthly, to enhance the quality of research in institutions through clear performance targets, with appropriate actions to support targets, aimed at driving publications in highly acclaimed journals.

Dr. Anand Kulkarni is the Senior Manager, Planning and Research RMIT University in Melbourne Australia overseeing planning, analysis and strategic projects for the University. Anand has previously held Senior Management and Executive roles in the State and Federal Governments of Australia leading large scale policy development. Anand has particular research interests in the Indian Economy, innovation and industry development. Anand is also a Fellow at the Centre For Policy Development in Australia. Anand holds Honors, Masters and Ph.D in Economics.


[1] There are 5 types of institutions in SciVal: Academic (Universities, Colleges, Medical Schools and Research Institutions); Corporate (corporate entities and law firms); Medical (hospitals); and other non Government organisations.


  1. Cornell University, INSEAD and WIPO 2015: The Global Innovation Index 2015: Effective Innovation Policies for Development, Fontainebleau, Ithaca and Geneva
  2. Mathew George Eby 2010 India’s Innovation Blueprint Woodhead Chandos Publishers
  3. The Royal Society 2011 Knowledge, networks and Nations, Global Scientific Collaboration in the 21st Century
  4. SciVal database

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