Diversified resources and academic influence: patterns of university–industry collaboration in Chinese research-oriented universities

Scientometrics

Volumn 104, Issue 2, 2015, Pages 489-509

  Fan, Xia ^a   Yang, Xiaowan ^a   Chen, Liming ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Chinese universities; Co authored publications; Latent cluster analysis; University industry collaborations

Indexed keywords

EID: 84937641796     PISSN: 01389130     EISSN: 15882861     Source Type: Journal    
DOI: 10.1007/s11192-015-1618-2     Document Type: Article

References (65)

1. Abramo, G., D’Angelo, C. A., Di Costa, F., & Solazzi, M. (2009). University–industry collaboration in Italy: A bibliometric examination. Technovation,29(6), 498–507.
2. Adams, J. D., Black, G. C., Clemmons, J. R., et al. (2005). Scientific teams and institutional collaborations: Evidence from US universities, 1981–1999. Research Policy,34(3), 259–285.
3. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control,AC-19, 716–723.
4. Arguelles, W., et al. (2015). Characterization of metabolic syndrome among diverse Hispanics/Latinos living in the United States: Latent class analysis from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). International Journal of Cardiology,184, 373–379.
5. Auranen, O., & Nieminen, M. (2010). University research funding and publication performance—An international comparison. Research Policy,39(6), 822–834.
6. Azagra-Caro, J. M., Archontakis, F., Gutiérrez-Gracia, A., et al. (2006). Faculty support for the objectives of university–industry relations versus degree of R&D cooperation: The importance of regional absorptive capacity. Research Policy,35(1), 37–55.
7. Biernacki, C., Celeux, G., & Govaert, G. (2003). Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models. Computational Statistics & Data Analysis,41, 561–575.
8. BIS (Department of Business, Innovation and Skills). (2011). Innovation and research strategy and growth. London: The Stationery Office.
9. Bulteel, K., Wilderjans, T. F., Tuerlinckx, F., Ceulemans, E. (2013). CHull as an alternative to AIC and BIC in the context of mixtures of factor analyzers. Behavior Research Methods, 45(3), 782–791.
10. Chen, D., & Li-Hua, R. (2011). Modes of technological leapfrogging: Five case studies from China. Journal of Engineering and Technology Management,28(1), 93–108.
11. D’Este, P., Tang, P., Mahdi, S., Neely, A., & Sánchez-Barrioluengo, M. (2013). The pursuit of academic excellence and business engagement: Is it irreconcilable? Scientometrics,95(2), 481–502.
12. Dias, J. G. (2006). Latent class analysis and model selection. In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nürnberger, & W. Gaul (Eds.), From data and information analysis to knowledge engineering (pp. 95–102). Berlin: Springer.
13. Dietz, J. S., & Bozeman, B. (2005). Academic careers, patents, and productivity: Industry experience as scientific and technical human capital. Research Policy,34(3), 349–367.
14. Draper, D. (1995). Assessment and propagation of model uncertainty. Journal of the Royal Statistical Society Series B, 57, 45–98.
15. Fonseca, J. R. S. (2009). Custer satisfaction study via a latent segment model. Consumer Services,16, 352–359.
16. Fonseca, J. R. S. (2013). Clustering in the field of social sciences: That’s your choice. International Journal of Social Research Methodology,16(5), 403–428. doi:10.1080/13645579.2012.716973.
17. Fonseca, J. R. S., & Cardoso, M. G. M. S. (2007). Mixture-model cluster analysis using information theoretical criteria. Intelligent Data Analysis,11(2), 155–173.
18. Fu, X., & Xiong, H. (2011). Open innovation in China: Policies and practices. Journal of Science and Technology Policy in China,2(3), 196–218.
19. Gazni, A., & Didegah, F. (2011). Investigating different types of research collaboration and citation impact: A case study of Harvard University’s publications. Scientometrics,87(2), 251–265.
20. Gerber, M., Wittekind, A., Grote, G., & Staffelbach, B. (2009). Exploring types of career orientation: A latent class analysis approach. Journal of Vocational Behavior,75, 303–318.
21. Glänzel, W., & Schubert, A. (1992). Some facts and figures on highly cited publications in the sciences, 1981–1985. Scientometrics,25(3), 373–380.
22. Gulbrandsen, M., & Smeby, J. C. (2005). Industry funding and university professors’ research performance. Research Policy,34, 932–950.
23. Han, Z., & Liu, Y. Q. (2010). Web 2.0 applications in top Chinese university libraries. Library Hi Tech,28(1), 41–62.
24. Hayati, Z., & Didegah, F. (2010). International scientific collaboration among Iranian researchers during 1998–2007. Library Hi Tech,28(3), 433–446.
25. HEFCE. (2006). Stratiogic plan 2006–11. Bristol: Higher Education Funding Council for England.
26. Henson, J. M., Reise, S. P., & Kim, K. H. (2007). Detecting mixtures from structural model differences using latent variable mixture modeling: A comparison of relative model fit statistics. Structural Equation Modeling,14(2), 202–226.
27. Hollenstein, H. (2003). Innovation modes in the Swiss service sector: A cluster analysis based on firm-level data. Research Policy,32(5), 845–863.
28. Homma, H., Ikeda, N., Attalage, R. A. (2008). Strengthening university-industry linkage in developing countries through international cooperation: Case of Sri Lanka through cooperation of Toyohashi university of technology, Japan. In M. Iskander (Ed.), Innovative techniques in instruction technology, E-learning, E-assessment, and Education (pp. 432–436). Netherlands: Springer.
29. Jonkers, K., & Tijssen, R. (2008). Chinese researchers returning home: Impacts of international mobility on research collaboration and scientific productivity. Scientometrics,77(2), 309–333.
30. Katz, J. S., & Martin, B. R. (1997). What is research collaboration. Reseach Policy,1(18), 1–18.
31. Kearnes, M. & Wienroth, M. (2009). ‘Arm’s length’? Narratives of impact and autonomy in UK research councils (Working paper). ESRC Project on Strategic Science: Research Intermediaries and the Governance of Innovation. Durham: Department of Geography, Durham University.
32. Kroll, H., & Liefner, I. (2008). Spin-off enterprises as a means of technology commercialization in a transforming economy—Evidence from three universities in China. Technovation,28(5), 298–313.
33. Kwon, K. S., Park, H. W., So, M., & Leydesdorff, L. (2012). Has globalization strengthened South Korea’s national research system? National and international dynamics of the triple helix of scientific co-authorship relationships in South Korea. Scientometrics,90(1), 163–176.
34. Lanza, S. T., Collins, L. M., Lemmon, D. R., & Schafer, J. L. (2007). PROC LCA: A SAS procedure for latent class analysis. Structural Equation Modeling,14(4), 671–694.
35. Laudel, G. (2002). What do we measure by co-authorships? Research Evaluation,11(1), 3–15.
36. Laursen, K., & Salter, A. (2006). Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal,27(2), 131–150.
37. Leydesdorff, L., & Sun, Y. (2009). National and international dimensions of the triple helix in Japan: University–industry–government versus international coauthorship relations. Journal of the American Society for Information Science and Technology,60(4), 778–788.
38. Liang, L., Chen, L., Wu, Y., & Yuan, J. (2012). The role of Chinese universities in enterprise–university research collaboration. Scientometrics,90(1), 253–269.
39. Liu, F. C., Mang, R. K., & Jiang, N. (2011). Research on evolutionary paths of industry–university institute networks of patent collaboration based on the 985 universities. China Soft Science,7, 178–192.
40. Lundberg, J., Tomson, G., Lundkvist, I., Skår, J., & Brommels, M. (2006). Collaboration uncovered: Exploring the adequacy of measuring university–industry collaboration through co-authorship and funding. Scientometrics,69(3), 575–589.
41. Magidson, J., & Vermunt, J. (2004). Latent class models. In D. Kaplan (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 175–198). Thousand Oaks: Sage.
42. Matos, A. L., et al. (2014). Neglect clusters of abusive parenting: A latent class analysis off families referred to child protective services in Portugal. Child Abusement and Neglection,38, 2053–2061.
43. Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics,36(3), 363–377.
44. Mohrman, K. (2003). Higher education reform in mainland Chinese universities: An American’s perspective. Hong Kong: Hong Kong America Center, Chinese University of Hong Kong.
45. Morgan, G. B., Hodge, K. J., Baggett, A. R. (2015). Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices. Computational Statistics and Data Analysis (in press).
46. Motohashi, K., & Muramatsu, S. (2012). Examining the university industry collaboration policy in Japan: Patent analysis. Technology in Society,34(2), 149–162.
47. Nelson, R. R. (2004). The market economy, and the scientific commons. Research Policy,33(3), 455–471.
48. Neves, B. B., & Fonseca, J. R. S. (2015). Latent class models in action: Bridging social capital & internet usage. Social Science Research,50, 15–30.
49. OECD. (2003). Turning science into business, patenting and licensing at public research organizations. Paris: OECD.
50. Perkmann, M., King, Z., & Pavelin, S. (2011). Engaging excellence? Effects of faculty quality on university engagement with industry. Research Policy,40(4), 539–552.
51. Peters, L. S., & Fusfeld, H. (1982). University–industry research relationships. National Science Foundation,235, 236–237.
52. Ru, P., Zhi, Q., Zhang, F., Zhong, X., Li, J., & Su, J. (2012). Behind the development of technology: The transition of innovation modes in China’s wind turbine manufacturing industry. Energy Policy,43, 58–69.
53. Savitskaya, I., Salmi, P., & Torkkeli, M. (2010). Barriers to open innovation: Case China. Journal of Technology Management & Innovation,5(4), 10–21.
54. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics,6, 461–464. doi:10.1214/aos/1176344136.
55. Sclove, S. L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika,52(3), 333–343.
56. Sooryamoorthy, R. (2009). Do types of collaboration change citation? Collaboration and citation patterns of South African science publications. Scientometrics,81(1), 177–193.
57. Tijssen, R. J. W. (2004). Is the commercialisation of scientific research affecting the production of public knowledge?: Global trends in the output of corporate research articles. Research Policy, 33(5), 709–733.
58. Tijssen, R. J., Van Leeuwen, T. N., & Van Wijk, E. (2009). Benchmarking university–industry research cooperation worldwide: Performance measurements and indicators based on co-authorship data for the world’s largest universities. Research Evaluation,18(1), 13–24.
59. Trigo, A., & Vence, X. (2012). Scope and patterns of innovation cooperation in Spanish service enterprises. Research Policy,41(3), 602–613.
60. Vrieze, S. I. (2012). Model selection and psychological theory: A discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Psychological Methods,17, 228–243. doi:10.1037/a0027127.
61. Wang, J., & Shapira, P. (2011). Funding acknowledgement analysis: An enhanced tool to investigate research sponsorship impacts: The case of nanotechnology. Scientometrics,87(3), 563–586.
62. Wong, P. K., & Singh, A. (2013). Do co-publications with industry lead to higher levels of university technology commercialization activity? Scientometrics,97(2), 245–265.
63. Zheng, J., Zhao, Z. Y., Zhang, X., Chen, D. Z., Huang, M. H., Lei, X. P., et al. (2012). International scientific and technological collaboration of China from 2004 to 2008: A perspective from paper and patent analysis. Scientometrics,91(1), 65–80.
64. Zhou, P., & Glänzel, W. (2010). In-depth analysis on China’s international cooperation in science. Scientometrics,82(3), 597–612.
65. Zhou, P., Thijs, B., & Glänzel, W. (2009). Regional analysis on Chinese scientific output. Scientometrics,81(3), 839–857.