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Interactive vs. non-interactive knowledge production by faculty members

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  • Joaquin Azagra-Caro
  • Juana Aznar-Marqez
  • Juan Blanco

Abstract

In this article, we develop a model of individual choice to study the determinants of faculty members allocation of effort between interactive and noninteractive activities. This model is tested by using censored and discrete choice econometric models to estimate optimum effort allocated to interactive activities and real interaction. We conclude, first, that individual responds to nonmonetary rather than monetary incentives and to the difficulty of producing noninteractive rather than interactive knowledge. Second, we detect the possible existence of rationing, since optimum effort and real interaction depend on different variables.

Suggested Citation

  • Joaquin Azagra-Caro & Juana Aznar-Marqez & Juan Blanco, 2008. "Interactive vs. non-interactive knowledge production by faculty members," Applied Economics, Taylor & Francis Journals, vol. 40(10), pages 1289-1297.
  • Handle: RePEc:taf:applec:v:40:y:2008:i:10:p:1289-1297
    DOI: 10.1080/00036840600771338
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    References listed on IDEAS

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    1. Alfonso GAMBARDELLA & Bronwyn H. HALL, 2004. "Propriety vs. Public Domain Licensing of Software and Research Products," Economics Working Papers ECO2004/15, European University Institute.
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    Cited by:

    1. Joaquín M. Azagra-Caro & Laura González-Salmerón & Pedro Marques, 2021. "Fiction lagging behind or non-fiction defending the indefensible? University–industry (et al.) interaction in science fiction," The Journal of Technology Transfer, Springer, vol. 46(6), pages 1889-1916, December.
    2. Llopis,Ãscar & Azagra-Caro,Joaquín M., 2015. "Who do you care about? Scientistsâ personality traits and perceived beneficiary impact," INGENIO (CSIC-UPV) Working Paper Series 201503, INGENIO (CSIC-UPV), revised 12 Jan 2018.
    3. Kalantaridis, Christos & Küttim, Merle & Govind, Madhav & Sousa, Cristina, 2017. "How to commercialise university-generated knowledge internationally? A comparative analysis of contingent institutional conditions," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 35-44.
    4. Sándor Huszár & Szabolcs Prónay & Norbert Buzás, 2016. "Examining the differences between the motivations of traditional and entrepreneurial scientists," Journal of Innovation and Entrepreneurship, Springer, vol. 5(1), pages 1-22, December.
    5. Azagra-Caro, Joaquín M. & Tijssen, Robert J.W. & Tur, Elena M. & Yegros-Yegros, Alfredo, 2019. "University-industry scientific production and the Great Recession," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 210-220.
    6. Chee‐Yang Fong & Keng‐Boon Ooi & Boon‐In Tan & Voon‐Hsien Lee & Alain Yee‐Loong Chong, 2011. "HRM practices and knowledge sharing: an empirical study," International Journal of Manpower, Emerald Group Publishing Limited, vol. 32(5/6), pages 704-723, August.
    7. Tur, Elena M. & Azagra-Caro, Joaquín M., 2018. "The coevolution of endogenous knowledge networks and knowledge creation," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 424-434.
    8. Joaquín M. Azagra-Caro & Anabel Fernández-Mesa & Nicolás Robinson-García, 2020. "‘Getting out of the closet’: scientific authorship of literary fiction and knowledge transfer," The Journal of Technology Transfer, Springer, vol. 45(1), pages 56-85, February.

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