Identifying the determinants of individual scientific performance: A perspective focused on AMO theory

  1. Felix Guerrero Alba 1
  2. Fernando Martin Alcazar 1
  3. Gonzalo Sanchez Gardey 1
  1. 1 Universidad de Cádiz
    info

    Universidad de Cádiz

    Cádiz, España

    ROR https://ror.org/04mxxkb11

Revista:
Intangible Capital

ISSN: 1697-9818

Año de publicación: 2021

Volumen: 17

Número: 2

Páginas: 124-147

Tipo: Artículo

DOI: 10.3926/IC.1654 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Intangible Capital

Resumen

Purpose: The aim of this study is to empirically analyse how motivation and the opportunity to investigate enhance the direct relation between the researcher’s human capital and individual scientific performance. Design/methodology: Following recent investigations of strategic human capital and the abilitiesmotivation- opportunity (AMO) theory, we propose a double quantitative-qualitative methodology to identify the determinants of individual scientific performance. Findings: Applying regression analysis to a sample of 471 Spanish academic researchers, we confirm the moderating role of a researcher’s motivation and opportunities. Originality/value: Drawing on the empirical evidence obtained, this work discusses the relevant determinants of scientific productivity, providing practical recommendations for research management and policy making.

Información de financiación

Authors are ordered alphabetically and have contributed equally to this paper. This study was supported by: 1.-The Spanish Ministry of Economy and Competitively under Grant ECO2014-56580-R; 2.-The Andalusian Government (Spain) under Grant P12-SEJ-1810; 3.-The Andalusian Government (Spain) under Grant P12-SEJ-1618; and 4.-Research Projects University of Cadiz under Grant PR2016-018.

Financiadores

    • PR2016-018
    • P12-SEJ-1810

Referencias bibliográficas

  • Auranen, O., & Nieminen, M. (2010). University research funding and publication performance—An international comparison. Research Policy, 39, 822-834. https://doi.org/10.1016/j.respol.2010.03.003
  • Agasisti, T., Catalano, G., Landoni, P., & Verganti, R. (2012). Evaluating the performance of academic departments: An analysis of research-related output efficiency. Research Evaluation, 21, 2-14. https://doi.org/10.1093/reseval/rvr001
  • Agasisti, T., Dal Bianco, A, Landoni, P., Sala, A., & Salerno, M. (2011). Evaluating the Efficiency of Research in Academic Departments: an Empirical Analysis in an Italian Region. Higher Education Quarterly, 65(3), 267-289. https://doi.org/10.1111/j.1468-2273.2011.00489.x
  • Amara, N., Rhaiem, M., & Halilem, N. (2020). Assessing the research efficiency of Canadian scholars in the management field: Evidence from the DEA and fsQCA. Journal of Business Research, 115, 296-306. https://doi.org/10.1016/j.jbusres.2019.10.059
  • Andreeva, T., & Sergeeva, A. (2016). The more the better ... or is it? The contradictory effects of HR practices on knowledge-sharing motivation and behaviour. Human Resource Management Journal, 26(2), 151-171. https://doi.org/10.1111/1748-8583.12100
  • Appelbaum, E., Bailey, T.T., Berg, P., & Kallenberg, A. (2000). Manufacturing advantage: Why high-performance work systems pay off. Ithaca, NY: Cornell University Press.
  • Ayaita, A., Pull, K., Backes-Gellner, U. (2019). You get what you ‘pay’for: Academic attention, career incentives and changes in publication portfolios of business and economics researchers. Journal of Business Economics, 89(3), 273-290. https://doi.org/10.1007/s11573-017-0880-6
  • Bäker, A. (2015). Non-tenured post-doctoral researchers´job mobility and research output: An analysis of the role of research discipline, department size, and coauthors. Research Policy, 44, 634-650. https://doi.org/10.1016/j.respol.2014.12.012
  • Barham, B.L., Foltz, J.D., & Prager, D. (2014). Making time for science. Research Policy, 43, 21-31. https://doi.org/10.1016/j.respol.2013.08.007
  • Bazeley, P. (2010). Conceptualising research performance. Studies in Higher Education, 35(8), 889-903. https://doi.org/10.1080/03075070903348404
  • Bell, E., & Bryman, A. (2007). The ethics of management research: An exploratory content analysis. British Journal of Management, 18, 63-77. https://doi.org/10.1111/j.1467-8551.2006.00487.x
  • Beltrán-Martín, I., & Bou-Llusar, J.C. (2018). Examining the intermediate role of employee abilities, motivation and opportunities to participate in the relationship between HR bundles and employee performance. Business Research Quaterly, 21, 99-110. https://doi.org/10.1016/j.brq.2018.02.001
  • Benet-Zepf, A., Marin-Garcia, J., & Küster, I. (2018). Clustering the mediators between the sales control systems and the sales performance using the AMO model: A narrative systematic literature review. Intangible Capital, 14(3), 387-408. https://doi.org/10.3926/ic.1222
  • Bentler, P.M. (1995). EQS Structural Equations Program Manual. Encino, CA: Multivariate Software Inc.
  • Bentley, P.J., & Kyvik, S. (2013). Individual Differences in Faculty Research Time Allocations Across 13 Countries. Research in Higher Education, 54(3), 329-348. https://doi.org/10.1007/s11162-012-9273-4
  • Bland, C.J., Center, B.A., Finstad, D.A., Risbey, K.R., & Staples, J.G. (2005). A theoretical, practical, predictive model of faculty and department research productivity. Academic Medicine : Journal of the Association of American   Medical Colleges, 80(3), 225-237. https://doi.org/10.1097/00001888-200503000-00006
  • Blumberg, M., & Pringle, C. (1982). The missing opportunity in organizational research: Some implications for a theory of work performance. Academy of Management Review, 7(4), 560-569. https://doi.org/10.5465/amr.1982.4285240
  • Bos-Nehles, A.C., Van Riemsdijk, M.J., & Kees-Looise, J. (2013). Employee perceptions of line management performance: Applying the AMO theory to explain the effectiveness of line managers’ HRM implementation, Human Resource Management, 52(6), 861-877. https://doi.org/10.1002/hrm.21578
  • Bouwmans, M., Runhaar, P., Wesselink, R., & Mulder, M. (2019). Stimulating teachers’ team performance through team-oriented HR practices: the roles of affective team commitment and information processing. The International Journal of Human Resource Management, 30(5), 856-878. https://doi.org/10.1080/09585192.2017.1322626
  • Boxall, P., & Purcell, J. (2003). Strategy and Human Resource Management. Basingstoke: Palgrave Macmillan.
  • Bozeman, B., Dietz, J., & Gaughan, M. (2001). Scientific and Technical Human Capital : An Alternative Model for Research Evaluation. International Journal of Technology Management, 22(8), 716-740. https://doi.org/10.1504/IJTM.2001.002988
  • Buchmueller, T.C., Dominitz, J., & Hansen, W.L. (1999). Graduate training and the early career productivity of Ph. D. economists. Economics of Education Review, 18(1), 65-77. https://doi.org/10.1016/S0272-7757(98)00019-3
  • Carayol, N, & Matt, M. (2004). Does research organization influence academic production? Laboratory level evidence from a large European university. Research Policy, 33(8), 1081-1102. https://doi.org/10.1016/j.respol.2004.03.004
  • Cattell, R.B. (1966). The Scree Test for the Number of Factors. Multivariate Behavioral Research, 1, 245-276. https://doi.org/10.1207/s15327906mbr0102_10
  • Chen, Y., Gupta, A., & Hoshower, L. (2006). Factors That Motivate Business Faculty to Conduct Research: An Expectancy Theory Analysis. Journal of Education for Business, 81(4), 179-189. https://doi.org/10.3200/JOEB.81.4.179-189
  • Coff, R., & Kryscynski, D. (2011). Invited Editorial: Drilling for Micro-Foundations of Human Capital-Based Competitive Advantages. Journal of Management, 37(5), 1429-1443. https://doi.org/10.1177/0149206310397772
  • Conway, J.M., & Lance, C.E. (2010). What reviewers should expect from authors regarding common method bias in organizational research. Journal of Business and Psychology, 25, 325-334. https://doi.org/10.1007/s10869-010- 9181-6
  • Cook, W.D., Ramón, N., Ruiz, J.L., Sirvent, I., & Zhu, J. (2019). DEA-based benchmarking for performance evaluation in pay-for-performance incentive plans. Omega, 84, 45-54. https://doi.org/10.1016/j.omega.2018.04.004
  • Curtin, N., Malley, J., & Stewart, A.J. (2016). Mentoring the Next Generation of Faculty: Supporting Academic Career Aspirations Among Doctoral Students. Research in Higher Education, 57, 714-738. https://doi.org/10.1007/s11162-015-9403-x
  • Deemer, E.D., Martens, M.P., & Buboltz, W.C. (2010). Toward a Tripartite Model of Research Motivation: Development and Initial Validation of the Research Motivation Scale. Journal of Career Assessment, 18(3), 292-309. https://doi.org/10.1177/1069072710364794
  • Delamont, S., Atkinson, P., & Parry, O. (1997). Critical mass and doctoral research: reflections on the Harris report. Studies in Higher Education, 22(3), 319-331. https://doi.org/10.1080/03075079712331380926
  • Diem, A., & Wolter, S.C. (2013). The Use of Bibliometrics to Measure Research Performance in Education Sciences. Research in Higher education, 54, 86-114. https://doi.org/10.1007/s11162-012-9264-5
  • Dundar, H., & Lewis, D.R. (1998). Determinants of research productivity in higher education. Research in higher education, 39(6), 607-631. https://doi.org/10.1023/A:1018705823763
  • Durette, B., Fournier, M., & Lafon, M. (2016). The core competencies of PhDs. Studies in Higher Education, 41(8), 1355-1370. https://doi.org/10.1080/03075079.2014.968540
  • Egghe, L. (2008). Mathematical theory of the hand g-index in case of fractional counting of authorship. Journal of the American Society for Information Science and Technology, 59(10), 1608-1616. https://doi.org/10.1002/asi.20845
  • Fox, M.F. (1983). Publication Productivity among Scientists: A Critical Review. Social Studies of Science, 13(2), 285-305. https://doi.org/10.1177/030631283013002005
  • Gonzalez-Brambila, C., & Veloso, F.M. (2007). The determinants of research output and impact: A study of Mexican researchers. Research policy, 36, 1035-1051. https://doi.org/10.1016/j.respol.2007.03.005
  • Hardre, P.L., & Kollmann, S.L. (2012). Motivational Implications of Faculty Performance Standards. Educational Management Administration & Leadership, 40(6), 724-751. https://doi.org/10.1177/1741143212456913
  • Harris, C.M., McMahan, G.C., & Wright, P.M. (2012). Talent and time together: The impact of human capital and overlapping tenure on unit performance. Personnel Review, 41(4), 408-427. https://doi.org/10.1108/00483481211229357
  • Hedjazi, Y., & Behravan, J. (2011). Study of factors influencing research productivity of agriculture faculty members in Iran. Higher education, 62(5), 635-647. https://doi.org/10.1007/s10734-011-9410-6
  • Hicks, D. (2012). Performance-based university research funding systems. Research Policy, 41(2), 251-261. https://doi.org/10.1016/j.respol.2011.09.007
  • Hirsch, J.E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569-16572. https://doi.org/10.1073/pnas.0507655102
  • Horta, H., & Santos, J.M. (2016). The impact of publishing during PhD studies on career research publication, visibility, and collaborations. Research in Higher Education, 57(1), 28-50. https://doi.org/10.1007/s11162-015-9380- 0
  • Iglesias, J.E., & Pecharroman, C. (2007). Scaling the h-index for different scientific ISI fields. Scientometrics, 73(3),303-320. https://doi.org/10.1007/s11192-007-1805-x
  • Janger, J, & Nowotny, K. (2016). Job choice in academia. Research Policy, 45(8), 1672-1683. https://doi.org/10.1016/j.respol.2016.05.001
  • Jiang, K, Lepak, D.P., Hu, J., & Baer, J.C. (2012). How Does Human Resource Management Influence Organizational Outcomes? A Meta-analytic Investigation of Mediating Mechanisms. Academy of Management Journal, 55(6), 1264-1294. https://doi.org/10.5465/amj.2011.0088
  • Johns, G. (2017). Reflections on the 2016 decade award: incorporating context in organisational research. Academy of Management Review, 42, 577-595. https://doi.org/10.5465/amr.2017.0044
  • Kaiser, H.F. (1974). An Index of Factorial Simplicity. Psychometrika, 39, 31-36. https://doi.org/10.1007/BF02291575
  • Käpylä, J, Jääskeläinen, A, & Lönnqvist, A. (2010). Identifying future challenges for productivity research: Evidence from Finland. International Journal of Productivity and Performance Management, 59(7), 607-623. https://doi.org/10.1108/17410401011075620
  • Karasek, R.A. (1979). Job demands, job decision latitude and mental strain. Implications for job redesign. Administrative Science Quarterly, 24, 285-308. https://doi.org/10.2307/2392498
  • Kim, K.Y, Pathak, S, & Werner, S. (2015). When do international human capital enhancing practices benefit the bottom line? An ability, motivation, and opportunity perspective. Journal of International Business Studies, 46(7), 784-805. https://doi.org/10.1057/jibs.2015.10
  • Knies, E, & Leisink P. (2014). Linking people management and extra-rolebehaviour: Results of a longitudinal study. Human Resource Management Journal, 24(1), 57-76. https://doi.org/10.1111/1748-8583.12023
  • Kumar, A, & Thakur, R.R. (2019). Objectivity in performance ranking of higher education institutions using dynamic data envelopment analysis. In press. https://doi.org/10.1108/IJPPM-03-2018-0089
  • Kwiek, M. (2016). The European research elite: A cross-national study of highly productive academics in 11 countries. Higher Education, 71(3), 379-397. https://doi.org/10.1007/s10734-015-9910-x
  • Landeta, J. (1999). El método Delphi, una técnica de previsión del futuro. Barcelona: Ariel S.A.
  • Lariviere, V, Macaluso, B, Archambault, E, & Gingras, Y. (2010). Which scientific elites? On the concentration of research funds, publications and citations. Research Evaluation, 19, 45-53. https://doi.org/10.3152/095820210X492495
  • Leahey, E, Beckman, C.M, & Stanko, T.L. (2017). Prominent but less productive: the impact of interdisciplinarity on scientifist´s research. Administrative Science Quaterly, 62(1),105-139. https://doi.org/10.1177/0001839216665364
  • Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social studies of science, 35(5), 673-702. https://doi.org/10.1177/0306312705052359
  • Lee, H.F, Miozzo M, & Laredo, P. (2010). Career patterns and competences of PhDs in science and engineering in the knowledge economy: The case of graduates from a UK research-based university. Research Policy, 39(7), 869-881. https://doi.org/10.1016/j.respol.2010.05.001
  • Lepak, D.P, Liao, H, Chung, Y, & Harden, E. (2006). A conceptual review of human resource management systems in strategic human resource management research. Research in Personnel and Human Resource Management, 25(1), 217-271. https://doi.org/10.1016/S0742-7301(06)25006-0
  • Levecque, K, Ansell, F, De Beuckelaer, A, Van der Heyden, J, & Gisle, L. (2017) Work organization and mental health problems in PhD students. Research Policy, 46, 868-879. https://doi.org/10.1016/j.respol.2017.02.008
  • Lindell, M.K, & Whitney, D.J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of applied psychology, 86(1), 114. https://doi.org/10.1037/0021-9010.86.1.114
  • Lissoni, F, Mairesse, J, Montobbio, F, & Pezzoni, M. (2011). Scientific productivity and academic promotion: a study on French and Italian physicists. Industrial and Corporate Change, 20(1), 253-294. https://doi.org/10.1093/icc/dtq073
  • Lovitts, B.E. (2005). Being a good course-taker is not enough: A theoretical perspective on the transition to independent research. Studies in Higher Education, 30(2), 137-154. https://doi.org/10.1080/03075070500043093
  • MacDuffie, J.P. (1995). Human resource bundles and manufacturing performance: Organizational logic and flexible production systems in the world auto industry. Industrial and Labor Relations Review, 48(2), 197-221. https://doi.org/10.1177/001979399504800201
  • Marie, J. (2008). Postgraduate science research skills: the role of creativity, tacit knowledge, thought styles and language. London Review of Education, 6(2), 149-158. https://doi.org/10.1080/14748460802185136
  • Marin-Garcia, J.A, & Martinez-Tomas, J. (2016). Deconstructing AMO framework: A systematic review Intangible Capital, 12(4), 1040-1087. https://doi.org/10.3926/ic.838
  • McNie, E.C, Parris, A, & Sarewitz, D. (2016). Improving the public value of science: A typology to inform discussion, design and implementation of research. Research Policy, 45(4), 884-895. https://doi.org/10.1016/j.respol.2016.01.004
  • Mitchell, T.R. (1982). Motivation: New directions for theory, research and practice. Academy of Management Review, 7(1), 80-88. https://doi.org/10.5465/amr.1982.4285467
  • Mudrak, J., Zabrodska, K., Kveton, P., Jelinek, M., Blatny, M., Solcova, I. et al. (2018). Occupational well-being among university faculty: A job demands-resources model. Research in Higher Education, 59(3), 325-348. https://doi.org/10.1007/s11162-017-9467-x
  • Nguyen, T.L.H. (2016). Building human resources Management capacity for university research: The case at four leading Vietnamese universities. Higher education, 71, 231-251. https://doi.org/10.1007/s10734-015-9898-2
  • Nonaka I., & Takeuchi, H. (1995). The Knowledge-creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press. https://doi.org/10.1016/0024-6301(96)81509-3
  • Okoli, C., & Pawlowski, S.D. (2004). The Delphi method as a research tool: an example, design considerations and applications. Information & Management, 42(1), 15-29. https://doi.org/10.1016/j.im.2003.11.002
  • Papadimitriou, M., & Johnes, J. (2018). Does merging improve efficiency? A study of English universities. In Press. https://doi.org/10.1080/03075079.2018.1450851
  • Ployhart, R.E., & Moliterno, T.P. (2011). Emergence of the human capital resource: A mulitlevel model. Academy of Management Review, 36(1), 127-150. https://doi.org/10.5465/amr.2009.0318
  • Peng, J.E., & Gao X. (2019). Understanding TEFL Academics’ Research Motivation and Its Relations with Research Productivity. SAGE Open, 9(3), 2158244019866295. https://doi.org/10.1177/2158244019866295
  • Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., & Podsakoff, N.P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. https://doi.org/10.1037/0021-9010.88.5.879
  • Prpic, K. (1996). Characteristics and determinants of eminent scientists’ productivity. Scientometrics, 36(2), 185-206. https://doi.org/10.1007/BF02017313
  • Rorstad, K., & Aksnes, D.W. (2015). Publication rate expressed by age, gender and academic position – A largescale analysis of Norwegian academic staff. Journal of Informetrics, 9, 317-333. https://doi.org/10.1016/j.joi.2015.02.003
  • Rowley, J. (2000). Is higher education ready for knowledge management?. International Journal of Educational Management, 14(7), 325-333. https://doi.org/10.1108/09513540010378978
  • Runhaar, P. (2017). How can schools and teachers benefit from human resources management? Conceptualising HRM from content and process perspectives. Educational Management Administration & Leadership, 45(4), 639-656. https://doi.org/10.1177/1741143215623786
  • Sagarra, M., Molinero, C.M., & Agasisti, T. (2017). Exploring the efficiency of Mexican universities: Integrating Data Envelopment Analysis and Multidimensional Scaling. Omega, 67,123-133. https://doi.org/10.1016/j.omega.2016.04.006
  • Shmatko, N., & Volkora, G. (2017). Service or Devotion?. Motivation Patterns of Russian Researchers. Foresight and STI Governance, 11(2),54-66. https://doi.org/10.17323/2500-2597.2017.1.54.66
  • Schuelke-Leech, B.A. (2013). Resources and research: An empirical study of the influence of departmental research resources on individual STEM researchers involvement with industry. Research Policy, 42(9), 1667-1678. https://doi.org/10.1016/j.respol.2013.06.010
  • Siemsen, E., Roth, A.V., & Balasubramanian, S. (2008). How motivation, opportunity, and ability drive knowledge sharing: The constraining-factor model. Journal of Operations Management, 26(3), 426-445. https://doi.org/10.1016/j.jom.2007.09.001
  • Su, X. (2011). Postdoctoral training, departmental prestige and scientists’ research productivity. The Journal of Technology Transfer, 36(3), 275-291. https://doi.org/10.1007/s10961-009-9133-3
  • Sutherland, K.A. (2017). Constructions of success in academia: an early career perspective. Studies in Higher Education, 42(4),743-759
  • Szulc, J.M., Davies, J., Tomczak, M.T., & McGregor, F.L. (2021). AMO perspectives on the well-being of neurodivergent human capital. Employee Relations, 43(4), 858-872. https://doi.org/10.1108/ER-09-2020-0446
  • Szulc, J.M., & Smith, R. (2021). Abilities, Motivations, and Opportunities of Furloughed Employees in the Context of Covid-19: Preliminary Evidence From the UK. Frontiers in Psychology, 12, 635144. https://doi.org/10.3389/fpsyg.2021.635144
  • Thunnissen, M., & Van Arensbergen, P. (2015). A multi-dimensional approach to talent: An empirical analysis of the definition of talent in Dutch academia. Personnel Review, 44(2), 182-199. https://doi.org/10.1108/PR-10-2013- 0190
  • Tiam, J., Nakamori, Y., & Wierzbicki, A.P. (2009). Knowledge management and knowledge creation in academia: A study based on surveys in a Japanese research university. Journal of Knowledge Management, 13(2), 76-92. https://doi.org/10.1108/13673270910942718
  • Tien, F.F. (2008). What Kinds of Faculty Are Motivated to Perform Research by the Desire for Promotion?. Higher Education, 55, 17-32. https://doi.org/10.1007/s10734-006-9033-5
  • Turner, L., & Mairesse, J. (2003). Individual productivity differences in scientific research: An econometric study of the publications of French physicists. Working Paper.
  • Ulrich, W., & Dash D.P. (2013). Research skills for the future: Summary and critique of a comparative study in eight countries. Journal of Research Practice, 9(1), 1-21.
  • Van der Weijden, I., Belder, R., Van Arensbergen, P., & Van den Besselaar, P. (2015). How do young tenured professors benefit from a mentor? Effects on management, motivation and performance. Higher Education, 69(2), 275-287. https://doi.org/10.1007/s10734-014-9774-5
  • Van der Weijden, I., de Gilderb, D., Groenewegenb, P., & Klasenc, E. (2008). Implications of managerial control on performance of Dutch academic (bio) medical and health research groups. Research policy, 37, 1616-1629. https://doi.org/10.1016/j.respol.2008.06.007
  • Van Waeyenber, T., & Decramer, A. (2018). Line managers’ AMO to manage employees’ performance: The route to effective and satisfying performance management. International Journal of Human Resource Management, 29(22), 3093-3114. https://doi.org/10.1080/09585192.2018.1445656
  • Wang, J., Peters, H.P., & Guan, J. (2006). Factors influencing knowledge productivity in German research groups: Lessons for developing countries. Journal of Knowledge Management, 10(4), 113-126. https://doi.org/10.1108/13673270610679408
  • Wang, Z., & Xu, H. (2017). How and when service-oriented high-performance work systems foster employee service performance: A test of mediating and moderating processes. Employee Relations, 39(4), 523-540. https://doi.org/10.1108/ER-07-2016-0140
  • White, C.S., James, K., Burke, L.A., & Allen, R.S. (2012). What makes a research star?. Factors influencing the research productivity of business faculty. International Journal of Productivity and Performance Management, 61(6), 584-602. https://doi.org/10.1108/17410401211249175
  • Wollersheim, J., Lenz, A., Welpe, I.M., & Spörrle, M. (2015). Me, myself, and my university: A multilevel analysis of individual and institutional determinants of academic performance. Journal of Business Economics, 85(3), 263-291. https://doi.org/10.1007/s11573-014-0735-3
  • Wright, P.M., Coff, R., & Moliterno, T.P. (2014). Strategic Human Capital: Crossing the Great Divide. Journal of Management, 40(2), 353-370. https://doi.org/10.1177/0149206313518437
  • Wright, P.M., & McMahan, G.C. (2011). Exploring human capital: putting ‘human’ back into strategic human resource management. Human Resource Management Journal, 21(2), 93-104. https://doi.org/10.1111/j.1748- 8583.2010.00165.x
  • Zucker, L.G., Darby, M.R., Furner, J, Liu, R.C., & Ma, H. (2007). Minerva unbound: Knowledge stocks, knowledge flows and new knowledge production. Research Policy, 36, 850-863. https://doi.org/10.1016/j.respol.2007.02.007