New approach to create more effective teams in the innovation process in enterprises
Abstract
The subject-related literature provided information about the skills, education, and formal competencies required to join teams working on the innovation process. According to findings presented in this article, the previous studies have investigated insufficiently the gender-related issues in the decisions of managers who involve specialists in the innovation process. Thus, the purpose of this research was to identify, examine, and describe differences in the participation of men and women in the innovation process, considering their personal characteristics, attitudes, and behaviours. The research covered 1,164 innovative companies – beneficiaries of the European Union Cohesion Policy of 2007–2013. The survey was distributed independently to women and men participating in innovative activities in the researched companies. Two independent responses were received from each company; thus, two independent data samples were created. Both data composition and preliminary analysis adhere to the requirements of Principal Component Analysis. The results allow for the new design proposal to increase the effectiveness of teams working on innovation-focused tasks. In addition to education and experience, managers can now consider personal characteristics and better select women and men to drive innovation.
Keyword : innovation management, innovation development, gender research, creation effective teams, decision making in innovative activity, process of innovation, manage new source of innovation progress
How to Cite
Okoń-Horodyńska, E., Zachorowska-Mazurkiewicz, A., Wisła, R., & Sierotowicz, T. (2020). New approach to create more effective teams in the innovation process in enterprises. Journal of Business Economics and Management, 21(3), 805-825. https://doi.org/10.3846/jbem.2020.12221
This work is licensed under a Creative Commons Attribution 4.0 International License.
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George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. Allyn & Bacon.
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Hair, J. F. Jr., Black, W. C., Babin, B. J., & Anderson. R. E. (2014). Multivariate data analysis. Pearson.
Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological Measurement, 66, 393–416. https://doi.org/10.1177/0013164405282485
Hunt, J., Herman, H., & Munroe, D. J. (2013). Why are women underrepresented amongst patentees? Research Policy, 42, 831–843. https://doi.org/10.1016/j.respol.2012.11.004
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Kaiser, H. F., & Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34(1), 111–117. https://doi.org/10.1177/001316447403400115
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Kunze, A., & Miller, A. R. (2017). Women helping women? Evidence from private sector data on workplace hierarchies. Review of Economics and Statistics, 99(5), 769–775. https://doi.org/10.1162/REST_a_00668
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