Determinants of research collaboration towards a knowledge-based economy in Ghana

Abstract

<jats:p> The purpose of this study was to analyse the determinants of the intention of academic researchers to collaborate on research projects with the carriers of innovation. An explanatory sequential mixed-methods approach was employed to analyse survey data from 266 stratified sampled researchers and 11 key informants from different disciplines in two of Ghana’s public universities. Analysis of variance results showed a quite high intention to collaborate, with no statistically significant differences across disciplines. Regression results indicate that attitude was the leading predictor of intention to collaborate, and it was explained by the conviction and relevance attached to the capacity of research collaboration to speed up career advancement, to be a source of income and to be a means of advancing research work. Perceived behavioural control, explained by research capability and boundary-spanning skills, and environmental possibility, made up of funding, reward and administrative support, also influenced the intention of respondents to engage in research collaboration. The authors therefore propose that the universities should acknowledge and count research collaboration as a criterion in the promotion of academics and, together with national actors, should spearhead the establishment of a national research and innovation fund, research and innovation award schemes, and the requisite administrative support. </jats:p>

Workforce development and higher education in Ghana: A symmetrical relationship between industry and higher education institutions

“…Importantly, HEIs are often faced with the responsibility of developing new programmes as well as generating new knowledge and seeking funds to undertake research activities (Ankrah and Omar, 2015), while firms are expected to develop innovative products that appeal to the needs of customers. While this study did not reveal any relationship between the participating firms and HEIs concerning the provision of financial support for the promotion of academic programmes as well as the development of the knowledge and skills of students and staff through research activities, other authors have endorsed the importance of such collaboration (see Lee-Davies, 2019; Mensah and Enu-Kwesi, 2018; Tseng et al, 2018). When the relationship between HEIs and industry is asymmetrical – operating primarily to the benefit of only one party (in the above case, the HEI) – it does not encourage industry to continue to engage with the HEI.…”

“…The intention of academics to engage in research collaboration is essential to the development of students’ knowledge and skills as well as of research activities. A study by Mensah and Enu-Kwesi (2018) found that the intention of academics to engage in research collaboration with firms was influenced by their attitude towards collaboration, their perceived control over such collaboration and their perception of the conduciveness of the environment for collaboration. Similar research by Lee-Davies (2019) revealed the importance of a strategic approach in HEIs to train senior staff to help academics understand and respond to the demands of industry–HEI collaboration and so to meet the broad objectives of their institution.…”

“…This, however, requires collaboration between industry and HEIs in the form of joint programme development and research project funding. Previous research in similar contexts has focused on the determinants of research collaboration between HEIs and industry aimed at developing a knowledge-based economy (Mensah and Enu-Kwesi, 2018). Although Mensah and Enu-Kwesi (2018) analysed the determinants of the intention of academic researchers to collaborate on research projects with the carriers of innovation, the authors relied on data from only two universities in Ghana.…”

The Influence of Family Business and Social Capital on Entrepreneurial Intentions among Female University Students in the Philippines

“…The correlations analysis was used to identify the nature and magnitude of the bivariate relationship between the variables utilized in the study. The latent composite variables were created through aggregation and averaging of the items scales for regression analysis as recommended by previous scholars such as Cheung & Vogel (2013) and Mensah & Enu-Kwesi (2018). The composite variables created were then used in the multiple regression model analysis to estimate the coefficients using the SPSS version 18.0.…”