Employee Tenure and Staff Performance: The Case of a Social Enterprise
In: Journal of business research, 2022, Vol.139, p.457-467
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In: Journal of business research, 2022, Vol.139, p.457-467
SSRN
In: International journal of development issues, Band 20, Heft 1, S. 1-23
ISSN: 1758-8553
PurposeThe purpose of this study is to determine whether there exists employee-client matching at the bottom of the pyramid (BOP) and the most favourable employee-client categorization in terms of employee productivity when serving the BOP market. This is important in a bid to determine how to effectively operate at the BOP given the market's unique characteristics.Design/methodology/approachThis study uses two methods depending on the research question. First, a one-way analysis of variance (ANOVA) is used to determine the different employee-client categories based on socio-economic status. Second, fixed effects analyses are performed based on these categories to determine the most suitable employee-client category.FindingsThe results show the existence of employee-client matching based on similar socio-economic status. However, multivariate testing reveals that the mismatch category, where employees are of higher socioeconomic status than the clients, generates more favourable employee productivity. Moreover, this result may be contingent on the geographical location of the firm.Practical implicationsThe findings are important for human resource management particularly the employment strategy of BOP firms. It suggests the need to consider employee profiles and client profiles when deciding which new markets to target.Originality/valueThe paper uses a global database of microfinance institutions as a case of BOP firms to investigate employee-client matching at the bottom of the pyramid.
In: International Journal of Development Issues, Band 20 No. 1, S. 1-23
SSRN
In: The journal of development studies, Band 58, Heft 2, S. 259-274
ISSN: 1743-9140
World Affairs Online
In: The journal of development studies, Band 58, Heft 2, S. 259-274
ISSN: 1743-9140
SSRN