Original Research
Knowledge exchange and ethnic networks of clustered small-scale enterprises in Africa: A case study of furniture cluster in Tanzania
Submitted: 08 May 2018 | Published: 16 April 2019
About the author(s)
Yessica C.Y. Chung, Department of Agribusiness Management, National Pingtung University of Science and Technology, Neipu, TaiwanAbstract
Background: Industrial clusters remain at the initial stage in the sub-Saharan Africa (SSA) region. They produce low-quality and similar products that are poorly innovative and therefore unable to expand. Ethnicity is a characteristic imprint of SSA clusters. However, little research has been done on SSA industrial clusters being able to explore ethnic effects on cluster development, in particular the cases where ethnic majority is over-presented.
Aim: This study aims to investigate the effect of ethnic network between ethnic majority and minority on knowledge exchange in clustered micro and small-scale enterprises in Africa.
Setting: This study was undertaken in the furniture cluster located in Arusha City, Tanzania, which has striking features in its ethnic composition of a dominant ethnic majority and a variety of ethnic minorities. A census survey on the 234 clustered furniture enterprises was conducted to collect comprehensive information on production skill and ethnicity at individual level.
Methods: Probit and ordered probit models are employed to analyse the difference in manufacturing skill between the ethnic majority and minority as well as the inter-ethnic and intra-ethnic enterprises.
Results: Results show a positive and significant effect of the strength of the ethnic networks in having advanced skills in furniture production; particularly evident is the skill that is governed by enterprises’ own capability rather than production facilities. Comparing technological skills between the inter-ethnic enterprises and intra-ethnic enterprises, the former are more likely to share similar manufacturing technology with each other than the latter. While individuals in the ethnic majority resemble uniform manufacturing techniques in higher-priced furniture work, the ethnic minority exhibits a similarity in producing common goods.
Conclusion: Ethnic network is a predictor of technological skills of clustered producers in the SSA region. However, the ethnic network effect can only influence the skills that are apparently observed and barely affects capital-intensive technology. These findings indicate the significance of the ethnic networking effect in knowledge exchange in Africa, but remain ineffective in overcoming capital constraints.
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