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Network Locations or Embedded Resources? The Effects of Entrepreneurs’ Social Networks on Informal Enterprise Performance in Ethiopia

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Abstract

Unlike the industrialized economies where economic exchange is mainly based on impersonal transactions, African economies rely heavily on interpersonal relationships and social networks. Though the study of social networks in African economies is not new, quantitative perspectives on returns of social networks in the informal sector have rarely been the subject of empirical analysis. While studies in Ethiopia have documented how rural households use their networks to improve agricultural productivity and livelihoods, little is known about the contribution of networks in the informal economy. Yet, debates are prevalent on the contribution of social networks in enterprise performance as their effects vary depending on the context of study. This paper thus examines the effects of entrepreneurs’ social networks on informal enterprise performance. Multi-stage sampling procedures involving purposive and systematic random-walk techniques were employed to draw samples. Ego-network data were collected through name generator and interpreter surveys constructed on the basis of regular relations of people related to resources needed and obtained by entrepreneurs for the operation of businesses. The data were analyzed using social network analysis and statistical procedures. Multiple regression models were used to investigate the extent to which an entrepreneurs’ location in networks and embedded resources affect enterprise performance. The findings revealed that while the diversity of contact resources has a significant positive effect on enterprise performance, an entrepreneurs’ location in a network has a significant negative effect.

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Notes

  1. A working definition of micro-enterprises in the Ethiopian context is that they are the smallest, usually informally organized businesses engaged in diverse activities including trade, services, handicrafts, etc. They are typically operated by the owner and immediate family (usually unpaid labor) and the income from the micro-enterprise is in most cases the sole source of income for the family (Desta 2010).

  2. Constraint is a measure of network structure. It measures the extent to which a network is directly or indirectly concentrated in a single alter. If all contacts of an ego are connected to each other (have dense network structure), then the ego is highly constrained (Burt, 2004). Constraint index shows the extent to which all of an entrepreneur’s network time and energy are concentrated on limited contacts. An entrepreneur with high network constraint depends on a small number of contacts within the network (Burt 1992).

  3. The random-walk technique used in this study is different from the one used to sample nodes in networks. In the case of this paper, individual street vendors, not nodes, were selected following a random-walk procedure by walking on foot in street vending cluster sites. However, a key purpose of random walks in network applications is to perform node sampling.

  4. E-NET is a social network analysis software focusing on the analysis of ego-network data. E-NET accepts data related to three aspects: ego’s characteristics, connection between ego and his/her alter, and relationships between alters (Borgatti 2006).

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Authors and Affiliations

  1. Centre for African and Oriental Studies, College of Social Sciences, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia

    Getahun Fenta Kebede

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Correspondence to Getahun Fenta Kebede.

Appendices

Appendix 1

Table 4 Distribution of samples with their sub-cities and cluster sites
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Appendix 2

Table 5 Coefficient of correlation (r) between the instrumental variables, SN measures, and enterprise profit
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Kebede, G.F. Network Locations or Embedded Resources? The Effects of Entrepreneurs’ Social Networks on Informal Enterprise Performance in Ethiopia. J Knowl Econ 11, 630–659 (2020). https://doi.org/10.1007/s13132-018-0565-6

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