Date of Award

1-1-2011

Document Type

Campus Access Dissertation

Department

Moore School of Business

First Advisor

Andrew Spicer

Abstract

In this study, I develop and test an institutional-contingency model for explaining business innovation in low-income markets of less-developed countries. To build the model, I begin with the basic insight of the BOP literature: that there exist both social and business motives for firms to enter impoverished markets. I then extend this assertion by defining poverty as a function of not only income but also institutions; it is not only income poverty that managers need to account for when entering low-income markets, but also the institutional context in which that poverty is embedded. An important implication of the institutional contingency model is that national context will likely shape: 1) the ability of a business innovation formed in one less-developed country to transfer and grow in another; and 2) the conditions when for-profit governance will be more effective than non-profit.

My model also contributes to the international-business literature. IB research that studies the transfer of business practices usually examines the flow of practices from advanced to less-developed countries. In contrast, my model looks at the transfer of indigenous practices created within less-developed countries themselves, a topic rarely examined in the literature.

A challenge of analyzing the transfer of practices across low-income countries is that we do not know which institutions matter in this process. Institutional factors that distinguish among rich countries, or even between rich and poor countries, are not

necessarily those that distinguish among poor countries themselves. For instance, the IB literature often assumes that a country's "regulatory" pillar (as measured by formal laws) will be relatively strong. But, this assumption may not hold in less-developed countries.

To develop specific institutional measures for analyzing differences among less-developed countries, I introduce the concept of "state fragility." This measure has been found to capture variation in the effectiveness of international-aid programs across less-developed countries (Rice & Patrick, 2008). I suggest that differences in state fragility will influence what type of business model will succeed in a particular low-income market.

I test the institutional-contingency model through an analysis of the global growth and commercialization of commercial microfinance. Microfinance, a scheme for provisioning small loans to impoverished entrepreneurs in less-developed countries, is often cited in the literature as the quintessential example of a business solution to global poverty (Prahalad, 2005). It has grown into an industry of tens of millions of borrowers worldwide. Furthermore, policymakers have actively pushed the industry to transition to a for-profit model. Global trends in microfinance thus provide an appropriate backdrop for testing the institutional-contingency model.

To test the institutional-contingency model, I develop two basic hypotheses. The first relates to the institutional contingencies that influence the global growth of microfinance. It predicts that microfinance will be most likely to grow in those countries that possess middle levels of state fragility. The second hypothesis relates to the institutional contingencies that shape the choice between a commercial and non-for-profit governance model for microfinance lending. It predicts that, in countries that have some kind of microfinance sector, the industry will be most likely to use the for-profit model in those countries with less fragility.

Using Random Coefficient Modeling (RCM), I conduct a longitudinal analysis of microfinance in 175 countries. I find support for the institutional-contingency model. State fragility is found to influence the global growth and commercialization of the microfinance industry business model. I then illustrate the effects of state fragility on the global-growth and commercialization of microfinance through two in-depth case studies.

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