Entrepreneurial Productivity Research Articles

Entrepreneurial Productivity: Sectoral Contribution To The GDP Of A Developing Economy

Using macroeconomic data for the period 1992-2004, this paper applies Granger’s causality adjusted regression model to examine the sectoral contribution to the gross domestic product, as a proxy for entrepreneurial productivity in Nigeria. The study found that only agricultural production and industrial/service output Granger caused changes in GDP, whereas oil production, capacity utilization and non-oil exports had no causality with GDP. The study concludes that oil output and non-oil exports are not significantly contributing to the economy and manufacturing capacity is grossly underutilized. The study recommends increased promotion of non-oil export; an improved operating financial environment; and, greater Nigerian content in the oil sector for increased entrepreneurial productivity.

Introduction

The innovation literature has a long-held tradition of using networks to understand processes of idea generation, opportunity recognition and the diffusion of knowledge. This dates back at least to Schumpeter (1912/1983), who talked about the importance of creating new combinations in the innovation process. However, the most dominant use of the network construct in the innovation research context to date is in its qualitative or metaphorical sense. For example, a study might interview a manager and ask them how important their professional network is for generating new ideas.While this has been a productive line of enquiry, new analytical techniques in graph theory (the quantitative analysis of networks) are only just starting to be applied to innovation research. When used to analyse social relationships, graph theory is generally referred to as network or social network analysis. The roots of this approach date back to the studies by Morello in psychology in the 1930s (Freeman, 2004).As network analysis has moved forward, sophisticated techniques in probabilistic network methods, weighted network and longitudinal network analysis have created further possibilities for understanding the interactions between network structures, agents and innovation across multiple levels of analysis. These techniques have been adopted from the physical sciences, and social network analysis has become complex network analysis (Newman, Barabasi and Watts, 2006). When the technical advances are combined with the recent increases in computing power, it has become much more feasible to use complex network analysis more broadly within the social sciences in general, and in innovation studies in particular.From this research we have begun to understand the importance of network structures and the relationship between agents and these structures in the process of innovation. Initial work in this area has focused on specifying the structure of business networks. For example, there have been several papers identifying networks with a 'small world' structure (short average distance through the network combined with high levels of clustering) (Verspagen and Duysters, 2004). More recent work has started to link structural characteristics of networks to innovation performance (Uzzi and Spiro, 2005; Schilling and Phelps, 2007).This special issue of Innovation: Management, Policy & Practice titled 'New Network Perspectives on the Innovation Process' (ISBN 978-1-921348- 32-7) looks at some of the state-of-the-art research incorporating complex network analysis in the study of the innovation process.The first paper by van der Valk and Gijbers (2010) provides an excellent overview of the use of social network analysis in innovation studies, reviewing all 49 papers using network analysis which have been published in the top 10 innovation journals. They then use social network analysis to identify the key issues that these techniques have been used to study: interpersonal and interorganisational collaboration networks, communication networks and technology and sectoral structures. Citation network analysis is one area of wide application for network analysis techniques. This paper provides a good overview of the use of social network analysis within innovation studies, which provides a useful context for the remaining papers in the special issue.The next paper by Maritz (2010) investigates the interactions between networks and entrepreneurial productivity in universities. He shows that academics with larger networks and with more frequent communication within these networks are both more entrepreneurial and more productive. This is an excellent example of the non-structural network papers. It makes extensive use of network concepts and ideas, and it demonstrates the importance of connections in generating novel ideas.Lee and Su (2010) use techniques that are similar to those of van der Valk and Gijsbers, but in this case their focus is on the research literature on regional innovation systems. …

The Entrepreneurial Revolution and Productivity in Indian Industry

The Entrepreneurial Revolution and Productivity in Indian Industry

Entrepreneurs, Investors, and Equity Financing

We develop a theoretical model of the interaction between investors and entrepreneurs in a stylized private-equity market. Analysis of the entrepreneur's and the investor's optimization problems leads to the derivation of the equilibrium ownership share accruing to the investor; comparative-static analysis of variation in this share then motivates four central hypotheses. We test these using unique data from a professionally-conducted survey of high-technology managers of start-up firms. Empirical analysis confirms the model's prediction of an inverse relationship between the ownership share yielded to the investor and the level of entrepreneurial profitability, productivity, and resources. Results also confirm a predicted positive association between ownership share and investor costs.

Marketing in subsistence marketplaces: consumption and entrepreneurship in a South Indian context

PurposeThe purpose of this paper is to discuss innovative consumer marketing approaches for simultaneous business success and social empowerment at the bottom of the pyramid (BOP) or in subsistence marketplaces.Design/methodology/approachThe paper draws from a research program comprising qualitative methods as well as case study analyses. The central aspect of the approach to this topic is that it is a bottom‐up perspective grounded in understanding consumers. The theoretical scope of the paper includes consumption, entrepreneurship, and social capital in impoverished environments.FindingsThe authors' key finding is that businesses must follow three principles for consumer marketing – deep understanding of subsistence consumer psychology, social embeddedness, and entrepreneurial empowerment.Research limitations/implicationsThis research has implications for theoretical and empirical advancement in the areas of structuring marketing activities, social embeddedness of marketing, and consumer policy.Practical implicationsThis research has implications for several aspects of consumer marketing strategy. The authors categorize these under the following: marketplace research, marketplace solutions, value propositions, communications, partnerships, harnessing social capital, designing marketing structure, and evolving the marketing mindset.Originality/valueThis paper suggests that consumption and entrepreneurial productivity are inextricably linked in subsistence contexts with important implications for consumer marketing. The paper has value to BOP researchers and BOP business practitioners wishing to take a nuanced view to understand their markets and serve them better.

Financing entrepreneurship: Bank finance versus venture capital

This paper examines the entrepreneur's choice between bank finance and venture capital. With bank finance, the entrepreneur keeps full control of the firm and has efficient incentives to exert effort. With venture capital finance, there is a two-sided moral hazard problem as both the entrepreneur and venture capitalist (VC) provide unverifiable effort. The entrepreneur benefits from the VC's managerial input but must surrender partial ownership of the venture, thus diluting the entrepreneur's incentive to provide effort. Venture capital tends to be preferred to bank finance when VC productivity is high and entrepreneurial productivity is low.

Can Entrepreneurship Be “Unproductive?” Towards An Evolutionary Interpretation

Can entrepreneurship ever be unproductive? This provocative question admits of many answers, generally depending upon defini? tional, theoretical and methodological groundings. The preconceptions of nineteenth century classical liberalism would appear to answer the question with a resounding no. When the entrepreneur was considered at all in this scenario, he or she was presented as the hero of the piece. It is well-known, additionally, that as classical economics became neoclassical economic theory, the equilibrating and positivistic mold into which economics was cast virtually eliminated a role for the entrepreneur. Modern theories of rent seeking cast the entrepreneur as a somewhat sinister character. Overt criticism of the entrepreneurial role in rent seeking as unproductive has, in fact, appeared in recent literature (Baumol, 1990). The purpose of this paper is to explore the notion of entrepreneurial productivity from the perspective of economic method and anecdotal (historical) evidence. Specifically, we will argue that so-called productivity of entrepreneurial action pivots critically on conceptions of competition and markets and on the applicability of Pareto Optimality to such arguments. We advance, after theoretical and historical investigation, a generalized Schumpeterian-modern Austrian interpretation of entrepreneurship as an evolutionary value-creating activity, albeit with the inclusion of economizing elements. By

A Time-Series Analysis of Self-Employment in the United States

In the early 1970s the proportion of the nonagricultural labor force self-employed in the United States ceased its downward trend and has been rising ever since. This study provides an analysis of the causes of this change. A general-equilibrium model of self- employment and wage employment is analyzed, and aggregate U.S. time- series data are used to test predictions derived from the model. The empirical analysis indicates that changes in technology, industrial structure, tax rates, and social-security retirement benefits have contributed to the reversal of the previous downward trend, which had persisted for over a century. Copyright 1987 by University of Chicago Press.