Network Analysis for Economics and Management Studies

Network Analysis for Economics and Management Studies

Lucio Biggiero
DOI: 10.4018/978-1-7998-2448-0.ch012
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Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.
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Introduction: Different Disciplinary Perspectives

Network analysis research has become so vast that it is almost impossible to give a synthesis of its developments and scope of applications. This impossibility holds also if restricting the review to Social Network Analysis (SNA), under which we can include network-based approaches in anthropology, psychology, sociology (SOC), and economic sciences in a broad sense, which can be further distinguished into economics (ECON), and management and organization sciences (MOS). The first three have been matter of many studies, even (to a less extent) from a historical perspective, while the latter two, which are the specific subject of this volume, have been not yet well reviewed, especially from a historical perspective. Moreover, the few existing contributions are very recent, in particular those concerning network economics, and while some contrasts SOC and ECON (Jackson, 2010a, 2010b) - with the partial exception of Knoke (2012), who restricts the view of network economics only to few themes - no one contrasts ECON and MOS. As it often happens, even though two scientific areas are largely overlapped1, they remain encapsulated into the respective disciplinary boundaries, so hindering a fruitful cross-fertilization. Most researchers in one area do not know the works in the other area. Therefore, the main aim of this chapter is to fill in this gap by directly contrasting ECON and MOS perspectives on network analysis.

There are various accounts of the history of network analysis in general, and SNA in particular. Among the former there is Barabasi’s (2002) fortunate and popular book, and the classic Biggs et al. (1976). Among the latter there are many contributions (Berkowitz, 1982; Leinhardt, 1977; Marsden & Lin, 1982; Scott, 1992), some of which quite recent (Freeman, 2004; Prell, 2011). Leaving aside books dedicated to specific methodological or real topics, there is a certain number of handbooks (Borgatti et al., 2013; Hanneman & Riddle, 2005; Knoke & Kuklinski, 1982; Scott, 1992; Wasserman & Faust, 1994; and the more recent Borgatti et al., 2013; Knoke & Yang, 2008; Robins, 2015; Scott & Carrington, 2011). And of course a lot of readings (Carrington et al., 2005; Wasserman & Galaskiewicz, 1994; Wellman & Berkowitz, 1988; among the many). There are also many books and papers dealing with both fields of social and natural sciences (Barabasi, 2002; Biggiero, 2011; Bornholdt & Schuster, 2003; Caldarelli, 2007; Dehmer & Emmert-Streib, 2009; Lewis, 2009; Newman, 2010; Newman et al., 2006), but with few exceptions they are written by mathematicians or physicists.

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