The Structure of Collaboration Networks: An Illustration of Indian Economics

By Krishna, M.; Paul, G. D. Bino | Journal of Social Structure, January 1, 2017 | Go to article overview

The Structure of Collaboration Networks: An Illustration of Indian Economics


Krishna, M., Paul, G. D. Bino, Journal of Social Structure


1.Introduction

It is well documented in the realm of economics literature that knowledge1 activity, both creation and dissemination of knowledge, is essential for enhancing a country's economic virility (Romer, 1990, Langlois, 2001). Despite the fact that the knowledge is an integral part of the production function, the structure of how different actors are connected to each other in the process of knowledge creation has been a rigorous subject for academic debate. It is observed that the process by which knowledge is being generated is inextricably connected with a concatenation of complex socioeconomic and behavioral aspects, such as institutional background, PhD origin, culture, and social identity, which have empirically been examined under the banner of social network analysis. As a scholarly theme, the application of social network analysis in deciphering the topology of structural connectedness has attracted profound intellectual curiosity, which is reflected very well in contemporary literature (Cowan et al. 2000; Langlois, 2001; Klamer and van Dalen, 2002; Cowan and Jonard, 2004). Among researchers, there is disagreement over what sort of social network configurations is imperative to enhance the knowledge activity and scientific productivity. There are two kinds of network forms that are central to the academic discussion: dense and sparse. While proponents of a densely connected structure argue that high degree of connectedness among actors has tremendous potential to generate new knowledge and innovative ideas by facilitating fast-flowing sharing of information, proponents of sparse networks, which are characterized by a low degree of links among actors, suggest that agents act strategically to form competitive advantageous in such a way that the interaction between two agents is facilitated by a third actor (Granovetter 1973, Burt 1992, Uzzi 1997).

In this context, there are two specific aspects that need to be dealt with. First, though the extant literature posits that the structure of knowledge activity wittingly or unwittingly is embedded in complex social forces, little research has been carried out in establishing a link between the degree of connectedness and visibility of actors in the structure. Second, there is hardly any attempt to extend the application of social network analysis to scholarly collaborations in developing countries, particularly India. Presumably, this deficit may have roots in the difficulty of obtaining the data on scholarly collaboration, which is mainly due to the poorly organized archive of authorship databases. In this study, we present an illustration of Indian economics in a dynamic framework under the expectation that the collaboration networks will be sparse. The following are the three research questions. First, what shapes the design of the collaboration networks? Second, does the organization of collaboration networks change over a period of time? Third, does the size of the collaboration matter in promulgating innovative ideas in the academic field? To answer these questions, we apply the framework of social network analysis to co-authorship data gleaned from six Indian economics journals, spanning from 1966 to 2005. The paper is exploratory, examining the nature of changes in scholarly collaboration in the journals using descriptive network methods - the size of the main component, average path length, average degree, and clustering coefficient.

The remainder of this study is organized into five sections. Section 2 provides a compendium of literature on social network models and the real-world networks in various disciplines, including neuroscience, physics, economics, and sociology. A detailed description of the methodology, which covers sample journals, data sources, network concepts and methods with an illustration of hypothetical data is given in section 3, followed by findings in section 4. The last section provides discussion and concluding remarks. …

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