This book is one of the first comprehensive works to fill the knowledge gap resulting from the limited number of empirical studies on interfirm networks. The in-depth empirical research presented here is based on a massive transaction relationship database of approximately 400,000 Japanese firms. This volume, unlike others, focuses on the role of interfirm networks in three different fields: (1) macroeconomic activities, (2) economic geography and firm dynamics, and (3) firm–bank relationships. The database for this work is constructed in collaboration with Japan's largest credit research company, Teikoku Data Bank, and covers a substantial portion of Japanese firms with information on firms' transaction partners, shareholders, financial institutions, and other attributes, including their locations and performance. Networks prevail in many aspects of economic activities and play a major role in explaining a wide variety of economic phenomena from business cycles to knowledge spillovers, which has motivated economists to produce a number of excellent works. In the policy arena, there has been a growing concern on the vulnerabilities of networks based on the casual observation that idiosyncratic shocks on firms can be amplified through inter-firm connections and leads to a systemic crisis. Typical examples are the manufacturing supply-chain networks in the automobile and electronics industries which propagated regionally concentrated shocks (the Great East Japan Earthquake and floods in Thailand in 2011) into global ones. An abundance of theoretical literature on the formation and functions of networks is available already. This book breaks new ground, however, and provides an excellent opportunity for the reader to gain a more integrated understanding of the role of networks in the economy. The Economics of Interfirm Networks will be of special interest to economists and practitioners seeking empirical and quantitative knowledge on interfirm and firm–bank networks.

This volume examines the nature of interfirm networks and their role in promoting industrial competitiveness. Where previous work in this area has tended to be descriptive, the distinguished contributors to this volume present a balanced theoretical and empirical approach to interfirm networking drawing on a variety of international case studies. I

Developments in technology and globalisation have led to an upsurge in inter-organizational relations. This book surveys the current field, connects differing perspectives and answers questions about who should collaborate, why, and how.

'A Handbook of Industrial Districts is a very well-organized and structured collection of scientific works on the theory of industrial districts.' - Roberta Capello, Regional Studies In this comprehensive original reference work, the editors have brought together an unrivalled group of distinguished scholars and practitioners to comment on the historical and contemporary role of industrial districts.

The purpose of this book is to provide a state-of-the-art overview of current research on spatial industrial clusters and inter-firm networks. Given the current political belief in many countries and regions that clusters can be a major vehicle for economic development and growth, it is important to have a good understanding of industrial clusters and how they emerge, grow, eventually stagnate and disappear. Also an understanding is needed about when and how to apply policy measures to support cluster development to increase economic welfare. This book contributes to the theoretical and empirical understanding of industrial clusters and cluster policies and offers a number of interesting case studies of industrial clusters and inter-firm networks from several different countries.

Today's firms are increasingly embedded in networks of alliances and other ties that influence their behavior and performance. In this, his first book on the subject, Ranjay Gulati examines the 'network resources' that arise from these ties, how successful firms manage these, and how they influence strategy, access to material resources, and perceptions of a firm's legitimacy held by key external parties such as investors and banks. The book synthesises Gulati's influential work on network dynamics from the last fifteen years, and presents the key findings from this extensive body of research. Gulati's insights are important for scholars, students, and practitioners interested in the behavior of firms in an increasingly networked economy. Ranjay Gulati is one of the leading theorists and researchers studying alliances and networks, and has written widely on the subject. His work has been published in leading academic journals such as Administrative Science Quarterly, and in the Harvard Business Review.

In Economics, networks are increasingly used to describe the many links created between independent companies, as well as between them and other institutions (universities, banks, venture capital, etc.). In the current global and knowledge-based economy, they can be characterised as knowledge factories and knowledge boosters. They feed the internal processes of innovation (collaborative innovation) or the external processes of innovation, created by the propagation effects that come from inter-firm collaboration. The book explains how innovation networks are at the origin of the production of new knowledge that will be transformed and used in common as well as in separated production processes. This characteristic of networks as knowledge factories gives incentives to further investment in the production of knowledge and ensures the cumulativeness of the innovation process. Some of the authors clearly take a territorial point of view and study how clusters (in different parts of the world: Europe, Eastern Asia and North America) propelled by the quality of the innovation networks they enclose, can be characterised as knowledge pools into which the local actors will be able to draw to reinforce their individual and collective competitiveness. This book also includes analyses of the quality of the networks built within clusters, which may help their identification.