Embeddedness, Business Networks and Social Capital:

A Conceptual Framework and an Empirical Example

Arto Kankaanpää, Department of Sociology, University of Turku, Finland, and Mikko Pohjola, Institute for Competition Policy Studies, Turku School of Economics and Business Administration, Finland

Embeddedness has become the core concept of “new” economic sociology. In addition to its metaphorical use, it has mainly been referred to as business-to-business networks when examining enterprises. In this paper, we intend to argue for and present much more complex picture of firms´ networks from a market perspective. We argue that firms are participating, not only in one but in many different types of networks within the market surroundings. An appreciation of this complexity is a crucial first step in appropriately examining and understanding business networks.

In order to understand the role of different types of networks in firms´ everyday activities and behaviour, we need a holistic view of firms´ web of social networks in the marketplace. This allows us to analyse, for example, variation in the network position of an individual firm, and network transitivity, i.e., how different material and immaterial resources are transferred from one network to another within the same firm and/or between different firms or how similar resources are used in different parts of firm´s networks. The material and immaterial gains, i.e., social capital, that firms receive from their membership in various networks are also of various form and nature.

Our empirical example comes from the core (i.e., biopharmaceutical, diagnostic, biomaterial and bioinformational) firms of the biotechnological cluster in Turku, Finland. Biotechnology is a particularly appropriate context in which to study the form and effects of various market networks, because firms in the industry both cluster geographically as well as exhibit high rates of alliance formation and network participation. In addition, in the uncertain market environment of biotechnology the network types tend to be diverse.