Learning and Innovation in Inter-Organizational Relationships and Networks

This paper gives a survey of insights into inter-firm alliances and networks for innovation, from a constructivist, interactionist perspective on knowledge, which leads to the notion of 'cognitive distance'.It looks at both the competence and the governance side of relationships.Given cognitive distance, organizations need to align cognition sufficiently to enable the fast and efficient utilization of opportunities from complementary capabilities.This, I propose, is done by means of a culturally mediated 'organizational cognitive focus'.The problem with that is that it yields a greater or lesser organizational myopia that, for the sake of innovation, needs to be complemented by means of outside relations with other firms, at larger cognitive distance. Hence the importance of networks for innovation.On the governance side, the paper gives a review of relational risks and instruments to manage them.Next to the effects of cognitive distance, the paper analyses the effects of density and strength of ties in innovation networks, concerning both competence and governance.inter-organizational relationships;networks;competence;governance;innovation;cognitive distance

Learning to Trust

Trust is full of puzzle and paradox.Trust is both rational and emotional. Trust can go beyond calculative self-interest, but has its limits.People may want to trust, while they may also feel threatened by it.If trust is not in place prior to a relationship, on the basis of institutions, prior experience, or reputation, it has to be built up, in specific relations.For that one needs to learn, in the sense of building empathy, and perhaps a certain degree of identification.In an attempt at a better understanding of the puzzles and processes of trust, this chapter applies the perspective of 'embodied cognition', and insights from mental 'framing' and decision heuristics from social psychology.learning;trust;institutions

Organization, Evolution, Cognition and Dynamic Capabilities

Using insights from ‘embodied cognition’ and a resulting ‘cognitive theory of the firm’, I aim to contribute to the further development of evolutionary theory of organizations, in the specification of organizations as ‘interactors’ that carry organizational competencies as ‘replicators’, within industries as ‘populations’. Especially, I analyze how, if at all, ‘dynamic capabilities’ can be fitted into evolutionary theory. I propose that the prime purpose of an organization is to serve as a cognitive ‘focusing device’. Here, cognition has a wide meaning, including perception, interpretation, sense making, and value judgements. I analyse how this yields organizations as cohesive wholes, and differences within and between industries. I propose the following sources of variation: replication in communication, novel combinations of existing knowledge, and a path of discovery by which exploitation leads to exploration. These yield a proposal for dynamic capabilities. I discuss in what sense, and to what extent these sources of variation are ‘blind’, as postulated in evolutionary theory.evolutionary economics;organization;cognition;dynamic capabilities

Generality, Specificity And Discovery

This paper offers a meta-theory concerning the relation between the general and the specific in science. This issue was recently called back to attention by Hodgson (2001). A heuristic of discovery, developed in earlier work (Nooteboom 1992, 1996, 1999b, 2000a), is used in an attempt to contribute to an understanding and a resolution of the tension between generality and specificity. That tension can be resolved if we look at general theory and specific conditions (or data, experience) not as separate entities or approaches that one has to choose from, in a static perspective, thus choosing to be a generalist or an empiricist, but as complementary, in a dynamic, dialectical process of theory development, in the process of discovery. The paper argues that there is an alternation of the general and the specific, in an ongoing cycle of formation and application of theory. Generalisation and abstraction are necessary to lift experience from specific contexts and carry it into new contexts with their own specificity. That, in turn, is needed for the theory to face failure and collect the experience that will lead to new generalisation. In the face of failure, adaptations are made to the specific context, in differentiation, and hints are found for novel specific elements to be absorbed, which yields hybridisation. This exerts pressure, and provides the material and the directions, to develop a new unity out of novel combinations, and we are back at the beginning of the cycle.learning;discovery;generality;specificity

Stages Of Discovery And Entrepreneurship

In an attempt at a systematic theory of entrepreneurship, this paper connects various literatures, from economics and business. In economics, there are many notions of entrepreneurship, some of which seem to contradict each other. For example, there are notions of entrepreneurship as an equilibrating and as a disequilibrating force. In this paper, these differences are connected with the issue of exploitation and exploration from the business literature. The question is how one can explore while maintaining exploitation. For this, a cycle of discovery has been proposed, with stages of equilibration and disequilibration which build on each other, in process where exploitation leads to exploration. It is proposed that different notions of entrepreneurship can be associated with different stages of that cycle. In this way, different types of entrepreneurship complement each other in an ongoing process of discovery.entrepreneurship;innovation;organizational learning;discovery

Innovation, Learning and Cluster Dynamics

This chapter offers a theory and an analytical framework for the analysis of cluster dynamics, i.e. the innovative performance and evolution of clusters.It develops three types of embedding: institutional embedding, structural embedding (network structure), and relational embedding (type and strength of ties).The analysis is conducted from a perspective of both competence (learning) arising from relations and governance of relational risk, which includes risk of lock-in and risk of spillover.A basic proposition is that innovative clusters face the challenge of combining exploration and exploitation.Hypotheses are specified concerning differences between networks for exploration and exploitation, and concerning combinations and transitions between them.Arguments are presented that in some important respects go against the thesis of the strength of weak ties .Some empirical evidence is presented from recent studies.innovation;organizational learning;clusters;industrial districts;networks