Learning patterns in early stage R&D projects: empirical evidence from the fibre raw material technology project in the Netherlands

Past research has reported that learning processes in early stage R&D are either chaotic, or absent. We challenge this finding by elaborating Van de Ven et al.’s trial‐and‐error learning model and explore an alternative conceptualization. We explored the combinations of positive and negative outcomes and action course continuation and modification. We use data gathered in an R&D setting of a 4‐years pre‐competitive knowledge generation project in the Dutch paper and board industry. Whereas the Van de Ven and Polley (1992) approach applied on our data also would lead us to conclude that ‘no learning’ would happen, our decomposed model identified three distinct learning patterns: (1) a virtuous pattern of positive outcomes resulting in continuations of action courses; (2) a vacuous pattern of negative outcomes resulting in modifications of action courses; and (3) a verification pattern of positive outcomes resulting in modifications of action courses. We observed the virtuous and verification patterns during the first 2 years and virtuous and vacuous learning in the second 2 years. These results might be useful for R&D managers since they provide insight into how an early stage R&D project can develop and where managers might intervene and adjust action courses.     

Credible expectations — The US Department of Energy's Hydrogen Program as enactor and selector of hydrogen technologies

There are many competing transition paths toward sustainability and even more competing visions and expectations, while only a limited of number of paths can be supported. In the literature so far, not much attention has been paid to the question: what makes one expectation more credible than another?On the basis of a case study on the US Department of Energy's (DOE) Hydrogen Program we show how credible expectations build on three arguments in favor of the promising option. First there is the technology's current level of performance and its historical progress toward that level. Second a path forward is constructed to argue that even higher levels of performance can be achieved. And third, an end target is constructed that relates to relevant societal needs. All three elements can, and often are, subject of contestation and competing options will provide the same type of arguments and relate to the same societal needs.Finally, a transition path needs promising enabling technologies to remain credible, and the ‘losers’ are dropped as soon as the credibility of the path is challenged.     

Sectoral Patterns of Interactive Learning: An Empirical Exploration of a Case in a Dutch Region

This paper pursues the development of a theoretical framework that explains interactive learning between innovator firms and external actors in both the knowledge infrastructure and the production chain. The research question is: What kinds of factors explain the interactive learning of innovator firms with distinct external actors? Our theoretical framework extends the resource-based perspective, which is predominant in network theory, with both an activity-based and a structural account of interactive learning. We contend basically that higher technological dynamics induce more complex innovative activities. But, more complex innovative activities increase the probability of internal resource deficits/shortages in the innovator firms. The lower the alignment of the innovative activities with the quality of the internal resource base, the higher the resource deficits/shortages and the more likely the search for complementary resources externally, which increases the likeliness of external relationships. In order to test the generality of our theoretical claims we analyse our models in four sectors with distinct technological dynamics as distinguished by Pavitt. For each sector we explore five models of the level of interactive learning of innovator firms with: (1) the public knowledge infrastructure (difficult to access, demands high internal competencies to utilize scientific knowledge), (2) the production chain (easy to access), (3) their users, (4) their suppliers, (5) their competitors. These analyses allow for a comparison between interactive learning with different external actors and give deeper insights into the differentiated interaction patterns involving innovation. Our findings show that patterns of interactive learning between sectors differ. Some are more resource based and others are more affected by the complexity of innovative activities. Particularly the patterns of interactive learning between, on the one hand, firms and the knowledge infrastructure, and on the other hand of firms with the production chain show important differences.     

Sectoral Patterns of Interactive Learning: An Empirical Exploration of a Case in a Dutch Region

This paper pursues the development of a theoretical framework that explains interactive learning between innovator firms and external actors in both the knowledge infrastructure and the production chain. The research question is: What kinds of factors explain the interactive learning of innovator firms with distinct external actors? Our theoretical framework extends the resource-based perspective, which is predominant in network theory, with both an activity-based and a structural account of interactive learning. We contend basically that higher technological dynamics induce more complex innovative activities. But, more complex innovative activities increase the probability of internal resource deficits/shortages in the innovator firms. The lower the alignment of the innovative activities with the quality of the internal resource base, the higher the resource deficits/shortages and the more likely the search for complementary resources externally, which increases the likeliness of external relationships. In order to test the generality of our theoretical claims we analyse our models in four sectors with distinct technological dynamics as distinguished by Pavitt. For each sector we explore five models of the level of interactive learning of innovator firms with: (1) the public knowledge infrastructure (difficult to access, demands high internal competencies to utilize scientific knowledge), (2) the production chain (easy to access), (3) their users, (4) their suppliers, (5) their competitors. These analyses allow for a comparison between interactive learning with different external actors and give deeper insights into the differentiated interaction patterns involving innovation. Our findings show that patterns of interactive learning between sectors differ. Some are more resource based and others are more affected by the complexity of innovative activities. Particularly the patterns of interactive learning between, on the one hand, firms and the knowledge infrastructure, and on the other hand of firms with the production chain show important differences.     

R&D Cooperation in a Transaction Cost Perspective

This paper investigates R&Dcooperation between buyers and suppliers, drawing bothon transaction cost theory and resource-based theoryof the firm. Results of logistic regression analyses,using a unique firm-level database containing 689manufacturing firms located in a Dutch region, supportassumptions of transaction cost theory. Frequentknowledge transfer and moderate and high levels ofasset specificity increase probabilities of R&Dcooperation. In particular, Williamson's assumptionsconcerning the moderating influences of uncertainty onbilateral governance are confirmed. Extending theoriginal transaction cost model with indicatorsderived from resource based theory of the firmincreases the performance of the model.