Facilitators of Knowledge Transfer in University-Industry Collaborations: A Knowledge-Based Perspective

Using the knowledge-based view of the firm as our theoretical underpinning, we study partnerships between industrial firms and university research centers (URCs) in order to identify facilitators of knowledge transfer, particularly focusing on how firms learn from URCs. Data for this study were obtained from senior-level executives from a random sample of one hundred and seventy-three firms located in the northeastern US. Results indicate that social connectedness, trust, URC technology transfer-intellectual property policies, technological relatedness and technological capability are significant facilitators of knowledge transfer. We also found that the type of knowledge transferred, i.e., explicit versus tacit, moderated these relationships. We conclude with implications for future research and R&D policy     

Is faster really better? An empirical test of the implications ofinnovation speed

New product innovation is critical to the competitive advantage of many firms. However, there is much hoopla, but little evidence, regarding the benefit of innovation speed. Specifically, there exists insufficient, often conflicting evidence about how dimensions of innovation strategy (cost, quality, and speed) relate to one another and how they ultimately affect project success. Evidence from 75 new product development projects clearly indicates that speed is positively related to quality and has the greatest influence on success. However, several external and firm-level factors were found to moderate the effect of innovation strategy dimensions on project success. Results point to the fact that relationships between dimensions of innovation strategy and project success vary with level and source of uncertainty, with the clearest finding being that speed leads to success primarily in more predictable contexts. This suggests that a fast-paced innovation strategy is best when "you know where you're going"     

The impact of firm size and age on knowledge strategies during product development: a study of the drug delivery industry

A successful new product development strategy involves the identification, development, and exploitation of key resources. Such exploitation of a firm's unique knowledge base ultimately leads to successful new products and, in turn, a sustainable competitive advantage. In this paper, we look at a firm's knowledge strategy along three dimensions, and examine the impact of firm size and age on the type of knowledge strategies used to build technological strength and competitive success. The three dimensions of knowledge strategy examined are: extent of emphasis on speed of learning, emphasis on internal versus external sourcing of knowledge, and the development of a broad versus a narrow knowledge base. Using a population of 27 firms from the drug delivery sector of the pharmaceutical industry, we found that firm size and age influenced the success of firm knowledge strategies. Interestingly, we found that the differences in the knowledge strategy dimensions between large and small firms and between old and young firms were not as great as expected. However, we found that firm size and age moderate the relationship between knowledge strategies and technological strength. In other words, firms that used appropriate knowledge strategies for their size and age optimized their technological strength. Concerning size, smaller firms that focused on faster learning and developing a narrow knowledge base were able to optimize technological strength. On the other hand, large firms that developed a broader knowledge base and focused on internal learning achieved similar success. Concerning age, younger firms that maintained connections to external sources of learning and developed a narrower, niche-based knowledge optimized their technological strength.     

Technological learning, strategic flexibility, and new productdevelopment in the pharmaceutical industry

The objective of this study was to better understand strategic management using the dynamic capabilities approach. The authors have focused on two fundamental constructs of dynamic capabilities, technological learning and strategic flexibility, and discerned their influence on organizational performance. Their main argument has been that a firm's strategic flexibility moderates the relationship between technological learning and technological performance as evidenced by new product development. Their model is based on the synthesis of the traditions of research in strategic and technology management. Technological learning has been defined in two dimensions: internal and external learning. Strategic flexibility has been operationalized in financial, marketing, manufacturing, and technological dimensions. Data from the US ethical pharmaceutical industry for 1977-1991 have been used to test their hypotheses. Although they found support for their basic argument, they have observed that the strategic flexibility factors are related with the variables in a more complex way. Furthermore, internal learning involves a different process than learning from external sources. The robustness of their finding is due to the longitudinal data and objective indicators used in measuring the constructs. Implications for further research and managerial actions are also discussed