25 November 2015

This monthly selection of articles has been carried out by Philippe Gugler and Damiano Lepori, the Center for Competitiveness, University of Fribourg.

The entire selection, carried out since 2013, can be consulted on the academic articles page of our web.

 

Defining clusters of related industries

By: Delgado M., Porter M., Stern S. Journal of Economic Geography, 10.1093/jeg/lbv017, 2015.

Abstract: “Clusters are geographic concentrations of industries related by knowledge, skills, inputs, demand and/or other linkages. There is an increasing need for cluster-based data to support research, facilitate comparisons of clusters across regions and support policymakers in defining regional strategies. This article develops a novel clustering algorithm that systematically generates and assesses sets of cluster definitions (i.e., groups of closely related industries). We implement the algorithm using 2009 data for U.S. industries (six-digit NAICS), and propose a new set of benchmark cluster definitions that incorporates measures of inter-industry linkages based on co-location patterns, input–output links, and similarities in labor occupations. We also illustrate the algorithm’s ability to compare alternative sets of cluster definitions by evaluating our new set against existing sets in the literature. We find that our proposed set outperforms other methods in capturing a wide range of inter-industry linkages, including the grouping of industries within the same three-digit NAICS.” [ABSTRACT FROM AUTHORS]

 

Causal Relations between Knowledge-Intensive Business Services and Regional Employment Growth

By: Brenner T., Capasso M., Duschl M., Frenken K., Treibich T. Urban & Regional research centre Utrecht, 2015.

Abstract: “This paper studies the causal relations between regional employment growth in Knowledge- Intensive Business Services (KIBS) and overall regional employment growth using German labour-market data for the period 1999-2012. Adopting a recently developed technique, we are able to estimate a structural vector autoregressive model in which the causal directions between KIBS and other sectors are examined including various time lags. One main finding holds that although regional growth has a negative short-term effect on KIBS, KIBS growth has a long-term positive effect on the whole regional economy. This result confirms the claim that KIBS can play a key role in regional policies. Distinguishing between financial and non-financial KIBS, we find that financial KIBS have a procyclical effect on regional growth underlining the potential de-stabilizing effect of a large financial sector.” [ABSTRACT FROM AUTHORS]

 

Formal And Informal Macro-Regional Transport Clusters As A Primary Step In The Design And Implementation Of Cluster-Based Strategies

By: Nezerenko O., Koppel O. Transport and Telecommunication Journal, Issue 3, 2015.

Abstract: “The aim of the study is the identification of a formal macro-regional transport and logistics cluster and its development trends on a macro-regional level in 2007-2011 by means of the hierarchical cluster analysis. The central approach of the study is based on two concepts: 1) the concept of formal and informal macro-regions, and 2) the concept of clustering which is based on the similarities shared by the countries of a macro-region and tightly related to the concept of macro-region. The authors seek to answer the question whether the formation of a formal transport cluster could provide the BSR a stable competitive position in the global transportation and logistics market.” [ABSTRACT FROM AUTHORS]

 

Networks, Space and Organizational Performance: A Study of the Determinants of Industrial Research Income Generation by Universities

By: Huggins R., Izushi H., Prokop D. Regional Studies, 2015.

Abstract: “This paper examines the extent to which both network structure and spatial factors impact on the organizational performance of universities as measured by the generation of industrial research income. Drawing on data concerning the interactions of universities in the UK with large research and development (R&D)-intensive firms, the paper employs both social network analysis and regression analysis. It is found that the structural position of a university within networks with large R&D-intensive firms is significantly associated with the level of research income gained from industry. Spatial factors, on the other hand, are not found to be clearly associated with performance, suggesting that universities operate on a level playing field across regional environments once other factors are controlled for.” [ABSTRACT FROM AUTHORS]

 

Persistence of various types of innovation analyzed and explained

By : Tavassoli S., Karlssonn C. Research Policy, Volume 44, Issue 10, Pages 1887–1901, 2015.

Abstract: “This paper analyzes the persistency in innovation behavior of firms. Using five waves of the Community Innovation Survey in Sweden, we have traced the innovative behavior of firms over a ten-year period, i.e., between 2002 and 2012. We distinguish between four types of innovations: process, product, marketing, and organizational innovations. First, using transition probability matrix, we found evidence of (unconditional) state dependence in all types of innovation, with product innovators having the strongest persistent behavior. Second, using a dynamic probit model, we found evidence of “true” state dependency among all types of innovations, except marketing innovators. Once again, the strongest persistency was found for product innovators.” [ABSTRACT FROM AUTHORS]

 

Mapping the technological landscape: Measuring technology distance, technological footprints, and technology evolution

By: Aharonson B., Schilling M. Research Policy, Volume 45, Issue 1, Pages 81–96, 2015.

Abstract: “We develop and apply a set of measures that enable a fine-grained characterization of technological capabilities based on the USPTO database. These measures can capture the distance between any two patents, and help to identify outlier patents. They also provide a rich characterization of a firm's technological footprint, including its depth and breadth. The measures also enable researchers to assess the technological overlap, similarity, and proximity of the technological footprints of two or more firms. At the level of the macro technology landscape, the measures can be used to explore such dynamics as technology agglomeration, knowledge spillovers, and technology landscape evolution. We show applications of each of the measures and compare the results obtained with those that would be obtained with previously existing measures of firm diversity, similarity and proximity, highlighting the advantages of the measures used here.” [ABSTRACT FROM AUTHORS]

 

Exploitative and exploratory innovations in knowledge network and collaboration network: A patent analysis in the technological field of nano-energy

By: Guan J., Liu N. Research Policy, Volume 45, Issue 1, Pages 97–112, 2015.

Abstract: “Innovations of organizations are doubly embedded in knowledge networks constituted by coupling among knowledge elements and in social networks formed by collaborative relationships among organizations. This study explores the structural properties of such relationships and their possible influences on organizational innovations in terms of exploitation and exploration in the emerging nano-energy field. Results indicate that the knowledge networks and the technology-based collaboration networks in the nano-energy field are decoupled and that they have different degrees of integration. Some structural features of knowledge and collaboration networks influence organizations’ exploitative and exploratory innovations in diverse ways. Firstly, direct ties of an organization's knowledge elements in a knowledge network have an inverted U-shaped effect on its exploitative innovation, which is not the case in exploratory innovation. Direct ties in a collaboration network have an inverted U-shaped effect on both its exploitative and exploratory innovations. Secondly, indirect ties of an organization's knowledge elements in a knowledge network affect its exploitative innovation, but not its exploratory innovation. However, indirect ties in a collaboration network affect exploratory innovation, but not exploitative innovation. Thirdly, non-redundancy among ties in a knowledge network exhibits the opposite effect, hindering exploitative innovation, but favoring exploratory innovation. By contrast, non-redundancy among ties in a collaboration network favors exploitative innovation, but shows a non-significant effect on exploratory innovation.” [ABSTRACT FROM AUTHORS]

 

Science and Technology Parks and cooperation for innovation: Empirical evidence from Spain

By : Vasquez-Urriago R., Barge-Gil A. Research Policy, Volume 45, Issue 1, Pages 137–147, 2015.

Abstract: “Science and Technology Parks (STPs) are one of the most important innovation policy initiatives. Previous studies show that location in a park promotes cooperation for innovation, but do not investigate whether this cooperation produces better results. We extend this literature by analyzing the effect of location on an STP on the results of cooperation for innovation and the mechanism facilitating this effect. We rely on a much larger sample of firms and STPs than previous studies, and, where necessary, account for selection bias and endogeneity. The results show that location in an STP increases the likelihood of cooperation for innovation, and the intangible benefits of cooperation with the main innovation partner, due mainly to a more diverse relationship.” [ABSTRACT FROM AUTHORS]

 

Bridging science and technology through academic–industry partnerships

By: Chai S., Shih W. Research Policy, Volume 45, Issue 1, Pages 148–158, 2015.

Abstract: “Partnerships that foster the translation of scientific advances emerging from academic research organizations into commercialized products at private firms are a policy tool that has attracted increased interest. This paper examines empirical data from the Danish National Advanced Technology Foundation, an agency that funds partnerships between universities and private companies. We assess the effect on participating firms’ innovative performance, comparing patent count, publication count and proportion of cross-institutional publications between funded and unfunded firms. Specifically, we measure the impact on each of these variables based on three dimensions – small and medium-sized enterprises (SME), younger firms, and size of the collaboration firms participated in – to establish boundary conditions. Our results suggest that receiving funding affects firms’ innovative behavior differently depending on the type of firm, where (1) peer-reviewed publications increased significantly more for SMEs and larger projects, (2) granted patents increased significantly up to 4 years after funding for young firms and those in larger projects, and (3) proportion of cross-institutional publications increased significantly more 3 years after funding for all three sample specifications.” [ABSTRACT FROM AUTHORS]

 

Knowledge creation in collaboration networks: Effects of tie configuration

By: Wang J. Research Policy, Volume 45, Issue 1, Pages 68–80, 2015.

Abstract: “This paper studies the relationship between egocentric collaboration networks and knowledge creation at the individual level. For egocentric networks we focus on the characteristics of tie strength and tie configuration, and knowledge creation is assessed by the number of citations. Using a panel of 1042 American scientists in five disciplines and fixed effects models, we found an inverted U-shaped relationship between network average tie strength and citation impact, because an increase in tie strength on the one hand facilitates the collaborative knowledge creation process and on the other hand decreases cognitive diversity. In addition, when the network average tie strength is high, a more skewed network performs better because it still has a “healthy” mixture of weak and strong ties and a balance between exploration and exploitation. Furthermore, the tie strength skewness moderates the effect of network average tie strength: both the initial positive effect and the later negative effect of an increase in tie strength are smaller in a more skewed network than in a less skewed one.” [ABSTRACT FROM AUTHOR]

 

Innovation, Technology and Economic Change

Edited by Fagerberg J., Mowery D. The International Library of Critical Writings in Economics series. Edward Elgar Publishing Limited, Cheltenham, UK, 2015.

Asbtract: “Several attempts have been made since the 1970s to collect key scholarly papers and document the progress of the field of innovation studies. The collection of papers included in this new title, most of which were published after the turn of the millennium, stands on the shoulders of these earlier volumes and seeks to provide a broad overview of recent progress in research on innovation and economic change. In their choice of papers, the editors address the characteristics of the field of innovation studies and its relationship to other areas of (social) science: innovation in firms; factors influencing firms’ innovation performance; innovation systems; innovation and economic “catch-up” and, finally, policy issues for innovation.” [ABSTRACT FROM EDITORS]