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.

Service regime and innovation clusters: An empirical study from service firms in Taiwan

By : Y.-C. Chang, M.-N. Chen. Research Policy, Vol. 45, Iss. 9, pp. 1845-1857, 2016.

Abstract: “The paper extends a notion of service regime framework as a synthesis approach to understand the diversity of innovation patterns in service firms. The service regime framework consists of three dimensions: innovation trajectories, appropriability, and user involvement. A dataset of leading top 311 Taiwanese service firms is collected through the postal questionnaire survey. The results reveal three newly stylized patterns of innovation in service firms: coupling innovation trajectories, joint use of formal and informal appropriability, and intimate user involvement. Moreover, four clusters following the firm-specific assumption to characterize heterogeneous compositions of the service regime are identified. The paper concludes that the service regime framework plays a major role in distinguishing specific service innovation clusters among firms and sectors. Finally, some policy implications for promoting service innovations are provided.” [ABSTRACT FROM AUTHORS]

Towards a Smart Specialization Strategy for Haifa, Israel

By : M. Benner, L. Bieringer, M. Knaupp, J. Wittemaier, A. Wruck. Heidelberg University, MPRA Paper No. 73299, 2016.

Abstract: “The notion of smart specialization has gained considerable prominence in the international discourse on regional development. The idea of directing the attention of regional policy towards strengths and opportunities in a region’s knowledge base, and of developing regional economic and innovation strategies in a participatory public-private entrepreneurial process of discovery has unfolded policy relevance especially in countries of the European Union and its neighborhood. Nevertheless, the concept of smart specialization can be applied to regional economies in other countries, too. The present study does so for the city of Haifa, Israel. It provides a profile of the Haifa regional economy, examines regional policies in the framework of the Israeli economic and political context, and identifies possibilities for regional policy to focus on in the coming years. Drawing on the idea of an entrepreneurial process of discovery on the regional level which is a critical component of the smart specialization concept, the study suggests how such an entrepreneurial process of discovery could be organized in the case of Haifa. Conclusions drawn from this study can inform the elaboration of smart specialization strategies in other regions, too.” [ABSTRACT FROM AUTHORS]

Smart Specialisation: Creating Growth through Trans-national cooperation and Value Chains

By: Å. Mariussen, R. Rakhmatullin, L. Stanionyte. European Commission, EUR 28049 EN, Publications Office of the European Union, doi:10.2791/658931, 2016.

Abstract: “S3 begins within a region/country by exploiting place-based expertise and industrial skills within the regional innovation eco-system. The paper refers to emerging research which indicates that some regions suffer from insufficient innovation eco-system complexity, followed by sub-optimal innovation performances and path lock-in. This indicates that regional innovation eco-systems could be further strengthened through transnational learning and collaboration. Several major forms of collaboration are identified. The paper suggests that macro-regional and trans-European smart specialisation strategies could be based on multi-level approaches to experimentally extend and strengthen regional innovation eco-systems. In order to achieve robust and long-lasting outcomes, these experiments could apply some existing S3 tools. Here, an important issue is the transition from temporary programmes, projects and networks to new institutional frameworks for co-evolution and collaboration between smart specialised regions. The next important step is to exploit the European diversity identified through regional RIS3 strategies. The long-term challenge is the strengthening of emergent European and macro-regional systems of innovation, and thus supporting the regions.” [ABSTRACT FROM AUTHORS]

The Dispersed Multinational: Does Connectedness Across Spatial Dimensions Lead to Broader Technological Search?

By: T. Hannigan, A. Perri, V. Giada Scalera. Università Ca’Foscari Venezia, Working Paper No. 11/2016, 2016.

Abstract: “The multinational enterprise (MNE) is the superior form of organization to play arbitrageur of country differences, particularly with respect to high knowledge activities. To this end, extant IB literature has devoted significant efforts to the transfer of knowledge across countries via local embeddedness. However, in a modern business environment characterized by dispersed value chain activities and falling spatial transaction costs, collaborative innovation relationships may be far more complex. In this paper, we argue that the connectedness of inventor networks – rather than knowledge spillovers - may transcend requirements of local embeddedness and serve as a crucial source of new ideas and exploration into new technologies. Further, we posit that these collaborations stem out of locations at the subnational level, such as cities, and fall along the somewhat orthogonal dimensions of foreign and domestic connections. Finally, we argue that the operational footprint of the firm serves as a positive moderator on the impact of connectedness on technological exploration.” [ABSTRACT FROM AUTHORS]

The Distribution of Technological Activities in Europe: A Regional Perspective

By: R. Evangelista, V. Meliciani, A. Vezzani. JRC Technical Report, European Commission. EUR 28041 EN, doi:10.2791/993237, 2016.

Abstract: “This study analyses the major patterns and trends in the spatial distribution of technological capacities in the EU area over the 1996-2011 period, adopting a regional perspective. More specifically, the study aims at: a) assessing the level of technological polarization in the EU area and its dynamics; b) highlighting major changes in the patterns of technological specialization of EU regions; c) identifying the technological trajectories that have been more effective, that is able to sustain long-term economic growth and facilitate catching-up processes of EU laggard regions.” [ABSTRACT FROM AUTHORS]

Agglomeration economies: the heterogeneous contribution of human capital and value chains

By: D. Diodato, F. Neffke, N. O’Clery. URU, Utrecht University; CID, Harvard University, Paper No. 16.26, 2016.

Abstract: “We document the heterogeneity across sectors in the impact labor and input-output links have on industry agglomeration. Exploiting the available degrees of freedom in coagglomeration patterns, we estimate the industry-specific benefits of sharing labor needs and supply links with local firms. On aggregate, coagglomeration patterns of services are at least as strongly driven by input-output linkages as those of manufacturing, whereas labor linkages are much more potent drivers of coagglomeration in services than in manufacturing. Moreover, the degree to which labor and input-output linkages are reflected in an industry’s coagglomeration patterns is relevant for predicting patterns of city-industry employment growth.“ [ABSTRACT FROM AUTHORS]

Agglomeration of Creative Industries: An Intra-metropolitan Analysis for Barcelona

By : E. Coll-Martinez, A.-I. Moreno-Monroy, J.-M. Arauzo-Carod. Universitat Rovira I Virgili, Creip Paper No. 16-2016, 2016.

Abstract: “The aim of this paper is to analyse the spatial patterns of agglomeration and coagglomeration of Creative Industries (CIs) in the Metropolitan Area of Barcelona (MAB). We compare agglomeration patterns of CIs to non-creative ones (Non-CIs) in order to identify specificities in their location patterns at an intra-metropolitan level. We use firms’ geo-located data for 2012 to calculate the distance-based M and m cumulative and density functions of agglomeration and coagglomeration. Our main results show that CIs and Non-CIs have different agglomeration patterns. Concretely, whilst CIs tend to cluster at very small distances, Non-CIs have a more dispersed pattern. Concerning the results of coagglomeration, these reveal that micro CIs and Non-CIs seem to be coagglomerated. Regarding agglomeration patterns of subgroups of CIs, we find that these sectors display high levels of agglomeration individually, and that there is a clear coagglomeration among them in the MAB. Finally, our results emphasise Barcelona’s centre as a magnet for Cultural and CIs." [ABSTRACT FROM AUTHORS]