This monthly selection of articles is been carried out by Philippe Gugler and Basile de Raemy, 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.

The relational embeddedness as the differentiator of the  cluster supply chain collaboration – a multidimensional comparative analysis

By: M. Frankowska, K. Cheba. Competitiveness Review, DOI: 10.1108/CR-11-2019-0114, January 2021.

Abstract: “Purpose – The purpose of this paper is to fill the research and cognitive gap by comparative analyzing of the cluster supply chain (CSC) and supply chains not belonging to the clusters to examine the relational embeddedness as the differentiator of supply chains operating in the clusters. Design/methodology/approach – The conceptual model was tested with data collected from 475 industrial companies cooperating with their partners within supply chains, including 135 CSC. To identify the livraisons between different indicators, the correspondence analysis was applied. Findings – The division of enterprises participating in this study into groups allows for the determination of relatively clear boundaries between enterprises belonging to the cluster and those that do not declare such affiliation. The obtained results confirmed that the relational embeddedness is the differentiator of the CSC collaboration. Research limitations/implications – The main limitations are referred to as the static character of the data. Practical  implications – The paper contains implications for cluster facilitators, as well as for cluster policy decision makers, to better design support for cluster organizations. Originality/value – This research is a contribution to the literature on inter-organizational structures, such as clusters and supply chains, and in particular, contributes to the creation of the scientific ground of SCS theory. The research allowed to better understand the nature of collaboration taking into consideration the fact of the relational embeddedness of the companies operating within supply chains located in clusters. It proves the existence of a new type of inter-organizational form that is CSC.” [ABSTRACT FROM AUTHORS]

The Role of a  University in Cluster Formation: Evidence from a National Institute of Science  and Technology in Korea

By: J. Lee. Regional Science and Urban Economics, DOI: 10.1016/j.regsciurbeco.2020.103617, January 2021.

Abstract: “Can a new technology-oriented research university start a virtuous cycle by inducing industrial agglomeration? In this paper, I study the effect of the opening of the Ulsan National Institute of Science and Technology (UNIST) in 2009 on local industrial specialization. Using synthetic control, I find that the opening of the university increased manufacturing employment through the entry of new firms between 2009 and 2016. These new firms were mainly found in industries technologically close to the university’s research. The number of firms in closely connected industries increased more than 30% compared with little change in less-related industries. My results suggest that a university can lead to local industrial specialization toward industries more closely related to that university’s innovative strengths.” [ABSTRACT FROM AUTHOR]

The different shades of innovation emergence in smart  service systems: the case of Italian cluster for aerospace technology

By: O. Troisi, A. Visvizi, M. Grimaldi. Journal of Business & Industrial Marketing, DOI: 10.1108/JBIM-02-2020-0091, January 2021.

Abstract: “Purpose – The purpose of this paper is to explore the emergence of innovation in smart service systems to conceptualize how actor’s relationships through technology-enabled interactions can give birth to novel technologies, processes, strategies and value. The objectives of the study are: to detect the different enablers that activate innovation in smart service systems; and to explore how these can lead dynamically to the emergence of different innovation patterns. Design/methodology/approach – The empirical research adopts an approach based on constructivist grounded theory, performed through observation and semi-structured interviews to investigate the development of innovation in the Italian CTNA (Italian acronym of National Cluster for Aerospace Technology). Findings – The identification and re-elaboration of the novelties that emerged from the analysis of the Cluster allow the elaboration of a diagram that classifies five different shades of innovation, introduced through some related theoretical propositions: technological; process; business model and data-driven; social and eco-sustainable; and practice-based. Originality/value – The paper embraces a synthesis view that detects the enabling structural and systems dimensions for innovation (the “what”) and the way in which these can be combined to create new technologies, resources, values and social rules (the “how” dimension). The classification of five different kinds of innovation can contribute to enrich extant research on value co-creation and innovation and can shed light on how given technologies and relational strategies can produce varied innovation outcomes according to the diverse stakeholders engaged.” [ABSTRACT FROM AUTHORS]

Local industrial  policies and development of agricultural clusters: a case study based on a tea  cluster in China

By: L. Zhao, J. Ruan, X. Shi. International Food and Agribusiness Management Review, DOI: 10.22434/IFAMR2019.0154, February 2021.

Abstract: “The purpose of this study is to discuss the effectiveness of local industrial policies and show that effective industrial policies contribute to both the evolution and development of the cluster in the Chinese context, based on comparative advantages and market failures. We adopted a single case study method and conducted interviews with 30 stakeholders in the tea clusters; a documentary investigation was also used as a supplement. This case study finds that local industrial policies have played an important role when market failures occur in the development of agricultural clusters. The local government implemented a series of industrial policies to promote the progress of the tea industry at various stages of development. The case study further demonstrates what can be considered as an effective industrial policy in the dynamic process of agricultural development. This case also provides empirical evidence for local governments to remain sensitive to challenges and to develop timely industrial policies when an industrial cluster is faced with either opportunities or crises. Therefore, it has implications for local governments that need to improve agriculture in undeveloped regions.” [ABSTRACT FROM AUTHORS]

Spatial spillovers of  agglomeration economies and productivity in the tourism industry: The case of  the UK 

By: Y. R. Kim, A. M. Williams, S. Park, J. L. Chen. Tourism Management, DOI: 10.1016/j.tourman.2020.104201, February 2021.

Abstract: “This research investigates the direct and (indirect) spatial spillover effects of agglomeration economies on the productivity of the tourism industry. With increasing concerns about the persistence of low (labour) productivity in tourism across many developed economies, there is an urgent need to address this productivity challenge. Using major under-exploited UK microeconomic panel data, spatial econometric modelling is employed to estimate the effects of agglomeration economies on productivity. Findings reveal the significant effects of agglomeration economies on productivity within a specific region, but also significant spatial spillover effects across neighbouring regions, suggesting the possibility of productivity convergences. Competitive and complementary effects of agglomeration economies on productivity are identified.” [ABSTRACT FROM AUTHORS]

Determining  factors of cities’ centrality in the interregional innovation networks of China’s  biomedical industry

By: Q. Ye, X. Xu. Scientometrics, DOI: 10.1007/s11192-020-03853-3, February 2021.

Abstract: “This study analyzed the determinants of regions’ degree centrality as well as their variation over time in interregional innovation networks and compared the differences in factors between developed and less developed regions (core and periphery). Focusing on China’s biomedical industry, we used the prefecture-level invention co-patents data (2012–2017) to construct intercity networks and related cities’ centrality to sector-region-specific factors. We found: (1) A “convergence” process of regional embeddedness exists in innovation networks among cities. (2) The volume of national public funding for fundamental researches in the biomedical industry plays the most important role in cities’ centrality, regardless of developed or undeveloped cities. (3) For the developed cities’ centrality position, the intensity of intraregional collaboration in the biomedical industry is the secondary influencing factor, besides, other positive factors involve innovation performance, industrial market application, and cluster competitiveness, but it does not affect peripheral cities. (4) The second most influential factor in peripheral cities’ centrality is the number of biomedical firms. We concluded that despite the influence of path dependence, in the field of the analytical industry, China’s public funding for basic research has narrowed the gap in networking capability between the developed and backward cities.” [ABSTRACT FROM AUTHORS]

Detecting industry clusters from the bottom up based  on co-location patterns mining: A case study in Dongguan, China

By: Z. Liu, X. Chen, W. Xu, Y. Chen, X. Li. Urban Analytics and City Science, DOI: 10.1177/2399808321991542, February 2021.

Abstract: “Industry cluster development is important to stimulate regional economy. Conventional spatial methods for detecting industry clusters use a pairwise manner to infer the co-location relationships of multiple industrial types or instances, which increases the difficulty of interpreting the results. This study proposes to use co-location patterns (CPs) mining method to directly capture the co-location of multiple industrial types from the bottom up without any conditions of data relations defined a priori. The method is applied in Dongguan, China, to investigate the industry cluster patterns at an intra-urban scale. At the city level, the results show prevalent CPs of information communication and technology industry and other associated sectors. At the subregional level, however, approximately 41% of the industrial CPs are different from those obtained at the city level. The local features of sub-regional industry clusters are associated with productions of, for instance, sporting goods and toys, digital instrument and office equipment, machine parts and woodware, and textile-related products.” [ABSTRACT FROM AUTHORS]

Do clustered firms  outperform the non-clustered? Evidence of financial performance in traditional  industries

By: D. Pavelkova, M. Zizka, L. Homolka, A. Knapkova, N. Pelloneva. Economic Research-Ekonomska Istraživanja, DOI: 10.1080/1331677X.2021.1874460, January 2021.

Abstract: “Previous research presented in numbers of studies strongly suggests that locating in a cluster generates valuable benefits to clustered firms. These include better access to suppliers and other scarce inputs, superior knowledge and innovation, a better position from which to build a social network as well as proximate to successful competitors. Yet when the positive impact of agglomeration and clustering has been questioned on the strictly financial performance of clustered firms, the results of these studies are not so convincing and question the enthusiasm for cluster theory shown by scholars, practitioners, and policymakers. The aim of our research is to enrich existing knowledge concerning the benefits of clustering, as well as to test if localisation in a natural cluster, and membership in a cluster organisation has a positive impact on financial performance. We propose to measure that by selected financial indicators such as ROA, ROS, labour productivity and Economic Value Added, focussing our research on traditional industrial sectors – plastics and textiles seated in the Czech Republic. The results of analysing firm-level data in the period of 2009–2016 fail to confirm any significant influence of firm localisation in natural cluster or membership in the cluster organisation on financial performance for firms in studied sectors. We achieved the same results by investigation of potential differences for young firms, SMEs or underperforming firms.” [ABSTRACT FROM AUTHORS]