Impact of clusters on regional economic performance

Abstract

Purpose -This paper aims to examine the methodology used to identify clusters on the one hand and assess the economic impact that those may have on regions on the other hand. Design/methodology/approach -The influential work on "clusters"lead by Michael Porter since the 1990s has become a tool for promoting innovation and growth at national and regional level. Even if the theory has become very popular, a few empirical investigations were conducted since. In a recent study, Delgado, Porter and Stern developed a model to investigate the impact of cluster composition on the performance of regions in the USA. They find strong evidence that industries operating in a strong cluster environment perform better. The aim of this study is to improve the methodology used in evaluating the cluster environment and then to replicate their model and apply it to a highly competitive industry in Switzerland, namely, the precision goods sector. It enables to look closely at the importance of the microeconomic environment surrounding an industry at the regional level. Findings -In Switzerland, the precision industry forms a traded cluster in three different regions. The model then reveals that those regions perform better. The results show that industries located in or nearby regions with a strong cluster environment experience higher employment growth rates. Originality/value -It highlights the importance of the microeconomic environment even in small competitive countries.

Why Is Collaborative Agglomeration of Innovation so Important for Improving Regional Innovation Capabilities? A Perspective Based on Collaborative Agglomeration of Industry-University-Research Institution

“…However, the inverted U-shaped relationship between innovation collaborative agglomeration and regional innovation capacity is not entirely equivalent to the "Williamson" effect of agglomeration, as the lack of collaboration among innovation subjects is another important cause of the crowding effect. Connell et al [56] found that industry agglomeration can stimulate knowledge sharing and collaborative innovation, and Resbeut and Gugler [8] also found that the more complementary closely related industries are, the higher the regional economic growth rate. e above study shows that the synergies effect among agglomerating subjects should not be ignored.…”

“…where LQ ij is the nationwide location entropy index of i innovative subject in j province, q ij is the full time equivalent of R&D personnel of the i innovative subject in j province, q j is the full time equivalent of R&D personnel in industry-university, industry-research institution, and university-research institution innovative subjects in j province, q i is the full time equivalent of the R&D personnel of the i innovative subject in whole country, q is a full time equivalent of R&D personnel in industry-university, industry-research institution, and university-research institution innovative subjects in whole country. Using equation (8), we can calculate the collaborative agglomeration level of industry-university, industry-research institution, and university-research institution, respectively:…”

“…Using equation (8), the value of collaborative agglomeration of any two sectors of IUR can be obtained. e following is the entropy method to measure the innovation collaborative agglomeration of the IUR three sectors.…”

“…In the high speed of economic growth in the past, the improvement of regional innovation capacity mainly relied on the scale expansion and concentration of innovation factors. Although the positive effects of agglomeration on economic growth and industrial development are well validated by existing studies [7][8][9], a constant expansion of scale is not necessarily always beneficial to economic development. It also causes undesirable consequences such as congestion, environmental pollution, and mismatch between the scale of innovation clusters and regional innovation capacity [10][11][12][13][14][15].…”

Determining Leading Economic Sectors, by Large Distribution or Extreme Growth?

“…LQ is a method that expands shift-share analysis, and this method helps to determine the capacities of regional economic sectors and to measure economic activity concentrations in a region against the role of economic sectors on the national economy (Crawley et al, 2013;Delgado et al, 2014;Resbeut & Gugler, 2016). As a result, the leading economic sector can be identified.…”