SKEMA RESEARCHRegional clusters and dynamics


Project Description

​Project Leader:

Ludovic Dibiaggio, Professor of economics at SKEMA Business School


Active members:


PhD students:

  • Tan Tran – Regional Alignment and Innovative productivity (Co-supervised by Cecile Ayerbe)
  • Parham Ahshur – Regional Strategic resources and entrepreneurship
  • Paige Clayton – University of North Carolina at Chapel Hill (Visiting PhD students)



  • Flora Bellone (Professor of Economics, GREDEG, Université Côte d’Azur)
  • Francesco Castellaneta (Professor of Strategy and Entrepreneurship, SKEMA Business School, GREDEG, Université Côte d’Azur)
  • Bruno Cirillo (Assistant Professor of Strategy, SKEMA Business School, GREDEG, Université Côte d’Azur)
  • Paige Clayton (PhD student, Department of Public Policy, University of North Carolina)
  • Maryann Feldman (Heninger Distinguished Professor in the department of Public Policy at the University of North Carolina)
  • Gianluigi Giustiziero (Assistant Professor of Strategy, SKEMA Business School, GREDEG, Université Côte d’Azur)
  • Catherine Laffineur (Assistant Professor of Economics, GREDEG, Université Côte d’Azur)
  • Benjamin Montmartin (Associate Professor of Economics SKEMA Business School, GREDEG, Université Côte d’Azur)
  • Lionel Nesta (Professor of Economics, GREDEG, Université Côte d’Azur and OFCE)
  • Francesco Vona (Research Fellow, OFCE)


Project Description:

The economy has undergone fundamental transformations over the last few decades with globalisation and technological advances such as digitisation, automation and the emergence of green technologies. These changes have affected the nature and the organisation of productive activities with significant consequences on regional industries.

Regions have shown very different abilities to adapt such structural changes and the increasing divergence between regions within most countries (OECD, 2016) have found very diverse and sometimes contradictory explanations. Academics at SKEMA are seeking to understand how regions may create a favorable innovative and entrepreneurial environment for local entrepreneurs and innovative firms.

The benefits of spatial concentration of firms are well known. Firms from the same industry may cluster to share similar infrastructures and resources (input sharing, labour market pooling and benefiting from other firms’ R&D). Firms from different industries may also benefit from the diversity of resources providing opportunities of experimenting productive technological combinations. 

Assuming potential synergies between scientific expertise, technological specialisation and local markets when aligned, this project analyses the micro dynamics underlying the construction of regional distinctive resources and capabilities. Leveraging SKEMA's multi-campus structure, GREDEG and OFCE multidisciplinary expertise, and the support of international partners, this project aims to shed light on the conditions to create productive structures of social interactions between scientific, technological and business communities and generate alignment dynamics within successful regions.

Regional alignment as regional capabilities indicator

Starting from a “one size does not fit all assumption” this project aims to understand the required conditions for regions to build regional alignment and to test to which extent regional alignment provides a useful indicator to analyse and explain innovative and economic performance heterogeneity across regions. One of the most striking observations is that while countries performance tends to convergence over time, we witness increasing within countries regional divergence. In other words, only most successful regions leads the overall country performance. 

The objective is to analyse if specific organisation of scientific, technological and industrial activities may be a better explanation that simple agglomeration or cluster effects. Different studies have been initiated to 1) provide historical explanations of the construction of regional alignment 2) test to which extent regional alignment explains innovative and economic performance heterogeneity between regions.

The role of regions in nascent green industries

The point of departure is the dual effects of environmental policies. On the one hand, environmental policies have a negative effect on industry competitiveness and employment, but this effect is mostly concentrated in highly polluting industries. On the other hand, they trigger innovation in upstream industries such as for suppliers of electric equipment, knowledge intensive engineering services and public R&D labs.

The objective of this project is to reconcile these two pieces evidence and provide the first macro-assessment of the labour market effects of environmental policies. Unlike previous works this project explicitly accounts for the geographical dimension of the relationship between polluting industries and upstream suppliers. 

Specifically, it takes advantage of the highly detailed regional dimension of US environmental policies, which vary at the county level, and explore whether the two contrasting effects of environmental regulation co-occur in geographical areas that experienced a more stringent environmental regulation. The idea is that polluting industries exposed to regulation should demand new equipment, knowledge and specialized services to actors (essentially some high-tech manufacturing industries, knowledge intensive business services and public R&D labs) that can be either located in the same region or in a different region. 

The evaluation of the macroeconomic effect of the policy differs completely in the two cases. In the first case, environmental policies harm polluting industries, but this effect may be more than compensated by the positive multiplier effect from upstream suppliers and knowledge providers in the areas, i.e. the so-called local multiplier effect. In the second case, the classical trade-off jobs vs. the environment emerges and the economic costs and the health benefits of environmental policies should be carefully evaluated.

From the methodological point of view, we retrieve the causal effect of environmental regulation by combining difference-in-difference and propensity score matching that allows to build a counterfactual, using counties with similar structural characteristics. The novelty of the approach is to combine standard evaluation methods with different methodologies to identify the industries and actors that are indirectly exposed to environmental regulation. This will reveal whether environmental regulation triggers intra-region worker mobility and changes in the supply of educational programmes required to fulfil skill mismatches.

Furthermore, in order to evidence proximity effects and explain such institutional complementarities, the study will analyse the antecedents and consequences of the structure of social networks (such as job mobility networks, scientific and technological knowledge networks, etc.) in different alignment contexts.

Plant and worker mobility: the role of regional characteristics

Using Brown (2008) classification of business functions that he split into core business processes and support business processes, this study relies on the organisational structure of multi-plants firms to analyse the determinants of plants death according to:

a) A measure of task connectivity between each plant to investigate which tasks are more likely to require proximity relative to others. The core assumption is that plants specialised in tasks that do not require proximity (plants specialised in some specific functions) are more likely to shut down than others. 

b) The intensity of routine functions of the plant. The core assumption is that routine functions are more likely to be relocated abroad to benefit from low factor costs. 

c) A measure of relatedness of the function with other establishments in the region. In the first part of the project, the dependent variable is the probability to close plant within multi-establishment firms. The variables of interest are the characteristics of establishments: distinguishing between a) The level of specialization (the share of employment in one specific function over total employment); b) Proximity to the firm’s core competency; c) Proximity to the the geographical area’s core competency; d) The level of alignment of the geographical area.

The second part of the study is interested in the labour market effects of organisational change. Plant shutdown, plant mobility from one region to another and increased specialisation of plants may lead to a reallocation of workers. This part aims to identify how workers react to plant closure depending on regional characteristics.

Incubators as connector to regional resources

Scholarly understanding of the role incubators play in boosting startup’s success, as well as to what degree certain practices contribute to this success, is still at an early stage. Business incubators and other supporting policies have been designed to compensate for the constraints and difficulties experienced by innovative SMEs due to their (small) size, youth, location or innovativeness. Business incubators are designed to help them develop their projects and access essential resources such as capital, money, and human capital in the first years of existence.  However, results concerning incubators performance have tended to be ambiguous, at best presenting mixed results. Furthermore, there is no clear understanding of what makes certain incubators perform better than others.

The aim of this study is to develop a more tailored methodology to test incubator performance by taking into consideration 1) their specificities and 2) regional capabilities conceived as resources platforms to local startups. Most studies tend to consider business incubators as homogenous entities, regardless of geographic, scientific, technological and industrial contexts. In the same spirit, studies tend to prescribe the replication of best practices based on the observation of best performing incubators.

Further, this study aims to redefine incubator best practices by providing a more contextualised approach to incubator selection criteria, services offered and subsequent opportunities provided by facilitating connections with local resources and competencies.

The first step will consist of an experimental approach in collaboration with colleagues from Bocconi University. The objective is to provide an understanding of causal relations between support services such as training or connection to local resources and startup performance. Further, we will test the role of incubators in helping young entrepreneurs with an academic background in biological fields to leverage their scientific expertise to up start new venture by giving them access to technological partners and to local markets. In collaboration with the IPMC research lab, we will compare the success likelihood of new ventures in biology related businesses depending on regional characteristics. The study will focus on the regions that have poor capabilities to test the practices of incubators that manage to compensate regional weaknesses.

 Skema Html Webpart