Revitalising Lagging Regions

Barzotto, Mariachiara; Corradini, Carlo; Fai, Felicia; Labory, Sandrine; Tomlinson, Philip R.

doi:10.4324/9780367422745

Cited by 20 publications

(11 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The former seems to be strongly related to the traditional endowment of high-tech manufacturing capabilities. On the other hand, the latter can be related to the lower capital-intensive nature of innovation in these fields and their broader technological applicability (Teece, 2018;Barzotto et al, 2019a). These findings indicate that the diffusion of I4.0 may be markedly uneven across regions, reflecting regional differences as well as heterogeneity in the technologies behind I4.0 transformation.…”

Section: Discussionmentioning

confidence: 96%

“…Overall, our findings show the diffusion of I4.0 as being defined by an heterogenous set of technologies, pointing to their different role in enabling a smart manufacturing transformation within regions. The novelty of these results contributes to the emerging literature exploring the ability of regions to unlock the innovative potential of I4.0 across sectors (Barzotto et al, 2019a;Muscio and Ciffolilli, 2020), as well as discussing new industrial policies for enabling wider access to the transformative effects of I4.0 (Bianchi et al, 2019;Hervas-Oliver et al, 2019).…”

Section: Introductionmentioning

confidence: 82%

“…Patent data have long been used in the literature to explore technological change as well as knowledge spillovers across regions (Maurseth and Verspagen, 2002;Moreno et al, 2005;Barzotto et al, 2019a). This is due to the granular information they offer on the location, time and specific technological classification of the invention, whilst marking the presence of a significant inventive step.…”

Section: Methodsmentioning

confidence: 99%

“…However, there is still limited evidence on the geography of I4.0 and the factors defining the readiness of a region to embed I4.0 technologies, as well as possible differences across various I4.0 technologies (Santini and Bellandi, 2017;De Propris and Bailey, 2020). These are important research questions for understanding whether I4.0 may create diffused technological opportunities among regions, as opposed to a persistent gap between technology leaders and laggards (Barzotto et al, 2019a;De Propris and Bailey, 2020).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The geography of Industry 4.0 technologies across European regions

2021

View full text Add to dashboard Cite

The geography of Industry 4.0 technologies across European regions This paper investigates the spatial distribution of Industry 4.0 (I4.0) considering both region-specific and technology-specific factors. Focusing on patent data for four technologies at the core of I4.0 between 2000 and 2014, we provide evidence of their uneven distribution across NUTS2 European regions. Our analysis confirms the role of regional absorptive capacity, cognitive and spatial proximity as drivers of I4.0 knowledge flows, but also indicates important variations among these technologies.Cumulated technological capabilities and spatial proximity exert a stronger effect on the diffusion of Robot and 3D Printing, whereas Big Data and Internet of Things tend to be more spatially distributed.

show abstract

Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 82%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The geography of Industry 4.0 technologies across European regions

2021

View full text Add to dashboard Cite

show abstract

“…Evidence suggests that for regions with lower levels of development, the business start-up process can be particularly difficult due to the underdevelopment of the overall innovation ecosystem and existing institutional failures [14]. Therefore, for such regions, along with SMARTspecialization policies, it is advisable to implement measures aimed at structural and technological change.…”

Section: Part 4 Recommendations For the Non-financial Supportmentioning

confidence: 99%

Regional Cluster Analysis as Approach for Sme Development Models

Kornyliuk

Ivashchenko

2021

Transformation of the Economy, Finance and Management in a Pandemic: The Development of Digital Technologies

View full text Add to dashboard Cite

The study analyzes the SME development regional trends in terms of key indicators. Using K-means clustering techniques, 4 groups were identified. Data show that the largest gap between the most and least developed clusters is observed in terms of spending on business innovation expenditures per capita, at the same time the average wage is the most consistent indicator. The obtained results allow to form recommendations for the intensification of innovation and investment development of small and medium-sized businesses, taking into account regional specifics. The set of recommendations was divided into financial and non-financial support measures. It is proposed to use mainly direct support aimed at stimulating individual projects for more developed regions, while for less developed regions it is advisable to use indirect tools. Non-financial support measures should be aimed primarily at eliminating institutional and systemic failures in business.

show abstract

Smart Specialisation Priorities of Less Developed Regions. A Critical Evaluation

Szávics

Benedek

2020

New Metropolitan Perspectives

View full text Add to dashboard Cite

This paper critically analysis the definition of smart specialisation priority areas of Romanian less developed regions, aiming to identify weaknesses in policy design that according to existing theories characterise such regions. Besides an empirical contribution to the literature, findings also have a practical relevance. They can be used by regions to redesign strategies in their preparation for the absorption of Cohesion Policy funds between 2021 and 2027. While in the definition of priority areas we could depict resemblance with the general practice presented in the literature, there are also shortcomings reported to the evaluation framework proposed in this paper based on official methodological and original theoretical aspects. These mainly refer to a less targeted approach within priorities, overlapping between priorities and horizontal character of vertically defined priorities. However, under these aspects, regional strategies present a high level of heterogeneity; thus, responsible institutions will need to invest different time and effort to revise policy documents.

show abstract

Revitalising Lagging Regions

Cited by 20 publications

References 0 publications

The geography of Industry 4.0 technologies across European regions

The geography of Industry 4.0 technologies across European regions

Regional Cluster Analysis as Approach for Sme Development Models

Smart Specialisation Priorities of Less Developed Regions. A Critical Evaluation

Contact Info

Product

Resources

About