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Sustaining Innovation: Regional Dynamics, Policy Frameworks, and Competitiveness

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1189

Special Issue Editor


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Guest Editor
Department of Economics, Management and Industrial Engineering and Tourism, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: innovation; entrepreneurship; technology transfer; quantitative methods; innovation ecosystems; sustainability; sustainable growth; sustainability-oriented innovation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Innovation is widely recognized to be a key driver of long-term growth and regional competitiveness. This recognition notwithstanding, the ability to uphold innovation remains overlooked in both the sectoral and the regional perspective. This Special Issue will explore the complex interplay between regional dynamics, innovation ecosystems, institutions, and public policies in fostering persistent innovation to promote competitiveness and regional resilience. By bringing together theoretical, empirical, and policy-oriented contributions, this Special Issue aims to raise our understanding of innovation trajectories, virtuous cycles of innovation, and their place-based determinants such as knowledge spillovers, industrial specialization, human capital, and local governance.

This Special Issue seeks contributions that address the persistent problems around regional innovation systems that are adapting to global challenges such as climate change, digital transformation, and demographic shifts while maintaining inclusive and resilient growth. Submissions may encompass, but are not limited to, cross-country comparisons, longitudinal studies, and mixed-method approaches.

Dr. Joana Costa
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • innovation persistence
  • place-based innovation
  • public policies
  • competitiveness

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Published Papers (2 papers)

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Research

22 pages, 2196 KB  
Article
How Can Artificial Intelligence Policies Promote the Sustainable Enhancement of Regional Science and Technology Industrial Competitiveness? A Fuzzy-Set Qualitative Comparative Analysis (fsQCA) of Policy Instruments
by Xueqing Pei and Chunlin Li
Sustainability 2026, 18(8), 4052; https://doi.org/10.3390/su18084052 - 19 Apr 2026
Viewed by 327
Abstract
The sustainable enhancement of regional science and technology industrial competitiveness is an important objective of artificial intelligence (AI) policy. However, how different AI policy instruments can be combined to achieve this goal remains insufficiently understood. This study aims to address this issue by [...] Read more.
The sustainable enhancement of regional science and technology industrial competitiveness is an important objective of artificial intelligence (AI) policy. However, how different AI policy instruments can be combined to achieve this goal remains insufficiently understood. This study aims to address this issue by identifying the configurational pathways through which combinations of AI policy instruments contribute to the sustainable enhancement of regional science and technology industrial competitiveness. Based on a policy instrument framework, we analyze AI policies issued by provincial-level governments in China and apply fuzzy-set qualitative comparative analysis (fsQCA), which is appropriate for examining the combined effects of multiple policy instruments. The results show that no single policy instrument is sufficient to produce high regional science and technology industrial competitiveness. Instead, sustained competitiveness is achieved through multiple equivalent configurations of policy instruments. Three driving pathways are identified—(supply and demand)-environmental resonance, demand-driven (supply-environmental) assurance, and supply–demand complementarity—covering five specific configurations. The variation across configurations indicates that effective AI policy mixes are contingent on regional resource endowments and development conditions. Technology R&D support, talent cultivation and collaboration, and application demonstration and promotion emerge as the most recurrent core conditions across configurations. Accordingly, local governments should develop coordinated AI policy mixes, align differentiated policy pathways with regional conditions, and prioritize technology R&D support, talent cultivation and collaboration, and application demonstration and promotion to sustain long-term regional competitiveness. Full article
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21 pages, 339 KB  
Article
Open Innovation and Public–Private Collaboration in Manufacturing: A Case Study from Piedmont, Northern Italy
by Matteo Gremo, Lucia Vigoroso, Maria Giulia Faga, Giuliana Magnacca and Federica Caffaro
Sustainability 2026, 18(6), 2803; https://doi.org/10.3390/su18062803 - 12 Mar 2026
Viewed by 438
Abstract
This study explores the dynamics of Open Innovation (OI) in manufacturing firms, with particular attention to collaboration with public research institutions. The research is performed in the Piedmont region, Northern Italy, which represents one of Italy’s leading innovation regions, with a strong manufacturing [...] Read more.
This study explores the dynamics of Open Innovation (OI) in manufacturing firms, with particular attention to collaboration with public research institutions. The research is performed in the Piedmont region, Northern Italy, which represents one of Italy’s leading innovation regions, with a strong manufacturing heritage and an active strategy to foster industrial transition through innovation clusters and partnerships. The research analyzes survey responses from 82 managers and decision-makers in manufacturing firms belonging to the local manufacturing ecosystem. The questionnaire investigated how company size, organizational structure for research and development (R&D), perceived importance of collaboration, innovation drivers and barriers, and trust in research institutions affect four types of innovation: product, process, marketing, and organizational. Results indicate that collaboration with other private companies is significantly associated with product innovation, while collaboration with public research institutions is associated to both product and process innovation. The level of R&D structuring in the management of innovative projects and trust in the expertise of public research organizations are also positively associated with product innovation. In addition, key drivers—such as the availability of dedicated financial resources, staff creativity, and openness to external partnerships—are significantly related to process innovation. The findings suggest that regional policymakers and industry stakeholders should promote targeted measures to strengthen OI adoption, particularly by improving the perceived competence and transparency of public research organizations. Full article
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