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Sustainability
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AI-Driven Entrepreneurship and Sustainable Business Innovation
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AI-Driven Entrepreneurship and Sustainable Business Innovation

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 November 2025 | Viewed by 11553

Special Issue Editors

Prof. Dr. Radosław Wolniak

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Guest Editor
Economics and Informatics Department, Organization and Management Faculty, Silesian University of Technology, 44-100 Gliwice, Poland
Interests: Industry 4.0; Smart City; quality management; AI in management
Special Issues, Collections and Topics in MDPI journals
Dr. Judyta Kabus

E-Mail Website
Guest Editor
Department of Logistics, Faculty of Management, Czestochowa University of Technology, Dabrowskiego Str. 69, 42-201 Czestochowa, Poland
Interests: management; CSR; sustainable development; logistics; city logistics; Handel; supply chain; innovations; FMCG; entrepreneurship
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Anna Brzozowska

E-Mail Website
Guest Editor
Department of Logistics, Faculty of Management, Czestochowa University of Technology, Czestochowa, Poland
Interests: marketing and logistics management; IT in business; EU project management; management and marketing in agribusiness; processes of integration with the European Union

Special Issue Information

Dear Colleagues,

We are excited to invite you to contribute to our upcoming Special Issue titled 'AI-Driven Entrepreneurship and Sustainable Business Innovation', which will be featured in the leading scholarly journal in the field. This Special Issue aims to explore the dynamic and rapidly evolving landscape of artificial intelligence (AI) and innovative practices in entrepreneurship and business management.

In an era where technology continuously reshapes business operations, understanding the implications, challenges, and opportunities presented by AI and innovation in entrepreneurship and business management is crucial. This Special Issue seeks to gather original articles and research that explore the transformation of business management, strategy, and policy through AI and innovative approaches.

The integration of AI in business has opened new avenues for enhancing customer experience, optimizing operational efficiency, and promoting sustainable business practices. We encourage the submission of articles that not only present theoretical and empirical research but also demonstrate the practical implementation of these technologies in the business industry.

We are particularly interested in contributions that address, but are not limited to, the following topics:

  • AI-driven strategies for personalized customer experiences;
  • The role of AI in sustainable business management;
  • Innovative approaches to marketing and business management;
  • Impact of AI on business policy and strategic planning;
  • Ethical considerations and challenges in implementing AI in business;
  • Case studies on the successful integration of AI in business management;
  • Future trends and predictions in AI and business;
  • AI in enhancing cultural heritage and business sectors;
  • The intersection of AI, big data, and business management;
  • Innovative business models leveraging AI;
  • AI's role in environmental, social, and governance (ESG) criteria.

This Special Issue aims to provide a platform for interdisciplinary dialogue and foster new ideas and approaches that challenge traditional practices in business management. We welcome original research articles, comprehensive reviews, case studies, and research notes that contribute to the theoretical and methodological advancement of the field.

We look forward to receiving your insightful contributions and advancing the discourse in this exciting field.

Prof. Dr. Radosław Wolniak
Dr. Judyta Kabus
Prof. Dr. Anna Brzozowska
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • artificial intelligence
  • business management
  • innovation in business
  • sustainable business practices
  • new technologies in business
  • digital transformation in business
  • customer experience in business
  • AI in business
  • ESG AI in business
  • entrepreneurship and AI
  • circular economy

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

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21 pages, 6322 KiB  
Article
Digitalisation to Improve Automated Agro-Export Logistics: A Comprehensive Bibliometric Analysis
by Luis Kevin Cortez-Clavo, Maryorie Irania Salazar-Muñoz and Rogger Orlando Morán-Santamaría
Sustainability 2025, 17(10), 4470; https://doi.org/10.3390/su17104470 - 14 May 2025
Viewed by 234
Abstract
Digitalisation in logistics has evolved in the search for continuous improvement and optimised processes. This study aims to determine the effectiveness of digitalisation implemented by companies to improve the automated logistics of cross-border trade in the agricultural sector. The research methodology was generated [...] Read more.
Digitalisation in logistics has evolved in the search for continuous improvement and optimised processes. This study aims to determine the effectiveness of digitalisation implemented by companies to improve the automated logistics of cross-border trade in the agricultural sector. The research methodology was generated through a bibliometric analysis, exploring the evolution of the state of the art through the Scopus, WOS and Dimensions databases, in order to select relevant empirical studies on digitalisation and automated logistics, using quality criteria and applying the PRISMA flow chart. The results highlighted that since 2017, there have been signs of increased interest from researchers, with authors such as Zoubek, Kumar and Ghobakhloo standing out. This review revealed how digitalisation contributes to the optimisation of costs and time in the logistics chain. Designing public policies allows for a better integration of technologies such as IoT and AI. Three important blocks were identified that have contributed to the effectiveness of digitalisation in automated logistics: the impact of digitalisation on logistics efficiency and the supply chain, technological integration and automation in cross-border logistics, and governance, policies and social considerations in logistics digitalisation. The conclusions reached were that digitalisation has been a fundamental element in improving logistics and making it autonomous within cross-border trade, allowing technology to become integrated and reducing obstacles in the supply chain through digital technologies such as artificial intelligence (AI). Full article
(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)
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26 pages, 763 KiB  
Article
Artificial Intelligence Technology, Organizational Learning Capability, and Corporate Innovation Performance: Evidence from Chinese Specialized, Refined, Unique, and Innovative Enterprises
by Shumei Han, Di Zhang, Hongfeng Zhang and Shuaijun Lin
Sustainability 2025, 17(6), 2510; https://doi.org/10.3390/su17062510 - 12 Mar 2025
Viewed by 1802
Abstract
In the context of global economic digital transformation and technological innovation, the application of AI Technology has a profound impact on corporate innovation and development. Existing research has primarily focused on the direct effect of AI Technology on Corporate Innovation Performance, while there [...] Read more.
In the context of global economic digital transformation and technological innovation, the application of AI Technology has a profound impact on corporate innovation and development. Existing research has primarily focused on the direct effect of AI Technology on Corporate Innovation Performance, while there is limited exploration of its interaction with organizational learning mechanisms. Based on the Dynamic Capabilities Theory, this study constructs a framework of “Technology—Individual Learning Capability—Team Learning Capability—Innovation Performance”, analyzing how AI Technology enhances learning capabilities to drive improvements in innovation performance and explores the moderating role of Organizational Learning Capability. Through empirical analysis of data from Specialized, Refined, Unique, and Innovative Enterprises in China, the study finds that AI Technology significantly enhances Corporate Innovation Performance, with Organizational Learning Capability playing a critical moderating role. Additionally, heterogeneity analysis indicates that factors such as production factors, industry characteristics, and firm size significantly influence the effectiveness of AI Technology in enhancing innovation performance. This research reveals the pathway through which AI Technology optimizes organizational learning mechanisms to improve innovation performance, offering both theoretical support and practical guidance for corporate strategic decision-making. Full article
(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)
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18 pages, 588 KiB  
Article
Intelligent Development, Knowledge Breadth, and High-Tech Enterprise Innovation: The Moderating Role of Knowledge Absorptive Capacity
by Jin Zhang and Duoxun Ba
Sustainability 2024, 16(18), 8155; https://doi.org/10.3390/su16188155 - 18 Sep 2024
Cited by 1 | Viewed by 1476
Abstract
Innovation serves as the cornerstone for high-quality development in high-tech enterprises, with intelligent development emerging as a central aspect of innovation efforts. However, how intelligent development promotes the innovative development of high-tech enterprises is still a topic of continuous debate and exploration. By [...] Read more.
Innovation serves as the cornerstone for high-quality development in high-tech enterprises, with intelligent development emerging as a central aspect of innovation efforts. However, how intelligent development promotes the innovative development of high-tech enterprises is still a topic of continuous debate and exploration. By integrating enterprise innovation theory and knowledge-based theory, this paper constructs a theoretical framework to examine the influence of intelligent development on high-tech enterprise innovation. Through an analysis of 694 listed high-tech enterprises on China’s manufacturing A-share market from 2013 to 2021, we empirically investigated the effects of mediating mechanisms and moderating effects of intelligent development on high-tech enterprise innovation. The results show that intelligent development significantly boosts high-tech enterprise innovation. Knowledge breadth plays a mediating role in the relationship between intelligent development and high-tech enterprise innovation, indicating that intelligent development promotes high-tech enterprise innovation by enhancing knowledge breadth. Additionally, knowledge absorptive capacity can strengthen the impact of knowledge breadth on high-tech enterprise innovation, that is, the stronger the knowledge absorptive capacity, the greater the impact of knowledge breadth on high-tech enterprise innovation. The conclusion of this paper provides a theoretical basis and practical guidance for high-tech enterprises regarding how to better use intelligent technology for innovation. Relevant enterprises can strengthen their knowledge management and mobility strategies and fully utilize the potential of intelligent technology to achieve more innovative and competitive development. Full article
(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)
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24 pages, 618 KiB  
Article
Artificial Intelligence and Technological Innovation: Evidence from China’s Strategic Emerging Industries
by Daojun Li, Haiqin Wang and Juan Wang
Sustainability 2024, 16(16), 7226; https://doi.org/10.3390/su16167226 - 22 Aug 2024
Cited by 6 | Viewed by 5253
Abstract
Artificial intelligence (AI) is the driving force for the leapfrog development of science and technology, the optimization and upgrading of industry, as well as the overall leap in productivity. Using panel data of strategic emerging firms in Chinese A-Share Listed companies from 2012 [...] Read more.
Artificial intelligence (AI) is the driving force for the leapfrog development of science and technology, the optimization and upgrading of industry, as well as the overall leap in productivity. Using panel data of strategic emerging firms in Chinese A-Share Listed companies from 2012 to 2022, this study empirically examines the impact of AI on technological innovation through a two-way fixed-effects model. The study discovered that technological innovation capability can be greatly enhanced by the degree of AI present in strategic emerging industry businesses. This conclusion remains valid following a series of robustness tests. The mechanism study demonstrates how the degree of AI increases businesses’ capacity for technological innovation by lowering funding constraints and boosting R&D investment. According to heterogeneity analysis, AI has varying empowering effects on different industries within strategic emerging industries. Its strongest empowering effect is observed in the western region, with the central and eastern regions seeing the weakest effects. Additionally, the promotion effect of AI is greater for state-owned enterprises than for non-state-owned enterprises. To better play the role of AI in encouraging the technical innovation of firms in strategic emerging industries, it is required to establish dedicated funds, create an AI technology innovation platform, and develop differentiated regulations. Full article
(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)
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Review

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21 pages, 1114 KiB  
Review
Innovation Reefs (I-Reef): Innovation Ecosystems Focused on Regional Sustainable Development
by Angelica Duarte Lima, André Luiz Przybysz, David Nunes Resende and Regina Negri Pagani
Sustainability 2024, 16(22), 9679; https://doi.org/10.3390/su16229679 - 6 Nov 2024
Viewed by 1370
Abstract
The creation of successful innovation ecosystems, like Silicon Valley, is challenging due to significant cultural, infrastructural, and resource differences between regions. In this context, the Innovation Reef (I-Reef) model emerges as a promising alternative, offering an approach for regions with limited resources to [...] Read more.
The creation of successful innovation ecosystems, like Silicon Valley, is challenging due to significant cultural, infrastructural, and resource differences between regions. In this context, the Innovation Reef (I-Reef) model emerges as a promising alternative, offering an approach for regions with limited resources to develop successful innovation ecosystems based on cooperation and mutual benefit among participants. This model has great potential to promote regional development, especially due to its focus on retaining and sharing the value generated. However, the role of I-Reef in sustainable regional development still needs to be further explored. Thus, the objective of this study is to deepen the theoretical understanding of the I-Reef model by analyzing its contribution to sustainable development. To achieve this, a comparison was made between I-Reef and established models such as business, innovation, knowledge, and entrepreneurial ecosystems. A systematic literature review conducted on Scopus found 704 articles published in the last three decades. The purpose was to identify the similarities and differences between the models of innovation business ecosystem models. The results show that there is alignment between I-Reef and the different ecosystems on several points. A central aspect of I-Reef is that it relies on a strong network of mutually beneficial relationships, much more oriented to sustainable development than the other models, which is a key factor in generating competitive advantage and development for the region. This characteristic is either not addressed or not placed at the core of the ecosystems discussed in the literature. For future research, empirical studies and validation of the I-Reef model with experts are suggested, as this theoretical study lays the foundation for more in-depth analyses. Full article
(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)
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