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Systems
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Business Model Innovation in the Digital Era
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Business Model Innovation in the Digital Era

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 4957

Special Issue Editors

Dr. Claudia Covucci

E-Mail Website
Guest Editor
Faculty of Society and Communication Sciences, Universitas Mercatorum, 00186 Rome, Italy
Interests: corporate sustainability; corporate social responsibility; social media; digital marketing; marketing management; management; entrepreneurship
Dr. Maria Giovanna Confetto

E-Mail Website
Guest Editor
Department of Political and Communication Sciences, University of Salerno, 84084 Fisciano, Italy
Interests: business management; marketing; corporate communication; digital marketing; social media; corporate sustainability; corporate social responsibility; brand management

Special Issue Information

Dear Colleagues,

This Special Issue focused on interconnected value systems as a powerful lens for analyzing business model innovation in the digital era. A value system refers to a network of activities, resources, and partners that enable a business to create and deliver value to its stakeholders. Indeed, business models in the digital age operate within a network of mutually dependent and constantly evolving components. Understanding their interrelationships is crucial for fostering innovation and resilience in today's dynamic business environment. It allows companies to view their operations holistically, optimize interactions within the broader ecosystem using digital technologies, navigate platforms’ complexity, and adapt to disruptive changes. Furthermore, it necessitates the development of new metrics to assess the performance and sustainability of these dynamic systems.

This Special Issue seeks original contributions that emphasize the interconnected nature of modern business models as complex systems, advancing our understanding of how holistic, systems-based approaches can drive innovation, resilience, and sustainability in an increasingly digital world. We welcome various research approaches, including theoretical frameworks, in-depth case studies, empirical research, and comparative studies. We are particularly interested in research that addresses (but are not limited to):

  • How digital technologies (e.g., Big Data, AI, blockchain) reshape the interactions between different components of a business model (value propositions, channels, customer segments, etc.);
  • The emergence of platform-based business models and how they redefine the boundaries and interdependencies within a value system;
  • The co-creation of value within digital ecosystems, where businesses collaborate with partners and stakeholders to deliver integrated solutions;
  • The impact of disruptive technologies on established value systems and the strategies for adaptation and innovation;
  • The development of metrics and frameworks to evaluate the performance and sustainability of interconnected value systems in the digital age.

Dr. Claudia Covucci
Dr. Maria Giovanna Confetto
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. Systems is an international peer-reviewed open access monthly 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

  • interconnected value systems
  • business model innovation
  • digital business model
  • digital ecosystems
  • value co-creation
  • value system
  • open innovation

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Published Papers (5 papers)

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Research

33 pages, 1136 KiB  
Article
Business Model Innovation: A Bridge Between Corporate Social Responsibility and Successful Performance for Medium-Size Enterprises (SMEs) in the Digital Era
by Mohammadsadegh Omidvar, Maria Giovanna Confetto and Maria Palazzo
Systems 2025, 13(5), 378; https://doi.org/10.3390/systems13050378 - 14 May 2025
Viewed by 299
Abstract
Business model innovation (BMI) is a topic that has attracted significant interest from both researchers and academics. While research has suggested that there are associations between BMI and corporate social responsibility (CSR), as well as between BMI and firm performance (FP), we lack [...] Read more.
Business model innovation (BMI) is a topic that has attracted significant interest from both researchers and academics. While research has suggested that there are associations between BMI and corporate social responsibility (CSR), as well as between BMI and firm performance (FP), we lack theoretical substantiation and empirical verification of these relationships. This study proposes that BMI mediates the link between CSR and FP. This research aims to investigate the mediating role of BMI between various aspects of CSR, introduced by Carroll, and the performance of medium-size enterprises (SMEs) in Iran. To achieve the research aim, 483 questionnaires were gathered from SMEs in Iran. To evaluate the conceptual model’s validity, structural equation modeling (SEM) was used. The results of this study show that BMI mediates the relationship between all the aspects of CSR introduced by Carroll and FP and only does not mediate the relationship between the environmental dimension and FP. As far as we know, this investigation is among the earliest to explore the relationship between BMI and CSR dimensions through mediation. In response to the increasing significance of environmental issues, this research incorporates a fresh element, namely environmental responsibility, into Carroll’s model. Managers can gain a better understanding of CSR and its impact on FP from the results of this research. This study reveals that managers emphasize certain aspects of CSR which can influence BMI and FP. Full article
(This article belongs to the Special Issue Business Model Innovation in the Digital Era)
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21 pages, 1121 KiB  
Article
A Systematic Mapping-Driven Framework for Vetting Participation in Business Ecosystems
by Margaret Mastropetrou, Konstadinos Kutsikos and George Bithas
Systems 2025, 13(4), 236; https://doi.org/10.3390/systems13040236 - 29 Mar 2025
Viewed by 255
Abstract
A key strategic option for many organizations across the globe is to examine whether and how business ecosystems can help them survive and thrive amidst continuous changes in business realities. Joining a business ecosystem, though, is not a straightforward decision. Current research efforts [...] Read more.
A key strategic option for many organizations across the globe is to examine whether and how business ecosystems can help them survive and thrive amidst continuous changes in business realities. Joining a business ecosystem, though, is not a straightforward decision. Current research efforts are falling short of fully identifying a concise and practical set of decision-making factors that potential ecosystem participants can meaningfully use. To address this limitation, the authors developed a framework of decision-making factors (motivations, prerequisites, ecosystem attractiveness), based on (a) their findings of a systematic mapping study they conducted and (b) their parallel research efforts in business ecosystems operations. The proposed framework encompasses a concrete “vocabulary” of decision-making factors that can enable complex “dialogs” between existing and new business ecosystem stakeholders. As a result, this research effort (a) offers a clear and unambiguous categorization of previously overloaded and ambiguous decision-making factors; (b) captures relationships between the three core components of the proposed framework, thus considering upfront any synergies or conflicts among them; and (c) makes the candidate organization’s decision-making process pragmatic, i.e., misalignment among the proposed factors should be considered a ‘red flag’ that may drive the candidate organization to pivot its decision-making process towards another business ecosystem. Full article
(This article belongs to the Special Issue Business Model Innovation in the Digital Era)
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25 pages, 3922 KiB  
Article
Marketing Strategy Metamorphosis Under the Impact of Artificial Intelligence Services
by Adrian Stancu and Mirela Panait
Systems 2025, 13(4), 227; https://doi.org/10.3390/systems13040227 - 26 Mar 2025
Viewed by 542
Abstract
Companies’ marketing decision-making effectiveness depends on the quality of actions and time. In the current digital era, any marketing decision making must be timely in response to customers’ feedback, and implementing artificial intelligence (AI) technology is one significant option. This paper focuses on [...] Read more.
Companies’ marketing decision-making effectiveness depends on the quality of actions and time. In the current digital era, any marketing decision making must be timely in response to customers’ feedback, and implementing artificial intelligence (AI) technology is one significant option. This paper focuses on designing an Algorithm for Marketing Strategy Decision Making (AMSDM) that employs AI services to process online feedback from customers regarding products and services from companies’ websites or other e-commerce and social media platforms. For this research, 1200 texts containing customer feedback were analyzed by Azure Text Analytics service, which identifies the types of customers’ online feedback, domains, subdomains, and keywords it refers to and understands the emotional tone and attitudes conveyed in customer responses through sentiment analysis techniques. The model performance was underlined by computing the Accuracy, Precision, Recall, and F1-Score metrics for both short and long phrases feedback. Furthermore, Azure Text Analytics was integrated into a C# script to extract the frequency of occurrence of domains, subdomains, and keywords. After that, the process of AMSDM and its advantages were detailed. The AMSDM eliminates the necessity for manual intervention and conserves both time and resources. Moreover, the real-time nature of the analysis allows companies to respond promptly to changing market dynamics and customer preferences. Full article
(This article belongs to the Special Issue Business Model Innovation in the Digital Era)
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19 pages, 867 KiB  
Article
Data-Driven Business Model Innovation in Europe: Ethical Data Practices and Ecosystem Involvement
by Marikka Heikkilä, Jukka Heikkilä and Farhan Ahmad
Systems 2025, 13(3), 164; https://doi.org/10.3390/systems13030164 - 27 Feb 2025
Viewed by 979
Abstract
Creating, sharing, and using data are expected to lead to the development of new innovative business models. This study investigates the interplay between business model change, ethical data practices, and participation in data ecosystems in fostering data-driven innovation. Using survey data from 1200 [...] Read more.
Creating, sharing, and using data are expected to lead to the development of new innovative business models. This study investigates the interplay between business model change, ethical data practices, and participation in data ecosystems in fostering data-driven innovation. Using survey data from 1200 European companies, analyzed through partial least squares structural equation modeling (PLS-SEM), the findings reveal that while firms recognize the potential benefits of data, business model change alone is insufficient to drive innovation. Instead, active engagement in data ecosystems and adherence to ethical data practices together have a significant positive impact on data-driven innovation. This research contributes to the business model innovation literature by highlighting the role of ecosystems and ethical governance in shaping sustainable data-driven innovations. This study also provides practical insights for firms seeking to transition toward more collaborative and ethically grounded data-driven business models. Full article
(This article belongs to the Special Issue Business Model Innovation in the Digital Era)
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28 pages, 2741 KiB  
Article
Integrating Artificial Intelligence into Service Innovation, Business Development, and Legal Compliance: Insights from the Hainan Free Trade Port Era
by Yincheng Li, Shumin Wang and Muhammad Bilawal Khaskheli
Systems 2024, 12(11), 463; https://doi.org/10.3390/systems12110463 - 31 Oct 2024
Cited by 1 | Viewed by 1935
Abstract
This research aims to inspect the application of Artificial Intelligence (AI) in product and service innovation from the perspective of the Hainan Free Trade Port (HFTP) and its relationship with corporate transformation, legal compliance, and regulatory oversight. Being critical to the fourth industrial [...] Read more.
This research aims to inspect the application of Artificial Intelligence (AI) in product and service innovation from the perspective of the Hainan Free Trade Port (HFTP) and its relationship with corporate transformation, legal compliance, and regulatory oversight. Being critical to the fourth industrial revolution, digital business and international cooperation, technology propels enterprises across various industries to transition from traditional models to intelligent and service-oriented ones. It also elucidates the theoretical foundations of AI products, the digital economy, and service innovation. It can be used to analyzes the challenges enterprises face in the HFTP while implementing AI technology, including funding, technology, management, operations, corporate culture, and innovative concepts. Based on the proposed research methodology, three hypotheses can be formulated. Hypothesis 1 states that the HFTP could facilitate enterprise transformation by applying supportive policies. Hypothesis 2 state that domestic laws and international agreements are urgently needed due to the legal risks arising from artificial intelligence. Hypothesis 3 state that HFTP enterprises comply with these laws while systemically assuring, in theory, and practice, the legal risks of artificial intelligence and its implications for legal regulation, which is a significant aspect of research, addressing legal risks related to data privacy, security, and algorithmic bias with many strategies being proposed. This shows how AI technology can change businesses in the HFTP, demonstrating the application of AI technology in the transformation of enterprises in the HFTP and the various risks they may encounter, providing valuable references for other enterprises regarding the practical significance of AI product and service innovation in the HFTP, and emphasizing the importance of international cooperation and legal instruction. Full article
(This article belongs to the Special Issue Business Model Innovation in the Digital Era)
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