Digital Transformation (DT) is crucial for driving Business Model Innovations (BMIs) across sectors. It encompasses the integration of technology in business areas, reshaping approaches and value creation, delivery and capture processes. DT is a strategic process that leverages digital technologies such as Artificial Intelligence, Cloud Computing, the Internet of Things, and Big Data Analytics (Schneider et al., 2020; Vial, 2021), to streamline and improve business processes, enhance customer experiences, and increase efficiency. DT involves three different levels: externally, with a focus on the digital enhancement of customer experience; internally, shaping organizational structures and architectures; holistically, leading to the creation of new BMs and revenue streams (Woerner and Wixom, 2015), also enhancing competitiveness in an increasingly digital marketplace.
Additionally, DT results in a significant increase in the amount and variety of data from heterogeneous sources, which can be used to gain insights into business operations and customer behavior, leading to improved decision-making and increased efficiency (Marcon et al., 2022). Proper data use could provide valuable information to conceptualize and introduce BMIs, acting on both the internal and external sides. From an internal perspective, DT has profoundly affected infrastructure management, acting on the ways organizations can collect, process, and handle data to improve their operations and processes. For example, by analyzing resource utilization and productivity data, organizations could identify areas for improvement, such as streamlining processes or reducing waste as well as they can use data for production traceability purposes (Arnold et al., 2016). From an external perspective, organizations could gain insights into consumer preferences and behaviors, using data to enhance the customer value proposition (Müller et al., 2018; Bresciani et al., 2021), through tailored products and services, personalized marketing and targeted advertising, which could turn into higher customer satisfaction and loyalty. In all cases, the use of data can lead to increased efficiency, reduced costs, and improved decision-making strengthening BMIs.
Since these changes have increasingly attracted academic, practitioner, and policy-maker interest, this track aims to contribute to the growing discussion of the proper use of DT data to foster BMIs, by addressing various topics such as (but not limited to):

• Digital Transformation as antecedent and enabler of Business Model Innovations;
• Unlocking the potential of Digital Transformation for data-driven Business Model Innovations;
• Disentangling opportunities and barriers in DT-driven Business Model Innovations;
• Data value creation and appropriation and Business Model Innovations;
• The role of Digital Transformation in reshaping entrepreneurship;
• Digital Transformation-related skills and capabilities for Business Model Innovations in high and low-tech industries;
• Digital Transformation, Business Model Innovation, and consumer behaviors;
• Digital Transformation and Business Model Innovations toward a sustainable competitive advantage;
• Strategizing Digital Transformation and Business Model Innovations for ecosystem development;
• Digital Transformation and Business Model Innovations for firms’ survival and performances.

Veronica Marozzo, University of Messina, Italy
Alessandra Costa, University of Messina, Italy
Tindara Abbate, University of Messina, Italy