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Technological advancements are reshaping the tourism industry, necessitating the adaptation of business models through digital technology utilisation for intelligent, sustainable and inclusive tourism offerings. The diverse nature of tourism businesses, encompassing size, technology access, risk aversion, labour intensity, and more, presents a spectrum of challenges and opportunities for business model innovation (BMI) and digital transformation (DT) to maintain competitiveness. This study focuses on the core aspects of DT and BMI within the tourism sector, offering pivotal insights to aid tourism companies embarking on the intricate journey of DT and BMI in this evolving landscape.

The study conducts an extensive literature review to identify critical issues and pathways for tourism businesses pursuing DT and BMI. The review is focused on the challenges, opportunities, risks and imperatives that tourism organisations have to navigate in the current DT landscape to renew their business model.

The findings underscore the pressing need for tourism businesses to undergo a holistic DT. While digital technologies are reshaping the essence of tourism value chains, the transformation extends beyond technology adoption to encompass a profound renewal of organisational culture, competencies, structure, leadership and operational models. This paradigm shift is indispensable for crafting more innovative, sustainable and more inclusive tourism development. The paper also provides strategic recommendations and outlines future research directions to fortify the transformational journey of the tourism sector.

The paper provides key insights into supporting DT and BMI in tourism businesses, advancing a nuanced understanding of the multifaceted challenges and opportunities tourism organisations face in the digital age.

This study aims to provide a methodology and tools to design new organizational processes and artificial intelligence (AI)-based scoring to optimize the resources management in healthcare units.

Process design and process data-driven simulation: the processes are designed by the business process modeling and notation and the unified modeling language standards. Data processing is performed by Correlation matrix analysis and by Fuzzy c-Means data clustering. The matching between the two methods provides the most indicated final corrective actions of the “TO BE” organizational model.

This proposed method, experimentally applied in this work merging the lean management model (LMM), process mining (PM) and AI methods, named process mining organization (PMO) model (Rosa et al., 2023 (b)), is able to improve organizational processes of a hospitalization unit (HU) by developing three propaedeutic phases: (1) analysis of the current state of the processes (“AS IS”) by identifying the critical issues as bottlenecks of processes, (2) AI data processing able to provide additional classified and predicted information allowing the “TO BE” workflow process and (3) implementation of corrective actions suggested by the PMO in order to support strategic decision-making processes in the short, medium and long term by classifying an order of priority about the healthcare procedures/protocols to perform.

The main limitation of the proposed case study is in the limited number of available digital data to process. This aspect reduces the capability to interpret result. In any case, the proposed methodology is a “launch” work to define a new approach to integrate organizational processes including workflow design and AI scoring. Future work will be focused on managerial implications due to use of the discussed method: design and development of new human resource (HR) organizational protocols following data analysis to optimize costs and care services and to decrease injury compensation claims.

Main implications are in healthcare managerial scenarios: design and development of new HR organizational protocols following data analysis to optimize costs and care services and to decrease injury compensation claims.

Care services optimization is addressed on HUs.

The design of HR organizational processes integrates AI-driven data decision-making processes. This case study examines AI-based innovation analytics addressed on resource efficiency.

The paper aims to interpret sustainable regional development (SRD) as an exchange ecosystem in which stakeholders provide reciprocal access to resources, benefiting both individual and systemic levels. This paper suggests that knowledge, as a shared and value-transcribed critical resource, nourishes a community’s motivational system (CMS), orienting it toward SRD. This inherently raises questions regarding the nature of social business models (SBM) that can best support community’s motivational system, as well as their sustainable regional development derivatives.

This paper employs the Fuzzy Expert System (FES) to analyze companies participating in the three most representative Italian consortia, aiming to empirically address the knowledge gap regarding the influence of social business model on sustainable regional development.

Applying our theoretical framework to Agro-food Protection Consortia – a specific type of hybrid social, regional value-oriented business organization – this paper demonstrates that knowledge sharing along environmental, social and economic dimensions enhances sustainable regional development. Using the IF (condition) → THEN (action) logic of fuzzy method, the study identified knowledge exchange as a key condition motivating actors to contribute to sustainable regional development. This dynamic approach enables better alignment between stakeholders and regional goals.

This paper presents practicable participatory strategic guidelines that balance informal and formal governance mechanisms with the catalytic and enhancing connection of strategic business initiatives for Sustainable Regional Development.

Despite the evident link between digitalisation and sustainability, many organisations have these two strategies operating on a parallel basis and not in a coordinated manner. Hence the objective of this work, which consists of proposing a model to analyse the connection existing between both strategies within the business environment, additionally relating them to innovation and Corporate Social Responsibility (CSR).

With that aim, the results of a survey answered by 98 managers of Spanish enterprises are examined using the PLS software, especially suited for the study of structural equations like the one put forward in this paper.

The conclusions drawn suggest that the most innovative firms are indeed the ones that invest to a greater extent in digitalisation and sustainability. It was also possible for us to verify that digitalisation exerts a positive influence on sustainability and that both the latter and digitalisation directly relate to CSR strategies. However, innovation as such does not constitute a requirement for CSR; instead, these Social Responsibility actions will take place when innovations rely on digitalisation and sustainability strategies.

Until now, most studies have addressed digitalisation and sustainability independently, with contradictory theoretical approaches in the literature about these two topics and a paucity of empirical results about the link between digitalisation and sustainability. The present study clarifies the relationships between sustainability and digitalisation, also relating them to innovation and CSR in the business environment.

This research delves into the realm of Business Model Innovation (BMI), integrating it with the human-centric, sustainable, and resilient principles of Industry 5.0, proposing a new theoretical framework.

An abductive approach has been chosen to expand existing knowledge developing new ideas based on emerging phenomena. Data were gathered via semi-structured interviews with directors, managers and curators of public institutions in Italy, Switzerland, Germany and Spain encompassing Galleries, Libraries, Archives, and Museums (GLAM). These data were subsequently subjected to thematic analysis.

The findings indicate that the main enablers for Business Model Innovation (BMI) in combination with Industry 5.0 encompassed stakeholder, customer and organizational engagement, collaborative environment, knowledge and innovation management, and sustainability. These drivers were effectively leveraged through three pivotal facilitators-inhibitors: technology, resources, and leadership.

The principal constraints are rooted in the narrow contextual focus and the limited participants number. However, upcoming research efforts may broaden the horizons of this multifaceted and extensive investigation.

This study is groundbreaking as it fills a significant gap in the existing literature by integrating Business Model Innovation (BMI) with the Industry 5.0 paradigm, a novel approach that has not been explored previously. Additionally, the inclusion of GLAM institutions in this research adds a unique dimension, as they have been largely overlooked in both research domains.