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The purpose of this paper is to explore the emergence of innovation in smart service systems to conceptualize how actor’s relationships through technology-enabled interactions can give birth to novel technologies, processes, strategies and value. The objectives of the study are: to detect the different enablers that activate innovation in smart service systems; and to explore how these can lead dynamically to the emergence of different innovation patterns.

The empirical research adopts an approach based on constructivist grounded theory, performed through observation and semi-structured interviews to investigate the development of innovation in the Italian CTNA (Italian acronym of National Cluster for Aerospace Technology).

The identification and re-elaboration of the novelties that emerged from the analysis of the Cluster allow the elaboration of a diagram that classifies five different shades of innovation, introduced through some related theoretical propositions: technological; process; business model and data-driven; social and eco-sustainable; and practice-based.

The paper embraces a synthesis view that detects the enabling structural and systems dimensions for innovation (the “what”) and the way in which these can be combined to create new technologies, resources, values and social rules (the “how” dimension). The classification of five different kinds of innovation can contribute to enrich extant research on value co-creation and innovation and can shed light on how given technologies and relational strategies can produce varied innovation outcomes according to the diverse stakeholders engaged.

Quality management practitioners have yet to cease the potential of digitalisation. Furthermore, there is a lack of tools such as frameworks guiding practitioners in the digital transformation of their organisations. The purpose of this study is to provide a framework to guide quality practitioners with the implementation of digitalisation in their existing practices.

A review of literature assessed how quality management and digitalisation have been integrated. Findings from the literature review highlighted the success of the integration of Lean manufacturing with digitalisation. A comprehensive list of Lean Six Sigma tools were then reviewed in terms of their effectiveness and relevance for the hybrid digitisation approach to process improvement (HyDAPI) framework.

The implementation of the proposed HyDAPI framework in an industrial case study led to increased efficiency, reduction of waste, standardised work, mistake proofing and the ability to root cause non-conformance products.

The activities and tools in the HyDAPI framework are not inclusive of all techniques from Lean Six Sigma.

The HyDAPI framework is a flexible guide for quality practitioners to digitalise key information from manufacturing processes. The framework allows organisations to select the appropriate tools as needed. This is required because of the varying and complex nature of organisation processes and the challenge of adapting to the continually evolving Industry 4.0.

This research proposes the HyDAPI framework as a flexible and adaptable approach for quality management practitioners to implement digitalisation. This was developed because of the gap in research regarding the lack of procedures guiding organisations in their digital transition to Industry 4.0.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

This paper will discuss one university’s efforts to initiate a process to better support PK-12 continuous school improvement goals for all 13 schools in their PDS network as a way to broaden the university’s mission and respond more formally to the individual school communities with which they partner.

The paper is conceptual in that it presents an innovative idea to stimulate discussion, generate new ideas and advance thinking about cross-institutional collaboration between universities and professional development schools.

The paper provides insights and ideas for bringing about change and growth in a seasoned PDS partnership network by connecting PK-12 continuous school improvement efforts to PDS partnership work.

This paper fulfills an identified need to study how seasoned partnerships can participate in simultaneous renewal by offering ideas that school–university partnership leaders can build upon as they make efforts to participate in the process of growth and change.

This study aims to examine how the legitimacy of internal auditing is reconstructed during enterprise resource planning (ERP)-driven technological change.

The study is based on the comparative analysis of internal auditing and its transformation due to ERP implementations at two case firms operating in the food sector in Egypt – one a major Egyptian multinational corporation (MNC) and the other a major domestic company (DC).

Internal auditors (IAs) at MNC saw ERP implementation as an opportunity to reconstruct the legitimacy of internal auditing work by engaging and partnering with actors involved with the ERP change. In doing so, the IAs acquired system certifications and provided line functions and external auditors with data-driven business insights. The “practical coping mechanism” adopted by the IAs led to the acceptance (and legitimacy) of their work. In contrast, IAs at DC adopted a purposeful strategy of disengaging, blaming and rejecting since they were skeptical of the top management team's (TMT's) sincerity. The “disinterestedness” led to the loss of legitimacy in the eyes of the stakeholders.

The article offers two contributions. First, it extends the literature by highlighting a spectrum of behavior displayed by IAs (coping with impending issues vs strategic purposefulness) during ERP-driven technological change. Second, the article contributes to the literature on legitimacy by highlighting four intertwined micro-processes – participating, socializing, learning and role-forging – that contribute to reconstructing the legitimacy of internal auditing.

This article explores the emergence of organizational digital transformation in the rapidly advancing technological era. It discusses the origins, driving forces, strategies, challenges and broader implications.

The article employs a scoping review methodology that synthesizes knowledge from the existing literature, research, case studies and other relevant sources.

The findings underscore the pivotal role that organizational digital transformation plays in an era of relentless technological advancement. Leadership, organizational culture and technological enablers are identified as crucial drivers of innovation and competitiveness within organizations. The article also emphasizes ethics as a crucial element of digital transformation, focusing in particular on concerns about data privacy and the morality of artificial intelligence. Additionally, the author talks about anticipated future trends that are anticipated to influence the future of digital transformation, such as the growing influence of artificial intelligence, the trend toward hyper-personalization and the emergence of quantum computing.

The assessment has failed to provide recommendations for the actual implementation because it has mainly concentrated on conceptual and strategic aspects. Furthermore, it does not clearly define the criteria for choosing real-world examples, which limits the representation of the different industries, size ranges of organizations and outcomes associated with digital transformation.

The article stresses the significance of paying attention to the forces driving digital transformation while navigating ethical and societal concerns. In addition to highlighting the importance of anticipating future trends for strategic planning in the rapidly changing digital landscape, it emphasizes the advantages as incentives for organizations to invest in digital initiatives.

The investigation demonstrates how technology contributes to progress while posing complex ethical and change management issues. In light of increased connectivity, data analytics and artificial intelligence, it highlights the crucial need for societal adaptability and highlights the crucial role that cooperative human–machine coexistence plays in responsible development and transformative societal evolution.

The article stands out because it examines organizational digital transformation in-depth while considering its historical roots, ethical implications and future prospects. It is a priceless contribution to the field because real-world case studies and a scoping review provide a distinctive viewpoint and a comprehensive view of the effects of digital transformation on organizations and society.

The study seeks to understand the possible opportunities that Industry 5.0 might offer for various aspects of inclusive sustainability. The study aims to discuss existing perspectives on the classification of Industry 5.0 technologies and their underlying role in materializing the sustainability values of this agenda.

The study systematically reviewed Industry 5.0 literature based on the PRISMA protocol. The study further employed a detailed content-centric review of eligible documents and conducted evidence mapping to fulfill the research objectives.

The advancement of Industry 5.0 is currently underway, with noteworthy initial contributions enriching its knowledge base. Although a unanimous definition remains lacking, diverse viewpoints emerge concerning the recognition of fundamental technologies and the potential for yielding sustainable outcomes. The expected contribution of Industry 5.0 to sustainability varies significantly depending on the context and the nature of underlying technologies.

Industry 5.0 holds the potential for advancing sustainability at both the firm and supply chain levels. It is envisioned to contribute proportionately to the three sustainability dimensions. However, the current discourse primarily dwells in theoretical and conceptual domains, lacking empirical exploration of its practical implications.

This study comprehensively explores diverse perspectives on Industry 5.0 technologies and their potential contributions to economic, environmental and social sustainability. Despite its promise, the practical evidence supporting the effectiveness of Industry 5.0 remains limited. Certain conditions are necessary to realize the benefits of Industry 5.0 fully, yet the mechanisms behind these conditions require further investigation. In this regard, the study suggests several potential areas for future research.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.