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Explainable Artificial Intelligence in Manufacturing Operations: A Bibliometric Analysis
No full textPart 2: New Horizons for Intelligent Manufacturing Systems with IoT, AI, and Digital TwinsInternational audienceThis paper presents a bibliometric analysis of explainable artificial intelligence (XAI) within the manufacturing sector, with a focus on the critical areas of quality, maintenance, and production. Despite the increasing integration of XAI in industrial applications, a bibliometric exploration of its impact across these specific dimensions remains uncharted. Our study fills this gap by employing bibliometric methods to map the landscape of XAI research in manufacturing, analyzing publication patterns and thematic evolutions. Understanding this landscape is crucial, as it not only highlights the current state and trajectory of XAI applications in manufacturing but also identifies key areas where further innovation and investigation can significantly enhance efficiency, transparency, and decision-making processes in the industry. Utilizing the Bibliometrix R-package and data from the Scopus database, we analyze 107 publications from 2019 to 2024. We chart the intellectual trajectory of XAI, delving into predominant themes and observing a research progression from foundational machine learning to its sophisticated applications, culminating in Industry 4.0 innovations. The analysis reveals an academic landscape where explainability is increasingly intertwined with the technological advances of smart manufacturing, spotlighting key topics and their evolution that reflect the field’s dynamic nature. This investigation offers a novel lens on the bibliometric trends shaping the development of transparent, intelligent systems within the manufacturing sector
Digital Transformation Towards Human-Centricity: A Systematic Literature Review
No full textPart 1: Digital Transformation Approaches in Production and ManagementInternational audienceThe advent of Industry 4.0, over its decade-long evolution, primarily concentrated on digital and smart technologies to enhance production efficiency, often overlooking human involvement and environmental considerations. Despite the recent emergence of Industry 5.0 as a new research paradigm, its exploration is still in its early stages, with limited systematic investigation and a lack of empirical evidence. Therefore, this paper aims to examine the research topics at the intersection of “Human-Centricity” and “Industry 5.0” in the field of manufacturing as covered by academic journals and conference proceedings. We used the systematic literature review method PRISMA to identify 77 publications. The results portray six avenues for future research: (i) Human-Centric Design and Human-Robot Interaction, (ii) Industry 5.0 Frameworks and Theoretical Models, (iii) AI and Advanced Data Analytics, (iv) Smart Manufacturing and Sustainability, (v) Training, Skills Development, and Worker Wellbeing, and (vi) Ergonomics and Safety in Manufacturing
Post-adoption Barriers to Metaverse Usage: An Active-Passive Resistance Perspective from Consumer Reviews
No full textPart 2: Digital Transformation and Organizational InnovationInternational audienceUnlike adoption, the post-adoption behaviour of metaverse applications has not been thoroughly investigated. The study aims to investigate the active and passive resistance-causing barriers experienced by users of Metaverse applications post adoption. A total of 70631 critical user reviews were obtained from 10 different Metaverse applications and subjected to text analytics procedures to identify relevant themes as barriers to post-adoption metaverse usage. The findings revealed high presence of system-related barriers and low presence of functional and psychological barriers as active resistance with high presence of passive resistance through individual barriers. The findings can be utilized by metaverse-developers to retain users post adoption
Public Value-Driven Assessment of Trustworthy AI in the Public Sector: A Review
No full textPart 1: Artificial Intelligence Adoption and ImpactInternational audienceDespite the potential benefits of Artificial Intelligence (AI) to enhance public services, the implementation of AI in the public sector is still limited. In this work, we review the trustworthy AI literature in the public sector and provide insights into the prevailing challenges of creating and sustaining public value with AI. Findings show that research on public value-driven AI assessment is still in its infancy. It lacks an overall critical perspective on human-centric AI in general and citizen engagement in particular. Recommendations are given for future research on conducting in-depth empirical studies geared towards measuring and operationalizing ethical and societal components of AI assessment frameworks in the public sector, specifically aiming at the creation of public value
Designing Collaborative Business Models for Sustainable Digital Solutions: The Case of a Shared-Micromobility Service
No full textPart 2: Digital Transformation and Organizational InnovationInternational audienceExisting firm-centric approaches to business model design cannot sufficiently capture the essential elements characterizing sustainable digital solutions enabled by collaborations in a network. To foster value co-creation and align the interests and responsibilities of all stakeholders involved in such networks, a network-centric perspective to business model design is more appropriate. In this paper, we present the design of a collaborative business model for a digital solution - a shared-micromobility solution. We examine three prominent approaches to represent the business model and discuss their limitations. Following an inductive approach based on the business case, we derive and propose core conceptual elements of collaborative business models in the context of sustainability
Rethinking Europe’s Digital Future: Challenges and Risks from GAFAM
No full textPart 2: Digital Transformation and Organizational InnovationInternational audienceThis study analyzes the effects, risks, and opportunities of digitalization for Europe, with a specific focus on the dominance of leading US digital companies known as GAFAM (Google, Amazon, Facebook, Apple, Microsoft). The central research question examines whether Europe could be at risk of falling into digital colonization due to the influence of these tech giants. Through a systematic literature review, the study evaluates Europe’s digital strategy and conducts a risk analysis of the associated economic and social challenges. The findings highlight the critical importance of addressing issues related to IT security, sustainability (green and sustainable IT), and AI safety for businesses operating in the digital landscape
A Systematic Literature Review on Service Robot Attributes and Organizational Climate’s Role
No full textPart 2: Digital Transformation and Organizational InnovationInternational audienceService robots are gaining increasing attention due to their potential productivity and efficiency gains. However, implementing service robots within an organization faces challenges because service robots possess characteristics that can affect employees in a negative or positive direction. It is therefore important to examine which characteristics matter most. Additionally, organizational characteristics, in particular the prevailing organizational climate, are important to provide a conducive work atmosphere in robot adoption. However, the latter has been less emphasized in service robot studies so far. Therefore, this study sets out to investigate the importance of both service robot characteristics and organizational climate for robot implementation in the workplace. Drawing on two respective systematic literature reviews, we have uncovered four groups of service robot attributes (i.e., social attributes, physical attributes, operating modes, and degrees of intelligence) and four groups of organizational climate attributes (i.e., resources, communication, leadership, and job autonomy), including their effects on particular service robot outcomes within an organization. Theoretically, this study adds insight through identifying key service robot characteristics and considering organizational climate as a novel angle for future research. For practice, this paper offers adoption advice to managers on service robot implementation while considering the organizational climate at work
Critical Success Factors for Designing and Implementing Network-Based Business Models
No full textPart 2: Digital Transformation and Organizational InnovationInternational audienceToday’s dynamic business environment requires organizations to transition from pipeline to network-based business models. Such business models involve diverse stakeholders, such as suppliers, customers, and partners, collaborating to co-create value as a network. Designing and implementing a network-based business model is challenging. While existing literature offers methods and tools, a gap remains in providing guidance for this transition. Critical success factors (CSFs) have proven effective in helping organizations identify actions necessary to succeed in key areas. This study aims to develop a catalog of CSFs related to network-based business models, providing guidance by categorizing and offering detailed descriptions of these factors. Following a design science approach, we developed an initial version of the catalog through a systematic literature review and revised and evaluated it through a focus group study and interviews. Our study contributes to research by providing a catalog of CSFs related to network-based business models, synthesized from a broad literature and empirically evaluated
Towards a Time-Dependent Approach for User Privacy Expression and Enforcement
No full textInternational audienc
Harnessing Generative AI for Sustainable Innovation: A Comparative Study of Prompting Techniques and Integration with Nature-Inspired Principles
No full textPart 1: AI-Driven TRIZ and InnovationInternational audienceAmidst growing environmental challenges and the imperative for sustainable solutions, this study explores how generative artificial intelligence (AI) can drive innovation in process engineering. It investigates the effectiveness of different prompting techniques and their integration with nature-inspired principles (NIP) in fostering sustainable innovation. The study employs a comparative methodology to assess the effectiveness of two distinct prompting techniques: basic and AI-automated prompting. It also examines the influence of integrating NIP derived from various natural ecosystems on the generated solutions. Experiments were conducted using a generative AI model and analysing the output, focusing on the number of unique and overlapping ideas. Furthermore, the quality of AI-generated solution concepts was evaluated using four parameters, such as feasibility, novelty, usefulness, and sustainability, each rated on a scale of 0 to 2. Three case studies within the process engineering domain were used, each representing a different problem-solving scenario. The results showed that the integration of NIP, particularly through the “one by one” strategy in AI-automated prompting, significantly increased the number of unique ideas compared to basic prompting, demonstrating its effectiveness in enhancing idea diversity and quality. Concepts generated through this approach also scored higher in novelty and sustainability, aligning with sustainable innovation goals. These findings have practical implications for developing innovative and sustainable engineering solutions, particularly in the early phases of design, offering insights into effective strategies for leveraging AI in eco-innovation