Contenu du sommaire : Artificial Intelligence and Sustainability

Revue Journal of Innovation Economics Mir@bel
Numéro no 44, 2024/2
Titre du numéro Artificial Intelligence and Sustainability
Texte intégral en ligne Accès réservé
  • Focus

    • Diversify Approaches to Better Understand the Compatibility of Artificial Intelligence and Sustainability: “I Love You… Me Neither” - Aude Rychalski, Mathilde Aubry p. 1-21 accès libre avec résumé en anglais
      The aim of this article is twofold: 1. Suggest an overview of current knowledge and understanding of both concepts and 2. Present the six contributions and their positioning in relation to current the literature linked to artificial intelligence and sustainability. For that, we use different but complementary sources. First, we ask artificial intelligence to reveal the mainstream view. Then we call on human intelligence to provide a critical perspective. Finally, we carry out a bibliometric analysis using the SCOPUS database and two different statistical analyses (the CCA – co-citation analysis, the BCA – bibliographic coupling analysis). The diversity of the sources used, and their complementarity allow us to propose a holistic vision of the subject, highlighting the concerns that surround it and identifying future avenues of research for academics. The articles selected in this special issue fill some of the gaps raised and call for further research.JEL Codes: O33, O44, Q55, Q56
  • Sustainability as the Missing Link to Uncover the Double Edge of NFT Technology Legitimacy - Insaf Khelladi, Sylvaine Castellano, Catherine Lejealle p. 23-51 accès libre avec résumé en anglais
    Although academic and practical interest in non-fungible tokens (NFTs) has continuously increased over the last few years, there is still a need to better understand their social acceptability. The aim of the study was to explore the double edge of NFT legitimacy for NFTs by unveiling the role of sustainability and by adopting technology legitimacy and the field of sustainability transition studies as a theoretical lens. Specifically, this research investigates the role of sustainability in securing and maintaining technology legitimacy within NFT projects. We interviewed 12 experts through exploratory qualitative research. The findings highlight three main ways in which sustainability participates in the legitimation of NFT projects. While sustainability can be inherent in the NFT project itself, this legitimation can also be derived from the perceived sustainability of the NFT technology or be part of innovative business models. Theoretical contributions and managerial implications are then discussed. JEL CODES: O33, O35, O50
  • Healthcare Sustainability: The Role of Artificial Intelligence Acceptance by Medical Staff - Chantal Ammi, Galina Kondrateva, Patricia Baudier p. 53-86 accès libre avec résumé en anglais
    Artificial Intelligence (AI) is applied to many activities, including healthcare. Based on two studies, this article aims to investigate the role of AI in healthcare sustainability by analyzing AI acceptance from the perspective of the United Theory of Acceptance and Use of Technology (UTAUT) and through the lens of the United Nations Sustainable Development Goals (SDGs), organized around three pillars: economy, environment and society. Our research uses a mixed method approach: a quantitative survey of medical staff and qualitative interviews with experts (AI and health). The findings confirm the importance of technology-trusting performance for AI solution acceptance, the impact of performance expectancy, habit and personal innovativeness on usage intention and the influence of technology anxiety. The qualitative study confirms that the societal, economic and ecological improvement-oriented SDGs are important in maintaining healthcare sustainability. Our results also shed light on the challenges faced when environmental goals lack a practical focus. JEL Codes: I12, J28, J81, M15, M54, O33
  • Making Artificial Intelligence Sustainable for Healthcare1 - Anna Bastone, Giulia Nevi, Francesco Schiavone, Fabian Bernhard, Luca Dezi p. 87-117 accès libre avec résumé en anglais
    This research aims to define a roadmap for the sustainable implementation of Artificial Intelligence (AI) in healthcare. Based on Triple Bottom Line (TBL) and the theory of dynamic capabilities (DC), the study highlights which steps and capabilities are needed to ensure an Artificial Intelligence (AI) implementation guaranteeing the three levels of sustainability ( people, profit and planet). This study tries to respond to the following research question: How can healthcare organizations ensure sustainable implementation of Artificial Intelligence? An exploratory qualitative analysis was conducted using the focus group method. The results highlight six main steps for the sustainable implementation of AI, each with specific capabilities to be developed. This study provides implications for both theory and practice. Future research will be needed to investigate the emerging aspects. JEL CODES: M21, I15, O30
  • Making Artificial Intelligence More Sustainable: Three Points of Entry into an Ethical Black Box - Yoann Bazin p. 119-136 accès libre avec résumé en anglais
    The technological leaps in artificial intelligence (AI) over the past twenty years have profoundly renewed its ability to support, if not replace, humans in many settings, further intensifying rising concerns about decisions made, actions taken, and their potential consequences. A robust conceptual framework to engage with AI ethics is thus more necessary than ever in order to make it more sustainable. To this purpose, this essay advances an approach to AI ethics ‘from within', defining it as the style of its algorithm(s) in practice. To demonstrate its practical value, I explore three points of entry: (1) value-laden patterns embedded in datasets used in machine learning, (2) the importance of value functions in the training and operating of AI, and (3) the possibility of adjusting some ‘ethics settings'. The example of algorithmic Human Resource Management (HRM) is examined to see how it can be brought closer to sustainable HRM. JEL Codes: O310
  • Varia

    • Navigating Disruptions with Bibliometrics: The New Space Case - Victor Dos Santos Paulino, Nonthapat Pulsiri, Christophe Bénaroya p. 137-160 accès libre avec résumé en anglais
      This paper extends disruptive innovation theory by employing bibliometric analysis to study the scope, magnitude, and interconnections of multilevel socio-technical disruptions termed “systemic disruption”. Focusing on the context of the space ecosystem from 2005 to 2021, characterized by many disruptions known as New Space, our analysis reveals six interconnected disruption clusters: new technology, new policy, new market, new entrant, new process, and new funding approach. The most influential disruptions are new technology, new policy, and new market. Notably, interconnections between new technology and new policy disruptions shape the scope and magnitude of systemic disruption through a co-evolution mechanism. This study advances disruptive innovation theory beyond technology disruptions and the level of individual organizations, expanding its applicability to systemic contexts. Furthermore, it provides guidance to researchers on applying bibliometric analysis in the field of innovation, while practitioners can leverage the research to plan innovation agendas considering the systemic nature of disruptions. JEL CODES: O33, L90, B0
    • Network Transformation during Technological Regime Change: The Case of the German Automotive Research Network - Patrick Wolf p. 161-190 accès libre avec résumé en anglais
      This study examines the structural changes in the German automotive research network to gain deeper insights into network transformation during regime change. Using a separable temporal exponential random graph model (STERGM), the author explores the influence of various factors on link formation and dissolution, including actor characteristics and general structural measures. Analyzing networking behavior over different time periods sheds light on the changing significance of these factors, particularly during the technological regime change in the German automotive sector. Findings reveal that link formation during regime change exhibits an increasing tendency toward cognitive and institutional distance between actors, with shorter durations of connections. Additionally, organizational size, urban location, and geographical proximity positively impact link formation. JEL CODES: O30, O33, L14
    • Overcoming Innovation Barriers along the Automotive Industry Value Chain – A Framed Experiment - Tobias Buchmann, Alexander Haering, Muhamed Kudic, Michael Rothgang p. 191-222 accès libre avec résumé en anglais
      The conditions under which R&D resources are allocated either to individual or collective R&D projects are largely unexplored. We contribute to closing this gap by asking under which conditions firms – each of which occupies a unique position along the automotive industry value chain – may overcome innovation barriers and spend scarce resources for collective R&D projects. We use a framed laboratory experiment to scrutinize the influence of different situations on the decision to spend the R&D budget for individual or collective R&D projects. The framing originates from a real-world case study of the massive metal forging industry. We identify constellations that support budget spending for collaborative purposes, e.g., sequential decision-making, which also increase the overall welfare, even in the case of unequally distributed R&D budgets.JEL Codes: O31, O32, C91.
  • Trends and Comments