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Cited by 76Sustainable Supply Chain ManagementEnvironmental Sustainability in BusinessSustainability and Innovation in Business

Sustainable business models and artificial intelligence: Opportunities and challenges

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Toniolo, Korinzia, Masiero, Eleonora, Massaro, Maurizio, Bagnoli, Carlo·2020·Contributions to Management Science
DOI 10.1007/978-3-030-40390-4_8
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Crossref · 10.1007/978-3-030-40390-4_8

Cites

61 of 61 references verified0 citation errors · 0 not checkable

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  • AI adoption in HRM leads to social performance by reducing human subjective bias in HR processes such as recruitment and employee appraisal, and improving employee experience and working conditions.

    “(6) social performance by reducing human subjective bias in HR processes such as recruitment and employee appraisal, and improving employee experience and working conditions by analysing enterprise social media anonymous data (Toniolo et al., 2020);”

    From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Toniolo et al., 2020

    The Social sustainability section says AI can reduce recruitment bias through standardized candidate assessment and that reduced workload can improve working conditions and employee well-being. It does not support the more specific claims about bias in employee appraisal or improving employee experience and working conditions by analysing anonymous enterprise social-media data. It describes these effects as possibilities, rather than establishing that AI adoption leads to them. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Considering the new set of skills and capabilities needed for managers, employees, and AI to collaborate, there will be a necessity to redesign jobs, create new ones, transform business model and strategies.

    “Considering the new set of skills and capabilities needed for managers, employees, and AI to collaborate, there will be a necessity to redesign jobs, create new ones, transform business model and strategies (Toniolo et al., 2020;WambaTaguimdje et al., 2020).”

    From Unlocking the value of artificial intelligence in human resource management through AI capability framework (2023) · cites this paper as Toniolo et al., 2020

    The Social sustainability section says AI requires greater skills for remaining tasks, can support human–machine collaboration, and is changing employees’ roles. The Introduction and §1.3 say AI affects business models and strategy. The copy does not state that AI will necessitate creating new jobs; it discusses replacing jobs and moving workers into different roles instead. Page numbers were not available in our copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Cites

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Research works printed but not linked: 5

  1. [12]12. Brynjolfsson, E., Mcafee, A. (2017). The Business of Artificial Intelligence: How AI Fits into Your Data Science Team. Harvard Business Review, No. July 2017, 1-20.
  2. [19]19. Davenport, T.H., Ronanki, R. (2018). Artificial Intelligence for the Real World: Don't start with moon shots. Harvard Business Review, 96(1), 108-116.
  3. [25]25. European Parliament and Council (2014). Directive 2014/95/EU of the European Parliament and of the Council of 22 october 2014 amending Directive 2013/34/EU as regards disclosure of non-financial and diversity information by certain large undertakings and groups. Official Journal of the European Union, 2014, No. September, 1-9.
  4. [48]48. Lüdeke-Freund, F. (2010). Towards a conceptual framework of business models for sustainability. Proceedings of the Knowledge Collaboration & Learning for Sustainable Innovation, Conference, Delft, 49(0), 1-28.
  5. [71]71. Shailer, G. (2004). An Introduction to Corporate Governance in Australia. Australia: Pearson Education.

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Authors
Toniolo, K., Masiero, E., Massaro, M., & Bagnoli, C.
Affiliations
Ca' Foscari University of Venice (IT)
Corresponding author
Toniolo, Korinzia
ORCID
Venue
Contributions to Management Science
Publisher
Springer International Publishing
Published
2020
Pages
103-117
ISSN
  • 1431-1941 (ISSN-L)
  • 2197-716X
DOI
10.1007/978-3-030-40390-4_8
OpenAlex
W3020297237
Cited by
76
References
61
Citations by year
2026: 19 · 2025: 15 · 2024: 17 · 2023: 14 · 2022: 4 · 2021: 6 · 2020: 1
FWCI
45.43
Type
book chapter
Language
en
Open access
Licence
Locations
  • Contributions to management science (publishedVersion)
  • ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion, other-oa)
  • ARCA (Università Ca' Foscari Venezia) (submittedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Sustainable Supply Chain Management
  • Social Sciences › Business, Management and Accounting › Marketing › Environmental Sustainability in Business
  • Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Sustainability and Innovation in Business
Keywords
sustainable business models, artificial intelligence, sustainability performance, multinational corporations, artificial intelligence adoption, environmental sustainability, social sustainability, economic sustainability, business model development

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