IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p11113-d1195652.html
   My bibliography  Save this article

Artificial Intelligence for the Management of Servitization 5.0

Author

Listed:
  • Bernardo Nicoletti

    (Temple University, I-00196 Rome, Italy)

  • Andrea Appolloni

    (Università di Rome Tor Vergata, I-00133 Rome, Italy)

Abstract

Purpose—The sale of physical products has been manufacturing companies’ main revenue source. A trend is known as servitization for earning revenue comes from services. With the convergence of servitization and digitization, many manufacturing organizations are undergoing digital servitization. In parallel, the digitization of industry is pushing new technological solutions to the top of the business agenda. Artificial intelligence can play a substantial role in this digital business transformation. This evolution is referred to in this paper as Servitization 5.0 and requires substantial changes. Aim—This paper explores the applications of artificial intelligence to Servitization 5.0 strategies and its role, particularly in changing organizations to EverythiA.I.ng as a Service. The paper underlines the contribution that A.I. can provide in moving to a human-centric, sustainable, and resilient servitization. Method used—The basis of the work is a literature review supported by information collected from business case studies by the authors. A follow-up study defined the models. The validity of the model was tested by collecting ten experts’ opinions who currently work within servitization contracts sessions. Findings—For manufacturing companies, selling services requires completely different business models. In this situation, it is essential to consider advanced solutions to support these new business models. Artificial Intelligence can make it possible. On the inter-organizational side, empirical evidence also points to the support of A.I. in collaborating with ecosystems to support sustainability and resilience, as requested by Industry 5.0. Original value—Regarding theoretical implications, this paper contributes to interdisciplinary research in corporate marketing and operational servitization. It is part of the growing literature that deals with the applications of artificial intelligence-based solutions in different areas of organizational management. The approach is interesting because it highlights that digital solutions require an integrated business model approach. It is necessary to implement the technological platform with appropriate processes, people, and partners (the four Ps). The outcome of this study can be generalized for industries in high-value manufacturing. Implications—As implications for management, this paper defines how to organize the structure and support for Servitization 5.0 and how to work with the external business environment to support sustainability.

Suggested Citation

  • Bernardo Nicoletti & Andrea Appolloni, 2023. "Artificial Intelligence for the Management of Servitization 5.0," Sustainability, MDPI, vol. 15(14), pages 1-13, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11113-:d:1195652
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/11113/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/14/11113/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020. "Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review," Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
    2. Palo, Teea & Åkesson, Maria & Löfberg, Nina, 2019. "Servitization as business model contestation: A practice approach," Journal of Business Research, Elsevier, vol. 104(C), pages 486-496.
    3. Wolfgang Ulaga & Werner Reinartz, 2011. "Hybrid Offerings: How Manufacturing Firms Combine Goods and Services Successfully," Post-Print hal-00642039, HAL.
    4. Yan Chen & Zijin Wang & Jaime Ortiz, 2023. "A Sustainable Digital Ecosystem: Digital Servitization Transformation and Digital Infrastructure Support," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    5. Li, Huashan & Pournader, Mehrdokht & Fahimnia, Behnam, 2022. "Servitization and organizational resilience of manufacturing firms: Evidence from the COVID-19 outbreak," International Journal of Production Economics, Elsevier, vol. 250(C).
    6. Opresnik, David & Taisch, Marco, 2015. "The value of Big Data in servitization," International Journal of Production Economics, Elsevier, vol. 165(C), pages 174-184.
    7. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    8. Hong Joo Lee & Hoyeon Oh, 2020. "A Study on the Deduction and Diffusion of Promising Artificial Intelligence Technology for Sustainable Industrial Development," Sustainability, MDPI, vol. 12(14), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lyudmila Davidenko & Nurzhanat Sherimova & Saule Kunyazova & Maral Amirova & Ansagan Beisembina, 2024. "Sustainable Economy: The Eco-Branding of an Industrial Region in Kazakhstan," Sustainability, MDPI, vol. 16(1), pages 1-16, January.
    2. Daxing Chen & Helian Xu & Guangya Zhou, 2024. "Has Artificial Intelligence Promoted Manufacturing Servitization: Evidence from Chinese Enterprises," Sustainability, MDPI, vol. 16(6), pages 1-19, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    2. Rabetino, Rodrigo & Kohtamäki, Marko & Gebauer, Heiko, 2017. "Strategy map of servitization," International Journal of Production Economics, Elsevier, vol. 192(C), pages 144-156.
    3. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    4. Stefano Bianchini & Giacomo Damioli & Claudia Ghisetti, 2023. "The environmental effects of the “twin” green and digital transition in European regions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 877-918, April.
    5. Bustinza, Oscar F. & Opazo-Basaez, Marco & Tarba, Shlomo, 2022. "Exploring the interplay between Smart Manufacturing and KIBS firms in configuring product-service innovation performance," Technovation, Elsevier, vol. 118(C).
    6. Basma Hamrouni & Abdelhabib Bourouis & Ahmed Korichi & Mohsen Brahmi, 2021. "Explainable Ontology-Based Intelligent Decision Support System for Business Model Design and Sustainability," Sustainability, MDPI, vol. 13(17), pages 1-28, September.
    7. Mosch, Philipp & Schweikl, Stefan & Obermaier, Robert, 2021. "Trapped in the supply chain? Digital servitization strategies and power relations in the case of an industrial technology supplier," International Journal of Production Economics, Elsevier, vol. 236(C).
    8. David Mhlanga, 2022. "Human-Centered Artificial Intelligence: The Superlative Approach to Achieve Sustainable Development Goals in the Fourth Industrial Revolution," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    9. Kohtamäki, Marko & Parida, Vinit & Oghazi, Pejvak & Gebauer, Heiko & Baines, Tim, 2019. "Digital servitization business models in ecosystems: A theory of the firm," Journal of Business Research, Elsevier, vol. 104(C), pages 380-392.
    10. Denicolai, Stefano & Zucchella, Antonella & Magnani, Giovanna, 2021. "Internationalization, digitalization, and sustainability: Are SMEs ready? A survey on synergies and substituting effects among growth paths," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    11. Chankook Park, 2022. "Expansion of servitization in the energy sector and its implications," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(4), July.
    12. Johansson, A. Elisabeth & Raddats, Chris & Witell, Lars, 2019. "The role of customer knowledge development for incremental and radical service innovation in servitized manufacturers," Journal of Business Research, Elsevier, vol. 98(C), pages 328-338.
    13. Carmen Isensee & Kai-Michael Griese & Frank Teuteberg, 2021. "Sustainable artificial intelligence: A corporate culture perspective [Sustainable artificial intelligence: Eine unternehmenskulturelle Perspektive]," Sustainability Nexus Forum, Springer, vol. 29(3), pages 217-230, December.
    14. Wei, Zelong & Huang, Wengao & Wang, Yanping & Sun, Lulu, 2022. "When does servitization promote product innovation? The moderating roles of product modularization and organization formalization," Technovation, Elsevier, vol. 117(C).
    15. Chen, Liping & Dai, Yishu & Ren, Fei & Dong, Xiaoying, 2023. "Data-driven digital capabilities enable servitization strategy——From service supporting the product to service supporting the client," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    16. Khanra, Sayantan & Dhir, Amandeep & Parida, Vinit & Kohtamäki, Marko, 2021. "Servitization research: A review and bibliometric analysis of past achievements and future promises," Journal of Business Research, Elsevier, vol. 131(C), pages 151-166.
    17. Frank, Alejandro G. & Mendes, Glauco H.S. & Ayala, Néstor F. & Ghezzi, Antonio, 2019. "Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 341-351.
    18. Gebauer, Heiko & Fleisch, Elgar & Lamprecht, Claudio & Wortmann, Felix, 2020. "Growth paths for overcoming the digitalization paradox," Business Horizons, Elsevier, vol. 63(3), pages 313-323.
    19. Steve J. Bickley & Benno Torgler, 2021. "Behavioural Economics, What Have we Missed? Exploring “Classical” Behavioural Economics Roots in AI, Cognitive Psychology, and Complexity Theory," CREMA Working Paper Series 2021-21, Center for Research in Economics, Management and the Arts (CREMA).
    20. Juan Jung & Gonzalo Gómez-Bengoechea, 2022. "A literature review on firm digitalization: drivers and impacts," Studies on the Spanish Economy eee2022-20, FEDEA.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11113-:d:1195652. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.