IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v256y2023ics0925527322003280.html
   My bibliography  Save this article

Adoption patterns and performance implications of Smart Maintenance

Author

Listed:
  • Bokrantz, Jon
  • Skoogh, Anders

Abstract

To substantiate and extend emergent research on maintenance in digitalized manufacturing, we examine adoption patterns and performance implications of the four dimensions of Smart Maintenance: data-driven decision-making, human capital resource, internal integration, and external integration. Using data collected from 145 Swedish manufacturing plants, we apply a configurational approach to study how emergent patterns of Smart Maintenance are shaped and formed, as well as how the patterns are related to the operating environment and the performance of the manufacturing plant. Cluster analysis was used to develop an empirical taxonomy of Smart Maintenance, revealing four emergent patterns that reflect the strength and balance of the underlying dimensions. Canonical discriminant analysis indicated that the Smart Maintenance patterns are related to operating environments with a higher level of digitalization. The results from ANOVA and NCA showed the importance of a coordinated and joint Smart Maintenance implementation to the maintenance performance and productivity of the manufacturing plant. This study contributes to the literature on industrial maintenance by expanding and strengthening the theoretical and empirical foundation of Smart Maintenance, and it provides managerial advice for making strategic decisions about Smart Maintenance implementation.

Suggested Citation

  • Bokrantz, Jon & Skoogh, Anders, 2023. "Adoption patterns and performance implications of Smart Maintenance," International Journal of Production Economics, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:proeco:v:256:y:2023:i:c:s0925527322003280
    DOI: 10.1016/j.ijpe.2022.108746
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527322003280
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2022.108746?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Swanson, Laura, 2003. "An information-processing model of maintenance management," International Journal of Production Economics, Elsevier, vol. 83(1), pages 45-64, January.
    2. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Wuest, Thorsten & Stahre, Johan, 2020. "Smart Maintenance: a research agenda for industrial maintenance management," International Journal of Production Economics, Elsevier, vol. 224(C).
    3. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Stahre, Johan, 2017. "Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030," International Journal of Production Economics, Elsevier, vol. 191(C), pages 154-169.
    4. Erik Brynjolfsson & Wang Jin & Kristina McElheran, 2021. "The power of prediction: predictive analytics, workplace complements, and business performance," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 217-239, October.
    5. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    6. MacKenzie, Scott B. & Podsakoff, Philip M., 2012. "Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies," Journal of Retailing, Elsevier, vol. 88(4), pages 542-555.
    7. Aboelmaged, Mohamed Gamal, 2014. "Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms," International Journal of Information Management, Elsevier, vol. 34(5), pages 639-651.
    8. Baofeng Huo & Barbara B. Flynn & Xiande Zhao, 2017. "Supply Chain Power Configurations and Their Relationship with Performance," Journal of Supply Chain Management, Institute for Supply Management, vol. 53(2), pages 88-111, April.
    9. Liang, Zhenglin & Liu, Bin & Xie, Min & Parlikad, Ajith Kumar, 2020. "Condition-based maintenance for long-life assets with exposure to operational and environmental risks," International Journal of Production Economics, Elsevier, vol. 221(C).
    10. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Wuest, Thorsten & Stahre, Johan, 2020. "Smart Maintenance: an empirically grounded conceptualization," International Journal of Production Economics, Elsevier, vol. 223(C).
    11. Tortorella, Guilherme Luz & Fogliatto, Flavio S. & Cauchick-Miguel, Paulo A. & Kurnia, Sherah & Jurburg, Daniel, 2021. "Integration of Industry 4.0 technologies into Total Productive Maintenance practices," International Journal of Production Economics, Elsevier, vol. 240(C).
    12. Huo, Baofeng & Ye, Yuxiao & Zhao, Xiande & Zhu, Kaihang, 2019. "Supply chain quality integration: A taxonomy perspective," International Journal of Production Economics, Elsevier, vol. 207(C), pages 236-246.
    13. Barbara Flynn & Mark Pagell & Brian Fugate, 2018. "Editorial: Survey Research Design in Supply Chain Management: The Need for Evolution in Our Expectations," Journal of Supply Chain Management, Institute for Supply Management, vol. 54(1), pages 1-15, January.
    14. Bokhorst, Jos A.C. & Knol, Wilfred & Slomp, Jannes & Bortolotti, Thomas, 2022. "Assessing to what extent smart manufacturing builds on lean principles," International Journal of Production Economics, Elsevier, vol. 253(C).
    15. Thomas J. Kull & Josip Kotlar & Martin Spring, 2018. "Small and Medium Enterprise Research in Supply Chain Management: The Case for Single†Respondent Research Designs," Journal of Supply Chain Management, Institute for Supply Management, vol. 54(1), pages 23-34, January.
    16. Florian, Eleonora & Sgarbossa, Fabio & Zennaro, Ilenia, 2021. "Machine learning-based predictive maintenance: A cost-oriented model for implementation," International Journal of Production Economics, Elsevier, vol. 236(C).
    Full references (including those not matched with items on IDEAS)

    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. Li, Siyu & Huo, Baofeng & Wang, Qiang, 2023. "The impact of buyer-supplier communication on performance: A contingency and configuration approach," International Journal of Production Economics, Elsevier, vol. 257(C).
    2. Crespo, Nuno Fernandes & Crespo, Cátia Fernandes & Silva, Graça Miranda, 2024. "Every cloud has a silver lining: The role of business digitalization and early internationalization strategies to overcome cloudy times," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Saihi, Afef & Ben-Daya, Mohamed & As'ad, Rami, 2023. "Underpinning success factors of maintenance digital transformation: A hybrid reactive Delphi approach," International Journal of Production Economics, Elsevier, vol. 255(C).
    4. Tortorella, Guilherme Luz & Fogliatto, Flavio S. & Cauchick-Miguel, Paulo A. & Kurnia, Sherah & Jurburg, Daniel, 2021. "Integration of Industry 4.0 technologies into Total Productive Maintenance practices," International Journal of Production Economics, Elsevier, vol. 240(C).
    5. Crespo, Cátia Fernandes & Crespo, Nuno Fernandes & Curado, Carla, 2022. "The effects of subsidiary’s leadership and entrepreneurship on international marketing knowledge transfer and new product development," International Business Review, Elsevier, vol. 31(2).
    6. Colombari, Ruggero & Geuna, Aldo & Helper, Susan & Martins, Raphael & Paolucci, Emilio & Ricci, Riccardo & Seamans, Robert, 2023. "The interplay between data-driven decision-making and digitalization: A firm-level survey of the Italian and U.S. automotive industries," International Journal of Production Economics, Elsevier, vol. 255(C).
    7. Vendrell-Herrero, Ferran & Bustinza, Oscar F. & Opazo-Basaez, Marco, 2021. "Information technologies and product-service innovation: The moderating role of service R&D team structure," Journal of Business Research, Elsevier, vol. 128(C), pages 673-687.
    8. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    9. Surajit Bag & Muhammad Sabbir Rahman & Gautam Srivastava & Peter Kilbourn & Nishikant Mishra, 2024. "Buyer–supplier partnerships and circular economy performance in food supply chains: Serial mediation by commitment contract and innovation performance," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 1247-1264, February.
    10. Eduardo Terán-Yépez & David Jiménez-Castillo & Manuel Sánchez-Pérez, 2023. "The role of affect in international opportunity recognition and the formation of international opportunity beliefs," Review of Managerial Science, Springer, vol. 17(3), pages 941-983, April.
    11. Hong, Paul & Jagani, Sandeep & Kim, Jinhwan & Youn, Sun Hee, 2019. "Managing sustainability orientation: An empirical investigation of manufacturing firms," International Journal of Production Economics, Elsevier, vol. 211(C), pages 71-81.
    12. Khaksar, Seyed Mohammad Sadegh & Shahmehr, Fatemeh S. & Miah, Shah & Daim, Tugrul & Ozdemir, Dilek, 2024. "Privacy concerns versus personalisation benefits in social robot acceptance by employees: A paradox theory — Contingency perspective," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    13. Surajit Bag & Muhammad Sabbir Rahman & Susmi Routray & Santosh Kumar Shrivastav & Soni Agrawal, 2024. "Exploring the potential of blockchain‐enabled smart contracts for achieving net‐zero emissions: An empirical study," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 3965-3985, July.
    14. Jung-Chieh Lee & Yuyin Tang & SiQi Jiang, 2023. "Understanding continuance intention of artificial intelligence (AI)-enabled mobile banking applications: an extension of AI characteristics to an expectation confirmation model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    15. Maestrini, Vieri & Luzzini, Davide & Caniato, Federico & Ronchi, Stefano, 2018. "Effects of monitoring and incentives on supplier performance: An agency theory perspective," International Journal of Production Economics, Elsevier, vol. 203(C), pages 322-332.
    16. Schniederjans, Dara G., 2017. "Adoption of 3D-printing technologies in manufacturing: A survey analysis," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 287-298.
    17. Nathaniel Boso & Paige S Carter & Jonathan Annan, 2016. "When is brand orientation a useful strategic posture?," Journal of Brand Management, Palgrave Macmillan, vol. 23(4), pages 363-382, July.
    18. Jason Miller & Beth Davis‐Sramek & Brian S. Fugate & Mark Pagell & Barbara B. Flynn, 2021. "Editorial Commentary: Addressing Confusion in the Diffusion of Archival Data Research," Journal of Supply Chain Management, Institute for Supply Management, vol. 57(3), pages 130-146, July.
    19. Shivam Gupta & Sachin Modgil & Piera Centobelli & Roberto Cerchione & Serena Strazzullo, 2022. "Additive Manufacturing and Green Information Systems as Technological Capabilities for Firm Performance," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(4), pages 515-534, December.
    20. Jajja, Muhammad Shakeel Sadiq & Asif, Muhammad & Montabon, Frank & Chatha, Kamran Ali, 2020. "The indirect effect of social responsibility standards on organizational performance in apparel supply chains: A developing country perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 139(C).

    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:eee:proeco:v:256:y:2023:i:c:s0925527322003280. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.