IDEAS home Printed from https://ideas.repec.org/a/spr/infsem/v22y2024i2d10.1007_s10257-024-00676-0.html
   My bibliography  Save this article

Leveraging the industrial internet of things for business process improvement: a metamodel and patterns

Author

Listed:
  • Christoph Stoiber

    (University of Regensburg)

  • Stefan Schönig

    (University of Regensburg)

Abstract

Industrial organizations of all kinds increasingly recognize the industrial internet of thing’s (IIoT) capabilities to enable valuable business process improvement (BPI). However, both theoretically and practically, there is a lack of clarity regarding the systematic and successful identification, specification, and implementation of corresponding applications. This article aims to bridge this research gap by presenting a comprehensive metamodel encompassing all relevant aspects and elements of IIoT applications with BPI propositions. The metamodel is the foundation for deriving generic yet practical patterns that can assist organizations in effectively executing IIoT projects. To evaluate the usefulness of the approach, five initial patterns were designed and applied by a market-leading organization. The metamodel and patterns contribute to the descriptive knowledge of the IIoT and facilitate sense-making, theory-led design, and practical project execution. To ensure rigor, the research endeavor followed fundamental principles of the design science research (DSR) methodology.

Suggested Citation

  • Christoph Stoiber & Stefan Schönig, 2024. "Leveraging the industrial internet of things for business process improvement: a metamodel and patterns," Information Systems and e-Business Management, Springer, vol. 22(2), pages 285-313, June.
  • Handle: RePEc:spr:infsem:v:22:y:2024:i:2:d:10.1007_s10257-024-00676-0
    DOI: 10.1007/s10257-024-00676-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10257-024-00676-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10257-024-00676-0?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Zhibo Pang & Qiang Chen & Weili Han & Lirong Zheng, 2015. "Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion," Information Systems Frontiers, Springer, vol. 17(2), pages 289-319, April.
    2. Aelita Skaržauskienė & Marius Kalinauskas, 2015. "The internet of things: when reality meets expectations," International Journal of Innovation and Learning, Inderscience Enterprises Ltd, vol. 17(2), pages 262-274.
    3. Christian Arnold & Daniel Kiel & Kai-Ingo Voigt, 2016. "How The Industrial Internet Of Things Changes Business Models In Different Manufacturing Industries," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-25, December.
    4. Nilgun Fescioglu-Unver & Sung Hee Choi & Dongmok Sheen & Soundar Kumara, 2015. "RFID in production and service systems: Technology, applications and issues," Information Systems Frontiers, Springer, vol. 17(6), pages 1369-1380, December.
    5. Sestino, Andrea & Prete, Maria Irene & Piper, Luigi & Guido, Gianluigi, 2020. "Internet of Things and Big Data as enablers for business digitalization strategies," Technovation, Elsevier, vol. 98(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. Jovanovic, Marin & Sjödin, David & Parida, Vinit, 2022. "Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms," Technovation, Elsevier, vol. 118(C).
    2. Christian Arnold & Kai-Ingo Voigt, 2019. "Determinants of Industrial Internet of Things Adoption in German Manufacturing Companies," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1-21, October.
    3. Leonid Mylnikov & Martin Kuetz, 2017. "Electric Power Supply Subsystem and its Role in Solving Production System Management and Planning Issues," International Journal of Energy Economics and Policy, Econjournals, vol. 7(5), pages 191-200.
    4. Mona Haji & Laoucine Kerbache & Mahaboob Muhammad & Tareq Al-Ansari, 2020. "Roles of Technology in Improving Perishable Food Supply Chains," Logistics, MDPI, vol. 4(4), pages 1-24, December.
    5. Reyes, Pedro M. & Li, Suhong & Visich, John K., 2016. "Determinants of RFID adoption stage and perceived benefits," European Journal of Operational Research, Elsevier, vol. 254(3), pages 801-812.
    6. Videsh Desingh & Baskaran R, 2022. "Internet of Things adoption barriers in the Indian healthcare supply chain: An ISM‐fuzzy MICMAC approach," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 318-351, January.
    7. Anthea van der Hoogen & Ifeoluwapo Fashoro & Andre P. Calitz & Lamla Luke, 2024. "A Digital Transformation Framework for Smart Municipalities," Sustainability, MDPI, vol. 16(3), pages 1-28, February.
    8. Ancillai, Chiara & Sabatini, Andrea & Gatti, Marco & Perna, Andrea, 2023. "Digital technology and business model innovation: A systematic literature review and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    9. Marco Cioppi & Ilaria Curina & Barbara Francioni & Elisabetta Savelli, 2023. "Digital transformation and marketing: a systematic and thematic literature review," Italian Journal of Marketing, Springer, vol. 2023(2), pages 207-288, June.
    10. Li Da Xu, 2020. "The contribution of systems science to Industry 4.0," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 618-631, July.
    11. Sebastian Saniuk & Sandra Grabowska & Bożena Gajdzik, 2020. "Social Expectations and Market Changes in the Context of Developing the Industry 4.0 Concept," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    12. Sarbu, Miruna, 2022. "The impact of industry 4.0 on innovation performance: Insights from German manufacturing and service firms," Technovation, Elsevier, vol. 113(C).
    13. 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).
    14. Zhengxin Wang & Minghuan Shou & Shuai Wang & Ruinan Dai & Keqian Wang, 2019. "An Empirical Study on the Key Factors of Intelligent Upgrade of Small and Medium-sized Enterprises in China," Sustainability, MDPI, vol. 11(3), pages 1-16, January.
    15. Atik Kulakli & Cenk Lacin Arikan, 2023. "Research Trends of the Internet of Things in Relation to Business Model Innovation: Results from Co-Word and Content Analyses," Future Internet, MDPI, vol. 15(2), pages 1-17, February.
    16. Bürger, Katrin & Roloff, Malte & Lundborg, Martin & Happ, Marina & Tenbrock, Sebastian & Papen, Marie-Christin, 2024. "Vernetzte Produktion: 360 Grad Überblick über die Perspektiven in KMU," WIK Discussion Papers 521, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH.
    17. Xiongnan Jin & Sejin Chun & Jooik Jung & Kyong-Ho Lee, 2017. "A fast and scalable approach for IoT service selection based on a physical service model," Information Systems Frontiers, Springer, vol. 19(6), pages 1357-1372, December.
    18. Leite, Higor & Hodgkinson, Ian R. & Lachowski Volochtchuk, Ana Vitória & Cavalcante Nascimento, Thiago, 2024. "‘It's not the boogeyman’: How voice assistant technology is bridging the digital divide for older people," Technovation, Elsevier, vol. 136(C).
    19. Payam Hanafizadeh & Ferdos Hatami Lankarani & Shahrokh Nikou, 2022. "Perspectives on management theory’s application in the internet of things research," Information Systems and e-Business Management, Springer, vol. 20(4), pages 749-787, December.
    20. Maha Shehadeh & Ahmad Almohtaseb & Jehad Aldehayyat & Ibrahim A. Abu-AlSondos, 2023. "Digital Transformation and Competitive Advantage in the Service Sector: A Moderated-Mediation Model," Sustainability, MDPI, vol. 15(3), pages 1-21, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:infsem:v:22:y:2024:i:2:d:10.1007_s10257-024-00676-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.