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Data Analysis Services Related to the IoT and Big Data: Strategic Implications and Business Opportunities for Third Parties

Author

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  • Izabella V. Lokshina

    (State University of New York at Oneonta, Management Information Systems, NY, USA)

  • Barbara J. Durkin

    (State University of New York at Oneonta, Management, NY, USA)

  • Cees J.M. Lanting

    (DATSA Belgium Consulting, Kessel-Lo, Belgium)

Abstract

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.

Suggested Citation

  • Izabella V. Lokshina & Barbara J. Durkin & Cees J.M. Lanting, 2017. "Data Analysis Services Related to the IoT and Big Data: Strategic Implications and Business Opportunities for Third Parties," International Journal of Interdisciplinary Telecommunications and Networking (IJITN), IGI Global, vol. 9(2), pages 37-56, April.
    • Handle: RePEc:igg:jitn00:v:9:y:2017:i:2:p:37-56
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    Cited by:

    1. Gupta, Himanshu & Yadav, Avinash Kumar & Kusi-Sarpong, Simonov & Khan, Sharfuddin Ahmed & Sharma, Shashi Chandra, 2022. "Strategies to overcome barriers to innovative digitalisation technologies for supply chain logistics resilience during pandemic," Technology in Society, Elsevier, vol. 69(C).

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