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Eyo, Bassey Itam.pdf (6.97 MB)

A business model framework for the Internet of Things

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thesis
posted on 2023-06-09, 19:46 authored by Bassey Itam Eyo
The Internet of Things (IoT) is an emerging technology with research interests transcending disciplines of computer sciences and computer engineering to agriculture, business management, civil engineering, architecture, medical sciences, social science etc. This is because of the potential expanding range of its application areas of wind mill operation and irrigation control, supply chain and logistics, manufacturing, home and office environment, healthcare, social care, etc. As it is usually the case with emerging technologies, IoT is faced with the challenge of bridging the gap between the technology development and corresponding business model design. Without a workable business model, the IoT paradigm may end up in research labs and subsequently fade away. A business model should show how lucrative it is to be in the IoT business by adding value to the customer and generating revenue for the business firm. This research is a contribution towards the goal of developing a business model for IoT, with customer/user value potential as the focal point. The comprehensive literature review carried out during this research (i) outlines the concept of business models; (ii) investigates through desk research, existing digital technology business models with focus on two (2) established digital technology firms and identified five generic components of their business models including but not limited to subscription, training, price, satisfaction, and trust, which were used for the primary investigation; (iii) investigates the IoT state-of-the-arts by elaborating on the IoT space and precursor technologies that are part of its ecosystem with the aim of describing, illustrating and developing application prototypes for three IoT scenarios of health monitoring, the use of the library and borrowing of books (a novel idea), and home environment; (iv) evaluates business model framework representation maps in current use, and specifically modified the general structure, content, and performance framework map to design an adoption framework map called a customer-focused business model framework map for IoT (CBMF4IoT). The unique approach to business model research involved conducting a user-led experiment to investigate the likelihood of IoT adoption of existing digital technology business models, as the customer value potential aspect of a business model design was the focal point of this research. Specifically, the experiment was aimed at determining if there was any significant differences in user inclinations towards the five generic components of existing digital technology business models based on smartphone context and IoT products context in a within-subjects design, with sample population drawn from University of Sussex community. The experimental design relied on participants' past experiences with smartphone for them to indicate their pre-purchase inclinations towards the five generics components. For the IoT products context, descriptions and diagrammatic illustration of the three IoT scenarios with their corresponding Just-in-Mind clickable prototypes served as educational tools to enable participants to be acquainted with IoT in order for them to indicate their potential pre-purchase inclinations towards the five generic components. A unique procedure for business model adoption likelihood was designed using the Sign test for high, low, and medium likelihood of adoption. The results of this test indicate medium likelihood of adoption for three of the generic components and low likelihood of adoption for two of the generic components. The results of this test was then fed to the CBMF4IoT. This thesis demonstrates that reusability of successful digital technology business models could potentially result in market success for an emerging digital technology in a B2C context, as users opinion formed the bases for the conclusions, instead of the conventional opinion gathering from only experts, business owners, and practitioners for a BM research.

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File Version

  • Published version

Pages

258.0

Department affiliated with

  • Informatics Theses

Qualification level

  • doctoral

Qualification name

  • phd

Language

  • eng

Institution

University of Sussex

Full text available

  • Yes

Legacy Posted Date

2019-11-26

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