Risk Handling and Vulnerability Assessment in IoT-Enabled Marketing Domain of Digital Business System

Liu, Y, Chandu, T and Joghee, S (2021) Risk Handling and Vulnerability Assessment in IoT-Enabled Marketing Domain of Digital Business System. Arabian Journal for Science and Engineering. ISSN 2191-4281

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Abstract

Rapid Internet development and technology contribute to the emergence of digital business models, product life, utilities, etc. Internet of Things (IoT) also handles e-business and functionality, or automated business structures. As additional computers and hardware are necessary for clustering, monitoring and maintenance are difficult. While the IoT e-business model improves overall business prospects, it poses many difficulties, including accurate business knowledge, risk, vulnerability evaluation and problem interpretation and handling of a large array of business data. Hence, in this study, IoT-enabled digital business system (IoTE-DBS) has been suggested for risk handling and vulnerability assessment of the reliable business model. The research examines the implications of digital business models, proposes a conceptual structure, and discusses how digital business models impact IoT-based businesses, business results and markets. The proposed model’s efficiency is assessed using end-user satisfaction, business process accuracy, the Pearson correlation coefficient, and the relative error.

Affiliation: Skyline University College
SUC Author(s): Joghee, S ORCID: https://orcid.org/0000-0002-4328-5902
All Author(s): Liu, Y, Chandu, T and Joghee, S
Item Type: Article
Uncontrolled Keywords: Risk handling, Vulnerability assessment, Internet of Things, Digital business system
Subjects: A Business and Management > AP Marketing
Divisions: Skyline University College > School of Business
Depositing User: Mr Veeramani Rasu
Date Deposited: 24 Mar 2022 08:16
Last Modified: 24 Mar 2022 08:16
URI: https://research.skylineuniversity.ac.ae/id/eprint/134
Publisher URL: https://doi.org/10.1007/s13369-021-06057-w
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/21688
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