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Predicting the Consequences of Perceived Data Privacy Risks on Consumer Behaviour: An Entropy-TOPSIS Approach Cover

Predicting the Consequences of Perceived Data Privacy Risks on Consumer Behaviour: An Entropy-TOPSIS Approach

Open Access
|Jul 2022

Abstract

Advancement in internet of things (IoT) and proliferation in the use of smart devices have raised concerns about the data privacy of online users. This study predicts the consequences of perceived data privacy risks on consumer behaviours in Lagos State, Nigeria using the integrated Entropy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We employed Entropy to assign weights to each criterion. Subsequently, responses were systematically ranked to arrive at an inference using TOPSIS. 84.8% agree that any perceived cyber security threat or a breach in their data privacy would stop them from proceeding with the transaction or activity online, or the use of a digital product. Similarly, (86.7%), agree it is critical that online businesses only ask for customer information that is relevant to the use of the product or service. Thus, the findings indicate that the privacy paradox of enlightened online consumers tends to diminish when they are faced with perceived data privacy and cybersecurity risks.

Language: English
Page range: 25 - 48
Published on: Jul 9, 2022
Published by: University of Information Technology and Management in Rzeszow
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 Sulaimon Olanrewaju Adebiyi, Gloria Amaka Olayemi, published by University of Information Technology and Management in Rzeszow
This work is licensed under the Creative Commons Attribution 4.0 License.