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

Abstract

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.