Understanding consumer motivation to share IoT products data

Almost every study undertaken by academicians or practitioners on the Internet of Things (IoT) has mainly highlighted the privacy concerns and information security issues with the IoT products. On the contrary, this paper aims to explore the motivators that could encourage customers of an IoT product to share their IoT product’s data with a third-party aggregator system to facilitate computer-generated product reviews which are defined as electronic Word of Thing (eWOT) in this paper.

An experiment was conducted with customized e-commerce prototypes of eWOT. Structural equation modeling analysis was conducted to test the measurement model by using confirmatory factor analysis and thereafter a structural model to test the relationships amongst the latent variables.

This paper found that five consumer motivators (personal innovativeness, enjoyment of helping, anticipated extrinsic rewards, moral obligations and venting negative feelings) contribute to eWOT intention.

This research advances the understanding of human interaction with computer-generated product reviews and opens up avenues for future studies in online consumer behavior in the IoT context.

This paper presents motivators for eWOT intention to share IoT product data. This is done through a novel concept of an experimental IoT-based prototype, namely, eWOT. These eWOT reviews can be generated from the IoT products data by applying analytics and using natural language generation. To the best of the authors’ knowledge, no other study has been conducted on this subject.