Increasing trust and value of mobile advertising in retailing: A survey design, machine learning approach, and blockchain in the trust path

Abstract

The U.S. mobile advertising market generated $175 billion in 2023, emphasizing its significant role in the marketing industry. This paper presents two studies that contribute to the trust path of mobile advertising, which can ultimately increase customers’ purchase intention. The survey study proposes a new moderator, mobile learning by ads, which can aid in developing the trust path theory in mobile advertising. We tested a research model that includes a moderated mediation relationship using a sample of 200 respondents. Survey results reveal that mobile learning strengthens the link between trust, value, and purchasing behavior. This finding highlights the importance of incorporating mobile learning strategies to enhance customer trust and ultimately increase purchase intention in mobile advertising. In the post hoc study, this paper introduces the text analysis to explore a large dataset containing 3499 tweets contributing to mobile advertising. Text analytics results indicate that blockchain and cybersecurity are the primary topics among users who focus on the trust path in mobile advertising. Blockchain and cybersecurity are the most identified topics because cyber-attacks and privacy concerns are growing in mobile advertising systems. Moreover, the fact that users remain optimistic about the trust path is significant for its theory development.