Purpose This research aims to explore the intricate dynamics influencing the adoption of AI-driven smart tourism technologies within the specific context of the United Arab Emirates. It seeks to address the following key questions: How do ethical AI practices and personalization impact tourist...

We examine the strategic considerations and effects of product placement services in digital content aggregators, focusing in particular on Spotify’s “Discovery Mode”. Discovery Mode introduces bias in users’ consumption bundle that content providers pay through discounted royalties, and...

This paper investigates the impact of social media algorithms on mental health outcomes. I exploit a quasi-experimental setting combining data from the Dutch Longitudinal Internet Studies for the Social Sciences (LISS) coupled with the introduction of the algorithmic feed on Instagram in 2016. I...

Recommender systems are indispensable in e-business due to the extensive product range and the large number of niche articles. Collaborative filtering (CF) algorithms play a central role in generating personalised recommendations. There are numerous CF approaches in the literature that have...

With the growing number of mobile device users and the rise of engaging social media platforms, the mobile advertising industry is evolving rapidly, presenting marketers with new challenges in reaching customers while maintaining positive attitudes toward advertising. In this paper, we...

With the growing number of mobile device users and the rise of engaging social media platforms, the mobile advertising industry is evolving rapidly, presenting marketers with new challenges in reaching customers while maintaining positive attitudes toward advertising. In this paper, we...

Recommender systems -RS- have experienced exponential growth in various fields, especially in the tourism sector, improving tourism activities' accuracy, personalization, and experience, thus strengthening indicators such as promotion. However, some challenges and opportunities exist to...

Due to rapid technological and Internet advancements, online shopping has become more popular, widespread, convenient, and easier for consumers. Common advantages of online shopping include convenience, product and service variety, price comparison, ability to view online customer reviews,...

The increase in online information and the expanding diversity of user preferences require developing improved recommender systems. Cross-domain recommender systems (CDRS) have emerged as a favorable solution to solve issues related to cold start, data sparsity, and diversity by leveraging...

Recently, e-commerce platforms have gained significant attention in the media. As the number of customers using these platforms continues to grow, they face challenges such as limited support, making it increasingly difficult for customers to find answers to their inquiries, leading to a high...

Recommendation agents (RAs) have proven to be effective decision-making tools for customers, as they can boost trust and loyalty when customers shop online. They can analyse large amounts of data using machine learning algorithms and predictive analytics capabilities to provide highly relevant...

In the fiercely competitive landscape of the peer-to-peer accommodation platform Airbnb, understanding customers' online recommendation behavior is essential for optimizing competitiveness and harnessing the potential of electronic word-of-mouth. This study aims to provide comprehensive insights...

We audit the job recommender algorithms used by four Chinese job boards by creating fictitious applicant profiles that differ only in their gender. Jobs recommended uniquely to the male and female profiles in a pair differ modestly in their observed characteristics, with female jobs advertising...

This paper investigates the value of recommendations for disseminating economic information, with a focus on frictions resulting from preference heterogeneity. We consider Bayesian expected-payoff maximizers who receive non-strategic recommendations by other consumers. The paper provides...

This paper investigates the value of recommendations for disseminating economic information, with a focus on frictions resulting from preference heterogeneity. We consider Bayesian expected-payoff maximizers who receive non-strategic recommendations by other consumers. The paper provides...

Using a modified version of TAM, this study investigates the factors that impact ChatGPT usage intentions among college students, with personalization acting as a moderator. A structured questionnaire was designed for data collection as part of the quantitative procedure. Smart PLS 4 was...