Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility, low-rank heterogeneity, and flexible...

Massive Open Online Courses (MOOCs) and the broad adoption of distance learning over the past few years have caused a remarkable shift in the educational landscape. However, the vast majority of available MOOCs often challenge learners in selecting courses that align with their academic goals,...

Operational alignment, defined as the alignment between business processes (BPs) and information systems (ISs), is essential for ensuring that IS capabilities effectively support organizational operations. Despite extensive efforts, existing approaches to operational alignment remain constrained...

Advances in data collection enable firms to use consumer information for personalized pricing. In Clavor'a Braulin's (2023) symmetric two-dimensional model, this reduces prices and profits, while partial privacy yields the highest profits. Extending the model to asymmetric firms and vertically...

Artificial intelligence (AI) is increasingly used in marketing to deliver personalized messages and services. Although such tools create new opportunities, their acceptance by consumers depends on several factors that go beyond technology itself. This study examines how trust and ethical...

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...

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...

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...

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...

Background: The study aims to examine the role of artificial intelligence-oriented personalisation in customer interaction of social commerce platforms in the developing market, such as Kosovo. Objectives: A quantitative design was used, and 312 active users were sampled, with surveys offered to...

Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility, low-rank heterogeneity, and flexible...

Algorithm- and data-based recommendation systems (DARS) have become a central component of the digital economy, shaping how users access, evaluate, and consume information and goods. These systems encompass both search rankings tailored to estimated user preferences and direct recommendations...

The integration of large language models (LLMs) into recommender systems (RS) has given rise to a new generation of Conversational RS (CRS). This study asks how CRS systems shape consumer behavior, and, in particular, their spending. Despite the rapid proliferation of such systems, including...

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...

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...

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,...