Platforms that provide product recommendations to consumers, such as marketplaces like Amazon or online travel agencies like Expedia, govern a substantial part of transactions in many markets. In addition to selling via platforms, most firms, however, also operate a direct channel. This paper...

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...

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...

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...

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...

Purpose: This article aims to reveal how online reviews in virtual communities affect the reputation of platform sellers. Through research, consumers are encouraged to make effective use of online reviews, and it also provides enlightenment for the marketing management of cross-border e-commerce...

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...

Food-related sustainability and health issues have led to calls for improving consumer food choices. As food purchase decisions predominantly occur in supermarkets and increasingly in online supermarkets, online interventions to stimulate healthy and sustainable grocery choices have gained...

Purpose This study investigates the effects of trust, satisfaction, and loyalty on AI‑driven e‑commerce, with a particular focus on how personalized recommendations moderate these relationships. It aims to explore how personalized AI features reshape consumer perceptions and decision-making....

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...

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...

Current studies primarily focus on the recommender systems (RSs) through the algorithmic accuracy, and which insufficient to fully measure accurately the practical effectiveness of the RSs and understand user experience. There is an urge examine the dynamic interactions on the critical user...

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...

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,...

This study documents the existence and prevalence of the “review updating” phenomenon, where consumers change the ratings and content of their existing reviews, and examines its implications for platforms and businesses. Using both primary and secondary data, a dataset comprising 3 million...

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...

In recent years, online shopping is one of the routine parts in people’s life. It is convenient and takes less effort to purchase it. Regarding the increasing revolution of e-commerce businesses, recommendation engine plays a crucial role in them. Recommendation engines are very popular and...