Search Results - subject_exact:"Empfehlungssystem"

Effects of product online reviews on product returns : a review and classification of the literature

Wang, Yun; Yu, Bo; Chen, Jing - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015459120

Selling on recommender platforms : demand boost versus customer migration

Karle, Heiko; Preuß, Marcel; Reisinger, Markus - 2026

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015596654

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Selling on recommender platforms : demand boost versus customer migration

Karle, Heiko; Preuß, Marcel; Reisinger, Markus - 2026

Book / Working Paper

Dynamic recommendation bias

Drugov, Mikhail; Jeon, Doh-Shin - 2026 - This version: April 29, 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015637970

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Dynamic recommendation bias

Drugov, Mikhail; Jeon, Doh-Shin - 2026

Book / Working Paper

A dual-drive recommendation model for smart healthcare platforms : synergizing proactive search and AI-driven decision-making

Gao, Lingyu; Xiaoli, Wang - 2026

The emergence of smart healthcare platforms has significantly enhanced the accessibility of medical services, yet it has also introduced critical challenges such as information overload and patient decision-making dilemmas. This study investigates the interaction and synergistic optimization of...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015653627

Choice architecture in occupational choices

Dell, Madison; Brox, Enzo; Palffy, Patricia; Schilter, … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015666902

How much should a conversational recommender system converse?

Kumar, Akshit; Manshadi, Vahideh; Tumu, Akhilesh - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015668668

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How much should a conversational recommender system converse?

Kumar, Akshit; Manshadi, Vahideh; Tumu, Akhilesh - 2026

Book / Working Paper

Platform-controlled search and distortions in attention allocation

Cai, Xiaoming; Gautier, Pieter; Wolthoff, Ronald - 2026

Digital platforms allocate buyer attention across sellers that differ in quality and breadth of appeal. We study a monopoly platform that sets meeting rates between buyers and two seller types - niche sellers whose high-quality good is valued by a fraction x of buyers and mass-market sellers...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015667360

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Platform-controlled search and distortions in attention allocation

Cai, Xiaoming; Gautier, Pieter; Wolthoff, Ronald - 2026

Book / Working Paper

Platform-controlled search and distortions in attention allocation

Cai, Xiaoming; Gautier, Pieter; Wolthoff, Ronald - 2026

Book / Working Paper

Platform-controlled search and distortions in attention allocation

Cai, Xiaoming; Gautier, Pieter; Wolthoff, Ronald - 2026

Book / Working Paper

A job i like or a job i can get : designing job recommender systems using field experiments

Bied, Guillaume; Caillou, Philippe; Crépon, Bruno; … - 2026

Recommendation systems (RSs) are increasingly used to guide job seekers on online platforms, yet the algorithms currently deployed are typically optimized for predictive objectives such as clicks, applications, or hires, rather than job seekers' welfare. We develop a job-search model with an...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015665784

Too many or too few? : information cues in recommender systems and consequences for search and purchase behavior

Fang, Xing; Kim, SunAh; Chintagunta, Pradeep K. - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015670065

From conversations to mechanisms: aligning advertiser incentives in AI-powered product recommendations

Bergemann, Dirk; Bojko, Marek; Dütting, Paul; Paes … - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015669110

Platform power in news aggregation : Andrey Simonov, Daniil Mikhailov, Ruben Enikolopov, Ruben Durante

Simonov, Andrey; Mikhailov, Daniil; Enikolopov, Ruben; … - 2026

News aggregators are among the primary gatekeepers of online news, shaping both consumption and production through the algorithms that rank stories and sources. We provide the first large-scale estimates of this algorithmic power using the example of Yandex News, Russia's largest aggregator....

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016060180

Recommendation power and competition

Peitz, Martin; Sobolev, Anton - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016083453

Personalized but valued? : how AI-driven advertising shapes perceived trust and purchase intention : a cross-national comparison

Dia, Soha; Harb, Hadi; Khreis, Malak; Taskiran, Meliha … - 2026

AI-driven personalization has become a defining feature of digital advertising, yet whether it drives purchase intention directly or depends on other underlying mechanisms remains insufficiently understood, particularly in under-studied emerging markets. This study investigates how perceived...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016073364

Recommendation design, pricing, and regulation

Marstaller, Laurenz - 2026

This paper studies how platforms jointly choose fees and recommendations and their implications for fee regulation. A platform charges sellers a commission rate and ranks products based on price and match-value. The analysis shows that price-sensitive rankings intensify seller competition,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016085885

Building digital bonds : the impact of AI-driven personalization on customer experience and AI relationship quality

Munandar, Dadang; Narimawati, Umi; Nusa, Inta Budi Setia; … - 2026

This study aims to examine the impact of AI-driven personalization on AI-enabled customer experience and perceived AI relationship quality. It further investigates the mediating roles of trust in AI and perceived personal relevance, as well as the moderating effects of privacy concern and...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015677215

Personalized pricing in the presence of privacy concerns

Chen, Zhiqi - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016084590

The role of AI in online reviews

Lermana, Valeria; Rigbi, Oren; Dover, Yaniv - 2026

The rapid adoption of large language models (LLMs) creates new opportunities for strategic content generation on online platforms, including potentially harmful forms of manipulation that may undermine platform effectiveness and reshape platform dynamics. However, measuring such activity is...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10016086312

Personalization, trust, and identity in AI-based marketing : an empirical study of consumer acceptance in Greece

Markou, Vasiliki; Serdaris, Panagiotis; Antoniadis, Ioannis - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015548881

A personalized content-based method to predict customers' preferences in an online apparel retailer

KabirMamdouh, Alireza; Kök, A. Gürhan - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015372705

Rating with the senses : how sensory encounters are reflected on online review ratings?

Hallikainen, Heli; Halinen, Marianna; Tervonen, Hannes; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015372971

Social dynamics of luxury customization : the unique impact of name personalization

O'Rourke, Anne-Maree; Lin, Joanna; Sung, Billy; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015373135

Collaborative filtering recommender systems : methods, strengths and weaknesses

Schmidtke, Marcel; Neeb, Jannik; Wöhner, Thomas - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015374761

Efficiency versus fairness in link recommendation algorithms

Grabisch, Michel; Mandel, Antoine; Rusinowska, Agnieszka - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015210771

The impact of different recommendation algorithms on consumer search behavior and merchants competition

Zhang, Weiyi; Wang, Yong - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015331921

The dark side of social media : recommender algorithms and mental health

Mandile, Simona - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015191592

Personalized content, engagement, and monetization in a mobile puzzle game

Pape, Louis-Daniel; Helmers, Christian; Iaria, Alessandro; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015181873

Recommending for a multi-sided marketplace : a multi-objective hierarchical approach

Wang, Yuyan; Tao, Long; Zhang, Xian Xing - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015197173

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Recommending for a multi-sided marketplace : a multi-objective hierarchical approach

Wang, Yuyan; Tao, Long; Zhang, Xian Xing - 2023

Book / Working Paper

Personalized recommendation, behavior-based pricing, or both? : examining privacy concerns from a cost perspective

Zhou, Chi; Bai, Danyang; Li, Tieshan; Yu, Jing - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015407212

Dance to my tune! : Discovery mode and built-in recommendation bias

Gambato, Jacopo; Sandrini, Luca - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015438179

Modeling sustainable city trips : integrating CO₂ e emissions, popularity, and seasonality into tourism recommender systems

Banerjee, Ashmi; Mahmudov, Tunar; Adler, Emil; Aisyah, … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015439402

Usage complementarity vs. basket co-occurrence : discount depth reliance in digitally personalized product recommendations

Choi, Jungsil; Park, Hyun Young - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015427542

AI-driven personalisation and customer engagement in social commerce : evidence from Kosovo

Emini, Adelina; Budić, Hrvoje; Klopotan, Igor - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015561571

The invisible algorithm: the impact of search and recommender systems on the digital creative industries

Schlott, Fabian; Gänßle, Sophia - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015564129

Regulating recommender systems? : effects of data-based individualization (and its limits) on competition in the digital world

Budzinski, Oliver; Stöhr, Annika - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015564160

The price of advice : experimental evidence on the effects of AI recommenders

Zac, Amit; Gal, Michal S. - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015568010

A deep learning framework for optimizing personalized online course recommendation and selection

Mrhar, Khaoula; Abik, Mounia - 2025

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,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015506761

Precommitment and personalized product recommendations : an incentivized study in online grocery shopping

Jansen, Laura Z. H.; Van Loo, Ellen J.; Kleef, Ellen van; … - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015610103

The moderating role of personalized recommendations in the trust-satisfaction-loyalty relationship : an empirical study of AI-driven e-commerce

Hassan, Noha; Abdelraouf, Mohamed; El-Shihy, Dina - 2025

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....

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015614155

The impact of Netflix's AI powered recommendation system on consumers' behavioral intentions

Etlioglu, Mehmet - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015593913

Biased recommendations and differentially informed consumers

Peitz, Martin; Sobolev, Anton - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015594803

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Biased recommendations and differentially informed consumers

Peitz, Martin; Sobolev, Anton - 2025

Book / Working Paper

Hybrid self-attention BiLSTM and incentive learning-based collaborative filtering for e-commerce recommendation systems

Abdalla, Hemn Barzan; Gheisari, Mehdi; Awlla, Ardalan … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015595602

Explanations increase citizen trust in police algorithmic recommender systems : findings from two experimental tests

Nieuwenhuizen, E. N.; Meijer, A. J.; Bex, F. J.; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015551063

Managing operational alignment complexity : a recommender system approach

Bidmeshk, Olfat Ganji; Woo, Carson; Mehraeen, Mohammad - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015557162

From booking to rating activities : a holistic analysis of online review behavior in a destination

Nicolau, Juan Luis; Bigné Alcañiz, J. Enrique; … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015583788

Impact of online reviews in virtual communities on cross-border e-commerce platform reputation

Ma, Shenglin; Zeng, Hongjun; Liu, Huifang; Yan, Han - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015605794

Measuring bias in job recommender systems : auditing the algorithms

Zhang, Shuo; Kuhn, Peter Joseph - 2025

We use an algorithm audit of China's four largest job boards to measure the causal effect of a job seeker's gender on the jobs that are recommended to them, and to identify the algorithmic processes that generate those recommendations. Focusing on identical male and female worker profiles...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015652616

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Measuring bias in job recommender systems : auditing the algorithms

Zhang, Shuo; Kuhn, Peter Joseph - 2024

Book / Working Paper

Artificial intelligence recommendations amplify the sharing of true and fake news on social media by appealing to fast cognition

Ma, Hanzhuo; Dennis, Alexander S.; Dennis, Alan; Huang, Wei - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015533993

Personalized pricing and consumer privacy

Houba, Harold; Motchenkova, Evgenia - 2025

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...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015559480

Mirror, mirror on the screen, “Wherein can I find me?" : On the sublime qualities of AI recommendation systems, algorithm conformity, and the else

Hond, Frank den; Vesa, Mikko - 2025

Algorithmic persuasion is a mode of organizing that happens through inducing experiences that covertly seek to influence behavior by presenting an ongoing stream of affective recommendations. This essay advances the thesis that this mode of algorithmic organizing has the capacity to affect...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015668562

YouCodeGirls – Nutzung von Künstlicher Intelligenz zur zielgruppengerechten Unterstützung von Lernprozessen

Stattkus, Daniel; Göritz, Lorena; Hein, Laura; Eckle, … - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015671453