Search Results - subject:"‘Personalization’"

Information Design for Social Learning on a Recommendation Platform

Lyu, Chen - 2022

Early consumption of a product often benefits later consumers by revealing quality information. Inefficiency arises, however, because early consumers do not internalize the social value of their consumption. How could a platform that intermediates information between early and late consumers...

Persistent link: https://www.econbiz.de/10014237208

The Economics of Recommender Systems : Evidence from a Field Experiment on MovieLens

Aridor, Guy; Gonçalves, Duarte; Kluver, Daniel; Kong, … - 2022

We conduct a field experiment on a movie-recommendation platform to identify if and how recommendations affect consumption. We use within-consumer randomization at the good level and elicit beliefs about unconsumed goods to disentangle exposure from informational effects. We find recommendations...

Persistent link: https://www.econbiz.de/10014240480

Impact of Customer Perception of Value Co-Creation for Personalization in Online Shopping

Abitha Kumari J, Jensolin; Gotmare, Preeti R. - 2022

Electronic commerce firms adopt advanced technologies to provide personalization of marketing-mix with data for … personalization co-created by consumers. This study explores customer's perception of value co-creation and how it impacts intention … to co-create value. Customer perception of value co-creation for personalization in an e-commerce context was …

Persistent link: https://www.econbiz.de/10014240543

Deep Learning-Based Recommendation System

Mehra, Kiran; Dubey, Rahul; Dubey, Ghanshyam Prasad - 2022

In current days, the recommendation system is the most popular thing which is used in almost all websites and apps like Internshala, LinkedIn, Instagram, Facebook, Amazon, Netflix, and many more. All of them have used the recommendation system to create practical solutions for the users. A...

Persistent link: https://www.econbiz.de/10014241307

Recommender Systems under Privacy Protection

Küçükgül, Can; Özer, Özalp; Wang, Shouqiang - 2022

The pervasive use of personal data by modern algorithmic recommender systems has sparked public outcry for tighter privacy regulations. Personal preferences over different product offerings are a basic constituent of consumer privacy. We study how a profit-driven online platform, who has...

Persistent link: https://www.econbiz.de/10014242457

Screening with persuasion

Bergemann, Dirk; Heumann, Tibor; Morris, Stephen - 2022

Persistent link: https://www.econbiz.de/10013326693

How to make recommendation systems fair : an adequate utility-based approach

Roengchai Tansuchat; Kosheleva, Olga - In: Asian journal of economics and banking : AJEB 6 (2022) 3, pp. 308-313

Purpose - In user-oriented websites, e.g. in news websites or in seller websites, it is important to take the user's preferences into account when deciding which items to place in higher-exposure locations. The traditional approach to solving this problem, based on maximizing the average user...

Persistent link: https://www.econbiz.de/10014231335

A Recommending System for Mobile Games Using Dynamic Nonparametric Model

Bae, Joonho; Park, Jinkyoo; Choi, Jeonghye; Soh, Seung Bum - 2022

We contribute to the literature on recommendation systems by proposing the Dynamic Nonparametric (DNP) model that incorporates a fully Bayesian approach into the traditional dynamic collaborative filtering and hence captures the change of customer preferences in the mobile game industry with...

Persistent link: https://www.econbiz.de/10013309296

Streaming platform and strategic recommendation bias

Bourreau, Marc; Gaudin, Germain - In: Journal of economics & management strategy : JEMS 31 (2022) 1, pp. 25-47

Persistent link: https://www.econbiz.de/10012815768

Multiple Treatment Modeling for Target Marketing Campaigns: A Large-Scale Benchmark Study

Gubela, Robin M.; Lessmann, Stefan; Stöcker, Björn - In: Information Systems Frontiers 26 (2022) 3, pp. 875-898

Machine learning and artificial intelligence (ML/AI) promise higher degrees of personalization and enhanced efficiency …

Persistent link: https://www.econbiz.de/10015327706