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Thomas He

Biographic Data

ID3847984
NAMEThomas He
GIVEN NAMESThomas
FAMILY NAMEHe
SIGNATUREHE T
AFFILIATIONSLudwig-Maximilians-Universität München
ORCID0000-0003-3969-7477
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS2
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2019
H-INDEX1
  • A factual and perceptional framework for assessing diversity effects of online recommender systems

    Open Access•Christian Matt, Thomas He et al.•ARTICLE•Internet Research•2019•Cited by: 2•References: 3

    Purpose The purpose of this paper is to explore the effects of online recommender systems (RS) on three types of diversity: algorithmic recommendation diversity, perceived recommendation diversity and sales diversity. The analysis distinguishes different recommendation algorithms and shows whether user perceptions match the actual effects of RS on sales. Design/methodology/approach An online experiment was conducted using a realistic shop design,…

  • Digitalization

    Open Access•Christine Legner, Torsten Eymann et al.•ARTICLE•Business & Information Systems…•2017

  • Digital Transformation Strategies

    Open Access•Christian Matt, Thomas He et al.•ARTICLE•Business & Information Systems…•2015

  • A factual and perceptional framework for assessing diversity effects of online recommender systems

    Open Access•Christian Matt, Thomas He et al.•ARTICLE•Internet Research•2019•Cited by: 2•References: 3

    Purpose The purpose of this paper is to explore the effects of online recommender systems (RS) on three types of diversity: algorithmic recommendation diversity, perceived recommendation diversity and sales diversity. The analysis distinguishes different recommendation algorithms and shows whether user perceptions match the actual effects of RS on sales. Design/methodology/approach An online experiment was conducted using a realistic shop design,…

  • Digital Transformation Strategies

    Open Access•Christian Matt, Thomas He et al.•ARTICLE•Business & Information Systems…•2015

  • Digitalization

    Open Access•Christine Legner, Torsten Eymann et al.•ARTICLE•Business & Information Systems…•2017

  • A factual and perceptional framework for assessing diversity effects of online recommender systems

    Open Access•Christian Matt, Thomas He et al.•ARTICLE•Internet Research•2019•Cited by: 2•References: 3

    Purpose The purpose of this paper is to explore the effects of online recommender systems (RS) on three types of diversity: algorithmic recommendation diversity, perceived recommendation diversity and sales diversity. The analysis distinguishes different recommendation algorithms and shows whether user perceptions match the actual effects of RS on sales. Design/methodology/approach An online experiment was conducted using a realistic shop design,…

Computer Science (3 works) · Business (2 works) · Engineering (2 works) · Big Data and Business Intelligence (1 work) · Business Process Modeling and Analysis (1 work) · Consumer Market Behavior and Pricing (1 work) · Credence (1 work) · Digital Marketing and Social Media (1 work) · Digital transformation (1 work) · Digital Transformation in Industry (1 work)

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