Examining the Preference Diversity displayed to Algorithmic versus Human Recommenders and the Corresponding Expectations of Recommendation Accuracy in High versus Low Involvement Contexts

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Keywords	algorithms, preferences, recommendations, accuracy, high/low involvement
Thesis Advisor	Mariadassou, Shwetha, Essa, Musa
Persistent URL	hdl.handle.net/2105/74267
Series	Marketing Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	van der Werff, Zoë. (2024, July 25). Examining the Preference Diversity displayed to Algorithmic versus Human Recommenders and the Corresponding Expectations of Recommendation Accuracy in High versus Low Involvement Contexts. Marketing Management. Retrieved from http://hdl.handle.net/2105/74267

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