Data modalities, consumer attributes and recommendation performance in the fashion industry

Sylwia Sysko-Romańczuk (), Piotr Zaborek (), Anna Wróblewska (), Jacek Dąbrowski and Sergiy Tkachuk
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Sylwia Sysko-Romańczuk: Warsaw University of Technology, Management Faculty
Piotr Zaborek: Warsaw School of Economics, Collegium of World Economy, Department of International Business
Anna Wróblewska: Warsaw University of Technology, Faculty of Mathematics and Information Science
Jacek Dąbrowski: Synerise SA
Sergiy Tkachuk: Systems Research Institute of Polish Academy of Sciences

Electronic Markets, 2022, vol. 32, issue 3, No 16, 1279-1292

Abstract: Abstract This paper investigates determinants of recommendation systems’ performance in an online experiment in a large European Internet footwear store. By combining transactional data and archival customer records, a unique database was compiled from which proxy variables were extracted to represent dimensions of consumer loyalty and shopping involvement. These variables were combined in regression analysis with technical characteristics of two types of algorithms employed for generating recommendations: the EMDE algorithm, relying on the LSH method, and the industry-standard CF-RS. Statistical analysis reveals that recommendations are more successful when visual data modality is combined with behavioural data. Better recommendation performance was found to be associated with lower levels of consumer involvement in shopping, as well as higher levels of trust and engagement with the vendor. Experience with the vendor showed a negative correlation with recommendation performance through both its main effect and by its interactions with other consumer-related variables.

Keywords: Data modalities; Online recommendation system performance; Consumer loyalty; Shopping involvement; Fashion industry (search for similar items in EconPapers)
JEL-codes: C45 C55 D12 L67 L81 M21 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12525-022-00579-3

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