The Impact of Recommender System Algorithms Implementation to Indonesian Shopee Consumers' Pre-Purchase Decision

Authors

  • Christy Jonathan Pradita University
  • Cecilia Fidela Pradita University
  • Annaiya Rihhadatul Aisya Pradita University
  • Andrew Pradita University
  • Bernard Limasta Sutawijaya Pradita University
  • Muhammad Ifdal Athallah Pradita University

Keywords:

Recommender system, Consumer Pre-Purchase Decision, Shopee, Algorithm

Abstract

COVID-19 pandemic has altered many fields, including trades. Related direct activities have currently shifted to online through e-commerce. One of those popular ones is Shopee. This study is conducted in order to seek the influence of the recommender system algorithm towards the pre-purchase decision of Indonesian Shopee users. Quantitative methods of research methodology are used to collect primary data through questionnaire distribution. Secondary data are compiled with qualitative methods through literature review based on various journal articles and books on information systems and consumer behavior. Results of the study implied that Shopee’s recommender system prompts its users to seek more information about products of their needs. Information gained by users will be used as their consideration material before committing the transaction. Such behavior is concluded as the pre-purchase decision. The algorithms in the recommender system are proven to positively influence the pre-purchase decision of Indonesian Shopee consumers.

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Published

2025-09-30

Issue

Vol. 7 No. 1 (2025): Another Day, Another Technology

Section

Articles

License

Copyright (c) 2025 Christy Jonathan, Cecilia Fidela, Annaiya Rihhadatul Aisya, Andrew, Bernard Limasta Sutawijaya, Muhammad Ifdal Athallah

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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