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Online Footsteps to Purchase: Exploring Consumer Behaviors on Online Shopping Sites

Published: 28 June 2015 Publication History

Abstract

As an important part of the Internet economy, online markets have gained much interest in research community as well as industry. Researchers have studied various aspects of online markets including motivations of consumer behaviors on online markets. However, due to the lack of log data of consumers' online behaviors including their purchase, it has not been thoroughly investigated or validated on what drives consumers to purchase products on online markets. Our research moves forward from prior studies by analyzing consumers' actual online behaviors that lead to actual purchases, and using datasets from multiple online shopping sites that can provide comparisons across different types of online shopping sites. We analyzed consumers' buying process and constructed consumers' behavior trajectory to gain deeper understanding of consumer behaviors on online markets. We find that a substantial portion (24%) of consumers in a general-purpose marketplace (like eBay) discover items from external sources (e.g., price comparison sites), while most (>95%) of consumers in a special-purpose shopping site directly access items from the site itself. We also reveal that item browsing patterns and cart usage patterns are the important predictors of the actual purchases. Using behavioral features identified by our analysis, we developed a prediction model to infer whether a consumer purchases item(s). Our prediction model of purchases achieved over 80% accuracy across four different online shopping sites.

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  • (2024)Self-supervised progressive graph neural network for enhanced multi-behavior recommendationInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02353-716:3(1573-1588)Online publication date: 4-Sep-2024
  • (2023)Cascading Residual Graph Convolutional Network for Multi-Behavior RecommendationACM Transactions on Information Systems10.1145/358769342:1(1-26)Online publication date: 15-Mar-2023
  • (2021)Prediction of Online Purchasing Behavior of Cameras UsingWeb Search Logsウェブ検索ログからのカメラのオンライン購買行動予測Transactions of the Japanese Society for Artificial Intelligence10.1527/tjsai.36-1_WI2-C36:1(WI2-C_1-10)Online publication date: 1-Jan-2021
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  1. Online Footsteps to Purchase: Exploring Consumer Behaviors on Online Shopping Sites

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    cover image ACM Conferences
    WebSci '15: Proceedings of the ACM Web Science Conference
    June 2015
    366 pages
    ISBN:9781450336727
    DOI:10.1145/2786451
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    Publication History

    Published: 28 June 2015

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    Author Tags

    1. Behavior Trajectory
    2. Consumer Behaviors
    3. E-commerce
    4. Internet Economy
    5. Online Markets
    6. Purchase Prediction

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    WebSci '15
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    WebSci '15: ACM Web Science Conference
    June 28 - July 1, 2015
    Oxford, United Kingdom

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    Overall Acceptance Rate 245 of 933 submissions, 26%

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    Cited By

    View all
    • (2024)Self-supervised progressive graph neural network for enhanced multi-behavior recommendationInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02353-716:3(1573-1588)Online publication date: 4-Sep-2024
    • (2023)Cascading Residual Graph Convolutional Network for Multi-Behavior RecommendationACM Transactions on Information Systems10.1145/358769342:1(1-26)Online publication date: 15-Mar-2023
    • (2021)Prediction of Online Purchasing Behavior of Cameras UsingWeb Search Logsウェブ検索ログからのカメラのオンライン購買行動予測Transactions of the Japanese Society for Artificial Intelligence10.1527/tjsai.36-1_WI2-C36:1(WI2-C_1-10)Online publication date: 1-Jan-2021
    • (2021)Learning to Recommend With Multiple Cascading BehaviorsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.295880833:6(2588-2601)Online publication date: 1-Jun-2021
    • (2020)Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research AgendaNew Frontiers in Mining Complex Patterns10.1007/978-3-030-48861-1_8(119-136)Online publication date: 14-May-2020
    • (2019)Predicting Time-Bounded Purchases During a Mega Shopping Festival2019 IEEE International Conference on Big Data and Smart Computing (BigComp)10.1109/BIGCOMP.2019.8679217(1-8)Online publication date: Feb-2019
    • (2018)Brand purchase prediction based on time‐evolving user behaviors in e‐commerceConcurrency and Computation: Practice and Experience10.1002/cpe.488231:1Online publication date: 23-Oct-2018
    • (2017)Heuristic approach to online purchase prediction based on internet store visitors classification using data mining methods2017 International Conference on Information and Digital Technologies (IDT)10.1109/DT.2017.8024313(304-307)Online publication date: Jul-2017

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