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International Workshop on New Frontiers in Mining Complex Patterns

NFMCP 2019: New Frontiers in Mining Complex Patterns pp 119–136Cite as

Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research Agenda

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11948))

Abstract

Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online.

This research was supported by the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 765395; the industry partner Raiffeisenlandesbank Oberösterreich AG; and supported, in part, by Science Foundation Ireland grant 13/RC/2094.

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Notes

  1. 1.

    Digital Commerce 360, Global E-commerce Sales 2019. https://www.digitalcommerce360.com/article/global-ecommerce-sales/.

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Author information

Authors and Affiliations

  1. Dublin City University, Dublin, Ireland

    Douglas Cirqueira & Marija Bezbradica

  2. Raiffeisenlandesbank Oberösterreich, Linz, Austria

    Markus Hofer

  3. University of Applied Sciences Upper Austria, Steyr, Austria

    Dietmar Nedbal

  4. Maynooth University, Maynooth, Ireland

    Markus Helfert

Authors
  1. Douglas Cirqueira
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  2. Markus Hofer
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  3. Dietmar Nedbal
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  4. Markus Helfert
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  5. Marija Bezbradica
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Corresponding author

Correspondence to Douglas Cirqueira .

Editor information

Editors and Affiliations

  1. University of Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  2. University of Bari Aldo Moro, Bari, Italy

    Corrado Loglisci

  3. CNR-ICAR, Rende, Italy

    Giuseppe Manco

  4. Federico II University, Naples, Italy

    Elio Masciari

  5. University of North Carolina, Charlotte, NC, USA

    Zbigniew Ras

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Cirqueira, D., Hofer, M., Nedbal, D., Helfert, M., Bezbradica, M. (2020). Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research Agenda. In: Ceci, M., Loglisci, C., Manco, G., Masciari, E., Ras, Z. (eds) New Frontiers in Mining Complex Patterns. NFMCP 2019. Lecture Notes in Computer Science(), vol 11948. Springer, Cham. https://doi.org/10.1007/978-3-030-48861-1_8

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  • DOI: https://doi.org/10.1007/978-3-030-48861-1_8

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