Customer purchase behavior prediction in E-commerce: a conceptual framework and research agenda
| Autor: | Marija Bezbradica, Dietmar Nedbal, Markus Hofer, Douglas Cirqueira, Markus Helfert |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Knowledge management
Systematic review Conceptual framework Consumer behavior Purchase prediction Behavior analytics Machine learning Data mining E-commerce Digital retail business.industry Computer science Big data Behavioral pattern Context (language use) Predictive analytics business Consumer behaviour |
| Zdroj: | Cirqueira, Douglas ORCID: 0000-0002-1283-0453 New Frontiers in Mining Complex Patterns ISBN: 9783030488604 NFMCP@PKDD/ECML Lecture Notes in Computer Science Lecture Notes in Computer Science-New Frontiers in Mining Complex Patterns NFMCP 2019: New Frontiers in Mining Complex Patterns |
| ISSN: | 0302-9743 1611-3349 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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