A Data-Driven Fuzzy Performance Evaluation System for E-commerce Platforms

Basar Oztaysi*, Erdem Dayi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the evolving landscape of e-commerce, assessing operational performance has become increasingly vital due to growing competition and the complexity of digital customer journeys. In this study, I propose a fuzzy performance measurement (PM) framework based on the marketing funnel approach, aiming to evaluate operational success beyond traditional financial indicators. The model incorporates 15 data-driven key performance indicators (KPIs), categorized into three stages: Awareness, Lead Nurture, and Sales. Fuzzy AHP is employed to determine the weights of KPIs, while performance score functions are used to translate actual values into meaningful scores. A sample application demonstrates how the method provides both overall and criterion-based performance evaluations. Results indicate that the proposed framework can offer actionable insights, particularly highlighting strengths and weaknesses across different operational dimensions. The study contributes to the literature by presenting a tactical-level PM model suitable for digital platforms and suggests future extensions using advanced fuzzy set theories.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference
EditorsCengiz Kahraman, Basar Oztaysi, Selcuk Cebi, Sezi Cevik Onar, Cagri Tolga, Irem Ucal Sari, Irem Otay
PublisherSpringer Science and Business Media Deutschland GmbH
Pages778-787
Number of pages10
ISBN (Print)9783031983030
DOIs
Publication statusPublished - 2025
Event7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 - Istanbul, Turkey
Duration: 29 Jul 202531 Jul 2025

Publication series

NameLecture Notes in Networks and Systems
Volume1531 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025
Country/TerritoryTurkey
CityIstanbul
Period29/07/2531/07/25

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

  • E-commerce
  • Fuzzy AHP
  • Performance measurement

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