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akaturk Academic measurement

Article detail · 2019

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

Journal

Sensors

ISSN 1424-8220

YÖKSİS OpenAlex Open access · gold SJR Q1 JCR Q1 Citations 53 Top 10% Percentile 98.5% FWCI 10.95
Year
2019
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue SENSORS
  • Catalog match (ISSN) Sensors
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

The study presents some results of customer paths' analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men's bathroom or women's bathroom. Since the study has a comprehensive scope, we focused on male and female customers' behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

53 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. ONUR DOĞAN İZMİR BAKIRÇAY ÜNİVERSİTESİ
  2. JUSE LUIS BAYO MONTON
  3. CARLOS FERNANDEZ LLATAS
  4. BAŞAR ÖZTAYŞİ İSTANBUL TEKNİK ÜNİVERSİTESİ