Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators

Cagatay Ozdemir; Sezi Cevik Onar; Selami Bagriyanik

doi:10.1007/978-3-030-51156-2_21

Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators

Cagatay Ozdemir^*, Sezi Cevik Onar, Selami Bagriyanik

^*Corresponding author for this work

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The value of data is gaining importance in recent years both in Turkey and globally through increase data production. As data began to gain importance, data mining began to change and evolve. With help of data mining, companies started to determine their customer management strategies based on intelligent data analysis. Literature reviews in this area show that many data analysis models studied in the field of customer management. When a more detailed literature review is made, it is observed that the number of sources where demand estimation and location analysis applied together with the machine learning algorithms is very low in all sectors and almost none in the shopping mall. Within the scope of this study, a new model has been developed by combining location analysis and demand forecasting models that will estimate the number of customers for shopping malls in order to overcome this deficiency in the literature. This model was strengthened with estimation algorithms and tested to generalize this model to all shopping malls. In this study conducted through a large-scale technology and communications services provider company, it was found that environmental factors had a significant effect on the number of customers going to shopping centers.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques
Subtitle of host publication	Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Publisher	Springer
Pages	171-179
Number of pages	9
ISBN (Print)	9783030511555
DOIs	https://doi.org/10.1007/978-3-030-51156-2_21
Publication status	Published - 2021
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey Duration: 21 Jul 2020 → 23 Jul 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1197 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2020
Country/Territory	Turkey
City	Istanbul
Period	21/07/20 → 23/07/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Customer strategy
Demand model
Intelligent data analysis
Location analysis
Machine learning
Predictive analysis
Regression model
Shopping mall

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-51156-2_21

Cite this

Ozdemir, C., Onar, S. C., & Bagriyanik, S. (2021). Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference (pp. 171-179). (Advances in Intelligent Systems and Computing; Vol. 1197 AISC). Springer. https://doi.org/10.1007/978-3-030-51156-2_21

Ozdemir, Cagatay ; Onar, Sezi Cevik ; Bagriyanik, Selami. / Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators. Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A. Cagri Tolga. Springer, 2021. pp. 171-179 (Advances in Intelligent Systems and Computing).

@inproceedings{f792374306644b01a4d2e35066abebef,

title = "Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators",

abstract = "The value of data is gaining importance in recent years both in Turkey and globally through increase data production. As data began to gain importance, data mining began to change and evolve. With help of data mining, companies started to determine their customer management strategies based on intelligent data analysis. Literature reviews in this area show that many data analysis models studied in the field of customer management. When a more detailed literature review is made, it is observed that the number of sources where demand estimation and location analysis applied together with the machine learning algorithms is very low in all sectors and almost none in the shopping mall. Within the scope of this study, a new model has been developed by combining location analysis and demand forecasting models that will estimate the number of customers for shopping malls in order to overcome this deficiency in the literature. This model was strengthened with estimation algorithms and tested to generalize this model to all shopping malls. In this study conducted through a large-scale technology and communications services provider company, it was found that environmental factors had a significant effect on the number of customers going to shopping centers.",

keywords = "Customer strategy, Demand model, Intelligent data analysis, Location analysis, Machine learning, Predictive analysis, Regression model, Shopping mall",

author = "Cagatay Ozdemir and Onar, {Sezi Cevik} and Selami Bagriyanik",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2020 ; Conference date: 21-07-2020 Through 23-07-2020",

year = "2021",

doi = "10.1007/978-3-030-51156-2_21",

language = "English",

isbn = "9783030511555",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "171--179",

editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Basar Oztaysi and Sari, {Irem Ucal} and Selcuk Cebi and Tolga, {A. Cagri}",

booktitle = "Intelligent and Fuzzy Techniques",

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Ozdemir, C, Onar, SC & Bagriyanik, S 2021, Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Advances in Intelligent Systems and Computing, vol. 1197 AISC, Springer, pp. 171-179, International Conference on Intelligent and Fuzzy Systems, INFUS 2020, Istanbul, Turkey, 21/07/20. https://doi.org/10.1007/978-3-030-51156-2_21

Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators. / Ozdemir, Cagatay; Onar, Sezi Cevik; Bagriyanik, Selami.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A. Cagri Tolga. Springer, 2021. p. 171-179 (Advances in Intelligent Systems and Computing; Vol. 1197 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators

AU - Ozdemir, Cagatay

AU - Onar, Sezi Cevik

AU - Bagriyanik, Selami

PY - 2021

Y1 - 2021

N2 - The value of data is gaining importance in recent years both in Turkey and globally through increase data production. As data began to gain importance, data mining began to change and evolve. With help of data mining, companies started to determine their customer management strategies based on intelligent data analysis. Literature reviews in this area show that many data analysis models studied in the field of customer management. When a more detailed literature review is made, it is observed that the number of sources where demand estimation and location analysis applied together with the machine learning algorithms is very low in all sectors and almost none in the shopping mall. Within the scope of this study, a new model has been developed by combining location analysis and demand forecasting models that will estimate the number of customers for shopping malls in order to overcome this deficiency in the literature. This model was strengthened with estimation algorithms and tested to generalize this model to all shopping malls. In this study conducted through a large-scale technology and communications services provider company, it was found that environmental factors had a significant effect on the number of customers going to shopping centers.

AB - The value of data is gaining importance in recent years both in Turkey and globally through increase data production. As data began to gain importance, data mining began to change and evolve. With help of data mining, companies started to determine their customer management strategies based on intelligent data analysis. Literature reviews in this area show that many data analysis models studied in the field of customer management. When a more detailed literature review is made, it is observed that the number of sources where demand estimation and location analysis applied together with the machine learning algorithms is very low in all sectors and almost none in the shopping mall. Within the scope of this study, a new model has been developed by combining location analysis and demand forecasting models that will estimate the number of customers for shopping malls in order to overcome this deficiency in the literature. This model was strengthened with estimation algorithms and tested to generalize this model to all shopping malls. In this study conducted through a large-scale technology and communications services provider company, it was found that environmental factors had a significant effect on the number of customers going to shopping centers.

KW - Customer strategy

KW - Demand model

KW - Intelligent data analysis

KW - Location analysis

KW - Machine learning

KW - Predictive analysis

KW - Regression model

KW - Shopping mall

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U2 - 10.1007/978-3-030-51156-2_21

DO - 10.1007/978-3-030-51156-2_21

M3 - Conference contribution

AN - SCOPUS:85088749184

SN - 9783030511555

T3 - Advances in Intelligent Systems and Computing

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EP - 179

BT - Intelligent and Fuzzy Techniques

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

A2 - Tolga, A. Cagri

PB - Springer

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2020

Y2 - 21 July 2020 through 23 July 2020

ER -

Ozdemir C, Onar SC, Bagriyanik S. Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Springer. 2021. p. 171-179. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-51156-2_21

Estimating Shopping Center Visitor Numbers Based on Various Environmental Indicators

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this