Decision Support System for the Location of Retail Business Stores

Naysha Loo; Carlos Hernandez; David Mauricio

doi:10.1007/978-981-33-4565-2_5

Decision Support System for the Location of Retail Business Stores

Naysha Loo, Carlos Hernandez, David Mauricio

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

3 Scopus citations

Abstract

Within the natural cycle of retail companies, there is the stage of expansion where one of the most critical and high impact processes is the process of selecting the location for new stores. So it is necessary to make the most appropriate decision, which allows in the medium and long term to have fewer risks and losses, and higher profits and sales. This work proposes a Decision Support System for the location of retail stores, which will provide entrepreneurs with available, updated, and relevant information on retail stores, public services, and influxes of people. In addition, the system allows to project and compare for two or more new store locations, the critical indicators: average monthly ticket, monthly influx, total monthly sale, demographic density, amount of competences. To validate the proposed system, 5 case studies were carried out on real stores in Lima, the results obtained for a 6-month projection show high precision in the projection of the indicators, reaching on average 98.64%, 97.29%, and 96.61% for the average ticket, the influx of customers and the total amount of sales, respectively.

Original language	English
Title of host publication	Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020
Editors	Marcelo V. García, Félix Fernández-Peña, Carlos Gordón-Gallegos
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	67-78
Number of pages	12
ISBN (Print)	9789813345645
DOIs	https://doi.org/10.1007/978-981-33-4565-2_5
State	Published - 2021
Externally published	Yes
Event	International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2020 - Ambato, Ecuador Duration: 26 Oct 2020 → 30 Oct 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1307 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2020
Country/Territory	Ecuador
City	Ambato
Period	26/10/20 → 30/10/20

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

Business analytics
Decision support system
Location
Predictive
SAP analytics cloud
Site retail selection

Access to Document

10.1007/978-981-33-4565-2_5

Cite this

Loo, N., Hernandez, C., & Mauricio, D. (2021). Decision Support System for the Location of Retail Business Stores. In M. V. García, F. Fernández-Peña, & C. Gordón-Gallegos (Eds.), Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020 (pp. 67-78). (Advances in Intelligent Systems and Computing; Vol. 1307 AISC). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-33-4565-2_5

Loo, Naysha ; Hernandez, Carlos ; Mauricio, David. / Decision Support System for the Location of Retail Business Stores. Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020. editor / Marcelo V. García ; Félix Fernández-Peña ; Carlos Gordón-Gallegos. Springer Science and Business Media Deutschland GmbH, 2021. pp. 67-78 (Advances in Intelligent Systems and Computing).

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abstract = "Within the natural cycle of retail companies, there is the stage of expansion where one of the most critical and high impact processes is the process of selecting the location for new stores. So it is necessary to make the most appropriate decision, which allows in the medium and long term to have fewer risks and losses, and higher profits and sales. This work proposes a Decision Support System for the location of retail stores, which will provide entrepreneurs with available, updated, and relevant information on retail stores, public services, and influxes of people. In addition, the system allows to project and compare for two or more new store locations, the critical indicators: average monthly ticket, monthly influx, total monthly sale, demographic density, amount of competences. To validate the proposed system, 5 case studies were carried out on real stores in Lima, the results obtained for a 6-month projection show high precision in the projection of the indicators, reaching on average 98.64%, 97.29%, and 96.61% for the average ticket, the influx of customers and the total amount of sales, respectively.",

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Loo, N, Hernandez, C & Mauricio, D 2021, Decision Support System for the Location of Retail Business Stores. in MV García, F Fernández-Peña & C Gordón-Gallegos (eds), Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020. Advances in Intelligent Systems and Computing, vol. 1307 AISC, Springer Science and Business Media Deutschland GmbH, pp. 67-78, International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2020, Ambato, Ecuador, 26/10/20. https://doi.org/10.1007/978-981-33-4565-2_5

Decision Support System for the Location of Retail Business Stores. / Loo, Naysha; Hernandez, Carlos; Mauricio, David.
Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020. ed. / Marcelo V. García; Félix Fernández-Peña; Carlos Gordón-Gallegos. Springer Science and Business Media Deutschland GmbH, 2021. p. 67-78 (Advances in Intelligent Systems and Computing; Vol. 1307 AISC).

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

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AU - Hernandez, Carlos

AU - Mauricio, David

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N2 - Within the natural cycle of retail companies, there is the stage of expansion where one of the most critical and high impact processes is the process of selecting the location for new stores. So it is necessary to make the most appropriate decision, which allows in the medium and long term to have fewer risks and losses, and higher profits and sales. This work proposes a Decision Support System for the location of retail stores, which will provide entrepreneurs with available, updated, and relevant information on retail stores, public services, and influxes of people. In addition, the system allows to project and compare for two or more new store locations, the critical indicators: average monthly ticket, monthly influx, total monthly sale, demographic density, amount of competences. To validate the proposed system, 5 case studies were carried out on real stores in Lima, the results obtained for a 6-month projection show high precision in the projection of the indicators, reaching on average 98.64%, 97.29%, and 96.61% for the average ticket, the influx of customers and the total amount of sales, respectively.

AB - Within the natural cycle of retail companies, there is the stage of expansion where one of the most critical and high impact processes is the process of selecting the location for new stores. So it is necessary to make the most appropriate decision, which allows in the medium and long term to have fewer risks and losses, and higher profits and sales. This work proposes a Decision Support System for the location of retail stores, which will provide entrepreneurs with available, updated, and relevant information on retail stores, public services, and influxes of people. In addition, the system allows to project and compare for two or more new store locations, the critical indicators: average monthly ticket, monthly influx, total monthly sale, demographic density, amount of competences. To validate the proposed system, 5 case studies were carried out on real stores in Lima, the results obtained for a 6-month projection show high precision in the projection of the indicators, reaching on average 98.64%, 97.29%, and 96.61% for the average ticket, the influx of customers and the total amount of sales, respectively.

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KW - Predictive

KW - SAP analytics cloud

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A2 - Gordón-Gallegos, Carlos

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2020

Y2 - 26 October 2020 through 30 October 2020

ER -

Loo N, Hernandez C, Mauricio D. Decision Support System for the Location of Retail Business Stores. In García MV, Fernández-Peña F, Gordón-Gallegos C, editors, Advances and Applications in Computer Science, Electronics and Industrial Engineering - Proceedings of CSEI 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 67-78. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-981-33-4565-2_5

Decision Support System for the Location of Retail Business Stores

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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