Comparison between Amazon Go stores and traditional retails based on queueing theory

The Amazon Go Store model’s introduction posed a breakthrough in the shopping market due to its ground-braking approach, in which customers exercise the so-called self-service checkout. Although many qualitative analysis studies can be found, along with some quantitative approaches, a literature rev...

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Autores:
Coronado-Hernandez, Jairo R.
Calderón-Ocho, Andrés F.
Portnoy, Ivan
Morales-Mercado, Jorge
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9053
Acceso en línea:
https://hdl.handle.net/11323/9053
https://repositorio.cuc.edu.co/
Palabra clave:
Queuing theory
Markovian model
Jackson networks
Retail shopping
Amazon Go Store
Rights
embargoedAccess
License
Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
id RCUC2_dc7314723a7904cf75b2a7555ab09e5e
oai_identifier_str oai:repositorio.cuc.edu.co:11323/9053
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Comparison between Amazon Go stores and traditional retails based on queueing theory
title Comparison between Amazon Go stores and traditional retails based on queueing theory
spellingShingle Comparison between Amazon Go stores and traditional retails based on queueing theory
Queuing theory
Markovian model
Jackson networks
Retail shopping
Amazon Go Store
title_short Comparison between Amazon Go stores and traditional retails based on queueing theory
title_full Comparison between Amazon Go stores and traditional retails based on queueing theory
title_fullStr Comparison between Amazon Go stores and traditional retails based on queueing theory
title_full_unstemmed Comparison between Amazon Go stores and traditional retails based on queueing theory
title_sort Comparison between Amazon Go stores and traditional retails based on queueing theory
dc.creator.fl_str_mv Coronado-Hernandez, Jairo R.
Calderón-Ocho, Andrés F.
Portnoy, Ivan
Morales-Mercado, Jorge
dc.contributor.author.spa.fl_str_mv Coronado-Hernandez, Jairo R.
Calderón-Ocho, Andrés F.
Portnoy, Ivan
Morales-Mercado, Jorge
dc.subject.proposal.eng.fl_str_mv Queuing theory
Markovian model
Jackson networks
Retail shopping
Amazon Go Store
topic Queuing theory
Markovian model
Jackson networks
Retail shopping
Amazon Go Store
description The Amazon Go Store model’s introduction posed a breakthrough in the shopping market due to its ground-braking approach, in which customers exercise the so-called self-service checkout. Although many qualitative analysis studies can be found, along with some quantitative approaches, a literature review on this matter shows a lack of comparative analysis between this model and traditional retail models using queueing theory, which could provide powerful insight into the improvements introduced by Amazon Go Store system. This work sets out the path to quantitative approaches for such comparison, as it aims to provide a performance analysis through queueing theory. The article compared two queueing systems; a traditional retail store vs. the Amazon Go Store. Both systems were analyzed as queueing stochastic networks. First, the traditional retail store was modeled as a two-stage (shopping and payment) network. On the other hand, the Amazon Go Store was modeled as a single-stage (shopping + payment) network. Both systems were assessed in two case scenarios: a high-demand typical day and a low-demand typical day. The implemented methodology allowed obtaining, for both compared systems, the key performance indicators (KPIs) such as the cycle time (CT), work in process (WIP), and the throughput (TP), revealing that the Amazon Go Store model exhibits better performance regarding the WIP and CT. Therefore, the Amazon Go Store model renders a higher-quality, more cost-effective service in the retail sector.
publishDate 2021
dc.date.issued.none.fl_str_mv 2021-09-29
dc.date.accessioned.none.fl_str_mv 2022-03-07T21:31:10Z
dc.date.available.none.fl_str_mv 2022-09-29
2022-03-07T21:31:10Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
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Corporación Universidad de la Costa
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dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartofjournal.spa.fl_str_mv Communications in Computer and Information Science
dc.relation.references.spa.fl_str_mv 1. Luczak, M.J., Mcdiarmid, C.: On the maximum queue length in the supermarket model. Ann. Probab. 34(2), 493–527 (2006). https://doi.org/10.1214/00911790500000710 MathSciNetCrossRefzbMATHGoogle Scholar
2. Luo, R., Shi, Y.: Analysis and optimization of supermarket operation mode based on queuing theory: queuing and pricing of personalized service. In: ACM International Conference Proceeding Series, pp. 221–224 (2020). https://doi.org/10.1145/3380625.3380635
3. Coronado-Hernández, J.R., Macías-Jiménez, M.A., Chica-Llamas, J.D., Zapata-Márquez, J.I.: Additional file. Assessment of organizational policies in a retail store based on a simulation model, pp. 1–14 (2020). https://figshare.com/articles/dataset/Additional_file_Assessment_of_organizational_policies_in_a_retail_store_based_on_a_simulation_model_/14214251
4. Zhao, T., He, C.: Supermarket application based on queueing theory. In: Zhong, Z. (eds.) Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012. LNEE, vol. 218, pp. 545–551. Springer, London (2013). https://doi.org/10.1007/978-1-4471-4847-0_67
5. Bello, R.-W., Otobo, F.N.: Hypothetical modeling of a supermarket queue-an approach. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 8(7), 55–59 (2018). https://doi.org/10.23956/ijarcsse.v8i7.815
6. Jhala, N., Bhathawala, P.: Analysis and application of queuing theory in Supermarkets. Int. J. Innov. Res. Sci. Eng. Technol. 6(9), 6 (2017). https://doi.org/10.15680/IJIRSET.2017.0609021
7. Igwe, A., Onwuere, J.U.J., Egbo, O.P.: Efficient queue management in supermarkets: a case study of Makurdi Town, Nigeria. Eur. J. Bus. Manag. 6(39), 185–192 (2014)
8. Morabito, R., De Lima, F.C.R.: A Markovian queueing model for the analysis of user waiting times in supermarket checkouts. Int. J. Oper. Quant. Manag. 10(2), 165–177 (2004)
9. Priyangika, J., Cooray, T.: Analysis of the sales checkout operation in supermarket using queuing theory. Univ. J. Manag. 4(7), 393–396 (2015)
10. Prasad, V., Vh, B., Koka, T.A.: Mathematical analysis of single queue multi server and multi queue multi server queuing models: comparison study. Glob. J. Math. Anal. 3(3), 97–104 (2015)
11. Koeswara, S., Kholil, M., Pratama, Z., Hendri: Evaluation on application of queuing theory on payment system in the supermarket ‘saga’ Padang Pariaman West Sumatra. In: IOP Conf. Ser. Mater. Sci. Eng. 453(1), 012045 (2018). https://doi.org/10.1088/1757-899X/453/1/012045
12. Artalejo, J., Falin, G.: Standard and retrial queueing systems: a comparative analysis. Rev. Matemática Complut. 15(1), 101–129 (2002). https://doi.org/10.5209/rev_rema.2002.v15.n1.16950 MathSciNetCrossRefzbMATH
13. Lu, Y., Musalem, A., Olivares, M., Schilkrut, A.: Measuring the effect of queues on customer purchases. Manage. Sci. 59(8), 1743–1763 (2013). https://doi.org/10.1287/mnsc.1120.1686
14. Li, K., Pan, Y., Liu, B., Cheng, B.: The setting and optimization of quick queue with customer loss. J. Ind. Manag. Optim. 16(3), 1539–1553 (2020). https://doi.org/10.3934/JIMO.2019016
15. Xing, W., Li, S., He, L.: Simulation model of supermarket queuing system. In: 2015 34th Chinese Control Conference (CCC), vol. 2015-Septe, pp. 8819–8823 (2015). https://doi.org/10.1109/ChiCC.2015.7261032
16. Chai, C.F.: Problem analysis and optimizing of setting service desks in supermarket based on M/M/C queuing system. In: Qi, E., Shen, J., Dou, R. (eds.) The 19th International Conference on Industrial Engineering and Engineering Management. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38391-5_88.
17. Ives, B., Cossick, K., Adams, D.: Amazon Go: disrupting retail? J. Inf. Technol. Teach. Cases 9(1), 2–12 (2019). https://doi.org/10.1177/2043886918819092
18. Polacco, A., Backes, K.: The Amazon Go concept: Implications, applications, and sustainability. J. Bus. Manag. 24(1), 79–92 (2018) Google Scholar
19. Pillai, R., Sivathanu, B., Dwivedi, Y.K.: Shopping intention at AI-powered automated retail stores (AIPARS). J. Retail. Consum. Serv. 57(August), 102207 (2020). https://doi.org/10.1016/j.jretconser.2020.102207
20. Chuawatcharin, R., Gerdsri, N.: Factors influencing the attitudes and behavioural intentions to use just walk out technology among Bangkok consumers. Int. J. Public Sect. Perform. Manag. 5(2), 146–163 (2019). https://doi.org/10.1504/IJPSPM.2019.099091
21. Shekokar, N., Kasat, A., Jain, S., Naringrekar, P., Shah, M.: Shop and go: an innovative approach towards shopping using deep learning and computer visión. In: 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), pp. 1201–1206 (2020)
22. Wankhede, K., Wukkadada, B., Nadar, V.: Just walk-out technology and its challenges: a case of Amazon Go. In: International Conference on Inventive Research in Computing Applications, ICIRCA 2018, vol. Icirca, pp. 254–257 (2018). https://doi.org/10.1109/ICIRCA.2018.8597403
23. Taha, H.A.: Operations Research an Introduction. Pearson Education Limited 2017, New York (2017)
24. Jackson, J.R.: Networks of waiting lines. Oper. Res. 5(4), 518–521 (1957)
25. Little, J.D.C., Graves, S.C.: Chapter 5 Little’s Law. Oper. Manag. 115(December), 81–100 (2008). https://doi.org/10.1007/978-0-387
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spelling Coronado-Hernandez, Jairo R.Calderón-Ocho, Andrés F.Portnoy, IvanMorales-Mercado, Jorge2022-03-07T21:31:10Z2022-09-292022-03-07T21:31:10Z2021-09-29978-303086701-01865-0929https://hdl.handle.net/11323/905310.1007/978-3-030-86702-7_30Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The Amazon Go Store model’s introduction posed a breakthrough in the shopping market due to its ground-braking approach, in which customers exercise the so-called self-service checkout. Although many qualitative analysis studies can be found, along with some quantitative approaches, a literature review on this matter shows a lack of comparative analysis between this model and traditional retail models using queueing theory, which could provide powerful insight into the improvements introduced by Amazon Go Store system. This work sets out the path to quantitative approaches for such comparison, as it aims to provide a performance analysis through queueing theory. The article compared two queueing systems; a traditional retail store vs. the Amazon Go Store. Both systems were analyzed as queueing stochastic networks. First, the traditional retail store was modeled as a two-stage (shopping and payment) network. On the other hand, the Amazon Go Store was modeled as a single-stage (shopping + payment) network. Both systems were assessed in two case scenarios: a high-demand typical day and a low-demand typical day. The implemented methodology allowed obtaining, for both compared systems, the key performance indicators (KPIs) such as the cycle time (CT), work in process (WIP), and the throughput (TP), revealing that the Amazon Go Store model exhibits better performance regarding the WIP and CT. Therefore, the Amazon Go Store model renders a higher-quality, more cost-effective service in the retail sector.15 páginasapplication/pdfengSpringer VerlagGermanyAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)Copyright © Elsevier B.Vhttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfComparison between Amazon Go stores and traditional retails based on queueing theoryArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionhttps://link.springer.com/chapter/10.1007/978-3-030-86702-7_30Communications in Computer and Information Science1. Luczak, M.J., Mcdiarmid, C.: On the maximum queue length in the supermarket model. Ann. Probab. 34(2), 493–527 (2006). https://doi.org/10.1214/00911790500000710 MathSciNetCrossRefzbMATHGoogle Scholar2. Luo, R., Shi, Y.: Analysis and optimization of supermarket operation mode based on queuing theory: queuing and pricing of personalized service. In: ACM International Conference Proceeding Series, pp. 221–224 (2020). https://doi.org/10.1145/3380625.33806353. Coronado-Hernández, J.R., Macías-Jiménez, M.A., Chica-Llamas, J.D., Zapata-Márquez, J.I.: Additional file. Assessment of organizational policies in a retail store based on a simulation model, pp. 1–14 (2020). https://figshare.com/articles/dataset/Additional_file_Assessment_of_organizational_policies_in_a_retail_store_based_on_a_simulation_model_/142142514. Zhao, T., He, C.: Supermarket application based on queueing theory. In: Zhong, Z. (eds.) Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012. LNEE, vol. 218, pp. 545–551. Springer, London (2013). https://doi.org/10.1007/978-1-4471-4847-0_675. Bello, R.-W., Otobo, F.N.: Hypothetical modeling of a supermarket queue-an approach. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 8(7), 55–59 (2018). https://doi.org/10.23956/ijarcsse.v8i7.8156. Jhala, N., Bhathawala, P.: Analysis and application of queuing theory in Supermarkets. Int. J. Innov. Res. Sci. Eng. Technol. 6(9), 6 (2017). https://doi.org/10.15680/IJIRSET.2017.06090217. Igwe, A., Onwuere, J.U.J., Egbo, O.P.: Efficient queue management in supermarkets: a case study of Makurdi Town, Nigeria. Eur. J. Bus. Manag. 6(39), 185–192 (2014)8. Morabito, R., De Lima, F.C.R.: A Markovian queueing model for the analysis of user waiting times in supermarket checkouts. Int. J. Oper. Quant. Manag. 10(2), 165–177 (2004)9. Priyangika, J., Cooray, T.: Analysis of the sales checkout operation in supermarket using queuing theory. Univ. J. Manag. 4(7), 393–396 (2015)10. Prasad, V., Vh, B., Koka, T.A.: Mathematical analysis of single queue multi server and multi queue multi server queuing models: comparison study. Glob. J. Math. Anal. 3(3), 97–104 (2015)11. Koeswara, S., Kholil, M., Pratama, Z., Hendri: Evaluation on application of queuing theory on payment system in the supermarket ‘saga’ Padang Pariaman West Sumatra. In: IOP Conf. Ser. Mater. Sci. Eng. 453(1), 012045 (2018). https://doi.org/10.1088/1757-899X/453/1/01204512. Artalejo, J., Falin, G.: Standard and retrial queueing systems: a comparative analysis. Rev. Matemática Complut. 15(1), 101–129 (2002). https://doi.org/10.5209/rev_rema.2002.v15.n1.16950 MathSciNetCrossRefzbMATH13. Lu, Y., Musalem, A., Olivares, M., Schilkrut, A.: Measuring the effect of queues on customer purchases. Manage. Sci. 59(8), 1743–1763 (2013). https://doi.org/10.1287/mnsc.1120.168614. Li, K., Pan, Y., Liu, B., Cheng, B.: The setting and optimization of quick queue with customer loss. J. Ind. Manag. Optim. 16(3), 1539–1553 (2020). https://doi.org/10.3934/JIMO.201901615. Xing, W., Li, S., He, L.: Simulation model of supermarket queuing system. In: 2015 34th Chinese Control Conference (CCC), vol. 2015-Septe, pp. 8819–8823 (2015). https://doi.org/10.1109/ChiCC.2015.726103216. Chai, C.F.: Problem analysis and optimizing of setting service desks in supermarket based on M/M/C queuing system. In: Qi, E., Shen, J., Dou, R. (eds.) The 19th International Conference on Industrial Engineering and Engineering Management. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38391-5_88.17. Ives, B., Cossick, K., Adams, D.: Amazon Go: disrupting retail? J. Inf. Technol. Teach. Cases 9(1), 2–12 (2019). https://doi.org/10.1177/204388691881909218. Polacco, A., Backes, K.: The Amazon Go concept: Implications, applications, and sustainability. J. Bus. Manag. 24(1), 79–92 (2018) Google Scholar19. Pillai, R., Sivathanu, B., Dwivedi, Y.K.: Shopping intention at AI-powered automated retail stores (AIPARS). J. Retail. Consum. Serv. 57(August), 102207 (2020). https://doi.org/10.1016/j.jretconser.2020.10220720. Chuawatcharin, R., Gerdsri, N.: Factors influencing the attitudes and behavioural intentions to use just walk out technology among Bangkok consumers. Int. J. Public Sect. Perform. Manag. 5(2), 146–163 (2019). https://doi.org/10.1504/IJPSPM.2019.09909121. Shekokar, N., Kasat, A., Jain, S., Naringrekar, P., Shah, M.: Shop and go: an innovative approach towards shopping using deep learning and computer visión. In: 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), pp. 1201–1206 (2020)22. Wankhede, K., Wukkadada, B., Nadar, V.: Just walk-out technology and its challenges: a case of Amazon Go. In: International Conference on Inventive Research in Computing Applications, ICIRCA 2018, vol. Icirca, pp. 254–257 (2018). https://doi.org/10.1109/ICIRCA.2018.859740323. Taha, H.A.: Operations Research an Introduction. Pearson Education Limited 2017, New York (2017)24. Jackson, J.R.: Networks of waiting lines. Oper. Res. 5(4), 518–521 (1957)25. Little, J.D.C., Graves, S.C.: Chapter 5 Little’s Law. Oper. Manag. 115(December), 81–100 (2008). https://doi.org/10.1007/978-0-3873613471431Queuing theoryMarkovian modelJackson networksRetail shoppingAmazon Go StorePublicationORIGINALComparison Between Amazon Go Stores and Traditional Retails Based on Queueing Theory.pdfComparison Between Amazon Go Stores and Traditional Retails Based on Queueing Theory.pdfapplication/pdf76076https://repositorio.cuc.edu.co/bitstreams/470fc994-b652-4cbc-a2e5-ba168d101200/download31115c42c20f62e982edb0649358227cMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/bdded96e-38ae-4ee0-a6ec-d0475fbc1b3e/downloade30e9215131d99561d40d6b0abbe9badMD52TEXTComparison Between Amazon Go Stores and Traditional Retails Based on Queueing Theory.pdf.txtComparison Between Amazon Go Stores and Traditional Retails Based on Queueing 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