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  1. Article: Reducing risk of infection - The COVID-19 queueing game.

    Perlman, Yael / Yechiali, Uri

    Safety science

    2020  Volume 132, Page(s) 104987

    Abstract: ... infected while queueing outside the store, while shopping, and while checking out with a cashier. The risk ... to minimize the risk of infection. In the first model, store' management chooses the number of cashiers ... The COVID-19 pandemic has forced numerous businesses such as department stores and supermarkets ...

    Abstract The COVID-19 pandemic has forced numerous businesses such as department stores and supermarkets to limit the number of shoppers inside the store at any given time to minimize infection rates. We construct and analyze two models designed to optimize queue sizes and customer waiting times to ensure safety. In both models, customers arrive randomly at the store and, after receiving permission to enter, pass through two service phases: shopping and payment. Each customer spends a random period of time shopping (first phase) and then proceeds to the payment area of the store (second phase) where cashiers are assigned to serve customers. We propose a novel approach by which to calculate the risk of a customer being infected while queueing outside the store, while shopping, and while checking out with a cashier. The risk is proportional to the second factorial moment of the number of customers occupying the space in each phase of the shopping route. We derive equilibrium strategies for a Stackelberg game in which the authority acts as a leader who first chooses the maximum number of customers allowed inside the store to minimize the risk of infection. In the first model, store' management chooses the number of cashiers to provide to minimize its operational costs and its customers' implied waiting costs based on the number allowed in the store. In the second model, the store partitions its total space into two separate areas - one for shoppers and one for the cashiers and payers - to increase cashiers' safety. Our findings and analysis are useful and applicable for authorities and businesses alike in their efforts to protect both customers and employees while reducing associated costs.
    Keywords covid19
    Language English
    Publishing date 2020-09-03
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1074634-1
    ISSN 1879-1042 ; 0925-7535
    ISSN (online) 1879-1042
    ISSN 0925-7535
    DOI 10.1016/j.ssci.2020.104987
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Reducing risk of infection – The COVID-19 queueing game

    Perlman, Yael / Yechiali, Uri

    Safety Science

    2020  Volume 132, Page(s) 104987

    Keywords Public Health, Environmental and Occupational Health ; Safety Research ; Safety, Risk, Reliability and Quality ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 1074634-1
    ISSN 1879-1042 ; 0925-7535
    ISSN (online) 1879-1042
    ISSN 0925-7535
    DOI 10.1016/j.ssci.2020.104987
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Reducing risk of infection – The COVID-19 queueing game

    Perlman, Yael / Yechiali, Uri

    Saf. Sci.

    Abstract: ... infected while queueing outside the store, while shopping, and while checking out with a cashier. The risk ... to minimize the risk of infection. In the first model, store’ management chooses the number of cashiers ... The COVID-19 pandemic has forced numerous businesses such as department stores and supermarkets ...

    Abstract The COVID-19 pandemic has forced numerous businesses such as department stores and supermarkets to limit the number of shoppers inside the store at any given time to minimize infection rates. We construct and analyze two models designed to optimize queue sizes and customer waiting times to ensure safety. In both models, customers arrive randomly at the store and, after receiving permission to enter, pass through two service phases: shopping and payment. Each customer spends a random period of time shopping (first phase) and then proceeds to the payment area of the store (second phase) where cashiers are assigned to serve customers. We propose a novel approach by which to calculate the risk of a customer being infected while queueing outside the store, while shopping, and while checking out with a cashier. The risk is proportional to the second factorial moment of the number of customers occupying the space in each phase of the shopping route. We derive equilibrium strategies for a Stackelberg game in which the authority acts as a leader who first chooses the maximum number of customers allowed inside the store to minimize the risk of infection. In the first model, store’ management chooses the number of cashiers to provide to minimize its operational costs and its customers’ implied waiting costs based on the number allowed in the store. In the second model, the store partitions its total space into two separate areas – one for shoppers and one for the cashiers and payers – to increase cashiers’ safety. Our findings and analysis are useful and applicable for authorities and businesses alike in their efforts to protect both customers and employees while reducing associated costs.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #741494
    Database COVID19

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