Business-Driven Support for Infrastructure as a Service Capacity Management Through System Dynamics Simulations

Fenner, Germano; Lima, Alberto Sampaio; Souza, José Neuman de; Moura, José Fábio Paulino de; Bezerra, Tarcio R.

doi:10.1109/tnsm.2020.3044892

Cited by 2 publications

(2 citation statements)

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“…(2018) propose weighted average and priority allocation rules, which provide methods for solving capacity allocation under limited capacity. Later, Fenner et al . (2021) propose a business-driven simulation model based on the concepts of system dynamics (SD), balanced scorecard (BSC) and analytic hierarchy process (AHP) in order to solve the capacity management decisions of IaaS suppliers in real operation scenarios, which provides important decision support for capacity management.…”

Section: Literature Reviewmentioning

confidence: 96%

“…In addition, Janakiraman et al (2018) propose weighted average and priority allocation rules, which provide methods for solving capacity allocation under limited capacity. Later, Fenner et al (2021) propose a businessdriven simulation model based on the concepts of system dynamics (SD), balanced scorecard (BSC) and analytic hierarchy process (AHP) in order to solve the capacity management decisions of IaaS suppliers in real operation scenarios, which provides important decision support for capacity management. At present, most of the literature mainly considers how to adjust production capacity to hedge the changes in market demand, but there is little study on the capacity allocation of catering merchants in different stages under different delivery modes.…”

Section: Literature Reviewmentioning

confidence: 99%

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The optimal capacity decision of the catering merchant in omnichannel – service, production and delivery capacity

Zhan

Jiang

Wang

2023

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PurposeOmnichannel sales have provided new impetus for the development of catering merchants. The authors thus focus on how catering merchants should manage capacities at the ordering, production and delivery stages to meet customers’ needs in different channels under third-party platform delivery and merchant self-delivery. This is of great significance for the development of the omnichannel catering industry.Design/methodology/approachThis paper formulates the capacity decisions of omnichannel catering merchants under the third-party platform delivery and merchant self-delivery mode. The authors mainly use queuing theory to analyze the queuing behavior of online and offline customers, and the impact of waiting time on customer shopping behavior. In addition, the authors also characterize the merchant’s capacity by the rate in queuing model.FindingsThe authors find that capacities at ordering stage and food production stage are composed of base capacities and safety capacities, but the delivery capacities only have the latter. And in the self-delivery mode, merchants can develop higher safety capacities by charging delivery fees. The authors prove that regardless of the delivery mode, omnichannel sales can bring higher profits to merchants by integrating demand.Originality/valueThe authors focus on analyzing the capacity management of omnichannel catering merchants at the ordering, production and delivery stages. And the authors also add the delivery process into the omnichannel for analysis, so as to solve the problem of capacity decision-making under different delivery modes. The management of delivery capacity and its impact on other stages’ capacities are not covered in other literature studies, which is one of the main innovations of this paper.

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Section: Literature Reviewmentioning

confidence: 96%

Section: Literature Reviewmentioning

confidence: 99%