{"title":"Optimizing management of emergency gas leaks: a case study in business analytics","authors":"Charles Hadlock, S. Woolford","doi":"10.1080/2573234X.2019.1638735","DOIUrl":null,"url":null,"abstract":"ABSTRACT Managing the response to reported gas leaks is of significant importance to both utilities and regulators. This paper utilizes a business analytics approach to investigate strategies for managing gas leak response while balancing the objectives of both utilities and regulators. The approach integrates the translation of the business issue into a quantitative framework by which actual gas leak data can be analysed and modelled to measure the performance of different gas leak response strategies. An agent-based simulation model is utilized to provide a decision support platform that translates the analytic results into a visualization tool to assist stakeholders and decision makers in evaluating the impact of different response strategies. The paper highlights both the analytic methods and the related “soft skills” that must be managed in the business analytics context to ensure an outcome that is acceptable for all stakeholders.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"32 1","pages":"88 - 99"},"PeriodicalIF":1.7000,"publicationDate":"2019-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2573234X.2019.1638735","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT Managing the response to reported gas leaks is of significant importance to both utilities and regulators. This paper utilizes a business analytics approach to investigate strategies for managing gas leak response while balancing the objectives of both utilities and regulators. The approach integrates the translation of the business issue into a quantitative framework by which actual gas leak data can be analysed and modelled to measure the performance of different gas leak response strategies. An agent-based simulation model is utilized to provide a decision support platform that translates the analytic results into a visualization tool to assist stakeholders and decision makers in evaluating the impact of different response strategies. The paper highlights both the analytic methods and the related “soft skills” that must be managed in the business analytics context to ensure an outcome that is acceptable for all stakeholders.