{"title":"An ARIMA model for the forecasting of healthcare waste generation in the Garhwal region of Uttarakhand, India","authors":"Ankur Chauhan, Amol Singh","doi":"10.1504/IJSOI.2017.086587","DOIUrl":null,"url":null,"abstract":"This study has been carried out to analyse and forecast the quantities of healthcare waste generated from the hospitals of Garhwal region of Uttarakhand, India. In this study, a suitable autoregressive integrated moving average (ARIMA) model has been developed, on the basis of different statistical parameters, for the forecasting of healthcare waste. The analysis of results on the basis of the statistical parameters such as adjusted R-square value, mean square error and mean absolute percentage error; the AR(1)MA(1) model has been found as the best ARIMA model for the forecasting of healthcare waste generation. The daily data of healthcare waste generation has been used to develop the ARIMA model in this study. The ARIMA model developed in this study would help the waste disposal firm to plan its waste collection and disposal strategy-related decisions in future.","PeriodicalId":35046,"journal":{"name":"International Journal of Services Operations and Informatics","volume":"8 1","pages":"352"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJSOI.2017.086587","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Services Operations and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSOI.2017.086587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 15
Abstract
This study has been carried out to analyse and forecast the quantities of healthcare waste generated from the hospitals of Garhwal region of Uttarakhand, India. In this study, a suitable autoregressive integrated moving average (ARIMA) model has been developed, on the basis of different statistical parameters, for the forecasting of healthcare waste. The analysis of results on the basis of the statistical parameters such as adjusted R-square value, mean square error and mean absolute percentage error; the AR(1)MA(1) model has been found as the best ARIMA model for the forecasting of healthcare waste generation. The daily data of healthcare waste generation has been used to develop the ARIMA model in this study. The ARIMA model developed in this study would help the waste disposal firm to plan its waste collection and disposal strategy-related decisions in future.
期刊介绍：
The advances in distributed computing and networks make it possible to link people, heterogeneous service providers and physically isolated services efficiently and cost-effectively. As the economic dynamics and the complexity of service operations continue to increase, it becomes a critical challenge to leverage information technology in achieving world-class quality and productivity in the production and delivery of physical goods and services. The IJSOI, a fully refereed journal, provides the primary forum for both academic and industry researchers and practitioners to propose and foster discussion on state-of-the-art research and development in the areas of service operations and the role of informatics towards improving their efficiency and competitiveness.
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