{"title":"使用定量技术预测商用车产量","authors":"Badri Toppur, T. Thomas","doi":"10.5709/ce.1897-9254.496","DOIUrl":null,"url":null,"abstract":"Firms selling commercial vehicles often face difficulties due to recessions in the globalized economy. Manufacturers are keen to anticipate demand in future quarters to optimize their production schedules. In this study, commercial vehicle production data from a leading Indian automotive manufacturer were analyzed us- ing moving averages, exponential smoothing, seasonal decomposition and autoregressive integrated moving average (ARIMA) models with the goal of forecasting. The results reveal that the ARIMA (0,1,1) model effectively predicts the sectoral downturn coinciding with the global financial crisis of 2008. As life returns to normal after the financial crisis caused by COVID-19, such models may be used to strategically move past the disruption.","PeriodicalId":44824,"journal":{"name":"Contemporary Economics","volume":"16 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting Commercial Vehicle Production Using Quantitative Techniques\",\"authors\":\"Badri Toppur, T. Thomas\",\"doi\":\"10.5709/ce.1897-9254.496\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Firms selling commercial vehicles often face difficulties due to recessions in the globalized economy. Manufacturers are keen to anticipate demand in future quarters to optimize their production schedules. In this study, commercial vehicle production data from a leading Indian automotive manufacturer were analyzed us- ing moving averages, exponential smoothing, seasonal decomposition and autoregressive integrated moving average (ARIMA) models with the goal of forecasting. The results reveal that the ARIMA (0,1,1) model effectively predicts the sectoral downturn coinciding with the global financial crisis of 2008. As life returns to normal after the financial crisis caused by COVID-19, such models may be used to strategically move past the disruption.\",\"PeriodicalId\":44824,\"journal\":{\"name\":\"Contemporary Economics\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Economics\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.5709/ce.1897-9254.496\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Economics","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.5709/ce.1897-9254.496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Forecasting Commercial Vehicle Production Using Quantitative Techniques
Firms selling commercial vehicles often face difficulties due to recessions in the globalized economy. Manufacturers are keen to anticipate demand in future quarters to optimize their production schedules. In this study, commercial vehicle production data from a leading Indian automotive manufacturer were analyzed us- ing moving averages, exponential smoothing, seasonal decomposition and autoregressive integrated moving average (ARIMA) models with the goal of forecasting. The results reveal that the ARIMA (0,1,1) model effectively predicts the sectoral downturn coinciding with the global financial crisis of 2008. As life returns to normal after the financial crisis caused by COVID-19, such models may be used to strategically move past the disruption.
期刊介绍：
The mission of the Contemporary Economics is to publish advanced theoretical and empirical research in economics, finance, accounting and management with the noticeable contribution and impact to the development of those disciplines and preferably with practice relevancies. All entirety of methods is desirable, including a falsification of conventional understanding, theory building through inductive or qualitative research, first empirical testing of a theory, meta-analysis with theoretical implications, constructive replication that clarifies the boundaries or range of a theory for theoretical research as well as qualitative, quantitative, field, laboratory, meta-analytic, and combination for an empirical research. This clear priority for comprehensive manuscripts containing a methodology-based theoretical and empirical research with implications and recommendations for policymaking does not exclude manuscripts entirely focused on theory or methodology. Manuscripts that raise significant, actual topics of international relevance will be highly appreciated. The interdisciplinary approach including – besides economic, financial, accounting or managerial –also other aspects, is welcomed.
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