{"title":"Varma模型在销售预测中的应用——以Urmia Gray水泥厂为例","authors":"R. B. Khodaparasti, Samad Moslehi","doi":"10.2478/tjeb-2014-0005","DOIUrl":null,"url":null,"abstract":"Abstract To forecast sales as reliably as possible is one of the most important issues in every business trade. Therefore, in recent years different models have been suggested to deal with this issue. One efficient model is the time series model. This study applies a multivariate time series model to forecast Urmia Gray Cement Factory's sales volume and more importantly, to propose an effective model to be used by other cement factories to predict their sales volume. The two independent variables of costs and revenues and the dependent variable of sales were used in the present study. Results of the study indicated the two independent variables had a positive and direct relationship with sales volume forecast.","PeriodicalId":30596,"journal":{"name":"Timisoara Journal of Economics and Business","volume":"7 1","pages":"101 - 89"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2478/tjeb-2014-0005","citationCount":"4","resultStr":"{\"title\":\"Application of the Varma Model for Sales Forecast: Case of Urmia Gray Cement Factory\",\"authors\":\"R. B. Khodaparasti, Samad Moslehi\",\"doi\":\"10.2478/tjeb-2014-0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract To forecast sales as reliably as possible is one of the most important issues in every business trade. Therefore, in recent years different models have been suggested to deal with this issue. One efficient model is the time series model. This study applies a multivariate time series model to forecast Urmia Gray Cement Factory's sales volume and more importantly, to propose an effective model to be used by other cement factories to predict their sales volume. The two independent variables of costs and revenues and the dependent variable of sales were used in the present study. Results of the study indicated the two independent variables had a positive and direct relationship with sales volume forecast.\",\"PeriodicalId\":30596,\"journal\":{\"name\":\"Timisoara Journal of Economics and Business\",\"volume\":\"7 1\",\"pages\":\"101 - 89\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2478/tjeb-2014-0005\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Timisoara Journal of Economics and Business\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/tjeb-2014-0005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Timisoara Journal of Economics and Business","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/tjeb-2014-0005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of the Varma Model for Sales Forecast: Case of Urmia Gray Cement Factory
Abstract To forecast sales as reliably as possible is one of the most important issues in every business trade. Therefore, in recent years different models have been suggested to deal with this issue. One efficient model is the time series model. This study applies a multivariate time series model to forecast Urmia Gray Cement Factory's sales volume and more importantly, to propose an effective model to be used by other cement factories to predict their sales volume. The two independent variables of costs and revenues and the dependent variable of sales were used in the present study. Results of the study indicated the two independent variables had a positive and direct relationship with sales volume forecast.