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dc.degree.departmentRestaurant, Hotel, and Instititutional Managementen_US
dc.rights.availabilityUnrestricted.
dc.creatorRyu, Kisang
dc.date.accessioned2016-11-14T23:13:52Z
dc.date.available2011-02-18T19:40:38Z
dc.date.available2016-11-14T23:13:52Z
dc.date.issued2002-05
dc.identifier.urihttp://hdl.handle.net/2346/11601en_US
dc.description.abstractInstitutional foodservice organizations require managers to keep tight control of costs. In the institutional foodservice industry, the task of forecasting is usually done by the foodservice managers. Having a good forecast of meal counts helps managers to plan and control. Managers recognize the need for better forecasting methods and the use of personal computers. Nevertheless, currently, many operation managers in foodservice frequently predict future customer demand basing on their judgments on experience or manually-generated naive models. According to Messersmith and Miller (1991), even simple quantitative techniques, such as naive methods, outperform the intuitive assessments of experts. However, Miller, McCahon, and Bloss (1991) discovered that manually generated naive models produced less accurate forecasts than did computerized mathematical models. Messersmith and Miller (1991) also indicated that mathematical forecasting models could provide users with a critical advantage over non-users in a competitive environment. Efficient computerized mathematical forecasting methods will help institutional foodservice management control or even reduce costs in addition to increased customer satisfaction.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherTexas Tech Universityen_US
dc.subjectFood serviceen_US
dc.subjectTexas Tech Universityen_US
dc.subjectUniversities and collegesen_US
dc.titleThe evaluation of forecasting methods at an institutional foodservice dining facility
dc.typeThesis


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