Research Reports from the Department of Operations
Document Type
Thesis
Publication Date
1-1-1980
Abstract
This study investigates the use of time series analysis to improve short-term forecasting of unit volume in a segment of the electrical industry. Various forecasting methods were compared based on their theoretical approaches and effectiveness in reducing forecast error residuals. The Box-Jenkins methodology was identified as the most reliable, outperforming other methods in producing accurate forecasts and parameter estimates for future demand. Statistical tests, including the F-ratio, confirmed the superiority of Box-Jenkins models over competing techniques, which often relied on erroneous assumptions. Key findings highlight the availability of better forecasting models, the potential of Box-Jenkins techniques to optimize forecasting outcomes, and the importance of integrating mathematical models with human judgment for addressing exogenous factors. These results provide valuable insights for improving decision-making processes and forecasting strategies in corporate settings.
Keywords
Operations research, Time-series analysis, Box-Jenkins forecasting, Electric industries--Forecasting, Decision making--Statistical methods
Publication Title
Master's thesis/Technical Memorandums from the Department of Operations, School of Management, Case Western Reserve University
Issue
Technical memorandum no. 468 ; Submitted in partial fulfillment of the requirements for the Degree of Master of Science.
Rights
This work is in the public domain and may be freely downloaded for personal or academic use
Recommended Citation
Cleveland, William C., "Time Series Analysis as an Approach to Short Term Forecasting of Unit Volume in a Part of the Electrical Industry" (1980). Research Reports from the Department of Operations. 599.
https://commons.case.edu/wsom-ops-reports/599