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ERIC Number: ED176773
Record Type: RIE
Publication Date: 1979
Pages: 75
Abstractor: N/A
Reference Count: 0
Approaches to Forecasting Demands for Library Network Services. Report No. 10.
Kang, Jong Hoa
The problem of forecasting monthly demands for library network services is considered in terms of using forecasts as inputs to policy analysis models, and in terms of using forecasts to aid in the making of budgeting and staffing decisions. Box-Jenkins time-series methodology, adaptive filtering, and regression approaches are examined and compared within a real context of forecasting demands for interlibrary loan services within the Illinois Library and Information Network (ILLINET). The evaluation of each forecasting method utilizes data for total ILLINET interlibrary loan demands. Developed as a result of the method comparisons, a set of interactive computer programs are listed which will allow the application of forecasting methods by a person who is not an expert in forecasting methodologies or in use of the computer. These programs include data entry, parameter estimation, and production of forecasting reports, and the design of each is briefly summarized. It is concluded that regression methods are most accurate and easiest to apply, and that improvements in forecasting accuracy can be achieved by using a fading memory method. Tables, equations, and a list of references are provided. (FM)
Publication Type: Numerical/Quantitative Data; Dissertations/Theses
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers: Illinois; User Demand
Note: Master's Thesis, University of Illinois at Urbana-Champaign; Report No. 10 in the series A Mathematical Model of the Illinois Interlibrary Loan Network; For related documents, see ED 134 201, ED 160 054, ED 163 931, and IR 007 759