Advances in Business and Management Forecasting: Advances in Business and Management Forecasting
Autor Kenneth D. Lawrence, Michael D. Geurtsen Limba Engleză Hardback – 24 ian 2008
The topics will normally include sales and marketing, forecasting, new product forecasting, judgmentally-based forecasting, the application of surveys to forecasting, forecasting for strategic business decisions, improvements in forecasting accuracy, and sales response models. It is both the hope and direction of the editorial board to stimulate the interest of the practitioners of forecasting to methods and techniques that are relevant.
In Volume 5, there are sections devoted to financial applications of forecasting, as well as demand forecasting. There is, also, a section on general business applications of forecasting, as well as one on forecasting methodologies.
*Presents state-of-the-art studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making.
*Publishes annually
Toate formatele și edițiile | Preț | Express |
---|---|---|
Hardback (2) | 764.89 lei 6-8 săpt. | |
Emerald Publishing – 24 ian 2008 | 764.89 lei 6-8 săpt. | |
Emerald Publishing – 16 feb 2006 | 817.54 lei 6-8 săpt. |
Preț: 764.89 lei
Preț vechi: 993.37 lei
-23% Nou
Puncte Express: 1147
Preț estimativ în valută:
146.43€ • 152.21$ • 121.41£
146.43€ • 152.21$ • 121.41£
Carte tipărită la comandă
Livrare economică 07-21 februarie 25
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780762314782
ISBN-10: 0762314788
Pagini: 312
Dimensiuni: 152 x 229 x 686 mm
Greutate: 0.56 kg
Editura: Emerald Publishing
Seria Advances in Business and Management Forecasting
ISBN-10: 0762314788
Pagini: 312
Dimensiuni: 152 x 229 x 686 mm
Greutate: 0.56 kg
Editura: Emerald Publishing
Seria Advances in Business and Management Forecasting
Public țintă
Practitioners in business and management forecastingCuprins
Financial Applications
1. The Application of Neural Network Models and Multiple Discriminant Analysis to Forecast Bond Rating Changes, David Caddar (Quinnipac College)
2. The Cross-Listing, Corporate Governance and Operating Performance-Evidence from the Chinese Market, Chen Shaw (University of Rhode Island)
3. Forecasting Option Spreads: The Use of Multiple Listing, Rebecca Abraham (Nova University
4. Forecasting a Competitive Bid Price, Michael D. Geurts (Brigham Young University)
Demand Forecasting
1. Plans, Predictions and Optimal Management of Supply-Distribution Networks, Frenck Waage (University of Massachusetts, Boston)
2. A Goal Programming Model for Hierarchical Forecasting, J. Gaylord May (Wake Forest University), Joanne N. Sulek (North Carolina AT&T State University)
3. A Linear Dynamic System for Demand Forecasting, Feng Zhang (Fairchild Semi Conductor)
4. A Comparison of Methods for Forecasting Intermittent Demand with Increasing or Decreasing Demand Occurrences, Matt Lindsey (University of Texas, Tyler), Pavar (University of North Texas)
Applications of Forecasting
1. Forecasting with Innovation Diffusion Models: A Life Cycle Example in the Telecommunications Industry, John F. Kros (East Carolina University)
2. United Way of America Annual Campaign: Contribution Forecasting by Major Cities, Marion Sobol (SMU) and Eli Snir (SMU)
3. Forecasting Movie Attendance, Michael D. Geurts (Brigham Young University)
4. Forecasting Women’s Fashion for Retail Stores, Michael D. Geurts (Brigham Young University)
Forecasting Methodologies
1. A Unified Approach to Analyzing Non-Symmetric and Symmetric Regression Models, French wage (University of Massachusetts, Boston)
2. Temporarily Aggregate Models to Improve the Accuracy of Seasonal Forecasts, Steven DeLurgio (University of Missouri, Kansas City)
3. Applying Resampling Schemes to Time Series Analysis, Jae J. Lee (SUNY, New Paltz)
4. Forecasting Comparable Units, Ronald Klimberg (St. Joseph’s University), Kenneth D. Lawrence (New Jersey Institute of Technology), and Sheila M. Lawrence (Rutgers University)
5. Forecasting New Products: Robust Re-weighted Regression Methods, Kenneth D. Lawrence (New Jersey Institute of Technology), Sheila M. Lawrence (Rutgers University), and Ronald Klimberg (St. Joseph’s University)
6. Forecasting Using Intelligent Agents, Daniel O’Leary (University of Southern California)
1. The Application of Neural Network Models and Multiple Discriminant Analysis to Forecast Bond Rating Changes, David Caddar (Quinnipac College)
2. The Cross-Listing, Corporate Governance and Operating Performance-Evidence from the Chinese Market, Chen Shaw (University of Rhode Island)
3. Forecasting Option Spreads: The Use of Multiple Listing, Rebecca Abraham (Nova University
4. Forecasting a Competitive Bid Price, Michael D. Geurts (Brigham Young University)
Demand Forecasting
1. Plans, Predictions and Optimal Management of Supply-Distribution Networks, Frenck Waage (University of Massachusetts, Boston)
2. A Goal Programming Model for Hierarchical Forecasting, J. Gaylord May (Wake Forest University), Joanne N. Sulek (North Carolina AT&T State University)
3. A Linear Dynamic System for Demand Forecasting, Feng Zhang (Fairchild Semi Conductor)
4. A Comparison of Methods for Forecasting Intermittent Demand with Increasing or Decreasing Demand Occurrences, Matt Lindsey (University of Texas, Tyler), Pavar (University of North Texas)
Applications of Forecasting
1. Forecasting with Innovation Diffusion Models: A Life Cycle Example in the Telecommunications Industry, John F. Kros (East Carolina University)
2. United Way of America Annual Campaign: Contribution Forecasting by Major Cities, Marion Sobol (SMU) and Eli Snir (SMU)
3. Forecasting Movie Attendance, Michael D. Geurts (Brigham Young University)
4. Forecasting Women’s Fashion for Retail Stores, Michael D. Geurts (Brigham Young University)
Forecasting Methodologies
1. A Unified Approach to Analyzing Non-Symmetric and Symmetric Regression Models, French wage (University of Massachusetts, Boston)
2. Temporarily Aggregate Models to Improve the Accuracy of Seasonal Forecasts, Steven DeLurgio (University of Missouri, Kansas City)
3. Applying Resampling Schemes to Time Series Analysis, Jae J. Lee (SUNY, New Paltz)
4. Forecasting Comparable Units, Ronald Klimberg (St. Joseph’s University), Kenneth D. Lawrence (New Jersey Institute of Technology), and Sheila M. Lawrence (Rutgers University)
5. Forecasting New Products: Robust Re-weighted Regression Methods, Kenneth D. Lawrence (New Jersey Institute of Technology), Sheila M. Lawrence (Rutgers University), and Ronald Klimberg (St. Joseph’s University)
6. Forecasting Using Intelligent Agents, Daniel O’Leary (University of Southern California)