Qualitative forecasting

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  • The Delphi Method: drawing upon the group’s expertise by getting individual submissions, without the drawback of face to face meetings. The Delphi Method is named after a famous Oracle who prophesied in the ancient Greek city of Delphi. An Oracle (wise person) interceded between men and gods.

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  • This chapter presents the following content: Quantitative approaches to forecasting, components of a time series, measures of forecast accuracy, smoothing methods, trend projection, trend and seasonal components, regression analysis, qualitative approaches.

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  • When you complete this chapter you should be able to: Understand the three time horizons and which models apply for each; explain when to use each of the four qualitative models; apply the naive, moving-average, exponential smoothing, and trend methods; compute three measures of forecast accuracy; develop seasonal indices; conduct a regression and correlation analysis; use a tracking signal.

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  • In this chapter, the following content will be discussed: Demand management, qualitative forecasting methods, simple & weighted moving average forecasts, exponential smoothing, simple linear regression, web-based forecasting.

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  • Chapter 2 "Forecasting", after completing this chapter, you should be able to: Explain the importance of forecasting in organizations, describe the three major approaches to forecasting, use a variety of techniques to make forecasts, measure the accuracy of a forecast over time using various methods,...

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  • In this chapter we will discuss: A forecasting framework, qualitative forecasting methods, time-series forecasting, moving average, exponential smoothing, forecasting errors, advanced time-series forecasting, causal forecasting methods, selecting a forecasting method.

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  • CHAPTER 3 2 PRODUCTION PLANNING Dennis B. Webster Thomas G. Ray Department of Industrial & Manufacturing Systems Engineering Louisiana State University Baton Rouge, Louisiana 32.1 32.2 INTRODUCTION FORECASTING 32.2.1 General Concepts 32.2.2 Qualitative Forecasting 32.2.3 Quantitative Forecasting 32.2.4 Forecasting Error Analysis 32.2.5 Conclusions on Forecasting INVENTORY MODELS 32.3.1 General Discussion 32.3.2 Types of Inventory Models 32.3.3 The Modeling Approach 987 988 988 988 988 993 994 994 994 995 996 32.5 32.3 32.4.

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  • This short text is the output of a desire to produce a helpful additional source for my students and from that, perhaps be of use to other similar students and managers of this subject area. After several years of working with classes on Management Decision Making, the need for a short and focused integrative text was clear to me. There are many excellent texts on both the qualitative and quantitative aspects of decision making, but few which address both.

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  • Further, the average serial correlation in sales changes for our sample firms is .17 which is also approximately consistent with a random walk. The assumption is not critical to most of our results (the major exception is that earnings is a random walk). Even if sales follow an autoregressive process in first differences, accruals still offset the negative serial I correlation in operating cash flow changes induced by inventory and working capital financing policies.

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  • Ensuring the emergency services and the public know where and when it will flood, and how serious the flooding is likely to be, is a complex task. The Environment Agency has increased the number of households and businesses offered a flood warning service. We have also launched a new National Flood Forecasting Centre with the Met Office that will allow us to better predict the scale and timing of flooding events and monitor them as they happen.

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  • Statistics has evolved into a very important discipline that is applied in many fields. In the modern age of computing, both statistical methodology and its applications are expanding greatly. Among the many areas of application, we (Friis and Cher- nick) have direct experience in the use of statistical methods to military problems, space surveillance, experimental design, data validation, forecasting workloads, predicting the cost and duration of insurance claims, quality assurance, the design and analysis of clinical trials, and epidemiologic studies. ...

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  • In comparison with quantitative testing, qualitative testing enables us to gain more insight into “why” participants are feeling a certain way or saying certain things. In qualitative testing, the facilitator is an active participant and is immersed in the subject matter during the testing sessions, so further exploring of ambiguous responses can occur in order to have a clear sense of what the consumer says and means. A primary purpose of qualitative research is to generate suggestions and recommendations.

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  • In this chapter, students will be able to understand: Evaluate the advantages and disadvantages of alternative systems (free floating, fixed, managed float) for the determination of exchange rates; understand the determinants of exchange rates (qualitative); how to forecast (quantitative) exchange rates using models: purchasing power parity, relative purchasing power parity, interest rate parity, an unbiased forward rate.

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