Integrating forecasting and planning

Specialization inhibits or prohibits interdisciplinary communication among diverse areas. It contributes to segmentation, which becomes a serious problem when several of those areas should depend upon knowledge which exists in other fields. Forecasting and Planning are two such areas, and it is the purpose of this article to show how planning can benefit by the proper utilization of existing knowledge in the field of forecasting.     

Energy forecasting

A selective and critical review of the state of the art in Energy Forecasting as perceived in assessing future interactions between fuel and feedstock availability for the chemical industry. Models are required of Energy supply and demand and their interaction through the energy market which is subject to national and international policies and conflict and to environmental restrictions and legislation. Significant advances have been made in modelling supply but neither an economic nor a technological approach alone is adequate for modelling demand. In particular there is lack of an adequate model of the industrial sector that reflects the diversity of the production function and adequately incorporates the relationship between technological change, capital investment and energy usage. In the UK the structure of industrial models is over constrained by the aggregation-structure of the national energy statistics. The economic and political forces required to bring about major changes in the capital infra structure are often ignored. There is need to establish logical lower practical limits to energy usage, to develop a system logic structure that provides transfer parameters between various levels and type of aggregation, to develop models which allow probability distributing of variables to be included and to model more effectively the interactions across the boundaries of economics, social and political science, physics, chemistry and mathematics.     

Leader vision formation and forecasting: The effects of forecasting extent,resources, and timeframe

Vision formation, and vision articulation, is held to be a central component of leader performance. Less is known, however, about the variables giving rise to viable visions. In the present effort, the impact of forecasting on vision formation was examined. Study participants were asked to write a speech describing their vision for a new school. Prior to writing this speech, participants were asked to forecast the outcomes of vision implementation. It was found that the extent of forecasting, along with forecasting of temporal and resources considerations, influenced the quality of vision statements. Forecasting was improved when people thought about causes, as opposed to goals, and implications, as opposed to facts. The implications of these findings for understanding leader performance in vision formation are discussed.     

Long-term planning and forecasting in Europe

In January 1968, in the light of the Consultative Assembly's recommendations (Recommendation 516) aimed at giving the Work Programme a forward-looking dimension, the Secretary General invited a group of personalities of world-wide reputation to discuss the role they thought the Council of Europe might play in the field of long-term planning and forecasting. Following this meeting, which was attended, among others, by MM. Pietro Ferraro, Bertrand de Jouvenel, Robert Jungk, Johan Galtung and Professor Karl Steinbuch, a number of proposals were formulated with a view to intensifying co-operation between member countries in the field of future research at both governmental and non-governmental level. Such co-operation was intended, inter alia, to lay a scientific foundation for work concerned with the future which might find a place in the activities of the Council of Europe. The first step in this direction would be to compile an inventory of European bodies engaged in long-term planning and forecasting studies and of their activities (research, seminars, publications, etc.).     

Socio-political forecasting and management information systems

This paper is an attempt to place the forecasting of socio-political variables in the context of actual information needs of industrial companies. Initially discussion is of the effect of socio-political variables upon companies with a review of this significance for decision makers and decision takers. An attempt is then made to categorise existing forecasting techniques in the context of socio-political data whilst regard is paid to the possible effects of socio-political variables on companies. Discussion is then broadened to a consideration of current practice both in the UK and in the USA. Problems implicit in current practice are commented upon and the paper ends with the conclusion that socio-political forecasting is currently significant to many companies and that there is a major potential role for management scientists to play in the development and implementation of appropriate techniques.     

Environmental forecasting and non-profit professional organizations

To undertake any kind of realistic planning activity, it is useful to have a long-term environmental forecast which provides the planner with an overall perspective. The planner will be functioning over the next decade in a very dynamic, complex and challenging political, economic, technological and social environment, and will require very effective planning efforts to cope with such changing environment. This article presents an approach and methodology that a planner could use in his/her organization's planning process. To the best of our knowledge, very few organizations—profit and non-profit oriented—undertake a formal long-term environmental forecast. This article might encourage several planners to examine this area of long range planning in their respective organizations. The long- term environmental forecasting approach presented in this article could be applied by planners in all types of organizations—small or large, profit oriented or non-profit oriented, old or new. This article, however, is based on a study which the authors did for a non-profit organization.     

旅游社会承载力的量测及管理研究

旅游业的发展使旅游目的地的社会特征发生了改变,其变化趋势在很大程度上取决于旅游目的地承载能力。每一个旅游目的地所维持的可接受的旅游发展水平是有一定限度的,如果超过了这个限度,就可能导致当地社会系统的退化。     

From backcasting towards forecasting

A comprehensive study of expected and actual industry growth patterns has suggested that a number of shortcomings in statistical forecasting derive from the role of “backcasting” in widely used methods of estimating probable future adjustment paths. After examining attendant problems and the conceptual bases for ameliorating them, attention in the paper centers on describing a technique for effecting some of these improvements and on analyzing the findings obtained by applying it to 28 series over periods of 60–80 years. Resulting implications for strengthening business and economic forecasting efforts are then discussed.     

Evaluating industrial technological forecasting

This article discusses an approach to the application of technological forecasting among a group of Italian companies. The information upon which the article is based has been obtained from a preliminary study. However, it should prove of interest to manufacturing organizations where similar problems necessitate a constructive approach to forecasting.     

Subjective probability in forecasting

Practical examples of the use of subjective probability in forecasting are rare in the literature, yet in long term forecasting there is a large subjective element in choosing between alternatives. The paper indicates the background to the preparation of such a forecast in the whisky industry and discusses the benefits to be derived from a quantitative assessment with due emphasis on the recognition of the subjective nature of the quantification.     

On Bayesian composite forecasting

Often decision makers have several forecasts of an uncertain and operationally relevant random variable. A rich literature now exists which argues that in this situation the decision maker should consider forming a forecast as a weighted average of each of the individual forecasts. In this paper, composite forecasting is discussed in a Bayesian context. The ability of the user to control the impact of the data on his composite weights is illustrated by an example using expert opinion forecasts of US hog prices.     

Future forecasting with LEAP

A rapidly changing business environment has caused numerous firms to adopt some form of environmental assessment as part of their strategic planning process. Extrapolative techniques and trend analysis are useful when forecasting for the short-term and in comparatively stable environments. Futuristic methodologies are appropriate in turbulent environments with long-term planning requirements. The Likelihood of Events Assessment Process (LEAP), a new method of forecasting developed by the author, is explained in detail using examples from a recent study which used top level life insurance executives to predict the relative likelihood of occurrence of planning dates for a set of events in the socio-political environment of business.     

The futility of forecasting

Long-range forecasting is an integral part of planning, but relying on its accuracy may be a mistake. The landscape is strewn with often wildly inaccurate forecasts. This article studies performances of some forecasts, analyses factors contributing to forecast error, and suggests ways in which management may deal with the uncertainty resulting from faulty forecasting performances.     

人工智能定价对消费者价格公平感知的影响

在GARCH模型框架下,提出过新的双曲GARCH形式(记为HGARCH),不仅与HY-GARCH模型一样可以同时刻画波动的强烈振幅和长记忆衰减两个性质,并且较之HY-GARCH模型,有更简单的条件方差非负约束条件.然而,当时间序列较长时,用单一参数结构不能充分捕捉可能发生的结构变化.为此,提出新的动态混合HGARCH模型(DM-HGARCH),使之可以同时拥有协方差平稳、长记忆和结构变化3个特性.讨论了新模型的弱平稳解存在条件,利用EM算法进行参数估计,并且用蒙特卡罗模拟给出估计在有限样本下的表现.最后将该模型分别用于1995年~2014年中国上证指数和美国标普500指数的日波动率建模.结果表明,在给定样本期间内,动态混合HGARCH模型(DM-HGARCH)对标普500指数有更好的样本内拟合和样本外预测表现.     

The choice of a forecasting model

The major purpose of studies of forecasting accuracy is to help forecasters select the ‘best’ forecasting method. This paper examines accuracy studies in particular that of Makridakis et al. [20] with a view to establishing how they contribute to model choice. It is concluded that they affect the screening that most forecasters go through in selecting a range of methods to analyze—in Bayesian terms they are a major determinant of ‘prior knowledge’. This general conclusion is illustrated in the specific case of the Makridakis Competition (M-Competition). A survey of expert forecasters was made in both the UK and US. The respondents were asked about their familiarity with eight methods of univariate time series forecasting, and their perceived accuracy in three different forecasting situations. The results, similar for both the UK and US, were that the forecasters were relatively familiar with all the techniques included except Holt-Winters and Bayesian. For short horizons Box-Jenkins was seen as most accurate while trend curves was perceived as most suitable for the long horizons. These results are contrasted with those of the M-Competition, and conclusions drawn on how the results of the M-Competition should influence model screening and model choice.     

Business forecasting: the good news and the bad

This paper records a personal view of the wide range of problems, philosophical and pragmatic, currently afflicting ‘business forecasting’. It is based on several years experience in both forecasting methodology development and direct project work with decision makers. The paper is not intended as a review of the current consensus, academic or otherwise but to engage in ‘constructive criticism’. In doing so the author has attempted to keep to the desired structure of ‘decision makers perception’, ‘methodology criticised’ and ‘development suggestions’ but the nature of the problem demands a more interactive approach which has resulted in fuzzy sets rather than distinct clusters of topics.