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.     

基于应用扩展和网络论坛的领先用户识别方法研究

回顾了领先用户识别的电话网络法,分析了它的应用局限性。电话网络法只适合领先用户相对分散的情况下,企业需要找到部分领先用户为企业新产品概念开发贡献产品创意。但当领先用户的应用扩展到产品推广之后,为了使领先用户在市场中的领导地位能影响普通用户,并进一步带来更好的新产品绩效,需要找到目标群体中的全部领先用户。网络论坛的设立使得领先用户在产品开发论坛中相对集中,从而问卷法识别领先用户的效率能够得到保证。确立了识别领先用户的三大指标:市场或技术趋势、客户收益、信息复杂性。用统计学与概率论的方法建立了领先用户的识别模型。     

基于竞争型制造商创新投入的零售商需求预测信息共享研究

本文考虑两个制造商的竞争,从创新投入的视角构建零售商需求预测信息共享模型,运用贝叶斯统计理论和斯坦伯格博弈方法,探讨了制造商之间的竞争和其开展的成本降低创新对零售商需求预测信息共享的影响。研究发现：（1）制造商的创新投入决策受竞争对手和零售商信息共享的双重影响。（2）由于两个竞争型制造商进行成本降低创新,存在一定的条件使得零售商可以通过免费共享需求信息而获利。（3）当制造商们的创新能力较强时,供应链能够自发达到完全信息共享状态。当制造商们的创新能力较弱时,零售商的信息共享价值为负,竞争型制造商可以通过支付信息共享费用来激励零售商共享需求预测信息。制造商支付的信息共享费用与创新能力、上游竞争强度、预测准确性和随机需求波动性正相关。本文的研究克服了Shang等（2016）关于上游竞争型供应链中零售商信息共享研究中未考虑制造商创新的不足,并进一步探讨了上游竞争型供应链中的信息共享激励机制。     

Accuracy in the long run—Where are we now

Long-term forecasting must be viewed as informative speculation about the future. It should be credited with relatively little scientific authenticity. At the present stage of theory and data, no magic methods can be expected to overcome the problem of satisfactory forecasting. Improvement, however, is certainly not just a question of putting more and more variables and more and more numbers into a computer. Methods which indicate how to cushion against uncertainty and methods which bring a greater awareness of options for the future are essential if we are to gain greater control over events. The hazy images of the long-term future which are generated by scenario and other forms of analysis form the guidelines within which short and especially medium-term choices must be made. But in the end we must recognise the inherent limitations of forecasting and forecasting methods and think of forecasting not so much as a method of prediction but as a contribution to tackling the future in a more integrated sense.     

Forecasting stock market prices in a thin security market

Stock market efficiency is a crucial concept when forecasting of future stock price behaviour is discussed. In the literature, a distinction is made between three potential levels of efficiency. Under a weak form of efficiency, information on historical price movements is of no value for predicting the future price development. Similarly, a semi-strong form of efficiency holds that no publicly available information can be successfully used in the prediction of prices. And finally, a strong form of efficiency means that the share prices fully reflect all relevant information including data not yet publicly available. Stock market efficiency has been extensively studied in different countries. On a thin security market, like in the Helsinki Stock Exchange, many anomalies and deviations from market efficiency have been obtained. This paper aims to contribute to that discussion. It is shown in the paper that both the monthly and quarterly stock market prices (the general stock market index) can be adequately forecasted using either univariate time-series analysis or multivariate econometric modelling. The univariate ARIMA-models seem to be slightly outperformed by the econometric models. It is further shown that the forecasting accuracy of the models can be improved when time-series and econometric forecasts are combined into a composite forecast. The empirical results obtained indicate an absence of efficiency on the Finnish security market.     

Scenarios, past, present and future.

A key point in considering strategic planning is that it is not forecasting. The future is unpredictable and is not a product of the past. This low opinion of forecasting has gained in influence recently. But such an approach creates a dilemma for the strategic planner. He needs to take into account potential future forces--but he can only do this with inadequate means. Forecasting methods, however, can suggest trends and it is possible to reduce the number of possible futures to a manageable number. This is, in effect, creating scenarios. The concept of using alternative scenarios in planning was popularized some 20 years back. The proviso was made that they should not be interpreted as forecasts. The methods have proved highly flexible and include the consensus technique, the iteration-through-synopsis technique, and the cross-impact method. Various studies using one or more of these have been implemented, perhaps the best known being by Meadows and by Mesarovic. These have been based on the so-called 'hard' method, using computers. 'Soft' methods are based more on the mind and use psychology and sociology, the most familiar being the Delphi method. A somewhat more sophisticated version is Cross-Impact Analysis.     

A note on supply risk and inventory outsourcing

To fully accommodate the correlations between semiconductor product demands and external information such as the end market trends or regional economy growth, a linear dynamic system is introduced in this paper to improve the forecasting performance in supply chain operations. In conjunction with the generic Gaussian noise assumptions, the proposed state-space model leads to an expectation-maximisation (EM) algorithm to estimate model parameters and predict production demands. When the dimension of external indicators is high, principal component analysis (PCA) is applied to reduce the model order and corresponding computational complexity without loss of substantial statistical information. Experimental study on some real electronic products demonstrates that this forecasting methodology produces more accurate predictions than other conventional approaches, which thereby helps improve the production planning and the quality of semiconductor supply chain management.     

小波包与混沌集成的股票市场预测新方法

基于小波包变换和混沌理论提出了一种股票市场建模及其预测的新方法,既能刻划时间序列的规律,又能捕捉混沌状态的特征.首先,应用小波包变换对上证综指和深证成指日收益率序列进行三层分解,分别得到第三层从低频到高频八个频率成分的时序,并在此基础上作进一步分析,结果表明中国股市存在混沌特性;然后,应用混沌理论分别建立从低频到高频八个时序的预测模型,分别对八个时序进行预测;最后,基于小波包理论对混沌模型预测的结果予以重构,实现对原始收益率序列的预测.与现有方法比较,结果表明该方法具有较高的精度,有极大的应用范围.     

结构突变下的高维汇率资产时变投资组合预测研究

金融市场存在结构突变现象是发生金融风险传染的关键所在,而风险传染又是投资组合研究中亟需解决的难点。本文以9种国际主要货币对美元汇率为研究对象,先构建隐马尔科夫模型来对汇率资产进行结构突变预测,并基于结构突变刻画的结果,构建动态R-Vine Copula模型来预测汇率资产的风险传染关系;最后,基于结构突变与风险传染的研究结果,筛选出适合的组合汇率资产,构建时变投资组合预测模型。实证结果表明：HMM模型能够有效地刻画出汇率资产中的结构突变;动态R-Vine Copula模型能够更加有效地刻画出汇率资产间的风险传染关系;基于结构突变与风险传染关系下的动态投资组合预测模型,具有降低投资组合风险与提升投资组合预测收益的优越性,能够为金融风险管理和投资组合研究提供模型参考。     

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.     

剔除非管理性因素影响的我国集成电路产业技术创新效率研究:基于广义三阶段 DEA 和 Tobit 模型

基于集成电路产业技术创新过程中所具有的特点,并考虑非管理性因素对技术创新效率产生的影响,运用广义三阶段DEA模型评价和比较我国集成电路产业整体及产业链各环节技术创新效率及差异,并进行投入要素的投影分析,在此基础上借助Tobit回归模型对技术创新效率的影响因素进行研究。结果表明,我国集成电路产业整体技术创新效率呈上升态势,而产业链各环节除封测业因技术换挡而呈现“N”型发展态势外,其余环节与产业整体情况相同;产业链各环节技术创新的投入冗余情况则各有不同,但制造业和装备业是投入冗余较为集中的环节;产业结构升级加速使得当前企业规模与技术创新效率呈现出负相关性,而企业R&D人员投入和人才密集性对技术创新效率分别存在消极和积极影响,可见效率提升的关键在于R&D人员的“质”而非“量”,政府支持程度则对技术创新效率有明显积极作用,但企业R&D经费投入对技术创新效率的影响并不显著,在当前产业发展阶段,高投入并不一定会产生高效率。     

二重趋势性季节型电力负荷预测组合灰色神经网络模型

对于具有增长和波动二重趋势性的季节型电力负荷,首次提出了季节型负荷预测的组合优化灰色神经网络模型,研究了同时考虑两种(非线性)趋势的复杂季节型负荷预测问题,说明了此优化模型分别优于两种单一发展趋势负荷预测模型,给出了电力负荷预测的应用实例,为季节型电力负荷预测提供了一种新的、有效的方法。     

Impact of Reseller's Forecasting Accuracy on Channel Member Performance

This article studies a three‐layer supply chain where a manufacturer sells a product through a reseller who then relies on its own salesperson to sell to the end market. The reseller has superior capability in demand forecasting relative to the manufacturer. We explore the main trade‐offs between the risk‐reduction effect and the information–asymmetry–aggravation effect of the improved forecasting accuracy. We show that under the optimal wholesale price contract, both the manufacturer and the reseller are always better off as the reseller's forecasting accuracy improves. Nevertheless, under the menu of two‐part tariffs, the manufacturer prefers the reseller to be either uninformed or perfectly informed about the market condition. We further find that the improved forecasting accuracy is beneficial for the reseller if its current forecasting system is either very poor or very good.     

基于滚动时间窗的碳市场价格分解集成预测研究

提高碳市场价格预测准确性对于交易风险监测以及碳市场平稳发展具有重要价值。针对复杂的、非线性碳市场价格数据的短期预测误差偏大、分解过程易产生数据泄露问题，提出了基于滚动时间窗的SSA-SVR分解集成预测框架。首先，选取时间窗数据，继而借助奇异谱分析将时间窗内碳价序列分解重构为高、低频序列；然后，使用支持向量回归方法对高、低频序列分别进行预测；最后，加和集成预测结果，得到下一时刻的碳市场价格预测值。通过不断更新时间窗的数据内容，动态执行“分解-预测-集成”过程，实现碳市场价格的实时预测。研究结果表明，本文所提出框架表现出优异且稳定的预测性能，在碳市场价格预测研究中具有良好的适用性和有效性。     

An appreciation of alternative sales forecasting models: Recent techniques based on historical data

The subject of statistical sales forecasting has recently been brought to prominence as a major area of management decision-making by the growth of a substantive literature and the establishment of several research groups to investigate the building of forecasting models. Whilst a lot of attention has been focused on the relatively newer disciplines of technological forecasting and multiple-equation model building of macro-economic systems, statistical sales forecasting methods have also been subject to considerable development and a number of radically new techniques have emerged. The authors believe that it is timely to review the current ‘state of the art’ of sales forecasting methodology. This study examines a wide range of models in use although it is not intended as a comprehensive guide.     

Case studies of technology roadmapping in mining

Mining is a long established art with legacy processes and institutional structures that face rapidly changing technological environments. The perception is that technology planning and forecasting receives priority attention only as far as they may be linked to making production tonnage in the short term, thus giving the impression that new technology may be introduced without developing a culture and operational requirements that influence successful implementation of new technologies. With depleting ore grades of existing mines, and the prevailing global financial crisis making it prohibitive to develop richer sources, mining is considered to be short-term risk averse and this accentuates a more conservative approach towards technology planning and forecasting. Based on surveys and interviews with practicing miners, this paper discusses three case studies on the practice of technology planning and forecasting in mining firms. It is evident that technology planning and forecasting, and particularly the use of the roadmapping approach, is not a ‘culture’ common to mining firms.     

Transportation after deregulation

For 40 years U.S. airlines operated under tight government control. Deregulation has put them in competition in an open market where they have had to become more efficient to compete. They have also had to bear the consequences of the—until the recent levelling off—rocketing price of fuel, a world-wide recession and a damaging strike of traffic controllers. However, services have increased, fares have stabilized and been pared down and adjusted to the market. The authors trace the strategic trends consequent on deregulation, the necessity for a change in company values and the importance of technological innovation.     

Planning for a university,using interactive forecasting

The benefits of programme review, forward planning and control have been demonstrated at the university-wide level. Within a faculty or department, there is also a clear need for developing and using planning methods which are rationally based and forward looking if appropriate responses to changing social and academic trends are to be made. This paper delineates a number of planning and control variables encountered at the faculty or departmental level, describes the development and use of a computer-based interactive forecasting model, and discusses the advantages and limitations of such models in planning a faculty's progress toward its goals.     

香港银行业开办人民币业务的风险评估

香港市场上人民币流通的规模变化,对于人民币业务开办的风险评估结论具有明显的影响。在渐进式的离岸业务推进模式下,当前可能会在特定的业务领域形成监管的模糊地带,但是总体上不会形成明显的风险隐患。通常而言离岸业务对于信息披露的要求较低,因而应当加强内地与香港的反洗钱合作。从当前的市场环境判断,当前香港市场上不会出现大规模的人民币对港币的替代。香港离岸的个人人民币业务的开展会对在岸的人民币业务形成一定的竞争,这种竞争压力随着香港离岸市场业务范围的扩大而继续增大。随着香港人民币离岸市场规模的不断扩大和业务范围的拓展,离岸人民币市场对于内地金融管制的冲击力会提高。从长期来看,随着人民币在香港流通规模的扩大,应及早研究人民币流通扩大背景下香港的金融体系改革战略问题。     

Forecasting the future business environment— The state of the art

The future business environment, from the standpoint of the Corporation, encompasses both internal and external factors. These factors are also interrelated; thus the task of forecasting needs to be undertaken having in mind a multitude of elements which may interact. The author argues that, given this complex environment; corporations should support the planning operation if it is to develop and if they are to benefit from it. This support includes being open to recommendations made, for without it a planning group cannot function and the forecasting element loses momentum.