Comments on "Effective Forecasting and Judgemental adjustments: An Empirical Evaluation and Strategies for Improvement in supply-chain planning

Cataloged from PDF version of article.Demand forecasting is a crucial aspect of the planning process in supply-chain companies. The most common approach to forecasting demand in these companies involves the use of a computerized forecasting system to produce initial forecasts and the subsequent judgmental adjustment of these forecasts by the company's demand planners, ostensibly to take into account exceptional circumstances expected over the planning horizon. Making these adjustments can involve considerable management effort and time, but do they improve accuracy, and are some types of adjustment more effective than others? To investigate this, we collected data on more than 60,000 forecasts and outcomes from four supply-chain companies. In three of the companies, on average, judgmental adjustments increased accuracy. However, a detailed analysis revealed that, while the relatively larger adjustments tended to lead to greater average improvements in accuracy, the smaller adjustments often damaged accuracy. In addition, positive adjustments, which involved adjusting the forecast upwards, were much less likely to improve accuracy than negative adjustments. They were also made in the wrong direction more frequently, suggesting a general bias towards optimism. Models were then developed to eradicate such biases. Based on both this statistical analysis and organisational observation, the paper goes on to analyse strategies designed to enhance the effectiveness of judgmental adjustments directly

Effects of feedback on probabilistic forecasts of stock prices

Cataloged from PDF version of article.This paper reports the results of an experiment in stock-price forecasting that investigated the effects of feedback on various dimensions of probability forecasting accuracy. Three types of feedback were used: (1) simple outcome feedback, (2) outcome feedback presented in the task format, and (3) performance feedback in the form of an overall accuracy score in addition to detailed calibration information. While calibration improved for all the feedback groups, forecasters' skill was found to improve only for the task-formated outcome feedback and performance feedback groups (but not for the simple outcome feedback group). Finally, the forecasters in the performance feedback group also improved their mean slope and mean probability scores, an effect not observed in the other feedback groups. It is suggested that, in a dynamic environment like the stock market, probability forecasting offers distinct advantages by providing an important channel of communication between the forecasters and the users of financial information

Towards a pedagogy for critical security studies: politics of migration in the classroom

International Relations (IR) has increasingly paid attention to critical pedagogy. Feminist, post-colonial and poststructuralist IR scholarship, in particular, have long been advancing the discussions about how to create a pluralist and democratic classroom where ‘the others’ of politics can be heard by the students, who can critically reflect upon complex power relations in global politics. Despite its normative position, Critical Security Studies (CSS) has so far refrained from joining this pedagogical conversation. Deriving from the literatures of postcolonial and feminist pedagogical practices, it is argued that an IR scholar in the area of CSS can contribute to the production of a critical political subject in the 'uncomfortable classroom', who reflects on violent practices of security. Three pedagogical methods will be introduced: engaging with the students’ life worlds, revealing the positionality of security knowledge claims, and opening up the class-room to the choices about how the youth’s agency can be performed beyond the classroom. The argument is illustrated through the case of forced migration with specific reference to IR and Politics students’ perceptions of Syrian refugees in Turkey. The article advances the discussions in critical IR pedagogy and encourages CSS scholarship to focus on teaching in accordance with its normative position

Issues in countries of the former Soviet Union as the driving force for female migration to Turkey

The article presents the results and conclusions of a postdoctoral research project entitled "The migration of women from former Soviet Union countries to Turkey: differences, similarities, and outcomes" that has been conducted in Turkey among women from countries of the former Soviet Union with the aim of exploring the issues in these countries as the driving force for female migration to Turkey and also the causes, problems, difficulties, opportunities, prospects, achievements and outcomes of female migrants in the host country. The basis of this scientific project was semi-structured interviews and focus groups among women from former Soviet Union countries in Turkey

Scenario generation and scenario quality using the cone of plausibility

The intelligence analysis domain is a critical area for futures work. Indeed, intelligence analysts’ judgments of security threats are based on considerations of how futures may unfold, and as such play a vital role in informing policy- and decision-making. In this domain, futures are typically considered using qualitative scenario generation techniques such as the cone of plausibility (CoP). We empirically examined the quality of scenarios generated using this technique on five criteria: completeness, context (otherwise known as ‘relevance/pertinence’), plausibility, coherence, and order effects (i.e., ‘transparency’). Participants were trained to use the CoP and then asked to generate scenarios that might follow within six months of the Turkish government banning Syrian refugees from entering the country. On average, participants generated three scenarios, and these could be characterized as baseline, best case, and worst case. All scenarios were significantly more likely to be of high quality on the ‘coherence’ criterion compared to the other criteria. Scenario quality was independent of scenario type. However, scenarios generated first were significantly more likely to be of high quality on the context and order effects criteria compared to those generated afterwards. We discuss the implications of these findings for the use of the CoP as well as other qualitative scenario generation techniques in futures studies

Effects of Task Format on Probabilistic Forecasting of stock prices

Cataloged from PDF version of article.This study aims to explore the differences in various dimensions of forecasting accuracy that may result from the task format used to elicit the probabilistic forecasts. In particular, we examine the effects of using multiple-interval and dichotomous formats on the performance of portfolio managers' probabilistic forecasts of stock prices. Probabilistic forecasts of these experts are compared with those provided by semi-experts comprised of other banking professionals trained in portfolio management, as well as with forecasts provided by a novice group. The results suggest that the task format used to elicit the probabilistic forecasts has a differential impact on the performance of experts, semi-experts, and novices. The implications of these findings for financial forecasting are discussed and directions for future research are given

Information use in supply chain forecasting

Demand forecasting to support supply chain planning is a critical activity, recognized as pivotal in manufacturing and retailing operations where information is shared across functional areas to produce final detailed forecasts. The approach generally encountered is that a baseline statistical forecast is examined in the light of shared information from sales, marketing and logistics and the statistical forecast may then be modified to take these various pieces of information into account. This experimental study explores forecasters’ use of available information when they are faced with the task of adjusting a baseline forecast for a number of retail stock keeping units to take into account a forthcoming promotion. Forecasting demand in advance of promotions carries a particular significance given their intensive supply chain repercussions and financial impact. Both statistical and qualitative information was provided through a forecasting support system typical of those found in practice. Our results show participants responding to the quantity of information made available, though with decreasing scale effects. In addition, various statistical cues (which are themselves extraneous) were illustrated to be particularly important, including the size and timing of the last observed promotion. Overall, participants appeared to use a compensatory strategy when combining information that had either positive or negative implications for the success of the promotions. However, there was a consistent bias towards underestimating the effect of the promotions. These observed biases have important implications for the design of organizational sales and operations planning processes and the forecasting support systems that such processes rely on

The Effects of feedback on judgmental interval predictions

Cataloged from PDF version of article.The majority of studies of probability judgment have found that judgments tend to be overconfident and that the degree of overconfidence is greater the more difficult the task. Further, these effects have been resistant to attempts to ‘debias’ via feedback. We propose that under favourable conditions, provision of appropriate feedback should lead to significant improvements in calibration, and the current study aims to demonstrate this effect. To this end, participants first specified ranges within which the true values of time series would fall with a given probability. After receiving feedback, forecasters constructed intervals for new series, changing their probability values if desired. The series varied systematically in terms of their characteristics including amount of noise, presentation scale, and existence of trend. Results show that forecasts were initially overconfident but improved significantly after feedback. Further, this improvement was not simply due to ‘hedging’, i.e. shifting to very high probability estimates and extremely wide intervals; rather, it seems that calibration improvement was chiefly obtained by forecasters learning to evaluate the extent of the noise in the series. D 2003 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved

Using scenarios to forecast outcomes of a refugee crisis

The Syrian civil war has led to millions of Syrians fleeing the country, and has resulted in a humanitarian crisis. By considering how such socio-political events may unfold, scenarios can lead to informed forecasts that can be used for decision-making. We examined the relationship between scenarios and forecasts in the context of the Syrian refugee crisis. Forty Turkish students trained to use a brainstorming technique generated scenarios that might follow within six months of the Turkish government banning Syrian refugees from entering the country. Participants generated from 3-6 scenarios. Over half were rated as ‘high’ quality in terms of completeness, relevance/pertinence, plausibility, coherence, and transparency (order effects). Scenario quality was unaffected by scenario quantity. Even though no forecasts were requested, participants’ first scenarios contained from 0-17 forecasts. Mean forecast accuracy was 45% and this was unaffected by forecast quantity. Therefore, brainstorming can offer a simple and quick way of generating scenarios and forecasts that can potentially help decision-makers tackle humanitarian crises

Effects of Structural Characteristics of Explanations on Use of a DSS

Cataloged from PDF version of article.Research in the field of expert systems has shown that providing supporting explanations may influence effective use of system developed advice. However, despite many studies showing the less than optimal use made of DSS prepared advice, almost no research has been undertaken to study if the provision of explanations enhances the users' ability to wisely accept DSS advice. This study outlines an experiment to examine the effects of structural characteristics of explanations provided within a forecasting DSS context. In particular, the effects of explanation length (short vs. long) and the conveyed confidence level (weak vs. strong confidence) are examined. Strongly confident and long explanations are found to be more effective in participants' acceptance of interval forecasts. In addition, explanations with higher information value are more effective than those with low information value and thus are persuasive tools in the presentation of advice to users. (c) 2005 Elsevier B.V. All rights reserved