Browsing by Author "Gönül, M. S."

Now showing 1 - 8 of 8

Open Access
Antecedents and effects of trust in forecasting advice
(Elsevier, 2013) Goodwin, P.; Gönül, M. S.; Önkal D.
Forecasting support systems (FSSs) have little value if users distrust the information and advice that they offer. Two experiments were used to investigate: (i) factors that influence the levels of users’ stated trust in advice provided by an FSS, when this advice is provided in the form of interval forecasts, (ii) the extent to which stated trust is associated with users’ modifications of the provided forecasts, and (iii) the consequences of these modifications for the calibration of the interval forecasts. Stated trust was influenced by the levels of noise in time series and whether a trend was present but was unaffected by the presence or absence of point forecasts. It was also higher when the intervals were framed as ‘best-case/worst-case’ forecasts and when the FSS provided explanations. Absence of trust was associated with a tendency to narrow the provided prediction intervals, which reduced their calibration.
Open Access
Decision analysis in Turkey
(INFORMS, 2014-05) Gönül, M. S.; Soyer, E.; Önkal, D.
Open Access
Decision making and the price setting newsvendor: experimental evidence
(Blackwell Publishing Ltd, 2016) Kocabıyıkoğlu, A.; Göğüş, C. I.; Gönül, M. S.
We present an experimental study of the price-setting newsvendor problem, which extends the traditional framework by allowing the decision maker to determine both the selling price and the order quantity of a given item. We compare behavior under this model with two benchmark conditions where subjects have a single decision to make (price or quantity). We observe that subjects deviate from the theoretical benchmarks when they are tasked with a single decision. They also exhibit anchoring behavior, where their anchor is the expected demand when quantity is the decision variable and is the initial inventory level when price is the decision variable. When decision makers set quantity and price concurrently, we observe no significant difference between the normative (i.e., expected profit-maximizing) prices and the decision makers' price choices. Quantity decisions move further from the normative benchmarks (compared to when subjects have a single decision to make) when the ratio of cost to price is less than half. When this ratio is reversed, there is no significant difference between order levels in single- and multi-task settings. In the multidecision framework, we also observe a tendency to match orders and expected demand levels, which subjects can control using prices.
Open Access
The effects of structural characteristics of explanations on use of a DSS
(Elsevier, 2006) Gönül, M. S.; Önkal D.; Lawrence, M.
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.
Open Access
Effects of trend strength and direction on performance and consistency in judgmental exchange rate forecasting
(Elsevier, 2013) Thomson, M. E.; Pollock, A. C.; Gönül, M. S.; Önkal D.
Using real financial data, this study examines the influence of trend direction and strength on judgmental exchange rate forecasting performance and consistency. Participants generated forecasts for each of 20 series. Half of the participants also answered two additional questions regarding their perceptions about the strength and direction of the trend present in each of the series under consideration. The performance on ascending trends was found to be superior to that on descending trends, and the performance on intermediate trends was found to be superior to that on strong trends. Furthermore, the group whose attention was drawn to the direction and strength of each trend via the additional questions performed better on some aspects of the task than did their “no-additional questions” counterparts. Consistency was generally poor, with ascending trends being perceived as being stronger than descending trends. The results are discussed in terms of their implications for the use and design of forecasting support systems.
Open Access
Judgmental adjustments of previously adjusted forecasts
(Wiley-Blackwell Publishing, 2008) Önkal D.; Gönül, M. S.; Lawrence, M.
Forecasts are important components of information systems. They provide a means for knowledge sharing and thus have significant decision-making impact. In many organizations, it is quite common for forecast users to receive predictions that have previously been adjusted by providers or other users of forecasts. Current work investigates some of the factors that may influence the size and propensity of further adjustments on already-adjusted forecasts. Two studies are reported that focus on the potential effects of adjustment framing (Study 1) and the availability of explanations and/or original forecasts alongside the adjusted forecasts (Study 2). Study 1 provides evidence that the interval forecasts that are labeled as "adjusted" are modified less than the so-called "original/unadjusted" predictions. Study 2 suggests that the provision of original forecasts and the presence of explanations accompanying the adjusted forecasts serve as significant factors shaping the size and propensity of further modifications. Findings of both studies highlight the importance of forecasting format and user perceptions with critical organizational repercussions.
Open Access
Scenarios as channels of forecast advice
(Elsevier, 2013-05) Önkal, D.; Sayım, K. Z.; Gönül, M. S.
Today's business environment provides tougher competition than ever before, stressing the important role played by information and forecasts in decision-making. The scenario method has been popular for focused organizational learning, decision making and strategic thinking in business contexts, and yet, its use in communicating forecast information and advice has received little research attention. This is surprising since scenarios may provide valuable tools for communication between forecast providers and users in organizations, offering efficient platforms for information exchange via structured storylines of plausible futures. In this paper, we aim to explore the effectiveness of using scenarios as channels of forecast advice. An experimental study is designed to investigate the effects of providing scenarios as forecast advice on individual and group-based judgmental predictions. Participants are given time series information and model forecasts, along with (i) best-case, (ii) worst-case, (iii) both, or (iv) no scenarios. Different forecasting formats are used (i.e., point forecast, best-case forecast, worst-case forecast, and surprise probability), and both individual predictions and consensus forecasts are requested. Forecasts made with and without scenarios are compared for each of these formats to explore the potential effects of providing scenarios as forecast advice. In addition, group effects are investigated via comparisons of composite versus consensus predictions. The paper concludes with a discussion of results and implications for future research on scenario use in forecasting.
Open Access
Why should i trust your forecasts?
(International Institute of Forecasters, 2012) Gönül, M. S.; Önkal D.; Goodwin, P.
Preview Mistrust is a serious problem for organizations. So much has been written about functional biases and misaligned incentives that one wonders how anyone can trust a forecast provider. Well, now we have some studies that shed new light on the factors that can build or impede trust in forecasting. In this article, Sinan, Dilek, and Paul discuss the latest research findings on the steps you can take to improve trust and reduce dysfunctional behavior in the forecast function. Their conclusions offer a check list of steps to eliminate or at least minimize the element of mistrust in your forecasts.