A quantitative investigation of students’ attitudes towards electronic book technology

The purpose of this study is to analyze the factors that have an impact on technology adoption for e-books utilizing the Analytic Hierarchy Process (AHP) and Multiple Regression Analysis methods. Findings indicate that perceived usefulness and ease of use are the most significant determinants in using e-books. Of key significance is that AHP results show that consumers make pairwise comparisons, adding environmental concerns to the selection process. Recognizing the importance of all these factors is valuable to e-book developers and marketers in presenting products that meet all consumer choice criteria. AHP provides researchers with a more thorough decision making analysis

Judgmental adjustments and scenario use: Individual versus group forecasts

Judgmental adjustments to model forecasts are common in organizations. Given that such adjustments may not always enhance forecast accuracy, it is essential to provide support tools to improve communication and information sharing between forecasters and decision-makers. Scenarios provide a possible toolbox to aid this process. Current work outlines a series of experiments investigating the effects of providing a set of scenarios as forecast advice on individual and group-based judgmental predictions. Findings suggest key directions for designing and implementing effective forecast management systems to benefit both the providers and users of forecasts

Fibonacci Series-Based Pairwise Comparison Scale for Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) is one of the most widely used quantitative tools in multi-criteria decision-making problems. Despite its popularity and use due to its simple but systematic procedure, AHP has limitations especially in terms of the numerical comparison scale used in one of its core steps: pairwise comparisons. AHP is based on verbal comparisons of alternatives/criteria, which are, then, converted into quantitative scores with a one-to-one mapping between the verbal comparisons and a predetermined numerical scale. The choice of the numerical scale affects an essential characteristic of pairwise comparisons: consistency. In order to understand the intrinsic consistency propinquities, this study evaluates the most widely used numerical pairwise comparison scale (Fundamental Scale) and other numerical scales that have been proposed since the initial formulation of AHP. After identifying the limitations of known scales, a new scale based on Fibonacci series is developed considering these limitations, and further analysis is conducted through extensive simulations. The results show that the proposed scale performs well when compared to the other scales

Why/when can scenarios be harmful for judgmental demand forecasts and the following production order decisions?

Judgmental demand forecasting constitutes an integral part of inventory management and production planning activities within organizations. Among forecasting academicians and practitioners, there is the generally accepted belief that the presence of scenarios is largely beneficial for future planning and may aid the decision makers in producing these demand predictions. However, there is only circumstantial evidence and some studies report controversial findings. One recent experimental work (Gonul, Goodwin & Onkal, ISF2019) investigated the interaction between the existence of optimistic and pessimistic scenarios and the presence of time-series information alone in the task of generating demand forecasts and the following production order decisions. The findings revealed that providing scenarios worsened forecast accuracy and swayed the production order decisions further away from the optimality. What were the reasons underlying these results? Why did scenarios degrade forecasters’ accuracy? This current work is an attempt to disentangle this puzzle by trying to shed some light on these controversial findings through the application of a Generalized Estimating Equations (GEE) model. The findings from this analysis will be discussed to guide future research on scenarios and judgmental forecasting

Trusting Forecasts

Accurate forecasting is necessary to remain competitive in today’s business environment. Forecast support systems are designed to aid forecasters in achieving high accuracy. However, studies have shown that people are distrustful of automated forecasters. This has recently been dubbed ‘algorithm aversion’. In this study, we explore the relationship between trust and forecasts, and if trust can be boosted in order to achieve a higher acceptance rate of system forecasts and lessen the occurrence of damaging adjustments. In a survey with 134 executives, we ask them to rate the determinants of trust in forecasts, what trust in forecasting means to them and how trust in forecasts can be increased. The findings point to four main factors that play a role in trusting forecasts: (1) the forecast bundle, (2) forecaster competence, (3) combination of forecasts, and (4) knowledge. Implications of these factors for designing effective forecast support and future-focused management processes are discussed

Commentary on Making Forecasting More Trustworthy

In their commentary on the previous article in Foresight, Issue 66, the authors agree that trust in forecasting may have actually declined rather than improved and make suggestions on what can be done to improve the situation

The effects of scenarios on judgmental demand forecasts and the subsequent production decisions

In production planning and inventory management activities, demand forecasts play a crucial role by shaping the decisions of how many to produce from different products subject to a fixed total capacity restriction. Such demand predictions can be supported by the presence of optimistic and pessimistic scenarios that provide a vibrant narrative to envisage the future. In this paper, through an experimental study, we are investigating i) the effects of providing only time-series information on the generation of judgmental demand forecasts and the subsequent production order decisions and ii) the interaction of presenting optimistic and pessimistic scenarios with this forecast generation and ordering process. The experimental design involved three between subject groups: i) only time-series information, no scenarios ii) time series information accompanied with weak optimistic and pessimistic scenarios iii) time series information accompanied with strong optimistic and pessimistic scenarios. Findings are disclosed and directions for future extensions are suggested

Immunohistochemical expression profiles of MUC1 and MUC2 mucins in urothelial tumors of bladder

Background: Mucins may show aberrant expression, localization, and/or glycosylation in multiple malignancies. However, information regarding expression of these mucins is mostly unknown in urothelial tumors. Aim: This study was conducted for examining the expressions of membrane associated and secreted mucin (MUC1) and a secreted gel-forming mucin (MUC2) in urothelial tumors of the urinary bladder. Subjects and Methods: Archival transurethral resection materials of 97 urothelial carcinoma cases were reexamined light microscopically and graded according to the 2004 WHO Classification. Pathological stage was given as pTa, pT1, and pT2. Demonstrative sections were recut for immunohistochemistry for MUC1 and MUC2. The results were statistically analyzed, and P < 0.05 was considered statistically significant. Results: The positivity for MUC1 and MUC2 was 89.7\% and 44.3\%, respectively. Independent from pathological stage of the tumor, MUC1 expression showed statistically significant correlation with tumor grade (P < 0.05). We did not find any correlation between pathological stage and MUC1 and MUC2 expression (P > 0.05). MUC1 staining pattern in papillary urothelial neoplasm of low malignant potential cases was more commonly apical and superficial (luminal cell layer only). Intermediate cells +/- basal cells or isolated cells or islands of tumor cells with cytoplasmic and/or circumferential membrane positivity for MUC1 and MUC2 were more commonly observed in both low- and high-grade carcinomas. The difference between groups in terms of MUC1 and MUC2 staining was statistically significant (P < 0.05). Conclusions: The staining patterns of both mucins are different between urothelial papillary tumors and may be used to make a differentiation, especially for low-grade papillary urothelial lesions. This difference may also be important in the carcinomatous transformation of urothelial neoplastic and preneoplastic lesions

Forecasts and Order Decisions: Reactions to Demand Variability

In a typical supply-chain management setting, making order decisions inherently entails forecasting the uncertain demand for the relevant products. Through this translation of demand forecasting into final order decisions, one of the persistent findings in recent years is the pull-to-centre effect. This effect can be summarized as the tendency of the decision makers to set their order decisions between the mean demand and the normative order quantity. In the current study, we attempt to explore how decision makers will react to demand uncertainty, particularly to changes in variability of the demand and investigate the corresponding pull-to-centre effect. We also try to identify a potential cognitive bias, overprecision, that may prevail in this forecasting and decision process. Findings are discussed and directions for future research are suggested

Evaluating strategic directional probability predictions of exchange rates

The current paper aims to examine strategic predictions (with forecast horizons greater than six months) via the empirical probability (EP) technique. This technique was proposed initially to examine short-term tactical predictions (with forecast horizons less than three months), as set out in Pollock et al. (2005). The proposed procedure is based on the hypothesis that changes in logarithms of daily exchange rates follow a normal distribution over short horizons (of 10 to 30 days), but longer term forecast evaluation requires consideration of cumulative parameters consistent with changing means and standard deviations arising from primary and secondary trends. It is shown that ex-post EPs can be obtained for any predictive horizon above 30 days (e.g., 180 days) by using a combination of shorter (e.g., 20-day) Student t distributions. The procedure is illustrated using daily Euro/USD series from 4 January 1999 to 29 January 2008 to evaluate a set of Euro/USD directional probability predictions