The basic principles of uncertain information fusion. An organised review of merging rules in different representation frameworks.

We propose and advocate basic principles for the fusion of incomplete or uncertain information items, that should apply regardless of the formalism adopted for representing pieces of information coming from several sources. This formalism can be based on sets, logic, partial orders, possibility theory, belief functions or imprecise probabilities. We propose a general notion of information item representing incomplete or uncertain information about the values of an entity of interest. It is supposed to rank such values in terms of relative plausibility, and explicitly point out impossible values. Basic issues affecting the results of the fusion process, such as relative information content and consistency of information items, as well as their mutual consistency, are discussed. For each representation setting, we present fusion rules that obey our principles, and compare them to postulates specific to the representation proposed in the past. In the crudest (Boolean) representation setting (using a set of possible values), we show that the understanding of the set in terms of most plausible values, or in terms of non-impossible ones matters for choosing a relevant fusion rule. Especially, in the latter case our principles justify the method of maximal consistent subsets, while the former is related to the fusion of logical bases. Then we consider several formal settings for incomplete or uncertain information items, where our postulates are instantiated: plausibility orderings, qualitative and quantitative possibility distributions, belief functions and convex sets of probabilities. The aim of this paper is to provide a unified picture of fusion rules across various uncertainty representation settings.

Can Future Managers and Business Executives be Influenced to Behave more Ethically in the Workplace? The Impact of Approaches to Learning on Business Students’ Cheating Behavior

This study considers the potential for influencing business students to become ethical managers by directing their undergraduate learning environment. In particular, the relationship between business students’ academic cheating, as a predictor of workplace ethical behavior, and their approaches to learning is explored. The three approaches to learning identified from the students’ approaches to learning literature are deep approach, represented by an intrinsic interest in and a desire to understand the subject, surface approach, characterized by rote learning and memorization without understanding, and strategic approach, associated with competitive students whose motivation is the achievement of good grades by adopting either a surface or deep approach. Consistent with the hypothesized theoretical model, structural equation modeling revealed that the surface approach is associated with higher levels of cheating, while the deep approach is related to lower levels. The strategic approach was also associated with less cheating and had a statistically stronger influence than the deep approach. Further, a significantly positive relationship reported between deep and strategic approaches suggests that cheating is reduced when deep and strategic approaches are paired. These findings suggest that future managers and business executives can be influenced to behave more ethically in the workplace by directing their learning approaches. It is hoped that the evidence presented may encourage those involved in the design of business programs to implement educational strategies which optimize students’ approaches to learning towards deep and strategic characteristics, thereby equipping tomorrow’s managers and business executives with skills to recognize and respond appropriately to workplace ethical dilemmas.