Qualitative ordinal scales: the concept of ordinal range

Many practical problems of quality control involve the use of ordinal scales. Questionnaires planned to collect judgments on qualitative or linguistic scales, whose levels are terms such as "good," "bad," "medium," etc., are extensively used both in evaluating service quality and in visual controls for manufacturing industry. In an ordinal environment, the concept of distance between two generic levels of the same scale is not defined. Therefore, a population (universe) of judgments cannot be described using "traditional" statistical distributions since they are based on the notion of distance. The concept of "distribution shape" cannot be defined as well. In this article, we introduce a new statistical entity, the so-called ordinal distribution, to describe a population of judgments expressed on an ordinal scale. We also discuss which of the traditional location and dispersion measures can be used in this context and we briefly analyze some of their properties. A new dispersion measure, the ordinal range, as an extension of the cardinal range to ordinal scales, is then proposed. A practical application in the field of quality is developed throughout the articl

dP-FMEA: An innovative Failure Mode and Effects Analysis for distributed manufacturing processes

The Failure Mode and Effects Analysis (FMEA) is a powerful tool to design and maintain reliable systems (products, services or manufacturing processes), investigating their potential failure modes from the threefold perspective of severity, occurrence and detection. The Process FMEA, or more briefly P-FMEA, is a declination of the FMEA for manufacturing processes (or parts of them). Being progressively characterized by decentralized networks of flexible manufacturing facilities, the current scenario significantly hampers the implementation of the traditional P-FMEA, which requires the joint work of a group of experts formulating collective judgments. This paper revises the traditional P-FMEA approach and integrates it with the ZMII-technique – i.e. a recent aggregation technique based on the combination of the Thurstone’s Law of Comparative Judgment and the Generalized Least Squares method – allowing experts distributed through organizations to formulate their judgments individually. The revised approach – referred to as “distributed-Process FMEA” or more briefly dP-FMEA – allows to manage a number of experts, without requiring them to physically meet and formulate collective decisions, thus overcoming a relevant limitation of the traditional P-FMEA. The dP-FMEA approach also includes a relatively versatile response mode and overcomes several other limitations of the traditional approach, including but not limited to: (i) arbitrary formulation and aggregation of expert judgments, (ii) lack of consideration of the dispersion of these judgments, and (iii) lack of estimation of the uncertainty of results. The description is supported by a real-life application example concerning a plastic injection-molding process

Using graphical models and multi-attribute utility theory for probabilistic uncertainty handling in large systems, with application to nuclear emergency management

Although many decision-making problems involve uncertainty, uncertainty handling within large decision support systems (DSSs) is challenging. One domain where uncertainty handling is critical is emergency response management, in particular nuclear emergency response, where decision making takes place in an uncertain, dynamically changing environment. Assimilation and analysis of data can help to reduce these uncertainties, but it is critical to do this in an efficient and defensible way. After briefly introducing the structure of a typical DSS for nuclear emergencies, the paper sets up a theoretical structure that enables a formal Bayesian decision analysis to be performed for environments like this within a DSS architecture. In such probabilistic DSSs many input conditional probability distributions are provided by different sets of experts overseeing different aspects of the emergency. These probabilities are then used by the decision maker (DM) to find her optimal decision. We demonstrate in this paper that unless due care is taken in such a composite framework, coherence and rationality may be compromised in a sense made explicit below. The technology we describe here builds a framework around which Bayesian data updating can be performed in a modular way, ensuring both coherence and efficiency, and provides sufficient unambiguous information to enable the DM to discover her expected utility maximizing policy

EXPLANATORY ECONOMETRIC METHOD FOR THE ANALYSIS OF THE BEHAVIOR MANAGEMENT IN ORGANIZATIONS IN ROMANIA

Our paper, entitled "Explanatory Econometric Method for the Analysis of the Behaviour Management in Organizations in Romania" reflects the wide opening of econometric modelling to quantify the Romanian management issues, representing a practical guidance on multiple recovery plans to fund the huge data collected as part COMOR project launched by the Scientific Society of Management in Romania to characterize the behaviour of managers in the Romanian economic organizations. Construction of these models offers possibilities for complex analysis, descriptive and factorial sequence of firms, counties, geographical areas, but comprehensive summary of studies on the macroeconomic level. Scientific knowledge through a comprehensive assessment of managerial behaviour in the most representative types of business organizations of all geographical areas of the country are, in the context of globalization, one way to prevent surprises market economy. Thus, the results of this exploratory research will provide economic environment, and not only strong argument for anticipating decisions in order to choose the best economic policies, with beneficial effects as conclusive and with as few undesirable implications. Research based on the opinions of thousands of respondents approved, processed through a variety of instruments subject of extensive econometric and interdisciplinary interpretation, psycho-socio-economic management, is a modest contribution to the affirmation of local scientific research that aim for theoretical and applied Romanian school of management by defining: - knowledge of behaviour management in all types of business organizations in Romania;- identifying the Romanian space dimensions of organizational culture as a reflection of the peculiarities of national culture and especially of the main ethnic-specific subcultures;- profile defining effective manager and leader of excellence in terms of character traits and their behaviour.econometrics, management, organizational culture, descriptive analysis, factorial analysis.

How do you say ‘hello’? Personality impressions from brief novel voices

On hearing a novel voice, listeners readily form personality impressions of that speaker. Accurate or not, these impressions are known to affect subsequent interactions; yet the underlying psychological and acoustical bases remain poorly understood. Furthermore, hitherto studies have focussed on extended speech as opposed to analysing the instantaneous impressions we obtain from first experience. In this paper, through a mass online rating experiment, 320 participants rated 64 sub-second vocal utterances of the word ‘hello’ on one of 10 personality traits. We show that: (1) personality judgements of brief utterances from unfamiliar speakers are consistent across listeners; (2) a two-dimensional ‘social voice space’ with axes mapping Valence (Trust, Likeability) and Dominance, each driven by differing combinations of vocal acoustics, adequately summarises ratings in both male and female voices; and (3) a positive combination of Valence and Dominance results in increased perceived male vocal Attractiveness, whereas perceived female vocal Attractiveness is largely controlled by increasing Valence. Results are discussed in relation to the rapid evaluation of personality and, in turn, the intent of others, as being driven by survival mechanisms via approach or avoidance behaviours. These findings provide empirical bases for predicting personality impressions from acoustical analyses of short utterances and for generating desired personality impressions in artificial voices

Similarity and the trustworthiness of distributive judgements

When people must either save a greater number of people from a smaller harm or a smaller number from a greater harm, do their choices reflect a reasonable moral outlook? We pursue this question with the help of an experiment. In our experiment, two-fifths of subjects employ a similarity heuristic. When alternatives appear dissimilar in terms of the number saved but similar in terms of the magnitude of harm prevented, this heuristic mandates saving the greater number. In our experiment, this leads to choices that are inconsistent with all standard theories of justice. We argue that this demonstrates the untrustworthiness of distributive judgments in cases that elicit similarity-based choice

How codes of ethics deal with fear in the workplace

The relationship between decision-making and emotions has been increasingly explored in the past thirty years by physicians, psychologists and economists. Because of the impact that emotions have on human behaviour, ethical implications need to be examined if we consider that managers could use emotions to motivate employees. This paper analyses the content of the code of ethics of 278 companies listed on the Italian stock exchange in order to verify how the codes take into account the emotion of fear experienced by employees in the workplace. Research findings revealed that companies have failed to consider the word “fear” and most of the other terms expressing similar emotions. On the other hand, their codes of ethics focused on ethical standards that should be respected, such as the dignity of each single individual and on unethical actions that must be avoided, such as acts of physical or psychological violence

Implications and Ramifications of a Sample-Size Approach to Intuition

[...from the chapter] In the present article, we delineate a different approach, which is by no means inconsistent, but largely overlaps with the aforementioned definitions. However, our approach is simpler and refrains from a number of rather strong assumptions to which other conceptions subscribe. Using a simple and straightforward criterion, we define intuition in terms of the size of the sample used in reaching a decision: Judgments and decisions are intuitive to the extent that they rest on small samples.