Using metrics in quality management

The author, who started using software metrics four years ago, shows how a metrics program evolved into something very useful for his company. He describes their three-stage procedure for implementing a data collection scheme, the principles with which they began and how those principles evolved as they were applied, and the principles learned from the work. He concludes with some opinions about the usefulness of various types of metrics     

Using hindsight in medical decision making

As the clinical picture of a patient evolves over time, more information becomes available. Certain procedure require time to perform, causing delay between the time when the tests are ordered and when the results are available. Furthermore, as the patient's condition changes over time, serial measurements can be made. The availability of more data allows a more accurate assessment of the patient. Uncertainties, guesses or errors that were made early in the clinical course of patient care can also be identified and resolved when more information is available. Reasoning with a stream of data that changes over time presents a challenge to the designers of expert systems. The use of hindsight in expert system requires that appropriate attention be paid to the temporal relations of the data and that care is exercised in revising decision. I present a data-dependency system, the Temporal Control Structure (TCS), designed to support reasoning with data changing over time and show how it can be used to implement reasoning by hindsight.     

Using OLAP and multidimensional data for decision making

Managers see information as a critical resource and require systems that let them exploit it for competitive advantage. One way to better use organizational information is via online analytical processing and multidimensional databases (MDDBs). OLAP and MDDBs present summarized information from company databases. They use multidimensional structures that let managers slice and dice views of company performance data and drill down into trouble spots. For over a decade, proponents have touted these tools as the ultimate executive information system, but most of the hype comes from product vendors themselves. Based on our experience with several OLAP tools, we have developed a more pragmatic approach to the design of multidimensional information systems that lets managers make the most of their companies' information assets     

Using the fuzzy multi-criteria decision making approach for measuring the possibility of successful knowledge management

This study develops a forecasting framework based on the fuzzy multi-criteria decision making (FMCDM) approach to help organizations build awareness of the critical influential factors on the success of knowledge management (KM) implementation, measure the success possibility of knowledge management projects, as well as identify the necessary actions prior to embarking on conducting knowledge management. Subjectivity, uncertainty and vagueness within the prediction process are dealt with using linguistic variables parameterized by triangular fuzzy numbers. By multiplying the importance weights of influential factors and the possible rating of success (failure), predicted success (failure) values are determined to enable organizations to decide whether to initiate knowledge management, inhibit adoption or undertake remedial improvements to increase the possibility of successful knowledge management project. The proposed approach is demonstrated using a real case involving a Taiwanese semiconductor engineering corporation.     

Using argumentation to model agent decision making in economic experiments

In this paper we demonstrate how a qualitative framework for decision making can be used to model scenarios from experimental economic studies and we show how our approach explains the results that have been reported from such studies. Our framework is an argumentation-based one in which the social values promoted or demoted by alternative action options are explicitly represented. Our particular representation is used to model the Dictator Game and the Ultimatum Game, which are simple interactions in which it must be decided how a sum of money will be divided between the players in the games. Studies have been conducted into how humans act in such games and the results are not explained by a decision-model that assumes that the participants are purely self-interested utility-maximisers. Some studies further suggest that differences in choices made in different cultures may reflect their day to day behaviour, which can in turn be related to the values of the subjects, and how they order their values. In this paper we show how these interactions can be modelled in agent systems in a framework that makes explicit the reasons for the agents’ choices based upon their social values. Our framework is intended for use in situations where agents are required to be adaptable, for example, where agents may prefer different outcome states in transactions involving different types of counter-parties.     

Using fuzzy decision making system to improve quality-based investment

In this paper, fuzzy set theory is used to select the quality-based investment in small firm. Here a new algorithm, which will consider both exogenous and endogenous variables as factors, is proposed to formulate the problem. The structure of the algorithm is based on fuzzy decision-making system (FDMS), which uses fuzzy control rules. Hence, one exogenous factor and five endogenous factors mentioned above are determined as input variables and fuzzified using membership function concept. Then, the weights of these factors are fuzzified to ensure the consistency of the decision maker when assigning the importance of one factor over another. Applying IF-THEN decision rules, quality-based investments are scored. Also the comparison with Analytical Hierarchy Process (AHP) and Fuzzy Linguistic Approach (FLA) in respect to these scores is presented.     

Using a decision support system in management education

The development of an innovative management decision support system in an educational context is described. Particular attention is devoted to the use of the system as an integral element of an MBA program and to the formal evaluation of the impact of the systems development process and the system on the users attitudes, values, information usage behavior and decision-making behavior.     

Naturalistic decision making

OBJECTIVE: This article describes the origins and contributions of the naturalistic decision making (NDM) research approach. BACKGROUND: NDM research emerged in the 1980s to study how people make decisions in real-world settings. Method: The findings and methods used by NDM researchers are presented along with their implications. RESULTS: The NDM framework emphasizes the role of experience in enabling people to rapidly categorize situations to make effective decisions. CONCLUSION: The NDM focus on field settings and its interest in complex conditions provide insights for human factors practitioners about ways to improve performance. APPLICATION: The NDM approach has been used to improve performance through revisions of military doctrine, training that is focused on decision requirements, and the development of information technologies to support decision making and related cognitive functions.     

Defining the drivers for accepting decision making automation in air traffic management

Air Traffic Management (ATM) operators are under increasing pressure to improve the efficiency of their operation to cater for forecasted increases in air traffic movements. One solution involves increasing the utilisation of automation within the ATM system. The success of this approach is contingent on Air Traffic Control Operators' (ATCOs) willingness to accept increased levels of automation. The main aim of the present research was to examine the drivers underpinning ATCOs' willingness to accept increased utilisation of automation within their role. Two fictitious scenarios involving the application of two new automated decision-making tools were created. The results of an online survey revealed traditional predictors of automation acceptance such as age, trust and job satisfaction explain between 4 and 7% of the variance. Furthermore, these predictors varied depending on the purpose in which the automation was to be employed. These results are discussed from an applied and theoretical perspective. STATEMENT OF RELEVANCE: Efficiency improvements in ATM are required to cater for forecasted increases in air traffic movements. One solution is to increase the utilisation of automation within Air Traffic Control. The present research examines the drivers underpinning air traffic controllers' willingness to accept increased levels of automation in their role.     

Norms in artificial decision making

A method for forcing norms onto individual agents in a multi-agent system is presented. The agents under study are supersoft agents: autonomous artificial agents programmed to represent and evaluate vague and imprecise information. Agents are further assumed to act in accordance with advice obtained from a normative decision module, with which they can communicate. Norms act as global constraints on the evaluations performed in the decision module and hence no action that violates a norm will be suggested to any agent. Further constraints on action may then be added locally. The method strives to characterise real-time decision making in agents, in the presence of risk and uncertainty.     

Using a multi-criteria decision making approach to evaluate mobile phone alternatives

The arrival of the mobile phone and its rapid and widespread growth may well be seen as one of the most significant developments in the fields of communication and information technology over the past two decades. The aim of this study is to propose a multi-criteria decision making (MCDM) approach to evaluate the mobile phone options in respect to the users' preferences order. Firstly, the most desirable features influencing the choice of a mobile phone are identified. This is realized through a survey conducted among the target group, the experiences of the telecommunication sector experts and the studies in the literature. Two MCDM methods are then used in the evaluation procedure. More precisely, Analytic Hierarchy Process (AHP) is applied to determine the relative weights of evaluation criteria and the extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the mobile phone alternatives. A case study illustrates the effectiveness of the proposed approach.     

Graphics in business decision making

Mountains of data can be converted into easily digested graphs so that decision makers can grasp the peaks and trends of economic situations and make rapid and confidential decisions. We will study how we can define simple models using a graphic-based Industrial Dynamics system (Forrester of MIT), then interact with them symbionically to obtain graphs of various manufacturing or sales considerations. We will proceed to apply graphic analysis techniques to these graphs in order to produce curves that identify the sensitivities of the analysis, to reinforce confidence in the decision to be made. Finally, we will discuss the progress and the potential of graphics in business decision making.     

Systematic decision process for intelligent decision making

In this paper, Systematic decision process (SDP) for solving Multiple Criteria Decision Making problems with application for manufacturing location selection is introduced. SDP is a comprehensive approach which is based on eliciting strength of preferences for assessing additive utility functions. SDP consists of three steps: I. assessing weights, II. assessing qualitative criteria, and III. ranking alternatives using the assessed additive utility function. Strengths of preferences can be expressed by using either qualitative or numerical ratings. If the decision maker is inconsistent in his/her responses, such inconsistencies are identified by the method. It is shown that the method has advantages in terms of simplicity and accuracy compared to existing methods such as Analytical Hierarchy Process. Furthermore, a quadratic optimization method for assessing weights of additive utility function by use of pair comparison of actual alternatives is developed. Computational experiments are provided.     

Using interval information on relative criteria tradeoffs in analyzing multicriterial decision making problems

We show and validate a mathematical model of multicriterial preferences, in which the preference relation is formed with interval estimates of relative tradeoffs of values of one criteria with values of other criteria. We develop a theory and multicriterial problem analysis methods based on this model.     

Multiknowledge for decision making

The representation of knowledge has an important effect on automated decision-making. In this paper, vector spaces are used to describe a condition space and a decision space, and knowledge is represented by a mapping from the condition space to the decision space. Many such mappings can be obtained from a training set. A set of mappings, which are created from multiple reducts in the training set, is defined as multiknowledge. In order to get a good reduct and find multiple reducts, the WADF (worst-attribute-drop-first) algorithm is developed through analysis of the properties of decision systems using rough set theory. An approach that combines multiknowledge and the naïve Bayes classifier is applied to make decisions for unseen instances or for instances with missing attribute values. Benchmark data sets from the UCI Machine Learning Repository are used to test the algorithms. The experimental results are encouraging; the prediction accuracy for unseen instances by using the algorithms is higher than by using other approaches based on a single body of knowledge.     

Pareto multi-criteria decision making

The paper concerns design governed by multiple objective criteria, which are conflicting in the sense of competing for common resources to achieve variously different performance objectives (financial, functional, environmental, esthetical, etc.). A multi-criteria decision making (MCDM) strategy is proposed that employs a tradeoff-analysis technique to identify compromise designs for which the competing criteria are mutually satisfied in a Pareto-optimal sense. The MCDM strategy is initially developed for the case of design governed by n = 2 objective criteria. It is then extended to design governed by n > 2 objective criteria, by introducing the concept of primary and aggregate criteria. It is proved that, from among the theoretically infinite number of feasible designs forming the Pareto front for a design problem governed by n independent objective criteria, there exists a unique Pareto-compromise design that represents a mutually agreeable tradeoff between all n criteria. This remarkable result is illustrated for a flexural plate design governed by n = 2 criteria, a bridge maintenance-intervention protocol design governed by n = 3 criteria, and a media centre envelop design governed by n = 11 criteria.