Dynamic decision networks for decision-making in self-adaptive systems:a case study

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

Increased salience of gains versus decreased associative learning differentiate bipolar disorder from schizophrenia during incentive decision making

Background Abnormalities in incentive decision making, typically assessed using the Iowa Gambling Task (IGT), have been reported in both schizophrenia (SZ) and bipolar disorder (BD). We applied the Expectancy-Valence (E-V) model to determine whether motivational, cognitive and response selection component processes of IGT performance are differentially affected in SZ and BD. Method Performance on the IGT was assessed in 280 individuals comprising 70 remitted patients with SZ, 70 remitted patients with BD and 140 age-, sex-and IQ-matched healthy individuals. Based on the E-V model, we extracted three parameters, 'attention to gains or loses', 'expectancy learning' and 'response consistency', that respectively reflect motivational, cognitive and response selection influences on IGT performance. Results Both patient groups underperformed in the IGT compared to healthy individuals. However, the source of these deficits was diagnosis specific. Associative learning underlying the representation of expectancies was disrupted in SZ whereas BD was associated with increased incentive salience of gains. These findings were not attributable to non-specific effects of sex, IQ, psychopathology or medication. Conclusions Our results point to dissociable processes underlying abnormal incentive decision making in BD and SZ that could potentially be mapped to different neural circuits. © 2012 Cambridge University Press.

Fuzzy assessment of performance of a decision making units using DEA:a non-radical approach

Data Envelopment Analysis (DEA) is recognized as a modern approach to the assessment of performance of a set of homogeneous Decision Making Units (DMUs) that use similar sources to produce similar outputs. While DEA commonly is used with precise data, recently several approaches are introduced for evaluating DMUs with uncertain data. In the existing approaches many information on uncertainties are lost. For example in the defuzzification, the a-level and fuzzy ranking approaches are not considered. In the tolerance approach the inequality or equality signs are fuzzified but the fuzzy coefficients (inputs and outputs) are not treated directly. The purpose of this paper is to develop a new model to evaluate DMUs under uncertainty using Fuzzy DEA and to include a-level to the model under fuzzy environment. An example is given to illustrate this method in details.

Multiple criteria decision-making techniques in higher education

Purpose: The purpose of this paper is to review the literature which focuses on four major higher education decision problems. These are: resource allocation; performance measurement; budgeting; and scheduling. Design/methodology/approach: Related articles appearing in the international journals from 1996 to 2005 are gathered and analyzed so that the following three questions can be answered: "What kind of decision problems were paid most attention to?"; "Were the multiple criteria decision-making techniques prevalently adopted?"; and "What are the inadequacies of these approaches?" Findings: Based on the inadequacies, some improvements and possible future work are recommended, and a comprehensive resource allocation model is developed taking account of these factors. Finally, a new knowledge-based goal programming technique which integrates some operations of analytic hierarchy process is proposed to tackle the model intelligently. Originality/value: Higher education has faced the problem of budget cuts or constrained budgets for the past 30 years. Managing the process of the higher education system is, therefore, a crucial and urgent task for the decision makers of universities in order to improve their performance or competitiveness. © Emerald Group Publishing Limited.

The influence of context on the strategic decision-making process:a review of the literature

This paper critically reviews the strategic decision-making process literature, with a specific focus on the effects of context. Context refers to the top management team, strategic decision-specific characteristics, the external environment and firm characteristics. This literature review also develops an illustrative framework that incorporates these four different categories of contextual variables that influence the strategic decision-making process. As a result of the variety and pervasiveness of contextual variables featured within the literature, a comprehensive and up-to-date review is essential for organizing and synthesizing the extant literature to explicate an agenda for future research. The purpose of this literature review is threefold: first, to critically review the strategic decision-making process literature to highlight the underlying themes, issues, tensions and debates in the field; second, to identify the opportunities for future theory development; and third, to state the methodological implications arising from this review. © 2013 British Academy of Management and John Wiley & Sons Ltd.

Intuition in strategic decision making:implications for strategic decision effectiveness

Intuition can produce effective strategic decisions because of its speed and ability to solve less-structured problems. Despite this, there are only a very small number of empirical studies that have examined intuition in the strategic decision-making process. We examine the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. We propose that the expertise of the decision-maker, environmental dynamism and the characteristics of the strategic decision itself moderate the relationship between the use of intuition in the strategic decision making process, and strategic decision effectiveness. We make a significant theoretical contribution by integrating the management and social-psychology literatures in order to identify the variables that affect the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. This article builds upon existing empirical research that has examined intuition in the strategic decision-making process, and reconciles some of the confounding results that have emerged. The paper presents a conceptual model and research propositions, which if empirically examined, would make a significant contribution to knowledge in the strategic decision-making domain of literature.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

A review of multi-criteria decision-making methods for bioenergy systems

Bioenergy schemes are multi-faceted and complex by nature, with many available raw material supplies and technical options and a diverse set of stakeholders holding a raft of conflicting opinions. To develop and operate a successful scheme there are many requirements that should be considered and satisfied. This paper provides a review of those academic works attempting to deal with problems arising within the bioenergy sector using multi-criteria decision-making (MCDM) methods. These methods are particularly suitable to bioenergy given its multi-faceted nature but could be equally relevant to other energy conversion technologies. Related articles appearing in the international journals from 2000 to 2010 are gathered and analysed so that the following two questions can be answered. (i) Which methods are the most popular? (ii) Which problems attract the most attention? The review finds that optimisation methods are most popular with methods choosing between few alternatives being used in 44% of reviewed papers and methods choosing between many alternatives being used in 28%. The most popular application area was to technology selection with 27% of reviewed papers followed by policy decisions with 18%. © 2012 Elsevier Ltd.

An examination of intuition in strategic decision-making:the role of context

Intuition is a vitally important concept in strategic decision making research because it enables decision-makers to rapidly detect patterns in dynamic environments in order to cope with the time-pressured, ill-structured and non-routine nature of strategic decision-making. Despite a growing body of conceptual literature emphasising the importance of intuition in strategic decision-making; there has been very little development of theory explaining the contextual factors that cause intuition to be used in the strategic decision-making process. This paper demonstrates that by integrating different contextual variables a clear understanding of the influences on the use of intuition in strategic decision-making can be developed. This article develops an integrative theoretical model together with testable research propositions, which if empirically examined, would make a substantial contribution to knowledge.

Classifying clinical decision making:a unifying approach

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

Unsupervised KDD to creatively support managers' decision making with fuzzy association rules:a distribution channel application

To be competitive in contemporary turbulent environments, firms must be capable of processing huge amounts of information, and effectively convert it into actionable knowledge. This is particularly the case in the marketing context, where problems are also usually highly complex, unstructured and ill-defined. In recent years, the development of marketing management support systems has paralleled this evolution in informational problems faced by managers, leading to a growth in the study (and use) of artificial intelligence and soft computing methodologies. Here, we present and implement a novel intelligent system that incorporates fuzzy logic and genetic algorithms to operate in an unsupervised manner. This approach allows the discovery of interesting association rules, which can be linguistically interpreted, in large scale databases (KDD or Knowledge Discovery in Databases.) We then demonstrate its application to a distribution channel problem. It is shown how the proposed system is able to return a number of novel and potentially-interesting associations among variables. Thus, it is argued that our method has significant potential to improve the analysis of marketing and business databases in practice, especially in non-programmed decisional scenarios, as well as to assist scholarly researchers in their exploratory analysis. © 2013 Elsevier Inc.

The role of shared decision-making in audiologic rehabilitation

Shared decision-making (SDM), a component of patient-centered care, is the process in which the clinician and patient both participate in decision-making about treatment; information is shared between the parties and both agree with the decision. Shared decision-making is appropriate for health care conditions in which there is more than one evidence-based treatment or management option that have different benefits and risks. The patient's involvement ensures that the decisions regarding treatment are sensitive to the patient's values and preferences. Audiologic rehabilitation requires substantial behavior changes on the part of patients and includes benefits to their communication as well as compromises and potential risks. This article identifies the importance of shared decision-making in audiologic rehabilitation and the changes required to implement it effectively.

Decision-making in product quality based on failure knowledge

Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.

An investigation of Albanian EFL teachers' decision-making in their use of CLT-oriented textbooks

Against a backdrop of ongoing educational reforms that seek to introduce Communicative Language Teaching (CLT) in Albanian primary and secondary state schools, Albanian teachers, among others, are officially required to use communication-based textbooks in their classes. Authorities in a growing number of countries that are seeking to improve and westernise their educational systems are also using communication-based textbooks as agents of change. Behind these actions, there is the commonly held belief that textbooks can be used to support teacher learning as they provide a visible framework teachers can follow. Communication-based textbooks are used in thousands of EFL classrooms around the world to help teachers to “fully understand and routinize change” (Hutchinson and Torres, 1994:323). However, empirical research on the role materials play in the classroom, and in particular the role of textbook as an agent of change, is still very little, and what does exist is rather inconclusive. This study aims to fulfill this gap. It is predominately a qualitative investigation into how and why four Albanian EFL teachers use Western teaching resources in their classes. Aiming at investigating the decision-making processes that teachers go through in their teaching, and specifically at investigating the relationship between Western-published textbooks, teachers’ decision making, and teachers’ classroom delivery, the current study contributes to an extensive discussion on the development of communicative L2 teaching concepts and methods, teacher decision making, as well as a growing discussion on how best to make institutional reforms effective, particularly in East-European ex-communist countries and in other developing countries. Findings from this research indicate that, prompted by the content of Western-published textbooks, the four research participants, who had received little formal training in CLT teaching, accommodated some communicative teaching behaviours into their teaching. The use of communicative textbooks, however, does not seem to account for radical, methodological changes in teachers’ practices. Teacher cognitions based on teachers’ previous learning experience are likely to act as a lens through which teachers judge classroom realities. As such, they shape, to a great degree, the decisions teachers make regarding the use of Western-published textbooks in their classes.