Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

Strategic decision making in small businesses:implications for strategic flexibility and strategic adaptation

Strategic decision making (SDM) in a small business is an informal, highly personalised cognitive process which is emergent in nature. SDM determines the extent to which decision makers generate innovative decision-making options, and is therefore critical in order for small businesses to achieve strategic flexibility to enable strategic adaptation to turbulent environments. By examining SDM in small businesses, this research has the potential to address a major criticism of the extant literature in that it has been pre-occupied with measuring the formality of strategic planning and has neglected the informal, highly personalised and cognitive nature of strategic decision making in a small businesses.

Understanding dynamics of strategic decision-making in venture creation:a process study of effectuation and causation

This study draws upon effectuation and causation as examples of planning-based and flexible decision-making logics, and investigates dynamics in the use of both logics. The study applies a longitudinal process research approach to investigate strategic decision-making in new venture creation over time. Combining qualitative and quantitative methods, we analyze 385 decision events across nine technology-based ventures. Our observations suggest a hybrid perspective on strategic decision-making, demonstrating how effectuation and causation logics are combined, and how entrepreneurs’ emphasis on these logics shifts and re-shifts over time. We induce a dynamic model which extends the literature on strategic decision-making in venture creation.

Greening operations: an investigation of environmental decision making

This PhD thesis belongs to three main knowledge domains: operations management, environmental management, and decision making. Having the automotive industry as the key sector, the investigation was undertaken aiming at deepening the understanding of environmental decision making processes in the operations function. The central research question for this thesis is ?Why and how do manufacturing companies take environmental decisions? This PhD research project used a case study research strategy supplemented by secondary data analysis and the testing and evaluation of a proposed systems thinking model for environmental decision making. Interviews and focus groups were the main methods for data collection. The findings of the thesis show that companies that want to be in the environmental leadership will need to take environmental decisions beyond manufacturing processes. Because the benefits (including financial gain) of non-manufacturing activities are not clear yet the decisions related to product design, supply chain and facilities are fully embedded with complexity, subjectivism, and intrinsic risk. Nevertheless, this is the challenge environmental leaders will face - they may enter in a paradoxical state of their decisions – where although the risk of going greener is high, the risk of not doing it is even higher.

Understanding manufacturing companies' environmental decision making structures

This paper provides an understanding of the current environmental decision structures within companies in the manufacturing sector. Through case study research, we explored the complexity, robustness and decision making processes companies were using in order to cope with ever increasing environmental pressures and choice of environmental technologies. Our research included organisations in UK, Thailand, and Germany. Our research strategy was case study composed of different research methods, namely: focus group, interviews and environmental report analysis. The research methods and their data collection instruments also varied according to the access we had. Our unity of analysis was decision making teams and the scope of our investigation included product development, environment & safety, manufacturing, and supply chain management. This study finds that environmental decision making have been gaining importance over the time as well as complexity when it is starting to move from manufacturing to non,manufacturing activities. Most companies do not have a formal structure to take environmental decisions; hence, they follow a similar path of other corporate decisions, being affected by organizational structures besides the technical competence of the teams. We believe our results will help improving structures in both beginners and leaders teams for environmental decision making across the different departments.

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.

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.

Purchase decision-making in fair trade and the ethical 'gap':'is there a fair trade twix?'

Children are increasingly being recognised as a significant force in the retail market place, as primary consumers, influencers of others, and as future customers. This paper adds to the literature on children as consumers by exploring their attitudinal responses to a specific group of products: Fair Trade lines. There has been no research to date that has specifically addressed children as consumers of Fair Trade or the ethical purchase decision-making process in this area. The methodological approach taken here is an essentially interpretive and naturalistic analysis of two focus groups of school children. The analysis found that there is an urgent need to develop meaningful Fair Trade brands that combine strong brand knowledge and positive brand images to bridge the ethical purchase gap between the formation of clear ethical attitudes and actual ethical purchase behaviour. Such an approach would both capture more of the children’s primary market and influence future purchase behaviour. It is argued that Fair Trade actors should coordinate new marketing communications campaigns that build brand knowledge structures holistically around the Fair Trade process and that extend beyond merely raising consumer awareness.

Integrated project evaluation and selection using multiple-attribute decision-making technique

The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again till the statutory regulatory authority approves the project. Moreover, project analysis through above process often results sub-optimal project as financial analysis may eliminate better options, as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system, which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple-attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated. © 2005 Elsevier B.V. All rights reserved.

Modelling and improving human decision making with simulation

Modelling human interaction and decision-making within a simulation presents a particular challenge. This paper describes a methodology that is being developed known as 'knowledge based improvement'. The purpose of this methodology is to elicit decision-making strategies via a simulation model and to represent them using artificial intelligence techniques. Further to this, having identified an individual's decision-making strategy, the methodology aims to look for improvements in decision-making. The methodology is being tested on unplanned maintenance operations at a Ford engine assembly plant

Multi-criteria decision making approaches for supplier evaluation and selection:a literature review

Supplier evaluation and selection problem has been studied extensively. Various decision making approaches have been proposed to tackle the problem. In contemporary supply chain management, the performance of potential suppliers is evaluated against multiple criteria rather than considering a single factor-cost. This paper reviews the literature of the multi-criteria decision making approaches for supplier evaluation and selection. Related articles appearing in the international journals from 2000 to 2008 are gathered and analyzed so that the following three questions can be answered: (i) Which approaches were prevalently applied? (ii) Which evaluating criteria were paid more attention to? (iii) Is there any inadequacy of the approaches? Based on the inadequacy, if any, some improvements and possible future work are recommended. This research not only provides evidence that the multi-criteria decision making approaches are better than the traditional cost-based approach, but also aids the researchers and decision makers in applying the approaches effectively.

Minority dissent and team innovation:the importance of participation in decision making

This study integrates research on minority dissent and individual creativity, as well as team diversity and the quality of group decision making, with research on team participation in decision making. From these lines of research, it was proposed that minority dissent would predict innovation in teams but only when teams have high levels of participation in decision making. This hypothesis was tested in 2 studies, 1 involving a homogeneous sample of self-managed teams and 1 involving a heterogeneous sample of cross-functional teams. Study 1 suggested that a newly developed scale to measure minority dissent has discriminant validity. Both Study 1 and Study 2 showed more innovations under high rather than low levels of minority dissent but only when there was a high degree of participation in team decision making. It is concluded that minority dissent stimulates creativity and divergent thought, which, through participation, manifest as innovation.

A concept-based framework for retrieving evidence to support emergency physician decision making at the point of care

The goal of evidence-based medicine is to uniformly apply evidence gained from scientific research to aspects of clinical practice. In order to achieve this goal, new applications that integrate increasingly disparate health care information resources are required. Access to and provision of evidence must be seamlessly integrated with existing clinical workflow and evidence should be made available where it is most often required - at the point of care. In this paper we address these requirements and outline a concept-based framework that captures the context of a current patient-physician encounter by combining disease and patient-specific information into a logical query mechanism for retrieving relevant evidence from the Cochrane Library. Returned documents are organized by automatically extracting concepts from the evidence-based query to create meaningful clusters of documents which are presented in a manner appropriate for point of care support. The framework is currently being implemented as a prototype software agent that operates within the larger context of a multi-agent application for supporting workflow management of emergency pediatric asthma exacerbations. © 2008 Springer-Verlag Berlin Heidelberg.