Decision theory to support evacuation in advance of catastrophic disaster including modular influence diagrams and spatial data analysis.

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Task classification and decision processes in monitoring behaviour

Task classification is introduced as a method for the evaluation of monitoring behaviour in different task situations. On the basis of an analysis of different monitoring tasks, a task classification system comprising four task 'dimensions' is proposed. The perceptual speed and flexibility of closure categories, which are identified with signal discrimination type, comprise the principal dimension in this taxonomy, the others being sense modality, the time course of events, and source complexity. It is also proposed that decision theory provides the most complete method for the analysis of performance in monitoring tasks. Several different aspects of decision theory in relation to monitoring behaviour are described. A method is also outlined whereby both accuracy and latency measures of performance may be analysed within the same decision theory framework. Eight experiments and an organizational study are reported. The results show that a distinction can be made between the perceptual efficiency (sensitivity) of a monitor and his criterial level of response, and that in most monitoring situations, there is no decrement in efficiency over the work period, but an increase in the strictness of the response criterion. The range of tasks exhibiting either or both of these performance trends can be specified within the task classification system. In particular, it is shown that a sensitivity decrement is only obtained for 'speed' tasks with a high stimulation rate. A distinctive feature of 'speed' tasks is that target detection requires the discrimination of a change in a stimulus relative to preceding stimuli, whereas in 'closure' tasks, the information required for the discrimination of targets is presented at the same point In time. In the final study, the specification of tasks yielding sensitivity decrements is shown to be consistent with a task classification analysis of the monitoring literature. It is also demonstrated that the signal type dimension has a major influence on the consistency of individual differences in performance in different tasks. The results provide an empirical validation for the 'speed' and 'closure' categories, and suggest that individual differences are not completely task specific but are dependent on the demands common to different tasks. Task classification is therefore shovn to enable improved generalizations to be made of the factors affecting 1) performance trends over time, and 2) the consistencv of performance in different tasks. A decision theory analysis of response latencies is shown to support the view that criterion shifts are obtained in some tasks, while sensitivity shifts are obtained in others. The results of a psychophysiological study also suggest that evoked potential latency measures may provide temporal correlates of criterion shifts in monitoring tasks. Among other results, the finding that the latencies of negative responses do not increase over time is taken to invalidate arousal-based theories of performance trends over a work period. An interpretation in terms of expectancy, however, provides a more reliable explanation of criterion shifts. Although the mechanisms underlying the sensitivity decrement are not completely clear, the results rule out 'unitary' theories such as observing response and coupling theory. It is suggested that an interpretation in terms of the memory data limitations on information processing provides the most parsimonious explanation of all the results in the literature relating to sensitivity decrement. Task classification therefore enables the refinement and selection of theories of monitoring behaviour in terms of their reliability in generalizing predictions to a wide range of tasks. It is thus concluded that task classification and decision theory provide a reliable basis for the assessment and analysis of monitoring behaviour in different task situations.

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.

Measurements of generalisation based on information geometry

Neural networks are statistical models and learning rules are estimators. In this paper a theory for measuring generalisation is developed by combining Bayesian decision theory with information geometry. The performance of an estimator is measured by the information divergence between the true distribution and the estimate, averaged over the Bayesian posterior. This unifies the majority of error measures currently in use. The optimal estimators also reveal some intricate interrelationships among information geometry, Banach spaces and sufficient statistics.

Bayesian invariant measurements of generalisation

The problem of evaluating different learning rules and other statistical estimators is analysed. A new general theory of statistical inference is developed by combining Bayesian decision theory with information geometry. It is coherent and invariant. For each sample a unique ideal estimate exists and is given by an average over the posterior. An optimal estimate within a model is given by a projection of the ideal estimate. The ideal estimate is a sufficient statistic of the posterior, so practical learning rules are functions of the ideal estimator. If the sole purpose of learning is to extract information from the data, the learning rule must also approximate the ideal estimator. This framework is applicable to both Bayesian and non-Bayesian methods, with arbitrary statistical models, and to supervised, unsupervised and reinforcement learning schemes.

Distributed control of computer communication systems

Flow control in Computer Communication systems is generally a multi-layered structure, consisting of several mechanisms operating independently at different levels. Evaluation of the performance of networks in which different flow control mechanisms act simultaneously is an important area of research, and is examined in depth in this thesis. This thesis presents the modelling of a finite resource computer communication network equipped with three levels of flow control, based on closed queueing network theory. The flow control mechanisms considered are: end-to-end control of virtual circuits, network access control of external messages at the entry nodes and the hop level control between nodes. The model is solved by a heuristic technique, based on an equivalent reduced network and the heuristic extensions to the mean value analysis algorithm. The method has significant computational advantages, and overcomes the limitations of the exact methods. It can be used to solve large network models with finite buffers and many virtual circuits. The model and its heuristic solution are validated by simulation. The interaction between the three levels of flow control are investigated. A queueing model is developed for the admission delay on virtual circuits with end-to-end control, in which messages arrive from independent Poisson sources. The selection of optimum window limit is considered. Several advanced network access schemes are postulated to improve the network performance as well as that of selected traffic streams, and numerical results are presented. A model for the dynamic control of input traffic is developed. Based on Markov decision theory, an optimal control policy is formulated. Numerical results are given and throughput-delay performance is shown to be better with dynamic control than with static control.

An application of strategic group theory to the UK pharmaceuticals industry

Conducts a strategic group mapping exercise by analysing R&D investment, sales/marketing cost and leadership information pertaining to the pharmaceuticals industry. Explains that strategic group mapping assists companies in identifying their principal competitors, and hence supports strategic decision-making, and shows that, in the pharmaceutical industry, R&D spending, the cost of sales and marketing, i.e. detailing, and technological leadership are mobility barriers to companies moving between sectors. Illustrates, in bubble-chart format, strategic groups in the pharmaceutical industry, plotting detailing-costs against the scale of activity in therapeutic areas. Places companies into 12 groups, and profiles the strategy and market-position similarities of the companies in each group. Concludes with three questions for companies to ask when evaluating their own, and their competitors, strategies and returns, and suggests that strategy mapping can be carried out in other industries, provided mobility barriers are identified.

Examining the strategy development process through the lens of complex adaptive systems theory

The development of strategy remains a debate for academics and a concern for practitioners. Published research has focused on producing models for strategy development and on studying how strategy is developed in organisations. The Operational Research literature has highlighted the importance of considering complexity within strategic decision making; but little has been done to link strategy development with complexity theories, despite organisations and organisational environments becoming increasingly more complex. We review the dominant streams of strategy development and complexity theories. Our theoretical investigation results in the first conceptual framework which links an established Strategic Operational Research model, the Strategy Development Process model, with complexity via Complex Adaptive Systems theory. We present preliminary findings from the use of this conceptual framework applied to a longitudinal, in-depth case study, to demonstrate the advantages of using this integrated conceptual model. Our research shows that the conceptual model proposed provides rich data and allows for a more holistic examination of the strategy development process. © 2012 Operational Research Society Ltd. All rights reserved.

Does stakeholder orientation matter? : empirical evidence about power and influence in local government decision-making

Despite being in the business agenda for almost thirty years, stakeholder management is still an under explored field in the public management context. The investigation presented in this doctoral thesis aims to ensure that stakeholder management is a useful technique able to raise issues about power and interests to public organisation’s strategic management processes. Stakeholder theory is tested in an exploratory study carried out with English Local Authorities whose focus is place on decision-making. The findings derive from two distinct and complementary studies: a cross-sectional survey undertaken with chief executives based on the quantitative approach and a qualitative investigation based on cross-sectional case studies and in-depth interviews of validation. While the first study aimed to produce a reliable and comprehensive list of stakeholders able to raise issues in decision-making, the second study aimed to depict the arena in which decision-making comes about. The findings indicate that local government decision-making is a multistakeholder process in which influences are exerted according to stakeholders’ power and interest. The findings also indicate that local government managers should take into account these tissues to avoid losing resources and legitimacy from its environmental supporters. Another issue raised by the investigation is related to the ethics upon which these types of relationships are based. According to the evidence gathered throughout the investigation, the formal model of accountability does not cover the whole set of stakeholders engaged in the process.

Decision-making algorithms in geometric modelling

Many of the applications of geometric modelling are concerned with the computation of well-defined properties of the model. The applications which have received less attention are those which address questions to which there is no unique answer. This thesis describes such an application: the automatic production of a dimensioned engineering drawing. One distinctive feature of this operation is the requirement for sophisticated decision-making algorithms at each stage in the processing of the geometric model. Hence, the thesis is focussed upon the design, development and implementation of such algorithms. Various techniques for geometric modelling are briefly examined and then details are given of the modelling package that was developed for this project, The principles of orthographic projection and dimensioning are treated and some published work on the theory of dimensioning is examined. A new theoretical approach to dimensioning is presented and discussed. The existing body of knowledge on decision-making is sampled and the author then shows how methods which were originally developed for management decisions may be adapted to serve the purposes of this project. The remainder of the thesis is devoted to reports on the development of decision-making algorithms for orthographic view selection, sectioning and crosshatching, the preparation of orthographic views with essential hidden detail, and two approaches to the actual insertion of dimension lines and text. The thesis concludes that the theories of decision-making can be applied to work of this kind. It may be possible to generate computer solutions that are closer to the optimum than some man-made dimensioning schemes. Further work on important details is required before a commercially acceptable package could be produced.

Real options in management and organizational strategy:a review of decision-making and performance implications

This paper contributes to the debate on the role of real options theory in business strategy and organizational decision-making. It analyses and critiques the decision-making and performance implications of real options within the management theories of the (multinational) firm, reviews and categorizes the organizational, strategic and operational facets of real options management in large business settings. It also presents the views of scholars and practitioners regarding the incorporation and validity of real options in strategy, international management and business processes. The focus is particularly on the decision-making and performance attributes of the real options logic concerning strategic investments, governance modes and multinational operations management. These attributes are examined from both strategic and operating perspectives of decision-making in organizations, also with an overview of the empirical evidence on real options decision-making and performance.

Philosophy, theory, and practice of green operations management

This paper proposes a more profound discussion of the philosophical underpins of sustainability than currently exists in the MOT literature and considers their influence on the construction of the theories on green operations and technology management. Ultimately, it also debates the link between theory and practice on this subject area. The paper is derived from insights gained in three research projects completed during the past twelve years, primarily involving the first author. From 2000 to 2002, an investigation using scenario analysis, aimed at reducing atmospheric pollution in urban centres by substituting natural gas for petrol and diesel, provided the first set of insights about public policy, environmental impacts, investment analysis, and technological feasibility. The second research project, from 2003 to 2005, using a survey questionnaire, was aimed at improving environmental performance in livestock farming and explored the issues of green supply chain scope, environmental strategy and priorities. Finally, the third project, from 2006 to 2011, investigated environmental decisions in manufacturing organisations through case study research and examined the underlying sustainability drivers and decision-making processes. By integrating the findings and conclusions from these projects, the link between philosophy, theory, and practice of green operations and technology management is debated. The findings from all these studies show that the philosophical debate seems to have little influence on theory building so far. For instance, although ‘sustainable development’ emphasises ‘meeting the needs of current and future generation’, no theory links essentiality and environmental impacts. Likewise, there is a weak link between theory and the practical issues of green operations and technology management. For example, the well-known ‘life-cycle analysis’ has little application in many cases because the life cycle of products these days is dispersed within global production and consumption systems and there are different stakeholders for each life cycle stage. The results from this paper are relevant to public policy making and corporate environmental strategy and decision making. Most of the past and current studies in the subject of green operations and sustainability management deal with only a single sustainability dimension at any one time. Here the value and originality of this paper lies in its integration between philosophy, theory, and practice of green technology and operations management.

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.

An empirical examination of the strategic decision-making process:the relationship between context, process, and outcomes

Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.