The overall research theme of this thesis is to analyse, from both a theoretical and an empirical perspective, how Operational Research modelling can be used in support of public sector performance measurement. The thesis includes four papers written by Van der Meer together with a variety of co-authors. Three of these papers discuss the application of a variety of OR models - in particular, Logistic Regression Analysis, Stochastic Frontier Analysis, Data Envelopment Analysis and Bayesian Belief Networks - relating to the performance of the Maritime and Coastguard Agency in coordinating Search And Rescue services around the UK coast. The fourth paper discusses the application of Discrete Event Simulation to support performance measurement in a Musculo-Skeletal Unit operating across two Glasgow hospitals that are both part of NHS Scotland. The thesis investigates five research questions, all of which can be directly traced back to the overall research theme. The evidence base for the investigation consists of the papers referred to above, in conjunction with a wide range of sources from the academic and professional literature. The conclusions may be briefly summarised as follows. First, there are five specific problems and challenges for performance measurement in public service organisations. Second, there are at least two categories of OR modelling approaches that can play an important role in support of public sector performance measurement; namely, models for measuring performance differentials and models for understanding the cause-and-effect relationships driving such performance differentials. Third, while there are advantages to a multimethodology approach to OR modelling, there are also a number of barriers (including paradigm incommensurability). Fourth, the adoption of Critical Realism as a philosophical basis for combining different OR models can resolve problems of paradigm incommensurability. Fifth, OR models that are founded on a realist ontology should be validated according to two specific groups of criteria.

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The potential benefits of logic-based modeling methods encourage business organizations to construct models offering flexible knowledge representation supported by correct and effective inference. However, owing to the problems of encoding expertise, the ambiguities in model executions, and the diversity of evaluation methods, there is no clear consensus on how best to apply logic-based formalization to existing informal or semi-formal modeling methods. This thesis facilitates formal business model specifications by establishing a generic business mode ling framework named GBMF which is declarative, context-independent, implementable and expressive for modeling high-level aspects of business. Within GBMF, business goals and activities, entities and relations, rules and strategies are expressible transparently using a repertoire of primitive constructs without requiring overly-burdensome programming effort. Execution logic of GBMF plans, entity constraints, plan-asset dependencies, process rules and defined controls are able to manipulate upon those constructs to manage business execution in a desirable way. Representing, formulating and implementing business model consistently with logic programming formalisms give the advantages of general-purpose expressiveness and well-understood execution regimes, so avoiding the need for either being confined to a specific phase of modeling lifecycle or supporting a specialized modeling language. Clear semantics and simple syntax of the core GBMF paves the way for further exploiting on quick prototyping, analytical simulation and functional extension. Case studies selected from a traditional business and an e-business demonstrate that GBMF can capture essential semantics. During the simulation of the instantiated business, related information at various levels of abstraction and detail can be retrieved and inferred with attendant logic reasoning mechanisms. A hybrid evaluation method is also provided to evaluate GBMF from multiple perspectives. Future work based on GBMF will be a graphical interface extension and inter-translations with other modeling techniques.

Problem structuring methods (PSMs) have been developed within operational research (OR) to assist a set of actors to agree on a problem structure and make commitments to consequential action. Their characteristic feature is the use of a model to represent alternative versions of the problem of common interest, combined with facilitation to help actors make constructive mutual adjustments. Whilst most PSMs have traditionally been applied with actors confronting problems within organizations, others have also been applied with actors working between and across organisations to address a problem of common interest. This research will explore the significance of PSMs in collaborative contexts of this kind. The aim of this research is to investigate the possible roles of PSMs in assisting actors of an inter-organisational domain who engage in collaboration to address a problematique of common interest in order to reach joint agreements with respect to it. The hypothesis investigated in this research is that the analytical assistance provided by PSMs can be expected to contribute to a collaboration process principally through improving actors' sense-making of their problematique, and through providing structure to the product of this sense- making activity. The interpretation of our hypothesis is that PSMs generate this effect through improving the quality of dialogue between actors. This effect should tend to impact positively on the ownership of the commitments resulting from the dialogue, and on mutual accommodations in the power balance among actors. In order to articulate this hypothesis, it has been necessary to conduct some conceptual clarification to achieve a clear meaning for the terms 'shared meaning', 'power', and 'dialogue'. Building upon this conceptual clarification, a model of collaboration as a process has been developed, which identifies the factors, pre-requisites and processes involved in actors' ability to achieve the intended products of collaboration. This model provides the basis for identifying the possible effects of PSMs, and for evaluating their effectiveness. To explore our hypothesis and the adequacy of the conceptual model, a case study drawn from an action research project in the UK construction industry was carried out. This action research project was industry-academic collaboration aimed at contributing to build a high value construction environment, and its principal output was the development of a PSM-based methodology for construction project reviews. The case study reported in this thesis involved the application of this methodology in a multi-organizational construction partnership in the hotel business. This involved engagement in and observation of ongoing partnership activity of three construction project teams. Reasonably clear and positive effects from the application of the methodology were found in the dialogue between participants, consistent with the hypothesis. Additional positive effects in terms of achieving inter-organisational learning within the selected partnership were also identified. Overall the results of the case study are encouraging; however, as they result from the application of a particular PSM-based methodology, extrapolation to more general conclusions about the potential of PSMs for multi-organisational collaboration should be made with caution. Nevertheless, the results of this research suggest valuable potential avenues for further research. The case experience also was generally supportive of the conceptual model of the collaboration process, in that the activities and processes observed could be interpreted without difficulties within the model's framework. The model offers a means for further theoretical and empirical work aimed at confirming and enriching its structure and validity.

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The operational reliability of organizations that deal on a routine basis with very dynamic circumstances has been a rich domain of study for organizational scholars for many years. Increasing reliance on the application of complex technologies and human processes in a range of social endeavour provokes our need to understand the attributes of such processes. Traditional contingency theoretic perspectives tend to produce archetypal resolutions that identify in rather specific terms what organizational forms can be matched with particular environmental characteristics. But as the organizational environment becomes more dynamic this approach seems less credible. This research therefore moves beyond the search for archetypes to investigate the processes by which resources are configured in order to deal with dynamic circumstances. Further, with self-managed teams increasingly acknowledged to be central to performance, contributing to fast, flexible and creative action and therefore used as the fundamental work group, this study focuses on the meso-level of the team. This helps to limit the scope of the research task while still offering opportunities for good theoretical and practical contribution. Adopting a grounded, qualitative methodology it triangulates evidence from three dissimilar domains (accident and emergency, air traffic control and fire service) that share a common context of unpredictability, high velocity and error sensitivity. The findings identify a specific type of situated behaviour, termed agile configuration, by which team members configure remarkably flexible and reliable behaviours in very dynamic situations, suggesting an almost limitless range of potential configuring behaviours that avoid the limitations of configurational archetypes. The adduced models and explanations provide theoretical insights that increase understanding of behaviour in extreme contingencies and therefore advance traditional contingency theoretic perspectives, with particular relevance for concepts of dynamic capability. These outcomes also have practical potential for the development of agile configuration competence in self managed teams and larger organizational groupings.

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The thesis investigates the possibility of using simulation for understanding and improving the design of decision making in a real context. The approach is based on the problem of representing decision making behaviour in Discrete Event Simulation. An investigation of existing techniques led to the design of a methodology known as Knowledge Based Improvement (KBI). The KBI covers the key stages of the process of using simulation for understanding and improving the design of decision making. Using a research strategy that involves a case study in Ford, the research tests each stage of KBI. The thesis explains how simulation can be used for understanding real decision making problems and for collecting the data required for modelling individual decision making strategies. The thesis demonstrates the possibility of a simulation based knowledge elicitation in a real context and it investigates the practical difficulties involved in this process. The research tests the process of understanding decision making policies by modelling specific decision makers using Artificial Intelligence. It tests the use of simulation for assessing the decision making strategies and it shows that simulation can be used for identifying efficient strategies and for improving the design of decision making practices. The thesis reports the degree of success of the approach in relation to the data that were collected and it describes the validation checks that were undertaken. In addition, it reports the lessons learned from the application of the KBI methodology, the overall success of the approach and the main limitations that were identified during the implementation.