Centralised or decentralised? Strategic implications of resource allocation models

This paper examines the strategic implications of resource allocation models (RAMs). Four interrelated aspects of resource allocation are discussed: degree of centralisation, locus of strategic direction, cross-subsidy, and locus of control. The paper begins with a theoretical overview of these concepts, locating the study in the contexts of both strategic management literature and the university. The concepts are then examined empirically, drawing upon a longitudinal study of three UK universities, Warwick, London School of Economics and Political Science (LSE), and Oxford Brookes. Findings suggest that RAMs are historically and culturally situated within the context of each university and this is associated with different patterns of strategic direction and forms of strategic control. As such, the RAM in use may be less a matter of best practice than one of internal fit. The paper concludes with some implications for theory and practice by discussing the potential trajectories of each type of RAM.

Dynamic models of energy allocation and investment

In dynamic models of energy allocation, assimilated energy is allocated to reproduction, somatic growth, maintenance or storage, and the allocation pattern can change with age. The expected evolutionary outcome is an optimal allocation pattern, but this depends on the environment experienced during the evolutionary process and on the fitness costs and benefits incurred by allocating resources in different ways. Here we review existing treatments which encompass some of the possibilities as regards constant or variable environments and their predictability or unpredictability, and the ways in which production rates and mortality rates depend on body size and composition and age and on the pattern of energy allocation. The optimal policy is to allocate resources where selection pressures are highest, and simultaneous allocation to several body subsystems and reproduction can be optimal if these pressures are equal. This may explain balanced growth commonly observed during ontogeny. Growth ceases at maturity in many models; factors favouring growth after maturity include non-linear trade-offs, variable season length, and production and mortality rates both increasing (or decreasing) functions of body size. We cannot yet say whether these are sufficient to account for the many known cases of growth after maturity and not all reasonable models have yet been explored. Factors favouring storage are also reviewed.

International comparison of resource allocation in health sciences : an analysis of expenditures on biomedical research in 19 industrialized countries /

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Benefits of all work and no play: The relationship between neuroticism and performance as a function of resource allocation

The authors evaluate a model suggesting that the performance of highly neurotic individuals, relative to their stable counterparts, is more strongly influenced by factors relating to the allocation of attentional resources. First, an air traffic control simulation was used to examine the interaction between effort intensity and scores on the Anxiety subscale of Eysenck Personality Profiler Neuroticism in the prediction of task performance. Overall effort intensity enhanced performance for highly anxious individuals more so than for individuals with low anxiety. Second, a longitudinal field study was used to examine the interaction between office busyness and Eysenck Personality Inventory Neuroticism in the prediction of telesales performance. Changes in office busyness were associated with greater performance improvements for highly neurotic individuals compared with less neurotic individuals. These studies suggest that highly neurotic individuals outperform their stable counterparts in a busy work environment or if they are expending a high level of effort.

Social Choice: Recent Developments

In the past quarter century, there has been a dramatic shift of focus in social choice theory, with structured sets of alternatives and restricted domains of the sort encountered in economic problems coming to the fore. This article provides an overview of some of the recent contributions to four topics in normative social choice theory in which economic modelling has played a prominent role: Arrovian social choice theory on economic domains, variable-population social choice, strategy-proof social choice, and axiomatic models of resource allocation.

Adaptive resource allocation for QoE-aware mobile communication networks

A real-time adaptive resource allocation algorithm considering the end user's Quality of Experience (QoE) in the context of video streaming service is presented in this work. An objective no-reference quality metric, namely Pause Intensity (PI), is used to control the priority of resource allocation to users during the scheduling process. An online adjustment has been introduced to adaptively set the scheduler's parameter and maintain a desired trade-off between fairness and efficiency. The correlation between the data rates (i.e. video code rates) demanded by users and the data rates allocated by the scheduler is taken into account as well. The final allocated rates are determined based on the channel status, the distribution of PI values among users, and the scheduling policy adopted. Furthermore, since the user's capability varies as the environment conditions change, the rate adaptation mechanism for video streaming is considered and its interaction with the scheduling process under the same PI metric is studied. The feasibility of implementing this algorithm is examined and the result is compared with the most commonly existing scheduling methods.

The role of trust in the resource allocation process of an old university

Allocation procedures, have attracted considerable interest among higher education institutions in recent years. Relevant previous research indicates that several universities adopt different approaches to the resource allocation problem, employing models and procedures that reflect their organisational arrangements and their internal socio – political dynamics. We argue that while studying accounting processes in their organisational context, the role of trust should also be considered carefully. In particular, it is very important to consider the attitudes of the individuals involved and interacting within organisational processes, and especially the trust between them, which plays an important role to the overall good governance of these processes. In our study, the role of interpersonal trust in an old Scottish University resource allocation process is examined. The study indicates that trust is a very necessary insight to the facilitation of social structures of accountability that enhance a better governance of the resource allocation process.

A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

Report of the Expert Group on Resource Allocation and Financing in the Health Sector

  Report of the Expert Group on Resource Allocation and Financing in the Health Sector Download this document (PDF 4.77mb) Alternatively, there is a lower resolution version available (PDF 2.31mb) Related Documents Resource Allocation, Financing and Sustainability in Health Care Evidence for the Expert Group on Resource Allocation and Financing in the Health Sector (Volume I) – PDF, 4.25mbAlternatively, a Lower Resolution version is available – PDF, 2.23mb Resource Allocation, Financing and Sustainability in Health Care Evidence for the Expert Group on Resource Allocation and Financing in the Health Sector (Volume II) – PDF 4.87mbAlternatively, a Lower Resolution version is available – PDF, 2.65mb Presentation by Professor, Frances Ruane Director , ESRI and Chair of the Expert Group. PDF 235KB Presentation by Professor Charles Normand, a member of the Expert Group. PDF 32KB

Population based resource allocation: The use of hybrid risk adjustment

The emphasis on integrated care implies new incentives that promote coordinationbetween levels of care. Considering a population as a whole, the resource allocation systemhas to adapt to this environment. This research is aimed to design a model that allows formorbidity related prospective and concurrent capitation payment. The model can be applied inpublicly funded health systems and managed competition settings.Methods: We analyze the application of hybrid risk adjustment versus either prospective orconcurrent risk adjustment formulae in the context of funding total health expenditures for thepopulation of an integrated healthcare delivery organization in Catalonia during years 2004 and2005.Results: The hybrid model reimburses integrated care organizations avoiding excessive risktransfer and maximizing incentives for efficiency in the provision. At the same time, it eliminatesincentives for risk selection for a specific set of high risk individuals through the use ofconcurrent reimbursement in order to assure a proper classification of patients.Conclusion: Prospective Risk Adjustment is used to transfer the financial risk to the healthprovider and therefore provide incentives for efficiency. Within the context of a National HealthSystem, such transfer of financial risk is illusory, and the government has to cover the deficits.Hybrid risk adjustment is useful to provide the right combination of incentive for efficiency andappropriate level of risk transfer for integrated care organizations.

Resource allocation analysis of the stochastic diffusion search

The Stochastic Diffusion Search (SDS) was developed as a solution to the best-fit search problem. Thus, as a special case it is capable of solving the transform invariant pattern recognition problem. SDS is efficient and, although inherently probabilistic, produces very reliable solutions in widely ranging search conditions. However, to date a systematic formal investigation of its properties has not been carried out. This thesis addresses this problem. The thesis reports results pertaining to the global convergence of SDS as well as characterising its time complexity. However, the main emphasis of the work, reports on the resource allocation aspect of the Stochastic Diffusion Search operations. The thesis introduces a novel model of the algorithm, generalising an Ehrenfest Urn Model from statistical physics. This approach makes it possible to obtain a thorough characterisation of the response of the algorithm in terms of the parameters describing the search conditions in case of a unique best-fit pattern in the search space. This model is further generalised in order to account for different search conditions: two solutions in the search space and search for a unique solution in a noisy search space. Also an approximate solution in the case of two alternative solutions is proposed and compared with predictions of the extended Ehrenfest Urn model. The analysis performed enabled a quantitative characterisation of the Stochastic Diffusion Search in terms of exploration and exploitation of the search space. It appeared that SDS is biased towards the latter mode of operation. This novel perspective on the Stochastic Diffusion Search lead to an investigation of extensions of the standard SDS, which would strike a different balance between these two modes of search space processing. Thus, two novel algorithms were derived from the standard Stochastic Diffusion Search, ‘context-free’ and ‘context-sensitive’ SDS, and their properties were analysed with respect to resource allocation. It appeared that they shared some of the desired features of their predecessor but also possessed some properties not present in the classic SDS. The theory developed in the thesis was illustrated throughout with carefully chosen simulations of a best-fit search for a string pattern, a simple but representative domain, enabling careful control of search conditions.

Structure and mechanism of diet specialisation: testing models of individual variation in resource use with sea otters

Studies of consumer-resource interactions suggest that individual diet specialisation is empirically widespread and theoretically important to the organisation and dynamics of populations and communities. We used weighted networks to analyze the resource use by sea otters, testing three alternative models for how individual diet specialisation may arise. As expected, individual specialisation was absent when otter density was low, but increased at high-otter density. A high-density emergence of nested resource-use networks was consistent with the model assuming individuals share preference ranks. However, a density-dependent emergence of a non-nested modular network for core resources was more consistent with the competitive refuge model. Individuals from different diet modules showed predictable variation in rank-order prey preferences and handling times of core resources, further supporting the competitive refuge model. Our findings support a hierarchical organisation of diet specialisation and suggest individual use of core and marginal resources may be driven by different selective pressures.