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.

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.

QoS-oriented resource allocation and scheduling of multiple composite Web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

Defoliation, nitrogen, and competition: effects on plant growth and resource allocation of Cleistogenes squarrosa and Artemisia frigida

Two species, Artemisia frigida Willd. (C-3, semishrub, and dominant on overgrazed sites) and Cleistogenes squarrosa (Trin.) Keng (C-4, perennial bunchgrass, and dominant or codominant on moderately grazed sites) were studied to determine the effects of defoliation, nitrogen (N) availability, competition, and their interactions on growth, biomass, and N allocation in a greenhouse experiment. The main treatments were: two nitrogen levels (NO = 0 mg N pot(-1), N1 = 60 mg N pot(-1)), two defoliation intensities (removing 60% of total aboveground biomass and no defoliation), and three competitive replacement series (monocultures of each species and mixtures at 0.5:0.5). Our results were inconsistent with our hypothesis on the adaptive mechanisms of A. frigida regarding the interactive effects of herbivory, N, and competition in determining its dominant position on overgrazed sites. Cleistogenes squarrosa will be replaced by A. frigida on over-grazed sites, although C. squarrosa had higher tolerance to defoliation than did A. frigida. Total biomass and N yield and N-15 recovery of C. squarrosa in mixed culture were consistently lower than in monocultures, whereas those of A. frigida grown in mixtures were consistently higher than in monocultures, suggesting higher competitive ability of A. frigida. Our results suggest that interspecific competitive ability may be of equal or greater importance than herbivory tolerance in determining herbivore-induced species replacement in semi-arid Inner Mongolian steppe. In addition, the dominance of A. frigida on overgrazed sites has been attributed to its ability to shift plant-plant interactions through (lap colonization, root niche differentiation, and higher resistance to water stress.

Capacity and resource allocation of cooperative MIMO in ad hoc networks

Cooperative MIMO (Multiple Input–Multiple Output) allows multiple nodes share their antennas to emulate antenna arrays and transmit or receive cooperatively. It has the ability to increase the capacity for future wireless communication systems and it is particularly suited for ad hoc networks. In this study, based on the transmission procedure of a typical cooperative MIMO system, we first analyze the capacity of single-hop cooperative MIMO systems, and then we derive the optimal resource allocation strategy to maximize the end-to-end capacity in multi-hop cooperative MIMO systems. The study shows three implications. First, only when the intra-cluster channel is better than the inter-cluster channel, cooperative MIMO results in a capacity increment. Second, for a given scenario there is an optimal number of cooperative nodes. For instance, in our study an optimal deployment of three cooperative nodes achieve a capacity increment of 2 bps/Hz when compared with direct transmission. Third, an optimal resource allocation strategy plays a significant role in maximizing end-to-end capacity in multi-hop cooperative MIMO systems. Numerical results show that when optimal resource allocation is applied we achieve more than 20% end-to-end capacity increment in average when compared with an equal resource allocation strategy.