Human resource allocation in a call centre

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Capital and asset structures and their influence on the performance of Egyptian nationalised industries:an application of financial statement analysis and survey

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Intellectual property asset management:how to identify, protect, manage and exploit intellectual property within the business environment

In the new ‘knowledge-intensive economies’ Intellectual assets increasingly play a key part on balance sheets. There is an increasing global awareness that in order to promote innovation and the growth of the economy, businesses must fully recognise and exploit their intellectual assets. A company’s ability to innovate rapidly and successfully is now regarded as essential and most breakthroughs are made by Small and Medium-sized Enterprises (SMEs), usually with no in-house legal professionals to help them. It is essential that those working with or creating intellectual property rights (IPR) are aware of the basics of Intellectual Property Law. Intellectual Property Asset Management provides business and management students at all levels with an accessible-straight-forward explanation of what the main Intellectual Property rights are and how these rights are protected. Locating the subject squarely in a business context and using case studies and examples throughout drawn from a wide range of business organisations, it explains how an organisation can exploit their rights through licensing, franchising and other means in order to make the best possible use of their IP assets. This book will provide students with: • the basic Intellectual Property law knowledge needed to identify a potential IP issue • the tools and understanding to assess an IP breach • the ability to identify where the problem cannot be solved in house and where expert legal assistance is required • the knowledge required to work effectively with lawyers and other legal professionals to achieve the desired outcome

Distributed sequential task allocation in foraging swarms

When designing a practical swarm robotics system, self-organized task allocation is key to make best use of resources. Current research in this area focuses on task allocation which is either distributed (tasks must be performed at different locations) or sequential (tasks are complex and must be split into simpler sub-tasks and processed in order). In practice, however, swarms will need to deal with tasks which are both distributed and sequential. In this paper, a classic foraging problem is extended to incorporate both distributed and sequential tasks. The problem is analysed theoretically, absolute limits on performance are derived, and a set of conditions for a successful algorithm are established. It is shown empirically that an algorithm which meets these conditions, by causing emergent cooperation between robots can achieve consistently high performance under a wide range of settings without the need for communication. © 2013 IEEE.

Evolutionary market agents for resource allocation in decentralised systems

We introduce self-interested evolutionary market agents, which act on behalf of service providers in a large decentralised system, to adaptively price their resources over time. Our agents competitively co-evolve in the live market, driving it towards the Bertrand equilibrium, the non-cooperative Nash equilibrium, at which all sellers charge their reserve price and share the market equally. We demonstrate that this outcome results in even load-balancing between the service providers. Our contribution in this paper is twofold; the use of on-line competitive co-evolution of self-interested service providers to drive a decentralised market towards equilibrium, and a demonstration that load-balancing behaviour emerges under the assumptions we describe. Unlike previous studies on this topic, all our agents are entirely self-interested; no cooperation is assumed. This makes our problem a non-trivial and more realistic one.

Systematic financial resources allocation processes:a model for critical resources mobilization and deployment for nigerian universities

Purpose – The purpose of this research is to study the perceived impact of some factors on the resources allocation processes of the Nigerian universities and to suggest a framework that will help practitioners and academics to understand and improve such processes. Design/methodology/approach – The study adopted the interpretive qualitative approach aimed at an ‘in-depth’ understanding of the resource allocation experiences of key university personnel and their perceived impact of the contextual factors affecting such processes. The analysis of individual narratives from each university established the conditions and factors impacting the resources allocation processes within each institution. Findings – The resources allocation process issues in the Nigerian universities may be categorised into people (core and peripheral units’ challenge, and politics and power); process (resources allocation processes); and resources (critical financial shortage and resources dependence response). The study also provides insight that resourcing efficiency in Nigerian universities appears strongly constrained by the rivalry among the resource managers. The efficient resources allocation process (ERAP) model is proposed to resolve the identified resourcing deficiencies. Research limitations/implications – The research is not focused to provide generalizable observations but ‘in-depth’ perceived factors and their impact on the resources allocation processes in Nigerian universities. The study is limited to the internal resources allocation issues within the universities and excludes the external funding factors. The resource managers’ responses to the identified factors may affect their internal resourcing efficiency. Further research using more empirical samples is required to obtain more widespread results and the implications for all universities. Originality/value – This study contributes a fresh literature framework to resources allocation processes focusing at ‘people’, ‘process’ and ‘resources’. Also a middle range theory triangulation is developed in relation to better understanding of resourcing process management. The study will be of interest to university managers and policy makers.

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.

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.

Aid allocation of the emerging Central and Eastern European donors

This paper examines the main characteristics of the (re-)emerging foreign aid policies of the Visegrád countries (the Czech Republic, Hungary, Poland, Slovakia), concentrating on the allocation of their aid resources. I adopt an econometric approach, similar to the ones used in the literature, for analysing the aid allocation of the OECD DAC donors. Using this approach, I examine the various factors that influence aid allocation of the Visegrád countries, using data for the years between 2001 and 2008. The most important conclusion is that the amount of aid a partner country gets from the four emerging donors is not influenced by the level of poverty or the previous performance of the recipients (measured by the level of economic growth or the quality of institutions). The main determining factor seems to be geographic proximity, as countries in the Western Balkans and the Post-Soviet region receive much more aid from the Visegrád countries than other recipients. Historical ties (pre-1989 development relations) and international obligations in the cases of Afghanistan and Iraq are also found to be significant explanatory factors. This allocation is in line with the foreign political and economic interests of these new donors. Although there are clear similarities between the four donors, this paper also identifies some individual country characteristics.

Self-affinity in financial asset returns

We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns. © 2012 Elsevier Inc. All rights reserved.

An Electromagnetism Metaheuristic for the Uncapacitated Multiple Allocation Hub Location Problem

In this article, the results achieved by applying an electromagnetism (EM) inspired metaheuristic to the uncapacitated multiple allocation hub location problem (UMAHLP) are discussed. An appropriate objective function which natively conform with the problem, 1-swap local search and scaling technique conduce to good overall performance.Computational tests demonstrate the reliability of this method, since the EM-inspired metaheuristic reaches all optimal/best known solutions for UMAHLP, except one, in a reasonable time.

Variable Neighborhood Search for Solving the Capacitated Single Allocation Hub Location Problem

In this paper a Variable Neighborhood Search (VNS) algorithm for solving the Capacitated Single Allocation Hub Location Problem (CSAHLP) is presented. CSAHLP consists of two subproblems; the first is choosing a set of hubs from all nodes in a network, while the other comprises finding the optimal allocation of non-hubs to hubs when a set of hubs is already known. The VNS algorithm was used for the first subproblem, while the CPLEX solver was used for the second. Computational results demonstrate that the proposed algorithm has reached optimal solutions on all 20 test instances for which optimal solutions are known, and this in short computational time.