10 resultados para Non-agroproductive activities

em Aston University Research Archive


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In developed countries travel time savings can account for as much as 80% of the overall benefits arising from transport infrastructure and service improvements. In developing countries they are generally ignored in transport project appraisals, notwithstanding their importance. One of the reasons for ignoring these benefits in the developing countries is that there is insufficient empirical evidence to support the conventional models for valuing travel time where work patterns, particularly of the poor, are diverse and it is difficult to distinguish between work and non-work activities. The exclusion of time saving benefits may lead to a bias against investment decisions that benefit the poor and understate the poverty reduction potential of transport investments in Least Developed Countries (LDCs). This is because the poor undertake most travel and transport by walking and headloading on local roads, tracks and paths and improvements of local infrastructure and services bring large time saving benefits for them through modal shifts. The paper reports on an empirical study to develop a methodology for valuing rural travel time savings in the LDCs. Apart from identifying the theoretical and empirical issues in valuing travel time savings in the LDCs, the paper presents and discusses the results of an analysis of data from Bangladesh. Some of the study findings challenge the conventional wisdom concerning the time saving values. The Bangladesh study suggests that the western concept of dividing travel time savings into working and non-working time savings is broadly valid in the developing country context. The study validates the use of preference methods in valuing non-working time saving values. However, stated preference (SP) method is more appropriate than revealed preference (RP) method.

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This PhD thesis belongs to three main knowledge domains: operations management, environmental management, and decision making. Having the automotive industry as the key sector, the investigation was undertaken aiming at deepening the understanding of environmental decision making processes in the operations function. The central research question for this thesis is ?Why and how do manufacturing companies take environmental decisions? This PhD research project used a case study research strategy supplemented by secondary data analysis and the testing and evaluation of a proposed systems thinking model for environmental decision making. Interviews and focus groups were the main methods for data collection. The findings of the thesis show that companies that want to be in the environmental leadership will need to take environmental decisions beyond manufacturing processes. Because the benefits (including financial gain) of non-manufacturing activities are not clear yet the decisions related to product design, supply chain and facilities are fully embedded with complexity, subjectivism, and intrinsic risk. Nevertheless, this is the challenge environmental leaders will face - they may enter in a paradoxical state of their decisions – where although the risk of going greener is high, the risk of not doing it is even higher.

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This paper provides an understanding of the current environmental decision structures within companies in the manufacturing sector. Through case study research, we explored the complexity, robustness and decision making processes companies were using in order to cope with ever increasing environmental pressures and choice of environmental technologies. Our research included organisations in UK, Thailand, and Germany. Our research strategy was case study composed of different research methods, namely: focus group, interviews and environmental report analysis. The research methods and their data collection instruments also varied according to the access we had. Our unity of analysis was decision making teams and the scope of our investigation included product development, environment & safety, manufacturing, and supply chain management. This study finds that environmental decision making have been gaining importance over the time as well as complexity when it is starting to move from manufacturing to non,manufacturing activities. Most companies do not have a formal structure to take environmental decisions; hence, they follow a similar path of other corporate decisions, being affected by organizational structures besides the technical competence of the teams. We believe our results will help improving structures in both beginners and leaders teams for environmental decision making across the different departments.

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Increased competition, geographically expanded marketplaces, technology replication and an ever discerning consumer base, are reasons why companies need to regularly reappraise their competencies in terms of activities and functions they perform themselves. Where viable alternatives exist, companies should consider outsourcing of non-core activities and functions. Within SCM (Supply Chain Management) it could be preferable if a “one stop shop” existed for companies seeking to outsource functions identified as non-core. “Traditionally” structured LSP’s who have concentrated their service offer around providing warehousing and transport activities are potentially at a crossroads – clients and potential clients requiring “new” services which could increase LSP’s revenues if provided, whilst failure to provide could perhaps result in clients seeking outsourced services elsewhere.

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This thesis explores the strategic positioning [SP] activities of charitable organizations [COs] within the wider sector of voluntary and non-profit organizations [VNPOs] in the UK. Despite the growing interest in SP for British COs in an increasingly competitive operating environment and changing policy context, there is lack of research in mainstream marketing/strategic management studies on this topic for charities, whilst the specialist literature on VNPOs has neglected the study of SP. The thesis begins with an extended literature review of the concept of positioning in both commercial [for-profit] and charitable organizations. It concludes that the majority of theoretical underpinnings of SP that are prescribed for COs have been derived from the commercial strategy/marketing literature. There is currently a lack of theoretical and conceptual models that can accommodate the particular context of COs and guide strategic positioning practice in them. The research contained in this thesis is intended to fill some of these research gaps. It combines an exploratory postal survey and four cross-sectional case studies to describe the SP activities of a sample of general welfare and social care charities and identifies the key factors that influence their choice of positioning strategies [PSs]. It concludes that charitable organizations have begun to undertake SP to differentiate their organizations from other charities that provide similar services. Their PSs have both generic features, and other characteristics that are unique to them. A combination of external environmental and organizational factors influences their choice of PSs. A theoretical model, which depicts these factors, is developed in this research. It highlights the role of governmental influence, other external environmental forces, the charity’s mission, organizational resources, and influential stakeholders in shaping the charity’s PS. This study concludes by considering the theoretical and managerial implications of the findings on the study of charitable and non-profit organizations.

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This thesis applies a hierarchical latent trait model system to a large quantity of data. The motivation for it was lack of viable approaches to analyse High Throughput Screening datasets which maybe include thousands of data points with high dimensions. High Throughput Screening (HTS) is an important tool in the pharmaceutical industry for discovering leads which can be optimised and further developed into candidate drugs. Since the development of new robotic technologies, the ability to test the activities of compounds has considerably increased in recent years. Traditional methods, looking at tables and graphical plots for analysing relationships between measured activities and the structure of compounds, have not been feasible when facing a large HTS dataset. Instead, data visualisation provides a method for analysing such large datasets, especially with high dimensions. So far, a few visualisation techniques for drug design have been developed, but most of them just cope with several properties of compounds at one time. We believe that a latent variable model (LTM) with a non-linear mapping from the latent space to the data space is a preferred choice for visualising a complex high-dimensional data set. As a type of latent variable model, the latent trait model can deal with either continuous data or discrete data, which makes it particularly useful in this domain. In addition, with the aid of differential geometry, we can imagine the distribution of data from magnification factor and curvature plots. Rather than obtaining the useful information just from a single plot, a hierarchical LTM arranges a set of LTMs and their corresponding plots in a tree structure. We model the whole data set with a LTM at the top level, which is broken down into clusters at deeper levels of t.he hierarchy. In this manner, the refined visualisation plots can be displayed in deeper levels and sub-clusters may be found. Hierarchy of LTMs is trained using expectation-maximisation (EM) algorithm to maximise its likelihood with respect to the data sample. Training proceeds interactively in a recursive fashion (top-down). The user subjectively identifies interesting regions on the visualisation plot that they would like to model in a greater detail. At each stage of hierarchical LTM construction, the EM algorithm alternates between the E- and M-step. Another problem that can occur when visualising a large data set is that there may be significant overlaps of data clusters. It is very difficult for the user to judge where centres of regions of interest should be put. We address this problem by employing the minimum message length technique, which can help the user to decide the optimal structure of the model. In this thesis we also demonstrate the applicability of the hierarchy of latent trait models in the field of document data mining.

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This article investigates how firms manage outsourcing in situations of a non-developed supplier market. This study followed the initial outsourcing activities and strategies of two case companies in the wood product manufacturing industry. The findings show that greater focus needs to be placed on operational aspects associated with non-developed supplier markets, which contrasts with the traditional strategic view of outsourcing. For practitioners, this article suggests that it is important to emphasise that the learning curve for a supplier can be lengthy, and also that alternative outsourcing routes are available when outsourcing to a non-developed supplier market.

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The firm is becoming more and more inclusive in its conception. And yet, marketing studies point to the same overwhelming conclusion that marketing, marketing departments and marketers are being increasingly 'pushed out' - excluded. We argue that where and when inclusion-exclusion intersect in the practice of strategic marketing is important, not least because their powerful boundary-setting and spanning roles have a determinant effect on the places and spaces, within which marketing strategists are (counter-) mobilized. This paper provides new insights relating to the contradictory forces existing around inclusion-exclusion in corporate strategizing. A further aim is to present the position of marketing (non-) influence within this context. The paper provides a unique theoretical contribution by illustrating some of the contradictions, struggles and activities that make the theoretical shift towards strategic inclusivity unstable, partial and by no means inevitable. A further contribution is a linking of this broader strategic debate, with anxieties over the influence of marketing in corporate strategizing. This leads to a discussion of the various ways that marketing research can sooth the anxiety of influence on multiple fronts via: understanding agency and strategic action; shaping marketing curriculum development; and, reconsidering the spatial dimensions of marketing influence. © 2010 Taylor & Francis.

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The Securities and Exchange Commission (SEC) in the United States and in particular its immediately past chairman, Christopher Cox, has been actively promoting an upgrade of the EDGAR system of disseminating filings. The new generation of information provision has been dubbed by Chairman Cox, "Interactive Data" (SEC, 2006). In October this year the Office of Interactive Disclosure was created(http://www.sec.gov/news/press/2007/2007-213.htm). The focus of this paper is to examine the way in which the non-professional investor has been constructed by various actors. We examine the manner in which Interactive Data has been sold as the panacea for financial market 'irregularities' by the SEC and others. The academic literature shows almost no evidence of researching non-professional investors in any real sense (Young, 2006). Both this literature and the behaviour of representatives of institutions such as the SEC and FSA appears to find it convenient to construct this class of investor in a particular form and to speak for them. We theorise the activities of the SEC and its chairman in particular over a period of about three years, both following and prior to the 'credit crunch'. Our approach is to examine a selection of the policy documents released by the SEC and other interested parties and the statements made by some of the policy makers and regulators central to the programme to advance the socio-technical project that is constituted by Interactive Data. We adopt insights from ANT and more particularly the sociology of translation (Callon, 1986; Latour, 1987, 2005; Law, 1996, 2002; Law & Singleton, 2005) to show how individuals and regulators have acted as spokespersons for this malleable class of investor. We theorise the processes of accountability to investors and others and in so doing reveal the regulatory bodies taking the regulated for granted. The possible implications of technological developments in digital reporting have been identified also by the CEO's of the six biggest audit firms in a discussion document on the role of accounting information and audit in the future of global capital markets (DiPiazza et al., 2006). The potential for digital reporting enabled through XBRL to "revolutionize the entire company reporting model" (p.16) is discussed and they conclude that the new model "should be driven by the wants of investors and other users of company information,..." (p.17; emphasis in the original). Here rather than examine the somewhat illusive and vexing question of whether adding interactive functionality to 'traditional' reports can achieve the benefits claimed for nonprofessional investors we wish to consider the rhetorical and discursive moves in which the SEC and others have engaged to present such developments as providing clearer reporting and accountability standards and serving the interests of this constructed and largely unknown group - the non-professional investor.

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Specification of the non-functional requirements of applications and determining the required resources for their execution are activities that demand a great deal of technical knowledge, frequently resulting in an inefficient use of resources. Cloud computing is an alternative for provisioning of resources, which can be done using either the provider's own infrastructure or the infrastructure of one or more public clouds, or even a combination of both. It enables more flexibly/elastic use of resources, but does not solve the specification problem. In this paper we present an approach that uses models at runtime to facilitate the specification of non-functional requirements and resources, aiming to facilitate dynamic support for application execution in cloud computing environments with shared resources. © 2013 IEEE.