996 resultados para Onward moves


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Mode of access: Internet.

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Signatures= 1-25⁶, 26⁵

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Mode of access: Internet.

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Prepared under the auspices of the Survey Research Center.

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This study examines the relationship between the number of prior moves, time living in an area and psychological reactions of employees undergoing job relocation. Relocating employees from a single organization completed questionnaires on average six weeks before and 10 weeks after their move. Results show that the greater the number of prior moves the lower was the reported stress following the move. However, the relationship between number of prior moves and well-being also followed a quadratic trend such that those with few and those with many prior moves reported the greatest stress. Furthermore, the longer the relocator had lived in the area prior to moving, the greater was the general stress and the job-related anxiety and depression following the move.

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Introduction to special issue: The JCMS Annual Review of the European Union in 2010

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This paper adds to the growing literature on endogenous timing of decisions in duopolies. We show for a price-setting duopoly game with sufficiently asymmetric and strictly convex cost functions that the less efficient firm moves first while the more efficient moves second with a higher price than the less efficient firm.

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We determine the endogenous order of moves in which the firms set their prices in the framework of a capacity-constrained Bertrand-Edgeworth triopoly. A three-period timing game that determines the period in which the firms announce their prices precedes the price-setting stage. We show for the non-trivial case (in which the Bertrand-Edgeworth triopoly has only an equilibrium in non-degenerated mixed-strategies) that the firm with the largest capacity sets its price first, while the two other firms set their prices later. Our result extends a finding by Deneckere and Kovenock (1992) from duopolies to triopolies. This extension was made possible by Hirata's (2009) recent advancements on the mixed-strategy equilibria of Bertrand-Edgeworth games.

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Using transcripts of chatroom grooming interactions, this paper explores and evaluates the usefulness of Swales’ (1981) move analysis framework in contributing to the current understanding of online grooming processes. The framework is applied to seven transcripts of grooming interactions taken from perverted-justice.com. The paper presents 14 identified rhetorical moves used in chatroom grooming and explores the broad structures that grooming conversations take by presenting these structures as colour-coded visualisations which we have termed “move maps”. It also examines how some individual linguistic features are used to realise a single move termed “Assessing and Managing Risk”. The findings suggest that move analysis can usefully contribute in two key ways: determining communicative functions associated with 'grooming language' and the visualisation of variation between grooming interactions.

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The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.