22 resultados para J22 - Time Allocation and Labor Supply

em Aston University Research Archive


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Despite recent research on time (e.g. Hedaa & Törnroos, 2001), consideration of the time dimension in data collection, analysis and interpretation in research in supply networks is, to date, still limited. Drawing on a body of literature from organization studies, and empirical findings from a six-year action research programme and a related study of network learning, we reflect on time, timing and timeliness in interorganizational networks. The empirical setting is supply networks in the English health sector wherein we identify and elaborate various issues of time, within the case and in terms of research process. Our analysis is wide-ranging and multi-level, from the global (e.g. identifying the notion of life cycles) to the particular (e.g. different cycle times in supply, such as daily for deliveries and yearly for contracts). We discuss the ‘speeding up’ of inter-organizational ‘e’ time and tensions with other time demands. In closing the paper, we relate our conclusions to the future conduct of the research programme and supply research more generally, and to the practice of managing supply (in) networks.

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This paper addresses the question of how just-in-time can be implemented within high variety manufacture. To illustrate some of the principles in relation to the high variety-low volume situation the case of a computer manufacturer is considered in detail. For contrast the paper also considers the case of the manufacture of highly-configured four wheel drive vehicles where both variety and volumes are high. The most important issue in high variety/low volume production is that JIT operation should be seen in terms of the tactical holding of inventory in upstream buffers within the supply chain so that value is not added to work in progress prematurely. Tactical buffers ensure that service levels are maintained and the risk of stock-outs is minimized. In high variety/high volume production schedule integrity is the key factor, unreliable schedules being a major inhibitor to the introduction of JIT.

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Deep hole drilling is one of the most complicated metal cutting processes and one of the most difficult to perform on CNC machine-tools or machining centres under conditions of limited manpower or unmanned operation. This research work investigates aspects of the deep hole drilling process with small diameter twist drills and presents a prototype system for real time process monitoring and adaptive control; two main research objectives are fulfilled in particular : First objective is the experimental investigation of the mechanics of the deep hole drilling process, using twist drills without internal coolant supply, in the range of diarneters Ø 2.4 to Ø4.5 mm and working length up to 40 diameters. The definition of the problems associated with the low strength of these tools and the study of mechanisms of catastrophic failure which manifest themselves well before and along with the classic mechanism of tool wear. The relationships between drilling thrust and torque with the depth of penetration and the various machining conditions are also investigated and the experimental evidence suggests that the process is inherently unstable at depths beyond a few diameters. Second objective is the design and implementation of a system for intelligent CNC deep hole drilling, the main task of which is to ensure integrity of the process and the safety of the tool and the workpiece. This task is achieved by means of interfacing the CNC system of the machine tool to an external computer which performs the following functions: On-line monitoring of the drilling thrust and torque, adaptive control of feed rate, spindle speed and tool penetration (Z-axis), indirect monitoring of tool wear by pattern recognition of variations of the drilling thrust with cumulative cutting time and drilled depth, operation as a data base for tools and workpieces and finally issuing of alarms and diagnostic messages.

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This chapter investigates the resistance by institutional actors in ambiguous supply chain environments for online grocery provision. Recent studies have shown that significant shifts in urban geographies are increasing consumers' expectations of online retail provision. However, at the same time there is also growing evidence that the collaborative practice in online grocery provision within the urban supply chains is resisted. That these trends are found despite growing demand of online provision highlights both the difficulty of bringing geographically dispersed supply partners together and the problems associated with operating within and across ambiguous environments. Drawing upon twenty-nine in-depth interviews with a range of institutional actors, including retail, logistics, and urban planning experts within an urban metropolis in an emerging market, we detail the different ways that collaboration is resisted in online retail provision. Several different patterns of resistance were identified in (non-) collaboration notably, ideological, functional, regulatory and spatial. © 2011, IGI Global. C.

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Supply chains are advocated widely as being the new units for commercial competition and developments have made the sharing of supply chain wide information increasingly common. Most organisations however still make operational decisions intended to maximise local organisational performance. With improved information sharing a holistic focus for operational decisions should now be possible. The development of a pan supply chain performance framework requires an examination of the conditions under which holistic-decisions provide benefits to either the individual enterprise or the complete supply chain. This paper presents the background and supporting methodology for a study of the impact of an overall supply chain performance metric framework upon local logistics decisions and the conditions under which such a framework would improve overall supply chain performance. The methodology concludes a simulation approach using a functionally extended Gensym's e-SCOR model, together with case based triangulation, to be optimum. Copyright © 2007 Inderscience Enterprises Ltd.

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We present an implementation of the domain-theoretic Picard method for solving initial value problems (IVPs) introduced by Edalat and Pattinson [1]. Compared to Edalat and Pattinson's implementation, our algorithm uses a more efficient arithmetic based on an arbitrary precision floating-point library. Despite the additional overestimations due to floating-point rounding, we obtain a similar bound on the convergence rate of the produced approximations. Moreover, our convergence analysis is detailed enough to allow a static optimisation in the growth of the precision used in successive Picard iterations. Such optimisation greatly improves the efficiency of the solving process. Although a similar optimisation could be performed dynamically without our analysis, a static one gives us a significant advantage: we are able to predict the time it will take the solver to obtain an approximation of a certain (arbitrarily high) quality.

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A scintillation proximity assay (SPA) has been used successfully to detect and quantify, in real-time, the kinetic progress of hydrolysis of [ H]acetate esters from scintillant-containing styrenic and poly(ethylene glycol) (PEG)-based polymer supports in both organic and aqueous media.

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The tendency of managers to focus on short-term results rather than on sustained company success is of particular importance to retail marketing managers, because marketing activities involve expenditures which may only pay off in the longer term. To address the issue of myopic management, our study shows how the complexity of the service profit chain (SPC) can cause managers to make suboptimal decisions. Hence, our paper departs from past research by recognizing that understanding the temporal interplay between operational investments, employee satisfaction, customer satisfaction, and operating profit is essential to achieving sustained success. In particular, we intend to improve understanding of the functioning of the SPC with respect to time lags and feedback loops. Results of our large-scale longitudinal study set in a multi-outlet retail chain reveal time-lag effects between operational investments and employee satisfaction, as well as between customer satisfaction and performance. These findings, along with evidence of a negative interaction effect of employee satisfaction on the relationship between current performance and future investments, show the substantial risk of mismanaging the SPC. We identify specific situations in which the dynamic approach leads to superior marketing investment decisions, when compared to the conventional static view of the SCP. These insights provide valuable managerial guidance for effectively managing the SPC over time. © 2012 New York University.

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Wider scientific community now accept that the threat of climate change as real and thus acknowledge the importance of implementing adaptation measures in a global context. In the UK , the physical effects of climate change are likely to be directly felt in the form of extreme weather events, which are predicted to escalate in number and severity in future under the changing climatic conditions. Construction industry; which consists of supply chains running across various other industries, economies and regions, will also be affected due to these events. Thus, it is important that the construction organisations are well prepared to withstand the effects of extreme weather events not only directly affecting their organisations but also affecting their supply chains which in turn might affect the organisation concerned. Given the fact that more than 99% of construction sector businesses are SMEs, the area can benefit significantly from policy making to improve SME resilience and coping capacity. This paper presents the literature review and synthesis of a doctoral research study undertaken to address the issue of extreme weather resilience of construction sector SMEs and their supply chains. The main contribution of the paper to both academia and practitioners is a synthesis model that conceptualises the factors that enhances resilience of SMEs and their supply chains against extreme weather events. This synthesis model forms the basis of a decision making framework that will enable SMEs to both reduce their vulnerability and enhance their coping capacity against extreme weather. The value of this paper is further extended by the overall research design that is set forth as the way forward.

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In the UK public sector, procurement decisions for outsourced services are usually taken at a local level, for example by a hospital trust or a local government authority. Cumulatively, these fragmented decisions can lead to ‘imbalanced’ supply markets (too few or too many suppliers), to the detriment of both suppliers and purchasers. This paper considers what can be done to manage imbalanced supply markets resulting from the fragmented procurement of outsourced services across a sector, using the case of the English National Health Service. The types and levels of action available within the health sector are explored.

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Projections into future increasingly suggest that the intensity and frequency of Extreme Weather Events (EWEs) will increase in the future. This has demanded the business organisations as well to be prepared to face the increasing risk of EWEs, in order to ensure their business continuity. However, current evidence base suggests that businesses, especially SMEs, are not adequately prepared to face the threat of such events. Ability to adequately prepare them has been hindered by the lack of in depth studies addressing this issue. The paper presents a doctoral study designed to investigate the resilience of SMEs operating in the construction sector; which is said to be a highly vulnerable sector for the impacts of EWEs, and their supply chains to EWEs. A conceptual framework developed to investigate this issue is presented and explained. It is argued that the resilience of construction SMEs and their supply chains against EWEs can be improved by a combination of reducing their vulnerability, enhancing coping capacity and implementing coping mechanisms. Importance of undertaking a broader view to include the whole supply chain in making business decisions with regard to EWEs by SMEs is also highlighted.

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We propose a robust adaptive time synchronization and frequency offset estimation method for coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems by applying electrical dispersion pre-compensation (pre-EDC) to the pilot symbol. This technique effectively eliminates the timing error due to the fiber chromatic dispersion, thus increasing significantly the accuracy of the frequency offset estimation process and improving the overall system performance. In addition, a simple design of the pilot symbol is proposed for full-range frequency offset estimation. This pilot symbol can also be used to carry useful data to effectively reduce the overhead due to time synchronization by a factor of 2.

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The popularity of online social media platforms provides an unprecedented opportunity to study real-world complex networks of interactions. However, releasing this data to researchers and the public comes at the cost of potentially exposing private and sensitive user information. It has been shown that a naive anonymization of a network by removing the identity of the nodes is not sufficient to preserve users’ privacy. In order to deal with malicious attacks, k -anonymity solutions have been proposed to partially obfuscate topological information that can be used to infer nodes’ identity. In this paper, we study the problem of ensuring k anonymity in time-varying graphs, i.e., graphs with a structure that changes over time, and multi-layer graphs, i.e., graphs with multiple types of links. More specifically, we examine the case in which the attacker has access to the degree of the nodes. The goal is to generate a new graph where, given the degree of a node in each (temporal) layer of the graph, such a node remains indistinguishable from other k-1 nodes in the graph. In order to achieve this, we find the optimal partitioning of the graph nodes such that the cost of anonymizing the degree information within each group is minimum. We show that this reduces to a special case of a Generalized Assignment Problem, and we propose a simple yet effective algorithm to solve it. Finally, we introduce an iterated linear programming approach to enforce the realizability of the anonymized degree sequences. The efficacy of the method is assessed through an extensive set of experiments on synthetic and real-world graphs.