892 resultados para J22 - Time Allocation and Labor Supply


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Mode of access: Internet.

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Mode of access: Internet.

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Cover title.

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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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Acknowledgments We are grateful for the thoughtful comments of two referees. We would also like to thank conference participants at the Scottish Economic Society Conference and seminar participants at Newcastle University. Receipt of financial support from the ESRC is gratefully acknowledged (RES-000-23-1240). The Health Economics Research Unit is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The views expressed in this article are solely those of the authors.

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Acknowledgments We are grateful for the thoughtful comments of two referees. We would also like to thank conference participants at the Scottish Economic Society Conference and seminar participants at Newcastle University. Receipt of financial support from the ESRC is gratefully acknowledged (RES-000-23-1240). The Health Economics Research Unit is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The views expressed in this article are solely those of the authors.

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This dissertation consists of three separate essays on job search and labor market dynamics. In the first essay, “The Impact of Labor Market Conditions on Job Creation: Evidence from Firm Level Data”, I study how much changes in labor market conditions reduce employment fluctuations over the business cycle. Changes in labor market conditions make hiring more expensive during expansions and cheaper during recessions, creating counter-cyclical incentives for job creation. I estimate firm level elasticities of labor demand with respect to changes in labor market conditions, considering two margins: changes in labor market tightness and changes in wages. Using employer-employee matched data from Brazil, I find that all firms are more sensitive to changes in wages rather than labor market tightness, and there is substantial heterogeneity in labor demand elasticity across regions. Based on these results, I demonstrate that changes in labor market conditions reduce the variance of employment growth over the business cycle by 20% in a median region, and this effect is equally driven by changes along each margin. Moreover, I show that the magnitude of the effect of labor market conditions on employment growth can be significantly affected by economic policy. In particular, I document that the rapid growth of the national minimum wages in Brazil in 1997-2010 amplified the impact of the change in labor market conditions during local expansions and diminished this impact during local recessions.

In the second essay, “A Framework for Estimating Persistence of Local Labor

Demand Shocks”, I propose a decomposition which allows me to study the persistence of local labor demand shocks. Persistence of labor demand shocks varies across industries, and the incidence of shocks in a region depends on the regional industrial composition. As a result, less diverse regions are more likely to experience deeper shocks, but not necessarily more long lasting shocks. Building on this idea, I propose a decomposition of local labor demand shocks into idiosyncratic location shocks and nationwide industry shocks and estimate the variance and the persistence of these shocks using the Quarterly Census of Employment and Wages (QCEW) in 1990-2013.

In the third essay, “Conditional Choice Probability Estimation of Continuous- Time Job Search Models”, co-authored with Peter Arcidiacono and Arnaud Maurel, we propose a novel, computationally feasible method of estimating non-stationary job search models. Non-stationary job search models arise in many applications, where policy change can be anticipated by the workers. The most prominent example of such policy is the expiration of unemployment benefits. However, estimating these models still poses a considerable computational challenge, because of the need to solve a differential equation numerically at each step of the optimization routine. We overcome this challenge by adopting conditional choice probability methods, widely used in dynamic discrete choice literature, to job search models and show how the hazard rate out of unemployment and the distribution of the accepted wages, which can be estimated in many datasets, can be used to infer the value of unemployment. We demonstrate how to apply our method by analyzing the effect of the unemployment benefit expiration on duration of unemployment using the data from the Survey of Income and Program Participation (SIPP) in 1996-2007.

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Using a matching and a difference in differences approach we analyzed the impact of a payroll costs reduction implemented through a tax reform in Colombia on worked hours and hourly income -- Existing studies have found mixed results, while increases in wages are commonly found, the results for employment and worked hours effects are a source of debate with no consensus on sight -- However, in line with earlier revisions of literature, we concluded that the effect of payroll costs reductions is positive and significant on both, worked hours and income -- In this paper, using socioeconomic data from Colombia we found that those individuals a effected by a payroll cost reduction between 2012-2014 exhibited significant increases in both hours and income compared to similar individuals una effected by this framework

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For multiple heterogeneous multicore server processors across clouds and data centers, the aggregated performance of the cloud of clouds can be optimized by load distribution and balancing. Energy efficiency is one of the most important issues for large-scale server systems in current and future data centers. The multicore processor technology provides new levels of performance and energy efficiency. The present paper aims to develop power and performance constrained load distribution methods for cloud computing in current and future large-scale data centers. In particular, we address the problem of optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers. Our strategy is to formulate optimal power allocation and load distribution for multiple servers in a cloud of clouds as optimization problems, i.e., power constrained performance optimization and performance constrained power optimization. Our research problems in large-scale data centers are well-defined multivariable optimization problems, which explore the power-performance tradeoff by fixing one factor and minimizing the other, from the perspective of optimal load distribution. It is clear that such power and performance optimization is important for a cloud computing provider to efficiently utilize all the available resources. We model a multicore server processor as a queuing system with multiple servers. Our optimization problems are solved for two different models of core speed, where one model assumes that a core runs at zero speed when it is idle, and the other model assumes that a core runs at a constant speed. Our results in this paper provide new theoretical insights into power management and performance optimization in data centers.

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To allocate and size capacitors in a distribution system, an optimization algorithm, called Discrete Particle Swarm Optimization (DPSO), is employed in this paper. The objective is to minimize the transmission line loss cost plus capacitors cost. During the optimization procedure, the bus voltage, the feeder current and the reactive power flowing back to the source side should be maintained within standard levels. To validate the proposed method, the semi-urban distribution system that is connected to bus 2 of the Roy Billinton Test System (RBTS) is used. This 37-bus distribution system has 22 loads being located in the secondary side of a distribution substation (33/11 kV). Reducing the transmission line loss in a standard system, in which the transmission line loss consists of only about 6.6 percent of total power, the capabilities of the proposed technique are seen to be validated.