887 resultados para Labor-intensive industrialization


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東アジア経済は労働集約財輸出を中心とする輸出指向工業化によって経済発展を遂げた。その輸出指向工業化の成功の本質が、市場の歪みの小ささにあったのか、それとも政府の積極的な輸出促進政策にあったのか、という点については長く議論が闘わされてきたものの、世界銀行の『東アジアの軌跡』出版以来、後者の論理がより注目されてきた。  現在の低所得国は、その多くがWTOに加盟しており、かつて東アジア経済が採用したような輸出促進政策を採用できないことから、低所得国の製造業品の輸出成長は期待できないという新輸出悲観論が広がっている。その中でバングラデシュやカンボジアは手厚い政府の促進政策なしに、労働集約財の代表である縫製品の輸出を伸ばしている。そこで本稿は、WTO時代にあって手厚い政府介入が行われなかったとしても、低所得国が低賃金を活用して工業化を進める可能性が十分あることを主張する。

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The international garment trade was liberalized in 2005 following the termination of the MFA (Multifibre Arrangement) and ever since then, price competition has intensified. Employing a unique firm dataset collected by the authors, this paper examines the changes in the performance of Cambodian garment firms between 2002/03 and 2008/09. During the period concerned, frequent firm turnover led to an improvement of the industry’s productivity, and the study found that the average total-factor productivity (TFP) of new entrants was substantially higher than that of exiting firms. Furthermore, we observed that thanks to productivity growth, an improvement in workers’ welfare, including a rise in the relative wages of the low-skilled, was taking place. These industrial dynamics differ considerably from those indicated by the “race to the bottom” argument as applied to labor-intensive industrialization in low income countries.

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This paper investigates how the garment industry escapes this vicious cycle and argues for the validity of labor-intensive industry as a starting point for full-fledged industrialization, even though it might at first seem to be a digression from the path to an innovation-led economy. By examining original firm-level data on garment-producing firms collected in 2002 and 2008 in Bangladesh, Cambodia, Kenya and Madagascar, the following conclusions are drawn: (1) low wages, though still sufficient for poverty reduction, are the main source of competitiveness in low-income countries; (2) after the successful initiation of industrialization causes wages to begin to rise, there is still a possibility for productivity enhancement; and (3) skill bias in technological progress is not yet a major factor, implying that the garment industry is still a labor-intensive industry. In sum, labor-intensive industry should not be discounted as a part of the development strategy of low-income countries.

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Service systems are labor intensive. Further, the workload tends to vary greatly with time. Adapting the staffing levels to the workloads in such systems is nontrivial due to a large number of parameters and operational variations, but crucial for business objectives such as minimal labor inventory. One of the central challenges is to optimize the staffing while maintaining system steady-state and compliance to aggregate SLA constraints. We formulate this problem as a parametrized constrained Markov process and propose a novel stochastic optimization algorithm for solving it. Our algorithm is a multi-timescale stochastic approximation scheme that incorporates a SPSA based algorithm for ‘primal descent' and couples it with a ‘dual ascent' scheme for the Lagrange multipliers. We validate this optimization scheme on five real-life service systems and compare it with a state-of-the-art optimization tool-kit OptQuest. Being two orders of magnitude faster than OptQuest, our scheme is particularly suitable for adaptive labor staffing. Also, we observe that it guarantees convergence and finds better solutions than OptQuest in many cases.

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The common assumptions that labor income share does not change over time or across countries and that factor income shares are equal to the elasticity of output with respect to factors have had important implications for economic theory. However, there are various theoretical reasons why the elasticity of output with respect to reproducible factors should be correlated with the stage of development. In particular, the behavior of international trade and capital flows and the existence of factor saving innovations imply such a correlation. If this correlation exists and if factor income shares are equal to the elasticity of output with respect to factors then the labor income share must be negatively correlated with the stage of development. We propose an explanation for why labor income share has no correlation with income per capita: the existence of a labor intensive sector which produces non tradable goods.

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Includes bibliography

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BACKGROUND: Sedation protocols, including the use of sedation scales and regular sedation stops, help to reduce the length of mechanical ventilation and intensive care unit stay. Because clinical assessment of depth of sedation is labor-intensive, performed only intermittently, and interferes with sedation and sleep, processed electrophysiological signals from the brain have gained interest as surrogates. We hypothesized that auditory event-related potentials (ERPs), Bispectral Index (BIS), and Entropy can discriminate among clinically relevant sedation levels. METHODS: We studied 10 patients after elective thoracic or abdominal surgery with general anesthesia. Electroencephalogram, BIS, state entropy (SE), response entropy (RE), and ERPs were recorded immediately after surgery in the intensive care unit at Richmond Agitation-Sedation Scale (RASS) scores of -5 (very deep sedation), -4 (deep sedation), -3 to -1 (moderate sedation), and 0 (awake) during decreasing target-controlled sedation with propofol and remifentanil. Reference measurements for baseline levels were performed before or several days after the operation. RESULTS: At baseline, RASS -5, RASS -4, RASS -3 to -1, and RASS 0, BIS was 94 [4] (median, IQR), 47 [15], 68 [9], 75 [10], and 88 [6]; SE was 87 [3], 46 [10], 60 [22], 74 [21], and 87 [5]; and RE was 97 [4], 48 [9], 71 [25], 81 [18], and 96 [3], respectively (all P < 0.05, Friedman Test). Both BIS and Entropy had high variabilities. When ERP N100 amplitudes were considered alone, ERPs did not differ significantly among sedation levels. Nevertheless, discriminant ERP analysis including two parameters of principal component analysis revealed a prediction probability PK value of 0.89 for differentiating deep sedation, moderate sedation, and awake state. The corresponding PK for RE, SE, and BIS was 0.88, 0.89, and 0.85, respectively. CONCLUSIONS: Neither ERPs nor BIS or Entropy can replace clinical sedation assessment with standard scoring systems. Discrimination among very deep, deep to moderate, and no sedation after general anesthesia can be provided by ERPs and processed electroencephalograms, with similar P(K)s. The high inter- and intraindividual variability of Entropy and BIS precludes defining a target range of values to predict the sedation level in critically ill patients using these parameters. The variability of ERPs is unknown.

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Cambodia's export-oriented garment industry has contributed greatly to poverty reduction in the country through employment of the poor. This paper provides a statistical verification of this contribution based on firm-level data from 164 sampled companies collected in 2003. Its main conclusions confirm the substantial impact that employment in the garment industry has had on poverty reduction in Cambodia. Firstly, entry-level workers receive wages far above the poverty line. Secondly, females make up the predominant share of the main category jobs in the industry. Thirdly, barriers to employment and to promotions up to certain job categories are not high in terms of education and experience. Another important finding is that a typical sample firm exhibited high profitability, although there was wide variation in profitability among firms. This average of high profitability could be a good predictor of Cambodia's viability in the intensified competition since the phase out of the Multi-Fiber Arrangement (MFA) at the beginning of 2005. A point of note is that Cambodia's pattern of industrial development led by a labor-intensive industry is similar to that of neighboring countries in East Asia which earlier went through the initial stage of industrial development, except that Cambodia has lacked a strong government industrial promotion policy which characterized the earlier group.

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As the success of East Asian countries has shown, labor-intensive industry is recognized to lead economic growth in the early stages of development, utilizing relatively low labor costs. This same growth process has already started in South and South East Asian LDCs since the mid-1990s. However, the manufacturing sector in sub-Saharan Africa has been underdeveloped and manufacturing exports, in particular labour-intensive goods, have stagnated. This paper investigates the international competitiveness of the African manufacturing sector and its determinants through an analytical survey of empirical studies and a comparison with Asian low income countries. Empirical evidences indicate that primary factors of competitiveness, namely productivity, labour cost and exchange rate are unfavorable in sub-Saharan Africa. Representative arguments attribute the weak competitiveness to problems in the business environment, factor endowment, and the exchange rate. However, careful review shows that labour cost is beyond the range explained by endowment and misalignment of exchange rates have been reduced in Africa. Moreover, comparison with Asian low income countries which have competitiveness in labour-intensive goods shows no difference in the quality of business environment, while the labour cost is significantly lower than sub-Saharan African countries. Although results should be considered tentative, high labour cost beyond endowment and conservative investment behavior emerge as important factors for the weak competitiveness in sub-Saharan Africa when controlling income level.

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Chinese agricultural cooperatives, called Farmer's Professional Cooperatives (FPCs), are expected to become a major tool to facilitate agro-industrialization for small farmers through the diffusion of new technologies, the supply of high-quality agricultural inputs and the marketing of their products. This study compares FPC participants with vegetable-producing non-participants and grain farmers in vegetable-producing areas in rural China to investigate the treatment effect of participation in FPCs as well as implementation of vegetable cultivation. I adopt parametric and nonparametric approaches to precisely estimate the treatment effects. Estimated results indicate no significant difference between participants and non-participants of FPCs on agricultural net income in both parametric and non-parametric estimations. In contrast, the comparison between vegetable and grain farmers using propensity score matching (PSM) reveals that the treatment effect of vegetable cultivation is significantly positive for total and agricultural incomes, although vegetable cultivation involves more labor-intensive efforts. These results indicate that it is the implementation of vegetable cultivation rather than the participation in an FPC that enhances the economic welfare of farmers, due to the non-excludability of FPCs' services as well as the risks involved in vegetable cultivation.

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Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

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The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

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Dengue virus is the most significant human viral pathogen spread by the bite of an infected mosquito. With no vaccine or antiviral therapy currently available, disease prevention relies largely on surveillance and mosquito control. Preventing the onset of dengue outbreaks and effective vector management would be considerably enhanced through surveillance of dengue virus prevalence in natural mosquito populations. However, current approaches to the identification of virus in field-caught mosquitoes require relatively slow and labor intensive techniques such as virus isolation or RT-PCR involving specialized facilities and personnel. A rapid and portable method for detecting dengue virus-infected mosquitoes is described. Using a hand held battery operated homogenizer and a dengue diagnostic rapid strip the viral protein NS1 was detected as a marker of dengue virus infection. This method could be performed in less than 30 min in the field, requiring no downstream processing, and is able to detect a single infected mosquito in a pool of at least 50 uninfected mosquitoes. The method described in this study allows rapid, real-time monitoring of dengue virus presence in mosquito populations and could be a useful addition to effective monitoring and vector control responses.

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Mesenchymal stem cells (MSC) are emerging as a leading cellular therapy for a number of diseases. However, for such treatments to become available as a routine therapeutic option, efficient and cost-effective means for industrial manufacture of MSC are required. At present, clinical grade MSC are manufactured through a process of manual cell culture in specialized cGMP facilities. This process is open, extremely labor intensive, costly, and impractical for anything more than a small number of patients. While it has been shown that MSC can be cultivated in stirred bioreactor systems using microcarriers, providing a route to process scale-up, the degree of numerical expansion achieved has generally been limited. Furthermore, little attention has been given to the issue of primary cell isolation from complex tissues such as placenta. In this article we describe the initial development of a closed process for bulk isolation of MSC from human placenta, and subsequent cultivation on microcarriers in scalable single-use bioreactor systems. Based on our initial data, we estimate that a single placenta may be sufficient to produce over 7,000 doses of therapeutic MSC using a large-scale process.