14 resultados para AIR CARGO ECONOMICS

em Duke University


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This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

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Conventional hedonic techniques for estimating the value of local amenities rely on the assumption that households move freely among locations. We show that when moving is costly, the variation in housing prices and wages across locations may no longer reflect the value of differences in local amenities. We develop an alternative discrete-choice approach that models the household location decision directly, and we apply it to the case of air quality in US metro areas in 1990 and 2000. Because air pollution is likely to be correlated with unobservable local characteristics such as economic activity, we instrument for air quality using the contribution of distant sources to local pollution-excluding emissions from local sources, which are most likely to be correlated with local conditions. Our model yields an estimated elasticity of willingness to pay with respect to air quality of 0.34-0.42. These estimates imply that the median household would pay $149-$185 (in constant 1982-1984 dollars) for a one-unit reduction in average ambient concentrations of particulate matter. These estimates are three times greater than the marginal willingness to pay estimated by a conventional hedonic model using the same data. Our results are robust to a range of covariates, instrumenting strategies, and functional form assumptions. The findings also confirm the importance of instrumenting for local air pollution. © 2009 Elsevier Inc. All rights reserved.

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The objective of this paper is to demonstrate an approach to characterize the spatial variability in ambient air concentrations using mobile platform measurements. This approach may be useful for air toxics assessments in Environmental Justice applications, epidemiological studies, and environmental health risk assessments. In this study, we developed and applied a method to characterize air toxics concentrations in urban areas using results of the recently conducted field study in Wilmington, DE. Mobile measurements were collected over a 4- x 4-km area of downtown Wilmington for three components: formaldehyde (representative of volatile organic compounds and also photochemically reactive pollutants), aerosol size distribution (representing fine particulate matter), and water-soluble hexavalent chromium (representative of toxic metals). These measurements were,used to construct spatial and temporal distributions of air toxics in the area that show a very strong temporal variability, both diurnally and seasonally. An analysis of spatial variability indicates that all pollutants varied significantly by location, which suggests potential impact of local sources. From the comparison with measurements at the central monitoring site, we conclude that formaldehyde and fine particulates show a positive correlation with temperature, which could also be the reason that photochemically generated formaldehyde and fine particulates over the study area correlate well with the fine particulate matter measured at the central site.

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Twelve months of aerosol size distributions from 3 to 560nm, measured using scanning mobility particle sizers are presented with an emphasis on average number, surface, and volume distributions, and seasonal and diurnal variation. The measurements were made at the main sampling site of the Pittsburgh Air Quality Study from July 2001 to June 2002. These are supplemented with 5 months of size distribution data from 0.5 to 2.5μm measured with a TSI aerosol particle sizer and 2 months of size distributions measured at an upwind rural sampling site. Measurements at the main site were made continuously under both low and ambient relative humidity. The average Pittsburgh number concentration (3-500nm) is 22,000cm-3 with an average mode size of 40nm. Strong diurnal patterns in number concentrations are evident as a direct effect of the sources of particles (atmospheric nucleation, traffic, and other combustion sources). New particle formation from homogeneous nucleation is significant on 30-50% of study days and over a wide area (at least a hundred kilometers). Rural number concentrations are a factor of 2-3 lower (on average) than the urban values. Average measured distributions are different from model literature urban and rural size distributions. © 2004 Elsevier Ltd. All rights reserved.

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Ambient sampling for the Pittsburgh Air Quality Study (PAQS) was conducted from July 2001 to September 2002. The study was designed (1) to characterize particulate matter (PM) by examination of size, surface area, and volume distribution, chemical composition as a function of size and on a single particle basis, morphology, and temporal and spatial variability in the Pittsburgh region; (2) to quantify the impact of the various sources (transportation, power plants, biogenic sources, etc.) on the aerosol concentrations in the area; and (3) to develop and evaluate the next generation of atmospheric aerosol monitoring and modeling techniques. The PAQS objectives, study design, site descriptions and routine and intensive measurements are presented. Special study days are highlighted, including those associated with elevated concentrations of daily average PM2.5 mass. Monthly average and diurnal patterns in aerosol number concentration, and aerosol nitrate, sulfate, elemental carbon, and organic carbon concentrations, light scattering as well as gas-phase ozone, nitrogen oxides, and carbon monoxide are discussed with emphasis on the processes affecting them. Preliminary findings reveal day-to-day variability in aerosol mass and composition, but consistencies in seasonal average diurnal profiles and concentrations. For example, the seasonal average variations in the diurnal PM2.5 mass were predominately driven by the sulfate component. © 2004 Elsevier Ltd. All rights reserved.

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PURPOSE: Review existing studies and provide new results on the development, regulatory, and market aspects of new oncology drug development. METHODS: We utilized data from the US Food and Drug Administration (FDA), company surveys, and publicly available commercial business intelligence databases on new oncology drugs approved in the United States and on investigational oncology drugs to estimate average development and regulatory approval times, clinical approval success rates, first-in-class status, and global market diffusion. RESULTS: We found that approved new oncology drugs to have a disproportionately high share of FDA priority review ratings, of orphan drug designations at approval, and of drugs that were granted inclusion in at least one of the FDA's expedited access programs. US regulatory approval times were shorter, on average, for oncology drugs (0.5 years), but US clinical development times were longer on average (1.5 years). Clinical approval success rates were similar for oncology and other drugs, but proportionately more of the oncology failures reached expensive late-stage clinical testing before being abandoned. In relation to other drugs, new oncology drug approvals were more often first-in-class and diffused more widely across important international markets. CONCLUSION: The market success of oncology drugs has induced a substantial amount of investment in oncology drug development in the last decade or so. However, given the great need for further progress, the extent to which efforts to develop new oncology drugs will grow depends on future public-sector investment in basic research, developments in translational medicine, and regulatory reforms that advance drug-development science.

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© 2013 The Association for the Study of Animal Behaviour.Social complexity, often estimated by group size, is seen as driving the complexity of vocal signals, but its relation to olfactory signals, which arguably arose to function in nonsocial realms, remains underappreciated. That olfactory signals also may mediate within-group interaction, vary with social complexity and promote social cohesion underscores a potentially crucial link with sociality. To examine that link, we integrated chemical and behavioural analyses to ask whether olfactory signals facilitate reproductive coordination in a strepsirrhine primate, the Coquerel's sifaka, Propithecus coquereli. Belonging to a clade comprising primarily solitary, nocturnal species, the diurnal, group-living sifaka represents an interesting test case. Convergent with diurnal, group-living lemurids, sifakas expressed chemically rich scent signals, consistent with the social complexity hypothesis for communication. These signals minimally encoded the sex of the signaller and varied with female reproductive state. Likewise, sex and female fertility were reflected in within-group scent investigation, scent marking and overmarking. We further asked whether, within breeding pairs, the stability or quality of the pair's bond influences the composition of glandular signals and patterns of investigatory or scent-marking behaviour. Indeed, reproductively successful pairs tended to show greater similarity in their scent signals than did reproductively unsuccessful pairs, potentially through chemical convergence. Moreover, scent marking was temporally coordinated within breeding pairs and was influenced by past reproductive success. That olfactory signalling reflects social bondedness or reproductive history lends support to recent suggestions that the quality of relationships may be a more valuable proxy than group size for estimating social complexity. We suggest that olfactory signalling in sifakas is more complex than previously recognized and, as in other socially integrated species, can be a crucial mechanism for promoting group cohesion and maintaining social bonds. Thus, the evolution of sociality may well be reflected in the complexity of olfactory signalling.

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BACKGROUND: The respiratory tract is a major target of exposure to air pollutants, and respiratory diseases are associated with both short- and long-term exposures. We hypothesized that improved air quality in North Carolina was associated with reduced rates of death from respiratory diseases in local populations. MATERIALS AND METHODS: We analyzed the trends of emphysema, asthma, and pneumonia mortality and changes of the levels of ozone, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matters (PM2.5 and PM10) using monthly data measurements from air-monitoring stations in North Carolina in 1993-2010. The log-linear model was used to evaluate associations between air-pollutant levels and age-adjusted death rates (per 100,000 of population) calculated for 5-year age-groups and for standard 2000 North Carolina population. The studied associations were adjusted by age group-specific smoking prevalence and seasonal fluctuations of disease-specific respiratory deaths. RESULTS: Decline in emphysema deaths was associated with decreasing levels of SO2 and CO in the air, decline in asthma deaths-with lower SO2, CO, and PM10 levels, and decline in pneumonia deaths-with lower levels of SO2. Sensitivity analyses were performed to study potential effects of the change from International Classification of Diseases (ICD)-9 to ICD-10 codes, the effects of air pollutants on mortality during summer and winter, the impact of approach when only the underlying causes of deaths were used, and when mortality and air-quality data were analyzed on the county level. In each case, the results of sensitivity analyses demonstrated stability. The importance of analysis of pneumonia as an underlying cause of death was also highlighted. CONCLUSION: Significant associations were observed between decreasing death rates of emphysema, asthma, and pneumonia and decreases in levels of ambient air pollutants in North Carolina.

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Air pollution is a common problem. Particulate matter generated from air pollution has been tied to adverse health outcomes associated with cardiovascular disease. Biomass fuels are a specific contributor to increased particulate matter and arise as a result of indoor heating, cook stoves and indoor food preparation. This is a two part cross sectional study looking at communities in the Madre de Dios region. Survey data was collected from 9 communities along the Madre de Dios River. Individual level household PM2.5 was also collected as a means to generate average PM data stratified by fuel use. Data collection was affected by a number of outside factors, which resulted in a loss of data. Results from the cross-sectional study indicate that hypertension is not a significant source of morbidity. Obesity is prevalent and significantly associated with kitchen venting method indicating a potential relationship.

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Examining how key components of coat protein I (COPI) transport participate in cargo sorting, we find that, instead of ADP ribosylation factor 1 (ARF1), its GTPase-activating protein (GAP) plays a direct role in promoting the binding of cargo proteins by coatomer (the core COPI complex). Activated ARF1 binds selectively to SNARE cargo proteins, with this binding likely to represent at least a mechanism by which activated ARF1 is stabilized on Golgi membrane to propagate its effector functions. We also find that the GAP catalytic activity plays a critical role in the formation of COPI vesicles from Golgi membrane, in contrast to the prevailing view that this activity antagonizes vesicle formation. Together, these findings indicate that GAP plays a central role in coupling cargo sorting and vesicle formation, with implications for simplifying models to describe how these two processes are coupled during COPI transport.