How to Attract Physicians to Underserved Areas? Policy Recommendations from a Structural Model

This paper exploits location choices of all generalist physicians graduated in Brazil between 2001 and 2013 to study policies aiming at increasing the supply of physicians in underserved areas. We set up and estimate a supply and demand model for physicians. We estimate physicians' locational preferences using a random coefficients discrete choice model. The demand has private establishments competing for physicians with private and public facilities around the country. Policy counterfactuals indicate that quotas in medical schools for students born in underserved areas and the opening of vacancies in medical schools in deprived areas are more cost-effective than financial incentives.

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Seismic Fragility Assessment of Building with Metallic Hysteretic Damper in Consideration of Stiffness Ratio

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.765.377 ◽

2018 ◽

Vol 765 ◽

pp. 377-382

Author(s):

Daniel Rumbi Teruna ◽

Hendrik Wijaya

Keyword(s):

Structural Model ◽

Fragility Curves ◽

Nonlinear Dynamic Analysis ◽

Steel Structure ◽

Seismic Energy ◽

Cost Effective ◽

Stiffness Ratio ◽

Demand Model ◽

Probabilistic Seismic Demand ◽

Steel Damper

The application of hysteretic steel damper for seismic protection and rehabilitation has been recognized efficient and cost effective method in reducing structural responses under seismic events. The damper absorbs seismic energy through its hysteretic behaviour. This study aims to assess the vulnerability of building strengthened with hysteretic steel damper considering variability of stiffness ratio parameter in hysteretic steel damper for the application in six-story steel building. Probabilistic Seismic Demand Model (PSDM) for the structural model is developed by using nonlinear dynamic analysis under 30 ground motions. Furthermore, fragility curves are constructed based on inter-story drift and spectrum acceleration. Finally, the performance of the steel structure with and without hysteretic steel damper in addition to optimal stiffness ratio is presented and compared.

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Temporal Differences in the Role of Marketing Communication in New Product Categories

Journal of Marketing Research ◽

10.1509/jmkr.2005.42.3.278 ◽

2005 ◽

Vol 42 (3) ◽

pp. 278-290 ◽

Cited By ~ 165

Author(s):

Sridhar Narayanan ◽

Puneet Manchanda ◽

Pradeep K. Chintagunta

Keyword(s):

Direct Effect ◽

Indirect Effect ◽

Structural Model ◽

Choice Model ◽

New Product ◽

Random Coefficients ◽

New Drugs ◽

Marketing Communication ◽

Temporal Differences

The authors investigate the changing role of marketing communication over the life cycle of a new product category. They postulate two effects of marketing communication on consumers' choices: an “indirect effect” through reduction of uncertainty about product quality and a “direct effect” (i.e., more is better). The authors expect that the indirect effect is relatively larger in the early, postlaunch stages. They develop a structural model of demand that allows for such temporal differences in the roles of marketing communication. They use a random coefficients discrete choice model with a Bayesian learning process to model physician learning about new drugs and market-level data for the prescription antihistamines category. They find that marketing communication has a primarily indirect effect 6–14 months after introduction but that the direct effect subsequently dominates. The results suggest that firms should follow a pattern of heavier communication at the introduction phase followed by lower levels.

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Establishment and prediction of energy demand model in Yunnan Province based on spatial nodes

E3S Web of Conferences ◽

10.1051/e3sconf/202129302061 ◽

2021 ◽

Vol 293 ◽

pp. 02061

Author(s):

Liu Siyang ◽

Wei Zirui ◽

Qian Wen ◽

Chen Yu ◽

Liu Qian ◽

...

Keyword(s):

Energy Demand ◽

Yunnan Province ◽

Model Simulation ◽

Supply And Demand ◽

Thermal Power ◽

Electricity Consumption ◽

Demand Model ◽

Total Energy Consumption ◽

Coal Consumption ◽

Set Up

Energy demand is closely related to energy price, GDP and population. By using the shortest path algorithm and K-means clustering, we set up the spatial nodes, and carried out the model simulation to predict the energy demand of Yunnan Province. The results show that the total energy consumption of Yunnan Province will still show an upward trend from 2020 to 2015; hydropower silicon integration projects in Yunnan Province, the power supply and demand situation in Yunnan Province will change from oversupply to basic balance between supply and demand, and the role of thermal power in dry season will be played to make the decline of coal consumption tend to be smooth; from 2020 to 2025, Yunnan’s electricity consumption will increase by about 8.02% year-on-year. However, according to the commissioning of some projects, the total electricity consumption in the province will be about 192.9 billion kwh in 2020, with a yearon-year increase of 12.3%.

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Solar Renewable Energy Credit Price Volatility and Investment Returns: Have Policies Stranded Capital Investment?

Commonwealth ◽

10.15367/com.v19i1.135 ◽

2017 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Somayeh Youssefi ◽

Patrick L. Gurian

Keyword(s):

Solar Energy ◽

Capital Investment ◽

Supply And Demand ◽

Price Volatility ◽

The United States ◽

Investment Model ◽

Capital Investments ◽

Demand Model ◽

Market Prices ◽

Investment Returns

Pennsylvania is one of a number of U.S. states that provide incentives for the generation of electricity by solar energy through Solar Renewal Energy Credits (SRECs). This article develops a return on investment model for solar energy generation in the PJM (mid-Atlantic) region of the United States. Model results indicate that SREC values of roughly $150 are needed for residential scale systems to break even over a 25-year project period at 3% interest. Market prices for SRECs in Pennsylvania have been well below this range from late 2011 through the first half of 2016, indicating that previous capital investments in solar generation have been stranded as a result of steep declines in the value of SRECs. A simple conceptual supply and demand model is developed to explain the sharp decline in market prices for SRECs. Also discussed is a possible policy remedy that would add unsold SRECs in a given year to the SREC quota for the subsequent year.

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The impact of regulations on labor markets in the U.S.

Corporate Law and Governance Review ◽

10.22495/clgrv1i1p4 ◽

2019 ◽

Vol 1 (1) ◽

pp. 36-40

Author(s):

Souad Adnane

Keyword(s):

Supply And Demand ◽

Demand Model ◽

Lead Teachers ◽

Associate's Degree ◽

Childcare Workers ◽

Educational Requirements ◽

The Cost ◽

Women's Labor Force Participation ◽

The Impact ◽

The U.S

The District of Columbia (DC) Office of the Superintendent of Education (OSSE) issued in December 2016 new educational requirements for childcare workers, according to which, all childcare center directors in the District must earn a bachelor’s degree by December 2022 and all lead teachers an associate’s degree by December 2020 (Institute for Justice, 2018). Moreover, DC has one of the lowest staff-child ratios in the country. How are regulations pertaining to childcare workers’ qualifications and staff-child ratio affecting the childcare market in DC? The present paper is an attempt to answer this question first by analyzing the effects of more stringent regulations on the cost and availability of childcare in the U.S based on existing studies. It also uses the basic supply and demand model to examine the possible impact of the new DC policy on the cost, quality and supply of childcare in the District and how it will affect working parents, especially mothers. Next, the paper discusses the impact of deregulation based on simulations and regressions conducted by studies covering the U.S., and implications for quality. It concludes that more stringent childcare regulations, regarding educational requirements and staff-child ratios, are associated with a reduced number of childcare centers and a higher cost, and eventually affects women’s labor force participation.

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Environmental Engineering Techniques to Restore Degraded Posidonia oceanica Meadows

Water ◽

10.3390/w13050661 ◽

2021 ◽

Vol 13 (5) ◽

pp. 661

Author(s):

Luigi Piazzi ◽

Stefano Acunto ◽

Francesca Frau ◽

Fabrizio Atzori ◽

Maria Francesca Cinti ◽

...

Keyword(s):

Large Scale ◽

Natural Habitat ◽

Cost Benefit ◽

Cost Effective ◽

Posidonia Oceanica ◽

Environmental Engineering ◽

Bottom Surface ◽

Sessile Invertebrates ◽

Set Up ◽

Short Time

Seagrass planting techniques have shown to be an effective tool for restoring degraded meadows and ecosystem function. In the Mediterranean Sea, most restoration efforts have been addressed to the endemic seagrass Posidonia oceanica, but cost-benefit analyses have shown unpromising results. This study aimed at evaluating the effectiveness of environmental engineering techniques generally employed in terrestrial systems to restore the P. oceanica meadows: two different restoration efforts were considered, either exploring non-degradable mats or, for the first time, degradable mats. Both of them provided encouraging results, as the loss of transplanting plots was null or very low and the survival of cuttings stabilized to about 50%. Data collected are to be considered positive as the survived cuttings are enough to allow the future spread of the patches. The utilized techniques provided a cost-effective restoration tool likely affordable for large-scale projects, as the methods allowed to set up a wide bottom surface to restore in a relatively short time without any particular expensive device. Moreover, the mats, comparing with other anchoring methods, enhanced the colonization of other organisms such as macroalgae and sessile invertebrates, contributing to generate a natural habitat.

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Self-Regulating Demand and Supply Equilibrium in Joint Simulation of Travel Demand and a Ride-Pooling Service

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198121997140 ◽

2021 ◽

pp. 036119812199714

Author(s):

Gabriel Wilkes ◽

Roman Engelhardt ◽

Lars Briem ◽

Florian Dandl ◽

Peter Vortisch ◽

...

Keyword(s):

Real Time ◽

Travel Demand ◽

State Of The Art ◽

Choice Model ◽

Mode Choice ◽

Attractive Alternative ◽

Full Potential ◽

Demand Model ◽

Modeling Framework ◽

Demand And Supply

This paper presents the coupling of a state-of-the-art ride-pooling fleet simulation package with the mobiTopp travel demand modeling framework. The coupling of both models enables a detailed agent- and activity-based demand model, in which travelers have the option to use ride-pooling based on real-time offers of an optimized ride-pooling operation. On the one hand, this approach allows the application of detailed mode-choice models based on agent-level attributes coming from mobiTopp functionalities. On the other hand, existing state-of-the-art ride-pooling optimization can be applied to utilize the full potential of ride-pooling. The introduced interface allows mode choice based on real-time fleet information and thereby does not require multiple iterations per simulated day to achieve a balance of ride-pooling demand and supply. The introduced methodology is applied to a case study of an example model where in total approximately 70,000 trips are performed. Simulations with a simplified mode-choice model with varying fleet size (0–150 vehicles), fares, and further fleet operators’ settings show that (i) ride-pooling can be a very attractive alternative to existing modes and (ii) the fare model can affect the mode shifts to ride-pooling. Depending on the scenario, the mode share of ride-pooling is between 7.6% and 16.8% and the average distance-weighed occupancy of the ride-pooling fleet varies between 0.75 and 1.17.

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A socio-psychological modal choice approach to modelling mobility and energy demand for electric vehicles

Energy Informatics ◽

10.1186/s42162-020-00123-7 ◽

2020 ◽

Vol 3 (S1) ◽

Author(s):

Khoa Nguyen ◽

René Schumann

Keyword(s):

Energy Demand ◽

Supply And Demand ◽

Stochastic Approach ◽

Social Characteristics ◽

Limited Information ◽

Demand Model ◽

Modal Choice ◽

Charging Infrastructure ◽

Human Decision ◽

Electro Mobility

Abstract The development of efficient electric vehicle (EV) charging infrastructure requires modelling of consumer demand at an appropriate level of detail. Since only limited information about real customers is available, most simulations employ a stochastic approach by combining known or estimated business features (e.g. arrival and departure time, requested amount of energy) with random variations. However, these models in many cases do not include factors that deal with the social characteristics of EV users, while others do not emphasise on the economic elements. In this work, we introduced a more detailed demand model employing a modal choice simulation framework based on Triandis’ Theory of Interpersonal Behaviour, which can be calibrated by empirical data and is capable of combining a diverse number of determinants in human decision-making. By applying this model on Switzerland mobility domain, an analysis on three of the most popular EV incentives from both supply and demand sides is provided, which aims for a better understanding of electro-mobility systems by relating its causes and effects.

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Factors Affecting the Lut Desert Tourism in Iran: Developing an Interpretive-Structural Model

Sustainability ◽

10.3390/su13137245 ◽

2021 ◽

Vol 13 (13) ◽

pp. 7245

Author(s):

Beniamino Murgante ◽

Mohammad Eskandari Sani ◽

Sara Pishgahi ◽

Moslem Zarghamfard ◽

Fatemeh Kahaki

Keyword(s):

Sampling Method ◽

Structural Model ◽

Tourism Development ◽

Cost Effective ◽

Structural Modeling ◽

Interpretive Structural Modeling ◽

Factors Affecting ◽

Purposive Sampling ◽

Interpretive Structural Model ◽

Lut Desert

The Lut desert is one of the largest and most attractive deserts in Iran. The value of desert tourism remains unclear for Iran’s economy and has only recently been taken into consideration by the authorities, although its true national and international value remains unclear. This study was aimed at investigating the factors that influence tourism development in the Lut desert. Data collected through the purposive sampling method was analyzed using Interpretive Structural Modeling and the MICMAC Analysis. According to the results, cost-effective travel expenses, security, and safety provided in the desert, together with appropriate media advertising and illustration of the Lut desert (branding) are the leading factors that influence tourism in the Lut desert in Iran. This paper highlighted the importance of desert tourism, especially in this region.

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K-seq, an affordable, reliable, and open Klenow NGS-based genotyping technology

Plant Methods ◽

10.1186/s13007-021-00733-6 ◽

2021 ◽

Vol 17 (1) ◽

Author(s):

Peio Ziarsolo ◽

Tomas Hasing ◽

Rebeca Hilario ◽

Victor Garcia-Carpintero ◽

Jose Blanca ◽

...

Keyword(s):

Cost Effective ◽

Genetic Distances ◽

Set Design ◽

Special Equipment ◽

Genetic Studies ◽

Set Up ◽

Genomic Regions ◽

Biology Laboratory ◽

Genotyping Technology ◽

Genetic Results

Abstract Background K-seq, a new genotyping methodology based on the amplification of genomic regions using two steps of Klenow amplification with short oligonucleotides, followed by standard PCR and Illumina sequencing, is presented. The protocol was accompanied by software developed to aid with primer set design. Results As the first examples, K-seq in species as diverse as tomato, dog and wheat was developed. K-seq provided genetic distances similar to those based on WGS in dogs. Experiments comparing K-seq and GBS in tomato showed similar genetic results, although K-seq had the advantage of finding more SNPs for the same number of Illumina reads. The technology reproducibility was tested with two independent runs of the tomato samples, and the correlation coefficient of the SNP coverages between samples was 0.8 and the genotype match was above 94%. K-seq also proved to be useful in polyploid species. The wheat samples generated specific markers for all subgenomes, and the SNPs generated from the diploid ancestors were located in the expected subgenome with accuracies greater than 80%. Conclusion K-seq is an open, patent-unencumbered, easy-to-set-up, cost-effective and reliable technology ready to be used by any molecular biology laboratory without special equipment in many genetic studies.

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