Effects Of Different Policies Research Articles

Collaborative Research and Rate of Interests

This article has made an attempt to link collaborative research in industry with government initiative and market rate of interests. Two firms involved in Cournot competition in the market decide whether to conduct research to devise a technique for cost reduction. The amount of cost reduction after the research and the initial amount of capital possessed by each firm are private information to each of the firms. In particular, both of them have capacity constraint. The objective of this article has been to figure out the impacts of the lending and borrowing rates of interest on collaborative research. In the process, we have studied the effectiveness of different policies to encourage collaborative research and development (R&D).

Assessing long-term effects of demand response policies in wholesale electricity markets

Different policies have been implemented around the world seeking to deliver demand response potential in the electricity markets. Externalities, namely the CO2 externality, have been one of the key concerns in the debate on the effectiveness of different policies regarding demand response development. Although most previous researches have centred on the short-term assessment of different policy choices to tackle the CO2 externality, little work has been focused on the long-term impacts, such as changes in welfare and investment dynamics, in consequence of the implementation of such policies. This paper relies on a long-term market simulation model to examine long-term dynamics of two specific policies presently used by policy makers. The first policy relates to the correction for the externality by setting a CO2 price at a level equal to the social cost of the associated CO2 emissions. The second policy consists in subsidizing carbon-free technologies such as demand response. We test for each policy two different scenarios regarding the possibility of internalization of the CO2 externality. The results show that in the long-run different policies should affect both investments and social costs, a market-driven development of demand response with the internalization of the CO2 externality being the most efficient approach.

Evaluating the Pros and Cons of Different Peer Review Policies via Simulation.

In the academic world, peer review is one of the major processes in evaluating a scholars contribution. In this study, we are interested in quantifying the merits of different policies in a peer review process, such as single-blind review, double-blind review, and obtaining authors feedback. Currently, insufficient work has been undertaken to evaluate the benefits of different peer review policies. One of the major reasons for this situation is the inability to conduct any empirical study because data are presently unavailable. In this case, a computer simulation is one of the best ways to conduct a study. We perform a series of simulations to study the effects of different policies on a peer review process. In this study, we focus on the peer review process of a typical computer science conference. Our results point to the crucial role of program chairs in determining the quality and diversity of the articles to be accepted for publication. We demonstrate the importance of discussion among reviewers, suggest circumstances in which the double-blind review policy should be adopted, and question the credibility of the authors feedback mechanism. Finally, we stress that randomness plays an important role in the peer review process, and this role cannot be eliminated. Although our model may not capture every component of a peer review process, it covers some of the most essential elements. Thus, even the simulation results clearly cannot be taken as literal descriptions of an actual peer review process. However, we can at least still use them to identify alternative directions for future study.

A non-probabilistic programming approach enabling risk-aversion analysis for supporting sustainable watershed development

Due to insufficiency and ineffectiveness of monitoring facilities, variations in natural conditions and changes of human behaviors, watershed planning is interwoven with imprecise data, resulting in a multitude of complexities. A robust interval fuzzy programming approach with superiority–inferiority and risk-aversion analyses (RIFP-SIRA) was developed for identifying sustainable agricultural and industrial production strategies at the watershed scale in a highly uncertain environment. RIFP-SIRA represented a novel attempt to tackle synergies of uncertain information in the forms of intervals with non-statistical bounds and conventional intervals. The developed method was applied to a Chinese watershed. A RIFP-SIRA model was formulated and analyzed under three scenarios to investigate the effects of different policies and standards on watershed development plans. Sensitivity of the model's solutions to varied risk-aversion and input-fluctuation levels were analyzed, verifying the superiority of RIFP-SIRA over the existing inexact approaches. This research revealed that RIFP-SIRA could provide local authorities with robust, yet flexible decision plans. It could enable a quantitative analysis over the trade-offs between the economic benefits and environmental risks in the absence of probabilistic information.

Carbon footprint and responsiveness trade-offs in supply chain network design

Concern related to sustainability and greenhouse gases has grown among citizens as well as firms, which are increasingly committing to carbon emission reduction targets. However, firms׳ emissions come from direct and indirect sources, and from the different stages of their supply chain. Therefore, comprehensive supply chain approaches are essential to ensure the cost-effectiveness of carbon management strategies. These approaches should capture operational and environmental trade-offs arising from the interaction between different supply chain processes such as procurement, manufacturing, transport and inventory management. Considering all these processes, we propose a model for supply chain network design that takes demand uncertainty into account and includes decisions on supply chain responsiveness under different carbon policies: caps on supply chain carbon footprints, caps on market carbon footprints, and carbon taxes. Our model supports the analysis of the effect of different policies on costs and optimal network configuration and allows us to distinguish between different product types: functional or innovative products. With detailed numerical examples, we illustrate the type of analysis and managerial insights that can be derived with our model, which include the assessment of supply chains׳ potential for carbon abatement, the study of the effect of different carbon policies on supply chain costs and network design, the analysis of the impact of various product characteristics, the test of an alternative profit maximisation model, and the determination of the value of a supply chain carbon tax that should induce specific levels of carbon abatement.

Reporting Incidental Findings in Genomic Scale Clinical Sequencing—A Clinical Laboratory Perspective: A Report of the Association for Molecular Pathology

Advances in sequencing technologies have facilitated concurrent testing for many disorders, and the results generated may provide information about a patient's health that is unrelated to the clinical indication, commonly referred to as incidental findings. This is a paradigm shift from traditional genetic testing in which testing and reporting are tailored to a patient's specific clinical condition. Clinical laboratories and physicians are wrestling with this increased complexity in genomic testing and reporting of the incidental findings to patients. An enormous amount of discussion has taken place since the release of a set of recommendations from the American College of Medical Genetics and Genomics. This discussion has largely focused on the content of the incidental findings, but the laboratory perspective and patient autonomy have been overlooked. This report by the Association of Molecular Pathology workgroup discusses the pros and cons of next-generation sequencing technology, potential benefits, and harms for reporting of incidental findings, including the effect on both the laboratory and the patient, and compares those with other areas of medicine. The importance of genetic counseling to preserve patient autonomy is also reviewed. The discussion and recommendations presented by the workgroup underline the need for continued research and discussion among all stakeholders to improve our understanding of the effect of different policies on patients, providers, and laboratories.

Impact of Different Carbon Policies on City Logistics Network

A programming model for a four-layer urban logistics distribution network is constructed and revised based on three types of carbon emissions policies such as Carbon tax, carbon emissions Cap, Carbon Trade. Effects of different policies on logistics costs and carbon emissions are analyzed based on a spatial Logistics Infrastructure layout of Beijing. Research findings are as follows: First, based on low-carbon policies, the logistics costs and carbon emissions can be changed by different modes of transport in a certain extent; second, only when carbon taxes and carbon trading prices are higher, carbon taxes and carbon trading policies can reduce carbon emissions while not significantly increase logistics costs at the same time, and more effectively achieve carbon reduction targets than use carbon cap policy.

Evaluation of the impacts of governmental policies on the biofuels supply chain design under uncertainty

There is a growing interest in the use of biomass as a source of energy around the world. In the USA, the renewable fuel standard (RFS) sets policies and mandates to support the production and consumption of biofuels. However, the uncertainties associated with the governmental and local policies and regulations on both production and consumption have imposed significant impacts on the biofuel supply chain network. This study aims to determine the optimal design of the biofuel supply chain to maximise annual profit under the impacts of governmental policies. In this study, two-stage stochastic programming models are developed in which conditional value at risk is considered as a risk measure to control the shortage of mandate. A case study in Iowa is conducted to investigate the effects of different policies and demonstrate the applicability and efficiency of the models.

Graft-versus-host disease prophylaxis after transplantation: a network meta-analysis.

BackgroundGraft-versus-host Disease (GvHD) prophylaxis after allogeneic hematopoietic stem-cell transplantation (HSCT) is an ongoing effort but relative effects of different policies are not systematically explored.MethodsWe systematically reviewed 30-year evidence on GvHD prophylaxis and quantified the relative effect of different policies using a network meta-analysis. We searched PubMed and the Cochrane Library for randomized studies on the topic. The primary outcome of interest was grade II-IV acute GvHD over 0 or I (with odds ratio OR <1 denoting benefit).FindingsThirty-three eligible studies that enrolled 3,440 patients (published up to June 2014), provided data on seven immunosuppressive drugs namely cyclosporin A (CsA), methotrexate (MTX), anti-thymocyte globulin (ATG), mycophenolate mofetil (MMF), tacrolimus, sirolimus or corticosteroids and their combinations to calculate 14 direct and 21 indirect effects. The majority of trials (32/33) referred to myeloablative conditioning and sibling transplants (25/33). Tacrolimus/MTX (OR 0.44; 95% 0.27–0.70, number needed to treat to benefit, i.e. to avert a case of II-IV GvHD, NNTB = 5) and ATG/CsA/MTX (OR 0.45; 95%CI 0.26–0.78; NNTB = 5) were superior over CsA/MTX. ATG/CsA/MTX did not differ from tacrolimus/MTX (indirect evidence). Sirolimus-based prophylaxis outperformed CsA/MTX (OR 0.10; 95%CI 0.02–0.49, NNTB = 4) and marginally outperformed tacrolimus/MTX (OR 0.22; 95%CI 0.05–1.11). Add-on corticosteroids had no benefit over CsA/MTX.ConclusionsTacrolimus/MTX and ATG/CsA/MTX were the outperformers over CsA/MTX, but sirolimus-based regimens showed also potential. More randomized data are needed for reduced-intensity conditioning, as well as for MMF and sirolimus-containing regimens.

Regulating prostitution: A health risk approach

We build an equilibrium model of prostitution where clients and sex workers choose to demand and supply sex under three legal regimes: prohibition, regulation and laissez-faire. The key feature is the endogenous evolution of the risk as a consequence of policy changes. We calibrate the model to empirical evidence from Italy and then compare the effect of different policies on the equilibrium quantity of prostitution and on the harm associated with it. A prohibition regime that makes it illegal to buy sex but not to sell it is more effective than the opposite regime in reducing quantity. Taxes are one inducement to go illegal and prevent some of the less risky individuals from joining the market, leaving it smaller but riskier. A licensing system that prevents some infected individuals from joining the legal market reduces the risk and is therefore associated with an increase in quantity. Prohibition is preferable to minimize quantity only if a high expected fine is feasible. Regulation is best to minimize harm.

An Agent-Based Model for Simulating Environmental Behavior in an Educational Organization

Agent-based modeling (ABM) is an increasingly popular technique for modeling organizations or societies. In this paper, an ABM of environmental decisions in an academic organization is devised. The decision-making model for the agents and the social network have been constructed using data obtained by responses of individuals of the organization to a questionnaire. As the number of responses is relatively small while the number of variables measured is relatively high, and obtained decision rules should be explicit, decision trees were selected to generate the decision-making model after applying different techniques to properly preprocess the data set. Regarding the social network, two networks working in parallel were developed: the hierarchical relationships, or vertical network, and the relations of friendship and companionship, or horizontal network. After that, the effects of different policies derived from the scenarios obtained from backcasting workshops were tested, with the intention of investigating how to make policies more effective. The results obtained for the academic organization are presented.

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

A multilevel analysis of effects of land use policy on land-cover change and local land use decisions

Drylands, which occupy more than 40% of the Earth's land surface, are highly susceptible to degradation. It is important to understand causes, mechanisms, and environmental consequences of dryland ecosystem degradation. Land use policies are known to play a critical role in driving land cover changes, as well as in mitigating land degradation and promoting sustainable development in drylands. We analyzed the effects of different policies on vegetation cover and the attitude of local people toward policy changes in Uxin county, Inner Mongolia, China, based on remote sensed Normalized Difference Vegetation Index (NDVI) time series and household surveys. Overall vegetation in the study area was found to recover during 1987–2007. Multilevel statistical modeling results demonstrated that NDVI, density of agricultural population, density of livestock, land use, accessibility to market, and mean annual precipitation all had significant effects on re-vegetation. Changes in land use policy, which restricted farmers and herdsmen in certain land use practices and eliminated rangeland overload, were found to be an important driver of vegetation recovery during 1997–2007. Local households in the area generally approve the policy but adjust it according to their cultural traditions or land use practices.

Employment assistance policies of Chinese government play positive roles! The impact of post-earthquake employment assistance policies on the health-related quality of life of Chinese earthquake populations

Sichuan is the province that is most affected by earthquakes in mainland China. The employment assistance policies have gained an important position in the reconstruction efforts of the government. And the health condition of survivors has long been a concern of humanities scholars. But most studies focused only on the psychological health of earthquake populations and not on their overall health status. This study used both original data and tracking data. The data analysis of this study was mainly based on comparative analysis of the two data. We conducted the first investigation in May and June and the second investigation in October and November. A total of 2,000 earthquake survivors from five hard-hit disaster areas (Wenchuan, Qingchuan, Mianzhu, Lushan, Dujiangyan) participated in the investigation. First, we give descriptive statistical analysis of the post-disaster employment assistance policies of Chinese government and health-related quality of life (HRQOL) of earthquake populations. Second, we will explore the relationship between the eight domains of HRQOL of earthquake populations. Third, we also conduct confirmatory factor analysis to the medical outcome study short form 36 (SF-36). Finally we employ the structural equation modeling (SEM) to explore the effects of post-disaster employment assistance policies on the HRQOL of earthquake populations. The following conclusions are obtained from our analysis: (1) both the post-disaster employment assistance policies and SF-36 scales have good internal consistency. (2) The assessment of the employment assistance policies is relatively low. (3) The physical health and mental health of earthquake populations are not optimistic, and the HRQOL scores are low. (4) The SEM of the effect of employment assistance policies on the HRQOL of earthquake populations shows that the implementation of the seven domains of the post-disaster employment assistance policies of Chinese government is closely related. (5) The effect of different employment assistance policies of Chinese government on HRQOL differs. A few suggestions on how to improve the HRQOL of earthquake populations are given to according to our understanding of the effect of different policies on employment.

Variability and dilemmas in harm reduction for anabolic steroid users in the UK: a multi-area interview study.

BackgroundThe UK continues to experience a rise in the number of anabolic steroid-using clients attending harm reduction services such as needle and syringe programmes.MethodsThe present study uses interviews conducted with harm reduction service providers as well as illicit users of anabolic steroids from different areas of England and Wales to explore harm reduction for this group of drug users, focussing on needle distribution policies and harm reduction interventions developed specifically for this population of drug users.ResultsThe article addresses the complexity of harm reduction service delivery, highlighting different models of needle distribution, such as peer-led distribution networks, as well as interventions available in steroid clinics, including liver function testing of anabolic steroid users. Aside from providing insights into the function of interventions available to steroid users, along with principles adopted by service providers, the study found significant tensions and dilemmas in policy implementation due to differing perspectives between service providers and service users relating to practices, risks and effective interventions.ConclusionThe overarching finding of the study was the tremendous variability across harm reduction delivery sites in terms of available measures and mode of operation. Further research into the effectiveness of different policies directed towards people who use anabolic steroids is critical to the development of harm reduction.

Conflicting interests in defining an 'optimal' battery size when introducing the PHEV?

The PHEV is an interesting option for reducing greenhouse gas emissions from transport or to increase energy security without losing performance in car operation. However finding an optimal battery size is of great importance for the overall economic and environmental performance of the PHEVs. This study investigates the resulting vehicle design, and fleet composition and performance when optimising the PHEV battery with respect to different objective functions possibly reflecting different actors’ interest: number of PHEVs, cumulative cost savings and share of electric driving respectively under various assumptions concerning policies and costs. A recently available data set of car movements, containing 445 privately driven Swedish cars that have been measured with GPS-equipment for 1-2 months each is utilized to get a representative car fleet. We find that the battery size and fleet performance are heavily influenced by not only the choice of objective function for the optimization but also by its interaction with the cost structure and performance requirement in the transition from an energy efficient fuel-driven car to a PHEV. The effect of different policies may also vary depending on these conditions and may favour various actors’ interests differently. We conclude that these aspects are important to consider both when designing vehicles and when formulating policies for the introduction of PHEVs.

The impact of historical exclusion on the calibration of the SLEUTH urban growth model

This paper aims to emphasize the importance of the calibration process in urban growth modeling studies. The application of cellular automata (CA) in urban modeling can give insights into a wide variety of urban phenomena. The SLEUTH model, being as a well-tested CA, was utilized. Calibration data for the model were acquired from different sources of remotely sensed data recorded in 1967, 1977, 1987, 1998 and 2007. In this context three different excluded maps representing different scenarios were utilized during the calibration process in order to analyze the effects of different policies on urban growth. Each calibration scenario yielded its own parameter values. Thirteen calibration metrics for each scenario were derived. Integrating different exclusion layers to the beginning of the calibration process has reduced the number of possible growth patterns. The overall growth characteristics of Adana were similar for all calibration results and defined as organic growth except for the fact that the spatial allocation and the amount of potential urban pixels were different.

Inflationary effect of coal price change on the Chinese economy

This study investigates the pass-through effect induced by coal price fluctuations on the Chinese economy 2007–2011 based on a non-competitive input–output model. Three scenarios with different domestic tariff regulation alternatives, i.e., Actual Regulation (AR), No Regulation (NR), and Strong Regulation (SR), are simulated to reflect the effectiveness of different policies. At the sectoral scale, the Coking sector has the largest price variation under all scenarios while agriculture sectors and services sectors are the least sensitive. Nation-level impacts are examined by the weighted price changes of commodities used for different purposes. With the government regulation in reality, about 5% of the GDP deflator and CPI changes as well as 25% of the PPI change over the research period are attributed to coal price increase. Comparison shows the AR scenario brings more stable fluctuations but higher inflation than the NR scenario. The SR scenario confirms that authorities can remarkably relieve short-run inflation by controlling domestic electricity and heat tariffs. The induced inflationary expense sums up to between 0.03% and 0.97% of China’s GDP, around three quarters of which are burdened by investors and foreigners. The quantitative effect investigated in this study can serve as empirical evidence for policy makers regarding inflation control in China.

Adopting Black Carbon/Elemental Carbon as a Tool in Mobility Planning: the General Urban Traffic Plan of the City of Milan, Italy

Background. As part of the Strategic Environmental Assessment (SEA) procedure of the General Urban Traffic Plan, the Municipality of Milan introduced Elemental Carbon - basing on the experience with the air quality measurement of Black Carbon within the city - among quantitative indicators. Aims. To obtain a particulate toxicity indicator, easy-to-use within the normal planning activities of a local Public Authority, estimating environmental and health potential effects of different policy scenarios. Methods. Being the carbonaceous nanoparticles such as Black Carbon (BC), a sensitive indicator of the spatial variation of road traffic emissions (‘traffic proximity’ indicator), the emissions of Elemental Carbon (EC), pollutant closely related to BC, have been adopted as tracers of the population exposure. According to the literature, a critical distance from the vehicular traffic source has been identified to which refer evaluations of some health effects that have 'sufficient evidence' (in. asthma). People living at a distance &lt;75 m from major roads have an increased probability by about 30% of receiving a diagnosis of asthma and by about 40%-50% to be on medication for asthma or have had recent acute episodes in children (McConnell et al, 2006; Perez, 2012; Brugge et al, 2007). Thus an exposure indicator has been defined as the daily mean vehicular EC emissions released at a distance less than 75 meters from places of residence. This indicator has been estimated for several mobility planning scenarios. Results. This approach has proven to allow easy scenario comparison analysis. In the city of Milan, road pricing scenario at 2015 leads to an increase of total population exposed to lower emission levels (&lt;10 grams/day) and to a decrease of total population exposed to highest emission levels (&gt;50 grams/day). Conclusions. BC/EC, excellent tracer of 'traffic proximity‘ exposure, offers the possibility to verify the effectiveness of different policies in mobility planning.

Research Workforce Diversity: The Case of Balancing National versus International Postdocs in US Biomedical Research.

The US government has been increasingly supporting postdoctoral training in biomedical sciences to develop the domestic research workforce. However, current trends suggest that mostly international researchers benefit from the funding, many of whom might leave the USA after training. In this paper, we describe a model used to analyse the flow of national versus international researchers into and out of postdoctoral training. We calibrate our model in the case of the USA and successfully replicate the data. We use the model to conduct simulation-based analyses of effects of different policies on the diversity of postdoctoral researchers. Our model shows that capping the duration of postdoctoral careers, a policy proposed previously, favours international postdoctoral researchers. The analysis suggests that the leverage point to help the growth of domestic research workforce is in the pregraduate education area, and many policies implemented at the postgraduate level have minimal or unintended effects on diversity.