As households shop less frequently, food decay makes perishable food consumption more costly. Therefore, I hypothesize that shopping frequency is an important factor of household food choice. I test this hypothesis using an instrumental variables approach on a system of equations using household panel data and conclude that fresh produce consumption and shopping frequency are jointly chosen. Positive causal impacts are found in both directions. However, the causal impact of shopping frequency on fresh produce consumption is of modest magnitude. Therefore, policy initiatives that improve access to food retailers with the intention of increasing healthful food consumption — by inducing households to shop more frequently at store formats that carry fruits and vegetables — may be ineffective even if the policy is successful at increasing household shopping frequency to those stores.
{"title":"Shopping Frequency, Fresh Produce Consumption, and Food Retail Environment","authors":"Scott J. Colby","doi":"10.2139/ssrn.2726859","DOIUrl":"https://doi.org/10.2139/ssrn.2726859","url":null,"abstract":"As households shop less frequently, food decay makes perishable food consumption more costly. Therefore, I hypothesize that shopping frequency is an important factor of household food choice. I test this hypothesis using an instrumental variables approach on a system of equations using household panel data and conclude that fresh produce consumption and shopping frequency are jointly chosen. Positive causal impacts are found in both directions. However, the causal impact of shopping frequency on fresh produce consumption is of modest magnitude. Therefore, policy initiatives that improve access to food retailers with the intention of increasing healthful food consumption — by inducing households to shop more frequently at store formats that carry fruits and vegetables — may be ineffective even if the policy is successful at increasing household shopping frequency to those stores.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"53 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79659271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The objective of this paper is to estimate the causal effect of retirement on health care utilization. To do so, we use data from the 1992-2008 waves of the Health and Retirement Study (HRS) and the 2004-2006 waves of the Survey of Health, Aging, and Retirement in Europe (SHARE). In particular, we estimate the causal impact of retirement on health care utilization as measured by: doctor visits, visits to a general practitioner, nights in the hospital, and preventative care use. This paper uses panel data and instrumental variable methods, exploiting variation in statutory retirement ages across countries, to estimate the causal effects. Cross-country comparisons allow us to examine the role of a health care system’s use of the general practitioner as a gate keeper to specialists in this relationship. We find that while retirement is associated with increased health care use, our causal estimates show that retirement leads to fewer doctor visits in both the US and continental Europe. Nights in the hospital are unaffected by retirement status. Further we find that health care systems with primary care physicians who act as gatekeepers are particularly effective at decreasing doctor visits at retirement. Therefore, we conclude that increasing the statutory retirement age to help the solvency of the retirement systems will also increase doctor visits as individuals continue to work longer. In the US, the burden of this increased utilization will likely be borne by private insurance companies and public insurance to the extent it covers working individuals in their 60’s. European evidence suggests that this increase in doctor visits due to delayed retirement will be particularly evident in health systems without strong gatekeeper roles for general practitioners.
{"title":"Does Retirement Impact Health Care Utilization?","authors":"Norma B. Coe, Gema Zamarro","doi":"10.2139/ssrn.2714144","DOIUrl":"https://doi.org/10.2139/ssrn.2714144","url":null,"abstract":"The objective of this paper is to estimate the causal effect of retirement on health care utilization. To do so, we use data from the 1992-2008 waves of the Health and Retirement Study (HRS) and the 2004-2006 waves of the Survey of Health, Aging, and Retirement in Europe (SHARE). In particular, we estimate the causal impact of retirement on health care utilization as measured by: doctor visits, visits to a general practitioner, nights in the hospital, and preventative care use. This paper uses panel data and instrumental variable methods, exploiting variation in statutory retirement ages across countries, to estimate the causal effects. Cross-country comparisons allow us to examine the role of a health care system’s use of the general practitioner as a gate keeper to specialists in this relationship. We find that while retirement is associated with increased health care use, our causal estimates show that retirement leads to fewer doctor visits in both the US and continental Europe. Nights in the hospital are unaffected by retirement status. Further we find that health care systems with primary care physicians who act as gatekeepers are particularly effective at decreasing doctor visits at retirement. Therefore, we conclude that increasing the statutory retirement age to help the solvency of the retirement systems will also increase doctor visits as individuals continue to work longer. In the US, the burden of this increased utilization will likely be borne by private insurance companies and public insurance to the extent it covers working individuals in their 60’s. European evidence suggests that this increase in doctor visits due to delayed retirement will be particularly evident in health systems without strong gatekeeper roles for general practitioners.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"238 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72549873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a variable selection procedure based on the shrinkage estimation technique for a categorical varying-coefficient model. We apply the method to identify the relevant determinants for body mass index (BMI) from a large amount of potential factors proposed in the multidisciplinary literature, using data from the 2013 National Health Interview Survey in the United States. We quantify the varying impacts of the relevant determinants of BMI across demographic groups.
{"title":"Variable Selection for a Categorical Varying-Coefficient Model with Identifications for Determinants of Body Mass Index","authors":"Jiti Gao, B. Peng, Zhao Ren, Xiaohui Zhang","doi":"10.2139/ssrn.2672074","DOIUrl":"https://doi.org/10.2139/ssrn.2672074","url":null,"abstract":"In this paper, we propose a variable selection procedure based on the shrinkage estimation technique for a categorical varying-coefficient model. We apply the method to identify the relevant determinants for body mass index (BMI) from a large amount of potential factors proposed in the multidisciplinary literature, using data from the 2013 National Health Interview Survey in the United States. We quantify the varying impacts of the relevant determinants of BMI across demographic groups.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76802696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies a dynamic model of a fee-for-service healthcare system in which healthcare providers compete for patients by prescribing antibiotics. Using antibiotics limits antibiotic-treatable infections, but fosters the growth of antibiotic-resistant infections. The paper demonstrates a 'Goldilocks' effect from provider competition. A perfectly competitive market for providers over-prescribes antibiotics because providers do not bear the cost of antibiotic-resistant infections. A patient monopolist under-prescribes antibiotics in order to increase the level of treatable infection. This is because while infection is a 'bad' for society, infection is a 'good' for a provider of antibiotics under a fee-for-service regime. Due to more moderate antibiotic use, oligopolistic competition can be the optimal decentralized market structure. The paper then demonstrates how the model can be used for policy analysis by computing the optimal licensing regime, prescription quota, and tax on antibiotics.
{"title":"Strategic Dynamics of Antibiotic Use and the Evolution of Antibiotic-Resistant Infections","authors":"J. Albert","doi":"10.2139/ssrn.2738783","DOIUrl":"https://doi.org/10.2139/ssrn.2738783","url":null,"abstract":"This paper studies a dynamic model of a fee-for-service healthcare system in which healthcare providers compete for patients by prescribing antibiotics. Using antibiotics limits antibiotic-treatable infections, but fosters the growth of antibiotic-resistant infections. The paper demonstrates a 'Goldilocks' effect from provider competition. A perfectly competitive market for providers over-prescribes antibiotics because providers do not bear the cost of antibiotic-resistant infections. A patient monopolist under-prescribes antibiotics in order to increase the level of treatable infection. This is because while infection is a 'bad' for society, infection is a 'good' for a provider of antibiotics under a fee-for-service regime. Due to more moderate antibiotic use, oligopolistic competition can be the optimal decentralized market structure. The paper then demonstrates how the model can be used for policy analysis by computing the optimal licensing regime, prescription quota, and tax on antibiotics.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72772024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We use a field experiment to investigate the effect of incentives on food purchase decisions at a grocery store. We recruit over 200 participants and track their purchases for a period of 6 months, permitting us a glimpse of more than 3,500 individual shopping trips. We randomize participants to one of several treatments, in which we incentivize fresh fruit and vegetable purchases, provide tips for fruit and vegetable preparation, or both. We report several key insights. First, our informational content treatment has little effect. Second, we find an important price effect: modest pecuniary incentives more than double the proportion of dollars spent on produce in the grocery store. Third, we find an interesting pattern of consumption after the experiment ends: even when incentives are removed, the treatment group has higher fruit and vegetable purchases compared to the control group. These long-term results are in stark contrast to either a standard price model or a behavioral model of 'crowd out.' Rather, our results are consonant with a habit formation model. This opens up the distinct possibility that short term incentives can be used as a key instrument to combat obesity.
{"title":"Incentives to Eat Healthy: Evidence from a Grocery Store Field Experiment","authors":"J. List, A. Samek, Terri Zhu","doi":"10.2139/ssrn.2664818","DOIUrl":"https://doi.org/10.2139/ssrn.2664818","url":null,"abstract":"We use a field experiment to investigate the effect of incentives on food purchase decisions at a grocery store. We recruit over 200 participants and track their purchases for a period of 6 months, permitting us a glimpse of more than 3,500 individual shopping trips. We randomize participants to one of several treatments, in which we incentivize fresh fruit and vegetable purchases, provide tips for fruit and vegetable preparation, or both. We report several key insights. First, our informational content treatment has little effect. Second, we find an important price effect: modest pecuniary incentives more than double the proportion of dollars spent on produce in the grocery store. Third, we find an interesting pattern of consumption after the experiment ends: even when incentives are removed, the treatment group has higher fruit and vegetable purchases compared to the control group. These long-term results are in stark contrast to either a standard price model or a behavioral model of 'crowd out.' Rather, our results are consonant with a habit formation model. This opens up the distinct possibility that short term incentives can be used as a key instrument to combat obesity.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"87 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87431616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction -- Complaint is "a statement of dissatisfaction formally to an aspect of the experience of the service". Formally, complaint is only one of the four types of complaining behavior. The majority appears in form of voicer, which is the complaint that something is wrong in the organization. Another type is activism, which is revenge. Two smaller types are irates and passivism. Irates shows the complaint by involving in the spread of negative news about hospital services, whereas the pacifists do not state the complaint but use the word "wait a second" to "finish" and finally never comeback.Methodology -- This study consists of qualitative and quantitative components. Qualitative component consists of interviews and document studies in the planning stage. While the interview, document study, and observation methods were performed in the implementation stage. The analysis was performed by comparing the theoretical principles adapted from the existing context.Result -- Patient complaints were reduced with sigma level from 2.98 to 3.78. Patients were satisfied with the services; 82%. Number of complaints was from 26 to 14. Sigma level for inpatient preparation was from 3.77 to be 4.03. 88%, the room was ready in Conclusion -- This study proved that the implementation of Lean Six Sigma in KMC has succeeded to reduce the patient complaints upon all output variables. Results found the highest sigma contained in the inpatient preparation.
{"title":"Patient Complaint Reduction: A Case Study in Maternity Ward of Kemang Medical Care (KMC)","authors":"A. H. Iswanto","doi":"10.2139/ssrn.2632792","DOIUrl":"https://doi.org/10.2139/ssrn.2632792","url":null,"abstract":"Introduction -- Complaint is \"a statement of dissatisfaction formally to an aspect of the experience of the service\". Formally, complaint is only one of the four types of complaining behavior. The majority appears in form of voicer, which is the complaint that something is wrong in the organization. Another type is activism, which is revenge. Two smaller types are irates and passivism. Irates shows the complaint by involving in the spread of negative news about hospital services, whereas the pacifists do not state the complaint but use the word \"wait a second\" to \"finish\" and finally never comeback.Methodology -- This study consists of qualitative and quantitative components. Qualitative component consists of interviews and document studies in the planning stage. While the interview, document study, and observation methods were performed in the implementation stage. The analysis was performed by comparing the theoretical principles adapted from the existing context.Result -- Patient complaints were reduced with sigma level from 2.98 to 3.78. Patients were satisfied with the services; 82%. Number of complaints was from 26 to 14. Sigma level for inpatient preparation was from 3.77 to be 4.03. 88%, the room was ready in Conclusion -- This study proved that the implementation of Lean Six Sigma in KMC has succeeded to reduce the patient complaints upon all output variables. Results found the highest sigma contained in the inpatient preparation.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88360968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Medical providers often have a significant influence on treatment decisions which they can use in their own financial interest. Classical models of supplier-induced demand predict that medical providers will supply fewer services if they face increasing prices. We test this prediction based on a reform of hospital financing in Germany. Uniquely, this reform changed the overall level of reimbursement – with increasing prices for some hospitals and decreasing prices for others – without affecting the relative prices for different types of patients. Based on administrative data, we find that hospitals do indeed react to increasing prices by reducing service supply.
{"title":"Do Hospitals Respond to Increasing Prices by Supplying Fewer Services?","authors":"M. Salm, A. Wübker","doi":"10.2139/ssrn.2640116","DOIUrl":"https://doi.org/10.2139/ssrn.2640116","url":null,"abstract":"Medical providers often have a significant influence on treatment decisions which they can use in their own financial interest. Classical models of supplier-induced demand predict that medical providers will supply fewer services if they face increasing prices. We test this prediction based on a reform of hospital financing in Germany. Uniquely, this reform changed the overall level of reimbursement – with increasing prices for some hospitals and decreasing prices for others – without affecting the relative prices for different types of patients. Based on administrative data, we find that hospitals do indeed react to increasing prices by reducing service supply.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83654724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies the impact of the Health Insurance Marketplace (the Marketplace) on consumers. The aim is to study the motivation behind the consumer choice and the roles that insurers and government play. It also provide insights in improving the efficiency in the Marketplace.This paper introduces a cost point of view in modeling consumer decision. Consumers make rational choice by optimizing the objective function. The objective function includes the actual costs and the cost equivalent of health utilization. It is driven by the evidence that consumers value their costs most importantly. Moreover, this paper presents a conceptual framework of dividing health utilization into regions. This captures the practical features such as over utilization in healthcare. Bounded rationality is also discussed and three potential directions are provided. This paper also builds a model to predict medical expenditure which consists of a regression, a transition, and an evolution of the parameters. This model is the first to use the number of service visits as predictors. This is consistent with the collecting process of data which is at an service event base. Moreover, it incorporates the behavior considerations of the different insurance status of consumers. Aside from this model, two alternatives models are considered for comparison. They reflect two existing approaches: regression on personal characteristics and log transformation for nonzero expenditures. The predictors are selected and their coefficients are evaluated using the longitudinal data from Medical Expenditure Panel Survey (MEPS). The two alternatives are compared with the model and it turns out that the model outperforms them in both prediction accuracy and variability explanation. Finally this paper presents simulation of consumer choice. The results suggest that the cost saver better matches the statistics from the federal government than the utility maximizer. The results provides implications to the share between insurers and consumers. The actuarial values (the share of expenditure paid by insurers) is calculated based on simulated participation. They demonstrates inconsistency with the standard ones. Therefore inefficiency exits in the actuarial value calculation. This paper also evaluates the government involvements in the Marketplace. The results suggest that its involvements, especially the government subsidies, effectively encourage the broader participation of insurance plans.
{"title":"Modeling the Impact of Health Care Reform on Consumers","authors":"Su Xie, S. Zenios","doi":"10.2139/ssrn.2612607","DOIUrl":"https://doi.org/10.2139/ssrn.2612607","url":null,"abstract":"This paper studies the impact of the Health Insurance Marketplace (the Marketplace) on consumers. The aim is to study the motivation behind the consumer choice and the roles that insurers and government play. It also provide insights in improving the efficiency in the Marketplace.This paper introduces a cost point of view in modeling consumer decision. Consumers make rational choice by optimizing the objective function. The objective function includes the actual costs and the cost equivalent of health utilization. It is driven by the evidence that consumers value their costs most importantly. Moreover, this paper presents a conceptual framework of dividing health utilization into regions. This captures the practical features such as over utilization in healthcare. Bounded rationality is also discussed and three potential directions are provided. This paper also builds a model to predict medical expenditure which consists of a regression, a transition, and an evolution of the parameters. This model is the first to use the number of service visits as predictors. This is consistent with the collecting process of data which is at an service event base. Moreover, it incorporates the behavior considerations of the different insurance status of consumers. Aside from this model, two alternatives models are considered for comparison. They reflect two existing approaches: regression on personal characteristics and log transformation for nonzero expenditures. The predictors are selected and their coefficients are evaluated using the longitudinal data from Medical Expenditure Panel Survey (MEPS). The two alternatives are compared with the model and it turns out that the model outperforms them in both prediction accuracy and variability explanation. Finally this paper presents simulation of consumer choice. The results suggest that the cost saver better matches the statistics from the federal government than the utility maximizer. The results provides implications to the share between insurers and consumers. The actuarial values (the share of expenditure paid by insurers) is calculated based on simulated participation. They demonstrates inconsistency with the standard ones. Therefore inefficiency exits in the actuarial value calculation. This paper also evaluates the government involvements in the Marketplace. The results suggest that its involvements, especially the government subsidies, effectively encourage the broader participation of insurance plans.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74576275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dennis J. Zhang, I. Gurvich, J. V. Mieghem, Eric Park, R. Young, Mark V. Williams
The Hospital Readmissions Reduction Program (HRRP), a part of the U.S. Patient Protection and Affordable Care Act, requires the Centers for Medicare and Medicaid Services to penalize hospitals with excess readmissions. We take an economic and operational (patient flow) perspective to analyze the effectiveness of this policy in encouraging hospitals to reduce readmissions. We develop a game-theoretic model that captures the competition among hospitals inherent in HRRP’s benchmarking mechanism. We show that this competition can be counterproductive: it increases the number of nonincentivized hospitals, which prefer paying penalties over reducing readmissions in any equilibrium. We calibrate our model with a data set of more than 3,000 hospitals in the United States and show that under the current policy, and for a large set of parameters, 4%–13% of the hospitals remain nonincentivized to reduce readmissions. We also validate our model against the actual performance of hospitals in the three years since the introduction of the policy. We draw several policy recommendations to improve this policy’s outcome. For example, localizing the benchmarking process—comparing hospitals against similar peers—improves the performance of the policy. This paper was accepted by Serguei Netessine, operations management .
{"title":"Hospital Readmissions Reduction Program: An Economic and Operational Analysis","authors":"Dennis J. Zhang, I. Gurvich, J. V. Mieghem, Eric Park, R. Young, Mark V. Williams","doi":"10.2139/ssrn.2366493","DOIUrl":"https://doi.org/10.2139/ssrn.2366493","url":null,"abstract":"The Hospital Readmissions Reduction Program (HRRP), a part of the U.S. Patient Protection and Affordable Care Act, requires the Centers for Medicare and Medicaid Services to penalize hospitals with excess readmissions. We take an economic and operational (patient flow) perspective to analyze the effectiveness of this policy in encouraging hospitals to reduce readmissions. We develop a game-theoretic model that captures the competition among hospitals inherent in HRRP’s benchmarking mechanism. We show that this competition can be counterproductive: it increases the number of nonincentivized hospitals, which prefer paying penalties over reducing readmissions in any equilibrium. We calibrate our model with a data set of more than 3,000 hospitals in the United States and show that under the current policy, and for a large set of parameters, 4%–13% of the hospitals remain nonincentivized to reduce readmissions. We also validate our model against the actual performance of hospitals in the three years since the introduction of the policy. We draw several policy recommendations to improve this policy’s outcome. For example, localizing the benchmarking process—comparing hospitals against similar peers—improves the performance of the policy. This paper was accepted by Serguei Netessine, operations management .","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89664971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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