P. Brockett, L. Golden, Stephan Zaparolli, Jack M. Lum
With kidnaping rates rising, the disruptive forces of kidnaping threaten the stability and success of corporate investment projects and put stress on appropriate corporate governance response methodologies. While kidnaping targets vary considerably among countries where it frequently occurs, most often the goal of kidnapers is money from ransom payments. Financial consequences of a kidnap ransom payment can be severe for companies, and psychological damage can be lasting to employees and their families. Given the increasingly global nature of business and increasing expansion into less politically and legally stable emerging markets, kidnap, ransom, and extortion pose a problem for management of corporations wishing to take advantage of emerging market opportunities. Kidnap and Ransom (K&R) Insurance is a risk control technique used by about 75% of Fortune 500 companies, nongovernmental organizations, and an increasing percentage of small to medium sized companies. It is a bundled package policy that includes the purchase of an insurance policy to indemnify the company for the costs of kidnap, ransom, and extortion. Such policies can also provide protective consulting beforehand, provide crisis response and negotiation assistance, as well as psychological support services after the fact. In this paper, we describe the K&R policy, its history, other nonfinancial corporate benefits provided by K&R policies, and discuss its use by corporate managers for the benefit of corporate, financial, and personnel stability. It can also be used in course on managing international risk.
{"title":"Kidnap and Ransom Insurance: A Strategically Useful, Often Undiscussed, Marketplace Tool for International Operations","authors":"P. Brockett, L. Golden, Stephan Zaparolli, Jack M. Lum","doi":"10.1111/rmir.12134","DOIUrl":"https://doi.org/10.1111/rmir.12134","url":null,"abstract":"With kidnaping rates rising, the disruptive forces of kidnaping threaten the stability and success of corporate investment projects and put stress on appropriate corporate governance response methodologies. While kidnaping targets vary considerably among countries where it frequently occurs, most often the goal of kidnapers is money from ransom payments. Financial consequences of a kidnap ransom payment can be severe for companies, and psychological damage can be lasting to employees and their families. Given the increasingly global nature of business and increasing expansion into less politically and legally stable emerging markets, kidnap, ransom, and extortion pose a problem for management of corporations wishing to take advantage of emerging market opportunities. Kidnap and Ransom (K&R) Insurance is a risk control technique used by about 75% of Fortune 500 companies, nongovernmental organizations, and an increasing percentage of small to medium sized companies. It is a bundled package policy that includes the purchase of an insurance policy to indemnify the company for the costs of kidnap, ransom, and extortion. Such policies can also provide protective consulting beforehand, provide crisis response and negotiation assistance, as well as psychological support services after the fact. In this paper, we describe the K&R policy, its history, other nonfinancial corporate benefits provided by K&R policies, and discuss its use by corporate managers for the benefit of corporate, financial, and personnel stability. It can also be used in course on managing international risk.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115227955","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}
Unlike other forms of insurance, individuals with health insurance generally expect to make claims through the policy period. Selecting an appropriate level of cost‐sharing is difficult and individuals may, ex‐post, regret the choice of a less‐than‐suitable coverage amount. Using a national health insurance survey of private market consumers from 2013 to 2017, we evaluate the potential for post‐purchase regret in the health plan purchasing decision. We employ an ordered logistic model and find that consumers whose plan choices were likely financially dominated by a foregone alternative are significantly more likely to express regret through reporting significantly lower likelihood of renewal, even when controlling for confounding considerations including affordability, self‐assessed risk, and satisfaction with the plan.
{"title":"Regret in Health Insurance Post‐Purchase Behavior","authors":"P. Born, E. Sirmans","doi":"10.1111/rmir.12120","DOIUrl":"https://doi.org/10.1111/rmir.12120","url":null,"abstract":"Unlike other forms of insurance, individuals with health insurance generally expect to make claims through the policy period. Selecting an appropriate level of cost‐sharing is difficult and individuals may, ex‐post, regret the choice of a less‐than‐suitable coverage amount. Using a national health insurance survey of private market consumers from 2013 to 2017, we evaluate the potential for post‐purchase regret in the health plan purchasing decision. We employ an ordered logistic model and find that consumers whose plan choices were likely financially dominated by a foregone alternative are significantly more likely to express regret through reporting significantly lower likelihood of renewal, even when controlling for confounding considerations including affordability, self‐assessed risk, and satisfaction with the plan.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133299734","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}
A health risk score was created to investigate the possibility of using data provided by wearable technology to help predict overall health and mortality, with the ultimate goal of using this score to enhance the pricing of health or life insurance. Subjects were categorized into low‐, increased‐, and high‐risk groups, and after results were adjusted for age and sex, Cox proportional hazards analysis revealed a high level of significance when predicting mortality. High‐risk subjects were shown to have a hazard ratio of 2.1 relative to those in the low‐risk group, which can be interpreted as an equivalent increase in age of 7.8 years. Our findings help to demonstrate the predictive capabilities of potential new rating factors, measured via wearables, that could feasibly be incorporated into actuarial insurance pricing models. The model also provides an initial step for insurers to begin to consider the incorporation of continuous wearable data into current risk models. With this in mind, an emphasis is placed on the limitations of the study in order to highlight the areas that must be addressed before incorporating aspects of this model within current pricing models.
{"title":"A Conceptual Model for Pricing Health and Life Insurance Using Wearable Technology","authors":"Michael V. McCrea, M. Farrell","doi":"10.1111/rmir.12112","DOIUrl":"https://doi.org/10.1111/rmir.12112","url":null,"abstract":"A health risk score was created to investigate the possibility of using data provided by wearable technology to help predict overall health and mortality, with the ultimate goal of using this score to enhance the pricing of health or life insurance. Subjects were categorized into low‐, increased‐, and high‐risk groups, and after results were adjusted for age and sex, Cox proportional hazards analysis revealed a high level of significance when predicting mortality. High‐risk subjects were shown to have a hazard ratio of 2.1 relative to those in the low‐risk group, which can be interpreted as an equivalent increase in age of 7.8 years. Our findings help to demonstrate the predictive capabilities of potential new rating factors, measured via wearables, that could feasibly be incorporated into actuarial insurance pricing models. The model also provides an initial step for insurers to begin to consider the incorporation of continuous wearable data into current risk models. With this in mind, an emphasis is placed on the limitations of the study in order to highlight the areas that must be addressed before incorporating aspects of this model within current pricing models.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123950335","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}
Insurance is an essential component of household and community resilience. It protects insureds financially against disaster losses, can encourage investments in cost†effective mitigation measures through premium reductions, and facilitates the rebuilding of property and long†term recovery. Private insurers face challenges in providing full protection against disasters. This has led governments around the world to create a variety of public insurance entities, often designed as public†private partnerships. At a November 2016 workshop, “Improving Disaster Financing: Evaluating Policy Interventions in Disaster Insurance Markets,†participants evaluated disaster insurance programs for flood, earthquake, and terrorism losses. This article synthesizes six papers and findings from the workshop and suggests ways to improve public†private partnerships for disaster financing in three interrelated areas: (1) risk communication, (2) risk reduction, and (3) risk transfer. It concludes with a proposal for a comprehensive insurance program that could harness the benefits of both the public and private sectors.
{"title":"Risk Management Roles of the Public and Private Sector","authors":"C. Kousky, H. Kunreuther","doi":"10.1111/rmir.12096","DOIUrl":"https://doi.org/10.1111/rmir.12096","url":null,"abstract":"Insurance is an essential component of household and community resilience. It protects insureds financially against disaster losses, can encourage investments in cost†effective mitigation measures through premium reductions, and facilitates the rebuilding of property and long†term recovery. Private insurers face challenges in providing full protection against disasters. This has led governments around the world to create a variety of public insurance entities, often designed as public†private partnerships. At a November 2016 workshop, “Improving Disaster Financing: Evaluating Policy Interventions in Disaster Insurance Markets,†participants evaluated disaster insurance programs for flood, earthquake, and terrorism losses. This article synthesizes six papers and findings from the workshop and suggests ways to improve public†private partnerships for disaster financing in three interrelated areas: (1) risk communication, (2) risk reduction, and (3) risk transfer. It concludes with a proposal for a comprehensive insurance program that could harness the benefits of both the public and private sectors.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126850997","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 expansion of Medicaid and the creation of the Health Insurance Marketplace has provided greater access to health insurance coverage for many Michigan residents. To date, Michigan's Health Insurance Marketplace has seen relative success, in part due to the presence of multiple regional insurance carriers and the state's embrace of managed care in its Medicaid program in the 1990s. This report examines the conditions in Michigan's exchange market and analyzes its experience to date with carrier participation, pricing, and provider networks.
{"title":"ACA Exchange Competitiveness in Michigan","authors":"Megan Foster Friedman, Joshua Fangmeier, Nancy Baum, Marianne Udow‐Phillips","doi":"10.1111/rmir.12077","DOIUrl":"https://doi.org/10.1111/rmir.12077","url":null,"abstract":"The expansion of Medicaid and the creation of the Health Insurance Marketplace has provided greater access to health insurance coverage for many Michigan residents. To date, Michigan's Health Insurance Marketplace has seen relative success, in part due to the presence of multiple regional insurance carriers and the state's embrace of managed care in its Medicaid program in the 1990s. This report examines the conditions in Michigan's exchange market and analyzes its experience to date with carrier participation, pricing, and provider networks.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127995590","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 National Flood Insurance Program (NFIP), housed in the Federal Emergency Management Agency (FEMA), has been providing flood insurance to households and businesses for almost 50 years. To inform the policy discussion leading up to reauthorization, this paper analyzes five aspects of the NFIP: (1) risk modeling and risk communication; (2) the roles of the public and private sector; (3) take-up rates; (4) incentives for risk reduction; and (5) rate setting and the financing of catastrophic flood events. Suggestions for reform are discussed.
{"title":"Financing Flood Losses: A Discussion of the National Flood Insurance Program","authors":"C. Kousky","doi":"10.2139/SSRN.2947917","DOIUrl":"https://doi.org/10.2139/SSRN.2947917","url":null,"abstract":"The National Flood Insurance Program (NFIP), housed in the Federal Emergency Management Agency (FEMA), has been providing flood insurance to households and businesses for almost 50 years. To inform the policy discussion leading up to reauthorization, this paper analyzes five aspects of the NFIP: (1) risk modeling and risk communication; (2) the roles of the public and private sector; (3) take-up rates; (4) incentives for risk reduction; and (5) rate setting and the financing of catastrophic flood events. Suggestions for reform are discussed.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133069529","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}
Extant literature shows that IPO first-day returns are correlated with market returns preceding the issue. We propose a rational explanation for this puzzling predictability by adding a public signal to Benveniste and Spindt (1989)’s information-based framework. A novel result of our model is that the compensation required by investors to truthfully reveal their information decreases with the public signal. This “incentive effect” receives strong empirical support in a sample of 6300 IPOs in 1983–2012. Controlling for the incentive effect, the positive relation between initial returns and pre-issue market returns disappears for top-tier underwriters, where the order book is held to be most informative, effectively resolving the predictability puzzle.
{"title":"Partial Adjustment to Public Information in the Pricing of IPOs","authors":"E. Bakke, Tore E. Leite, K. Thorburn","doi":"10.2139/ssrn.2021802","DOIUrl":"https://doi.org/10.2139/ssrn.2021802","url":null,"abstract":"Extant literature shows that IPO first-day returns are correlated with market returns preceding the issue. We propose a rational explanation for this puzzling predictability by adding a public signal to Benveniste and Spindt (1989)’s information-based framework. A novel result of our model is that the compensation required by investors to truthfully reveal their information decreases with the public signal. This “incentive effect” receives strong empirical support in a sample of 6300 IPOs in 1983–2012. Controlling for the incentive effect, the positive relation between initial returns and pre-issue market returns disappears for top-tier underwriters, where the order book is held to be most informative, effectively resolving the predictability puzzle.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117207743","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 examine whether enterprise risk management (ERM) is legally required for financial institutions (e.g., banks, securities brokerage firms, insurance, hedge funds and mutual funds), government entities, publicly traded companies, and private enterprises. We find that ERM is legally required for U.S. financial institutions and for some government-sponsored enterprises. Legally required means required by U.S. statutes, federal case law, or U.S. regulatory agencies (e.g., Securities and Exchange Commission [SEC]). ERM is an important factor for rating organizations (e.g., Standard & Poor's [S&P]), but not legally required. We found no U.S. statutes or federal court cases requiring an ERM framework for private enterprises, although ERM is accepted as a value-contributing best practice, and elements of ERM are practiced by some private enterprises. For publically traded companies, elements of ERM are required by federal statute, by the SEC, and by S&P. We suggest that if a private enterprise is sued in U.S. federal court alleging breach of a legal duty to practice ERM, the suit will likely be dismissed. We trace the development of ERM from a traditional risk management (TRM) base. Fortunately, ERM is recognized as a value-contributing best practice in corporate governance even when legal standards do not require it.
{"title":"Is ERM Legally Required? Yes for Financial and Governmental Institutions, No for Private Enterprises","authors":"A. Whitman","doi":"10.1111/rmir.12045","DOIUrl":"https://doi.org/10.1111/rmir.12045","url":null,"abstract":"We examine whether enterprise risk management (ERM) is legally required for financial institutions (e.g., banks, securities brokerage firms, insurance, hedge funds and mutual funds), government entities, publicly traded companies, and private enterprises. We find that ERM is legally required for U.S. financial institutions and for some government-sponsored enterprises. Legally required means required by U.S. statutes, federal case law, or U.S. regulatory agencies (e.g., Securities and Exchange Commission [SEC]). ERM is an important factor for rating organizations (e.g., Standard & Poor's [S&P]), but not legally required. We found no U.S. statutes or federal court cases requiring an ERM framework for private enterprises, although ERM is accepted as a value-contributing best practice, and elements of ERM are practiced by some private enterprises. For publically traded companies, elements of ERM are required by federal statute, by the SEC, and by S&P. We suggest that if a private enterprise is sued in U.S. federal court alleging breach of a legal duty to practice ERM, the suit will likely be dismissed. We trace the development of ERM from a traditional risk management (TRM) base. Fortunately, ERM is recognized as a value-contributing best practice in corporate governance even when legal standards do not require it.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127121094","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 study examines the effect of tort reform on medical malpractice insurers with an emphasis on the effect of cap levels on noneconomic damages. While previous research finds that caps on noneconomic damages have a beneficial effect on insurer performance, these studies do not evaluate the effects of caps of varying size. Examining insurer data from 1997 to 2007, we test whether cap levels matter. We find that insurer performance generally improves when the cap is set at $250,000, but caps exceeding $250,000 are not associated with improved performance, as they are possibly not binding on award amounts.
{"title":"The Differential Effects of Noneconomic Damage Cap Levels on Medical Malpractice Insurers","authors":"P. Born, Faith Roberts Neale","doi":"10.1111/rmir.12005","DOIUrl":"https://doi.org/10.1111/rmir.12005","url":null,"abstract":"This study examines the effect of tort reform on medical malpractice insurers with an emphasis on the effect of cap levels on noneconomic damages. While previous research finds that caps on noneconomic damages have a beneficial effect on insurer performance, these studies do not evaluate the effects of caps of varying size. Examining insurer data from 1997 to 2007, we test whether cap levels matter. We find that insurer performance generally improves when the cap is set at $250,000, but caps exceeding $250,000 are not associated with improved performance, as they are possibly not binding on award amounts.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122839016","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 demonstrate that jumps in financial asset prices are not nearly as common as generally thought, and that they account for only a very small proportion of total return variation. We base our investigation on an extensive set of ultra high-frequency equity and foreign exchange rate data recorded at milli-second precision, allowing us to view the price evolution at a microscopic level. We show that both in theory and practice, traditional measures of jump variation based on low-frequency tick data tend to spuriously attribute a burst of volatility to the jump component thereby severely overstating the true variation coming from jumps. Indeed, our estimates based on tick data suggest that the jump variation is an order of magnitude smaller. This finding has a number of important implications for asset pricing and risk management and we illustrate this with a delta hedging example of an option trader that is short gamma. Our econometric analysis is build around a pre-averaging theory that allows us to work at the highest available frequency, where the data are polluted bymicrostructure noise. We extend the theory in a number of directions important for jump estimation and testing. This also reveals that pre-averaging has a built-in robustness property to outliers in high-frequency data, and allows us to show that some of the few remaining jumps at tick frequency are in fact induced by data-cleaning routines aimed at removing the outliers.
{"title":"Fact or Friction: Jumps at Ultra High Frequency","authors":"Kim Christensen, R. Oomen, M. Podolskij","doi":"10.2139/ssrn.1848774","DOIUrl":"https://doi.org/10.2139/ssrn.1848774","url":null,"abstract":"In this paper, we demonstrate that jumps in financial asset prices are not nearly as common as generally thought, and that they account for only a very small proportion of total return variation. We base our investigation on an extensive set of ultra high-frequency equity and foreign exchange rate data recorded at milli-second precision, allowing us to view the price evolution at a microscopic level. We show that both in theory and practice, traditional measures of jump variation based on low-frequency tick data tend to spuriously attribute a burst of volatility to the jump component thereby severely overstating the true variation coming from jumps. Indeed, our estimates based on tick data suggest that the jump variation is an order of magnitude smaller. This finding has a number of important implications for asset pricing and risk management and we illustrate this with a delta hedging example of an option trader that is short gamma. Our econometric analysis is build around a pre-averaging theory that allows us to work at the highest available frequency, where the data are polluted bymicrostructure noise. We extend the theory in a number of directions important for jump estimation and testing. This also reveals that pre-averaging has a built-in robustness property to outliers in high-frequency data, and allows us to show that some of the few remaining jumps at tick frequency are in fact induced by data-cleaning routines aimed at removing the outliers.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125925555","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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