Since the beginning of this century, ‘disruptive technologies, such as artificial intelligence, blockchain, big data, autonomous vehicles, and genetic editing, have transformed the economic and social fabric of peoples’ lives. Some colloquially refer to these changes as the 4th industrial revolution. This has led to a wide range of emerging policy issues centered on three policy areas: ethics, security, and research and development. Unlike the earlier digital policy literature that was focused on the application of informational technology, this chapter explores the role of algorithms that underlie these technologies. In this chapter, we raise key-related considerations for algorithmic policy design. First, codesign and nudging are two emerging tools applied in algorithmic policy design. Second, collaboration and learning are central processes. Finally, we highlight two important policy design outputs: trust and public value.
{"title":"Fourth Industrial Revolution and Algorithms: New Challenges for Policy Design","authors":"Tanya Heikkila, A. Wellstead","doi":"10.2139/ssrn.3838920","DOIUrl":"https://doi.org/10.2139/ssrn.3838920","url":null,"abstract":"Since the beginning of this century, ‘disruptive technologies, such as artificial intelligence, blockchain, big data, autonomous vehicles, and genetic editing, have transformed the economic and social fabric of peoples’ lives. Some colloquially refer to these changes as the 4th industrial revolution. This has led to a wide range of emerging policy issues centered on three policy areas: ethics, security, and research and development. Unlike the earlier digital policy literature that was focused on the application of informational technology, this chapter explores the role of algorithms that underlie these technologies. In this chapter, we raise key-related considerations for algorithmic policy design. First, codesign and nudging are two emerging tools applied in algorithmic policy design. Second, collaboration and learning are central processes. Finally, we highlight two important policy design outputs: trust and public value.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"121 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78865802","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}
Yian Yin, Yuxiao Dong, Kuansan Wang, Dashun Wang, Benjamin F. Jones
Knowledge of how science is consumed in public domains is essential for a deeper understanding of the role of science in human society. While science is heavily supported by public funding, common depictions suggest that scientific research remains an isolated or ‘ivory tower’ activity, with weak connectivity to public use, little relationship between the quality of research and its public use, and little correspondence between the funding of science and its public use. This paper introduces a measurement framework to examine public good features of science, allowing us to study public uses of science, the public funding of science, and how use and funding relate. Specifically, we integrate five large-scale datasets that link scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains – government documents, the news media, and marketplace invention. We find that the public uses of science are extremely diverse, with different public domains drawing distinctively across scientific fields. Yet amidst these differences, we find key forms of alignment in the interface between science and society. First, despite concerns that the public does not engage high-quality science, we find universal alignment, in each scientific field and public domain, between what the public consumes and what is highly impactful within science. Second, despite myriad factors underpinning the public funding of science, the resulting allocation across fields presents a striking alignment with the field’s collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet collectively science and society interface with remarkable, quantifiable alignment between scientific use, public use, and funding. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
{"title":"Science as a Public Good: Public Use and Funding of Science","authors":"Yian Yin, Yuxiao Dong, Kuansan Wang, Dashun Wang, Benjamin F. Jones","doi":"10.2139/ssrn.3837737","DOIUrl":"https://doi.org/10.2139/ssrn.3837737","url":null,"abstract":"Knowledge of how science is consumed in public domains is essential for a deeper understanding of the role of science in human society. While science is heavily supported by public funding, common depictions suggest that scientific research remains an isolated or ‘ivory tower’ activity, with weak connectivity to public use, little relationship between the quality of research and its public use, and little correspondence between the funding of science and its public use. This paper introduces a measurement framework to examine public good features of science, allowing us to study public uses of science, the public funding of science, and how use and funding relate. Specifically, we integrate five large-scale datasets that link scientific publications from all scientific fields to their upstream funding support and downstream public uses across three public domains – government documents, the news media, and marketplace invention. We find that the public uses of science are extremely diverse, with different public domains drawing distinctively across scientific fields. Yet amidst these differences, we find key forms of alignment in the interface between science and society. First, despite concerns that the public does not engage high-quality science, we find universal alignment, in each scientific field and public domain, between what the public consumes and what is highly impactful within science. Second, despite myriad factors underpinning the public funding of science, the resulting allocation across fields presents a striking alignment with the field’s collective public use. Overall, public uses of science present a rich landscape of specialized consumption, yet collectively science and society interface with remarkable, quantifiable alignment between scientific use, public use, and funding. \u0000 \u0000Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"351 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80032607","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 recent times, a growing trend has been noticed in the usage of online food delivery services. With the increased usage of technology, every industry is being re-shaped, to better serve the needs of customers, who are the kings of the market. Businesses which are regularly upgraded in order to meet the evolving expectations of customers are those that can succeed in the long run. It is not the technology behind the services provided, rather it is the experience provided to the consumer using real food technology. With this in the background, it should be noted that even customers who had previously preferred to purchase food through offline means, are now turning to online food delivery Apps to make their purchases. The dining out culture is now being transformed into the eating in culture. And this trend is observed to be prominent among youth (15 – 34), especially in the metropolitan cities where there are constant traffic jams and the heavy population density, which results in even short distance travelling being a highly time - consuming process. The resultant effect is that a greater number of Indian households are being seen turning to online food delivery services as an easier and more convenient alternative. As the usage of food delivery Apps grows in the metropolitan cities in India, a growing trend is also being seen in smaller cities. It has therefore become a necessity for online food delivery service providers to identify the preferences and perceptions of consumers to enable them to meet their expectations. Through this study the historical background, current scenario and possible future developments are analyzed in order to help online food delivery services develop better strategies to improve sales and increase the customer base.
{"title":"Emerging Trends Towards Online Food Delivery Apps in India","authors":"Samuel Anbu Selvan S. C. B, S. Andrew","doi":"10.2139/ssrn.3837117","DOIUrl":"https://doi.org/10.2139/ssrn.3837117","url":null,"abstract":"In recent times, a growing trend has been noticed in the usage of online food delivery services. With the increased usage of technology, every industry is being re-shaped, to better serve the needs of customers, who are the kings of the market. Businesses which are regularly upgraded in order to meet the evolving expectations of customers are those that can succeed in the long run. It is not the technology behind the services provided, rather it is the experience provided to the consumer using real food technology. With this in the background, it should be noted that even customers who had previously preferred to purchase food through offline means, are now turning to online food delivery Apps to make their purchases. The dining out culture is now being transformed into the eating in culture. And this trend is observed to be prominent among youth (15 – 34), especially in the metropolitan cities where there are constant traffic jams and the heavy population density, which results in even short distance travelling being a highly time - consuming process. The resultant effect is that a greater number of Indian households are being seen turning to online food delivery services as an easier and more convenient alternative. As the usage of food delivery Apps grows in the metropolitan cities in India, a growing trend is also being seen in smaller cities. It has therefore become a necessity for online food delivery service providers to identify the preferences and perceptions of consumers to enable them to meet their expectations. Through this study the historical background, current scenario and possible future developments are analyzed in order to help online food delivery services develop better strategies to improve sales and increase the customer base.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80951591","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}
Digital technologies are radically transforming our work environments and demand for skills, with certain jobs being automated away and others demanding mastery of new digital techniques. This global challenge of rapidly changing skill requirements due to task automation overwhelms workers. The digital skill gap widens further as technological and social transformation outpaces national education systems and precise skill requirements for mastering emerging technologies, such as Artificial Intelligence, remain opaque. Online labour platforms could help us to understand this grand challenge of reskilling en masse. Online labour platforms build a globally integrated market that mediates between millions of buyers and sellers of remotely deliverable cognitive work. This commentary argues that, over the last decade, online labour platforms have become the ‘laboratories’ of skill rebundling; the combination of skills from different occupational domains. Online labour platform data allows us to establish a new taxonomy on the individual complementarity of skills. For policy makers, education providers and recruiters, a continuous analysis of complementary reskilling trajectories enables automated, individual and far-sighted suggestions on the value of learning a new skill in a future of technological disruption.
{"title":"One Size Does not Fit All: Constructing Complementary Digital Re-Skilling Strategies Using Online Labour Market Data","authors":"F. Stephany","doi":"10.2139/ssrn.3835690","DOIUrl":"https://doi.org/10.2139/ssrn.3835690","url":null,"abstract":"Digital technologies are radically transforming our work environments and demand for skills, with certain jobs being automated away and others demanding mastery of new digital techniques. This global challenge of rapidly changing skill requirements due to task automation overwhelms workers. The digital skill gap widens further as technological and social transformation outpaces national education systems and precise skill requirements for mastering emerging technologies, such as Artificial Intelligence, remain opaque. Online labour platforms could help us to understand this grand challenge of reskilling en masse. Online labour platforms build a globally integrated market that mediates between millions of buyers and sellers of remotely deliverable cognitive work. This commentary argues that, over the last decade, online labour platforms have become the ‘laboratories’ of skill rebundling; the combination of skills from different occupational domains. Online labour platform data allows us to establish a new taxonomy on the individual complementarity of skills. For policy makers, education providers and recruiters, a continuous analysis of complementary reskilling trajectories enables automated, individual and far-sighted suggestions on the value of learning a new skill in a future of technological disruption.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83177849","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 the modern data-driven economy, trade secrets are becoming a more important part of firms’ intellectual property strategies. For their part, governments worldwide have been introducing new legislation to broaden and toughen the protection for trade secrets citing estimates of the cost of trade secret theft on the order of 1 to 3% of the GDP of the advanced countries. For the United States alone, this would put the cost of trade secret theft on the order of USD 180 to 540 billion. This note considers the “proxy” approach that has been used to generate these widely cited estimates as well as the extent of evidence that actually supports these claims. It concludes that the value of cross-border trade secret theft is much smaller than is suggested by the proxy methodology and suggests a more appropriate methodology to estimate the value of this illicit flow. The note also advances a number of considerations that temper the concern over cross-border trade secret theft.
{"title":"Quantifying Trade Secret Theft: Policy Implications","authors":"Dan Ciuriak, María Ptashkina","doi":"10.2139/ssrn.3706511","DOIUrl":"https://doi.org/10.2139/ssrn.3706511","url":null,"abstract":"In the modern data-driven economy, trade secrets are becoming a more important part of firms’ intellectual property strategies. For their part, governments worldwide have been introducing new legislation to broaden and toughen the protection for trade secrets citing estimates of the cost of trade secret theft on the order of 1 to 3% of the GDP of the advanced countries. For the United States alone, this would put the cost of trade secret theft on the order of USD 180 to 540 billion. This note considers the “proxy” approach that has been used to generate these widely cited estimates as well as the extent of evidence that actually supports these claims. It concludes that the value of cross-border trade secret theft is much smaller than is suggested by the proxy methodology and suggests a more appropriate methodology to estimate the value of this illicit flow. The note also advances a number of considerations that temper the concern over cross-border trade secret theft.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87234246","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}
Recent research shows that much recent rise in wage inequality comes from growing differences between firms, especially sorting of skilled workers to high-paying firms. This paper explores the role of proprietary software in these changes. Using job ad data, we find that proprietary software is strongly associated with firm wage fixed effects and also with firm skills. Software accounts for half or more of skill sorting across firms. Moreover, both skill sorting and firm wage effects are greater for larger firms. The huge growth in proprietary software helps explain the growth in skill sorting that increases wage inequality.
{"title":"Firm Differences: Skill Sorting and Software","authors":"James Bessen, Erich Denk, Chen Meng","doi":"10.2139/ssrn.3862782","DOIUrl":"https://doi.org/10.2139/ssrn.3862782","url":null,"abstract":"Recent research shows that much recent rise in wage inequality comes from growing differences between firms, especially sorting of skilled workers to high-paying firms. This paper explores the role of proprietary software in these changes. Using job ad data, we find that proprietary software is strongly associated with firm wage fixed effects and also with firm skills. Software accounts for half or more of skill sorting across firms. Moreover, both skill sorting and firm wage effects are greater for larger firms. The huge growth in proprietary software helps explain the growth in skill sorting that increases wage inequality.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"150 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79861306","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 attempt to answer the question about the cots-benefits of modernization of the investment offices. More specifically are they worth it? Four different approaches were used to answer the question: 1) a qualitative perspective, 2) a human efficiency perspective; 3) a technology cost-savings perspective; and 4) a hard-to-measure perspective. Overall, we found the answer to the question to be a resounding yes across all quantifiable and intangible measures.
{"title":"Is it Worth it?","authors":"Ken Akoundi, Kartik Uchil","doi":"10.2139/SSRN.3813443","DOIUrl":"https://doi.org/10.2139/SSRN.3813443","url":null,"abstract":"In this paper we attempt to answer the question about the cots-benefits of modernization of the investment offices. More specifically are they worth it? \u0000Four different approaches were used to answer the question: 1) a qualitative perspective, 2) a human efficiency perspective; 3) a technology cost-savings perspective; and 4) a hard-to-measure perspective. \u0000Overall, we found the answer to the question to be a resounding yes across all quantifiable and intangible measures.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83970488","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}
Accessing external finance for innovation is notoriously difficult. We study the effect of financial constraints on the probability of conducting process innovation, while also considering the role of past innovating experience. Theoretically, we show a firm’s optimal process innovation decision is a function of its previous decision, financial constraints, and a set of control variables. This decision naturally leads to a set of population moments, which we then test empirically using Australian microdata from 2006-2018. Our results reveal that if a firm does not conduct process innovation in the previous year, financial constraints reduce the probability of process innovation by around 10%. Whereas if a firm does conduct process innovation in the previous period, financial constraints reduce the probability of process innovation by around 12%.
{"title":"Do Financial Constraints Reduce Process Innovation? Evidence from Australian Firms","authors":"Siddarth Roche, Sizhong Sun, R. Welters","doi":"10.2139/ssrn.3809505","DOIUrl":"https://doi.org/10.2139/ssrn.3809505","url":null,"abstract":"Accessing external finance for innovation is notoriously difficult. We study the effect of financial constraints on the probability of conducting process innovation, while also considering the role of past innovating experience. Theoretically, we show a firm’s optimal process innovation decision is a function of its previous decision, financial constraints, and a set of control variables. This decision naturally leads to a set of population moments, which we then test empirically using Australian microdata from 2006-2018. Our results reveal that if a firm does not conduct process innovation in the previous year, financial constraints reduce the probability of process innovation by around 10%. Whereas if a firm does conduct process innovation in the previous period, financial constraints reduce the probability of process innovation by around 12%.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80273557","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 chapter explores the role of legal design in tackling challenges related to balancing protection and access while applying intellectual property rights to indigenous dress heritage (DH). First, we address the problems with the current mainstream approach to IPR, where the main focus is on economic incentives, while societal values are generally less considered. We then contextualize this discourse within the framework of indigenous DH, focusing on Sámi DH. Our analysis shows how moving from a purely economic-centric to a more social-planning type of justification for IPR could help in better reflecting societal values into IP. We argue that a design thinking approach would be important to reach this goal and we elaborate on how legal design could trigger such positive development.
{"title":"Intellectual Property Rights and Indigenous Dress Heritage: Towards More Social Planning Types of Practices via User-Centric Approaches","authors":"R. Ballardini, H. Härkönen, Iiris Kestilä","doi":"10.2139/ssrn.3807077","DOIUrl":"https://doi.org/10.2139/ssrn.3807077","url":null,"abstract":"The chapter explores the role of legal design in tackling challenges related to balancing protection and access while applying intellectual property rights to indigenous dress heritage (DH). First, we address the problems with the current mainstream approach to IPR, where the main focus is on economic incentives, while societal values are generally less considered. We then contextualize this discourse within the framework of indigenous DH, focusing on Sámi DH. Our analysis shows how moving from a purely economic-centric to a more social-planning type of justification for IPR could help in better reflecting societal values into IP. We argue that a design thinking approach would be important to reach this goal and we elaborate on how legal design could trigger such positive development.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83992075","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}
I present a statistical discrimination model of the labor market in which employers are initially uncertain about the productivity of worker groups and endogenously learn about it through their hiring. Previous hiring experiences with groups shape subsequent incentives of employers to hire from these groups again and learn more about their productivity, leading to differential learning across employers and biased beliefs about the productivity of groups. Given a market-clearing wage, optimal hiring follows a cutoff rule in posterior beliefs: employers with sufficiently negative experiences with workers from a group stop hiring from the group, preserving negative biases and leading to a negatively-skewed distribution of beliefs about their productivity. When employers have noisier initial information on the productivity of one worker group, discrimination against the group can arise and persist without productivity differentials or prior employer biases, with market competition, and with or without worker signaling or investment decisions. The model generates steady state predictions analogous to the Becker (1957) taste-based model, in a statistical framework with beliefs replacing preferences, explaining apparent prejudice as the result of "incorrect" statistical discrimination. The model also generates additional predictions with policy implications that contrast with traditional models of discrimination.
{"title":"Endogenous Learning, Persistent Employer Biases, and Discrimination","authors":"L. LePage","doi":"10.2139/ssrn.3640663","DOIUrl":"https://doi.org/10.2139/ssrn.3640663","url":null,"abstract":"I present a statistical discrimination model of the labor market in which employers are initially uncertain about the productivity of worker groups and endogenously learn about it through their hiring. Previous hiring experiences with groups shape subsequent incentives of employers to hire from these groups again and learn more about their productivity, leading to differential learning across employers and biased beliefs about the productivity of groups. Given a market-clearing wage, optimal hiring follows a cutoff rule in posterior beliefs: employers with sufficiently negative experiences with workers from a group stop hiring from the group, preserving negative biases and leading to a negatively-skewed distribution of beliefs about their productivity. When employers have noisier initial information on the productivity of one worker group, discrimination against the group can arise and persist without productivity differentials or prior employer biases, with market competition, and with or without worker signaling or investment decisions. The model generates steady state predictions analogous to the Becker (1957) taste-based model, in a statistical framework with beliefs replacing preferences, explaining apparent prejudice as the result of \"incorrect\" statistical discrimination. The model also generates additional predictions with policy implications that contrast with traditional models of discrimination.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82351786","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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