IO: Productivity最新文献_第3页

Fourth Industrial Revolution and Algorithms: New Challenges for Policy Design 第四次工业革命与算法:政策设计的新挑战

IO: Productivity Pub Date : 2021-05-03 DOI: 10.2139/ssrn.3838920

Tanya Heikkila, A. Wellstead

引用次数: 0

Science as a Public Good: Public Use and Funding of Science 科学作为一种公共产品:科学的公共使用和资助

IO: Productivity Pub Date : 2021-05-01 DOI: 10.2139/ssrn.3837737

Yian Yin, Yuxiao Dong, Kuansan Wang, Dashun Wang, Benjamin F. Jones

{"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}

引用次数: 6

Emerging Trends Towards Online Food Delivery Apps in India 印度在线送餐应用的新趋势

IO: Productivity Pub Date : 2021-04-30 DOI: 10.2139/ssrn.3837117

Samuel Anbu Selvan S. C. B, S. Andrew

{"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}

引用次数: 6

One Size Does not Fit All: Constructing Complementary Digital Re-Skilling Strategies Using Online Labour Market Data 一种模式不适合所有:利用在线劳动力市场数据构建互补的数字再技能战略

IO: Productivity Pub Date : 2021-04-28 DOI: 10.2139/ssrn.3835690

F. Stephany

{"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}

引用次数: 0

Quantifying Trade Secret Theft: Policy Implications 量化商业秘密盗窃:政策影响

IO: Productivity Pub Date : 2021-04-09 DOI: 10.2139/ssrn.3706511

Dan Ciuriak, María Ptashkina

引用次数: 1

Firm Differences: Skill Sorting and Software 公司差异:技能分类和软件

IO: Productivity Pub Date : 2021-04-01 DOI: 10.2139/ssrn.3862782

James Bessen, Erich Denk, Chen Meng

引用次数: 1

Is it Worth it? 值得吗?

IO: Productivity Pub Date : 2021-04-01 DOI: 10.2139/SSRN.3813443

Ken Akoundi, Kartik Uchil

引用次数: 0

Do Financial Constraints Reduce Process Innovation? Evidence from Australian Firms 财务约束会减少工艺创新吗?来自澳大利亚公司的证据

IO: Productivity Pub Date : 2021-03-22 DOI: 10.2139/ssrn.3809505

Siddarth Roche, Sizhong Sun, R. Welters

引用次数: 2

Intellectual Property Rights and Indigenous Dress Heritage: Towards More Social Planning Types of Practices via User-Centric Approaches 知识产权和土著服装遗产:通过以用户为中心的方法走向更多的社会规划类型实践

IO: Productivity Pub Date : 2021-03-18 DOI: 10.2139/ssrn.3807077

R. Ballardini, H. Härkönen, Iiris Kestilä

引用次数: 1

Endogenous Learning, Persistent Employer Biases, and Discrimination 内生性学习、持续雇主偏见与歧视

IO: Productivity Pub Date : 2021-03-02 DOI: 10.2139/ssrn.3640663

L. LePage

{"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}

引用次数: 3