The financial industry offers a unique setting to study innovations. Financial innovations (FIs) have fueled the growth of economies, markets, and societies. The financial industry has successfully become the breeding ground for innovative services, processes, business models, and technologies. Three market developments are disrupting the industry and opening up a new era for the financial services industry. Disruptions from within and outside the industry offer new generations of radically-innovative services. Moreover, new generations of consumers differ from previous generations in their needs and wants and look for innovative ways to handle their financial needs. Finally, significant developments related to financial innovations have emerged in Asia and developing countries. In light of these market disruptions, this study systematically reviews the academic research literature on FIs in two phases. The first phase provides a quantitative review of 546 journal articles published between 1990 and 2018. This analysis found that disciplines differ with regard to the employed research methodologies, the units of analysis, sources of data, and the innovations they examined. The analysis found a positive trend in the number of published articles during this period. However, studies have primarily focused on the US and Europe and less so on other parts of the world. In the second phase, the study synthesizes the extant research on FIs and maps them in five research areas: firms' introduction and adoption of FIs, financial innovation development, the outcomes of financial innovations, regulations and intellectual property, and consumers. This synthesis further identifies research gaps in the available research that highlight future research opportunities in light of the three market disruptions.
{"title":"Research on Financial Innovations: An Interdisciplinary Review","authors":"Mohammad G. Nejad","doi":"10.2139/ssrn.3895792","DOIUrl":"https://doi.org/10.2139/ssrn.3895792","url":null,"abstract":"The financial industry offers a unique setting to study innovations. Financial innovations (FIs) have fueled the growth of economies, markets, and societies. The financial industry has successfully become the breeding ground for innovative services, processes, business models, and technologies. Three market developments are disrupting the industry and opening up a new era for the financial services industry. Disruptions from within and outside the industry offer new generations of radically-innovative services. Moreover, new generations of consumers differ from previous generations in their needs and wants and look for innovative ways to handle their financial needs. Finally, significant developments related to financial innovations have emerged in Asia and developing countries. In light of these market disruptions, this study systematically reviews the academic research literature on FIs in two phases. The first phase provides a quantitative review of 546 journal articles published between 1990 and 2018. This analysis found that disciplines differ with regard to the employed research methodologies, the units of analysis, sources of data, and the innovations they examined. The analysis found a positive trend in the number of published articles during this period. However, studies have primarily focused on the US and Europe and less so on other parts of the world. In the second phase, the study synthesizes the extant research on FIs and maps them in five research areas: firms' introduction and adoption of FIs, financial innovation development, the outcomes of financial innovations, regulations and intellectual property, and consumers. This synthesis further identifies research gaps in the available research that highlight future research opportunities in light of the three market disruptions.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"117 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79482733","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}
Ryan Hill, Yian Yin, Carolyn Stein, Dashun Wang, Benjamin F. Jones
The ability to confront new questions, opportunities, and challenges is of fundamental importance to human progress and the resilience of human societies, yet the capacity of science to meet new demands remains poorly understood. Here we deploy a new measurement framework to investigate the scientific response to the COVID-19 pandemic and the adaptability of science as a whole. We find that science rapidly shifted to engage COVID-19 following the advent of the virus, with scientists across all fields making large jumps from their prior research streams. However, this adaptive response reveals a pervasive "pivot penalty", where the impact of the new research steeply declines the further the scientists move from their prior work. The pivot penalty is severe amidst COVID-19 research, but it is not unique to COVID-19. Rather it applies nearly universally across the sciences, and has been growing in magnitude over the past five decades. While further features condition pivoting, including a scientist's career stage, prior expertise and impact, collaborative scale, the use of new coauthors, and funding, we find that the pivot penalty persists and remains substantial regardless of these features, suggesting the pivot penalty acts as a fundamental friction that governs science's ability to adapt. The pivot penalty not only holds key implications for the design of the scientific system and human capacity to confront emergent challenges through scientific advance, but may also be relevant to other social and economic systems, where shifting to meet new demands is central to survival and success.
{"title":"Adaptability and the Pivot Penalty in Science","authors":"Ryan Hill, Yian Yin, Carolyn Stein, Dashun Wang, Benjamin F. Jones","doi":"10.2139/ssrn.3886142","DOIUrl":"https://doi.org/10.2139/ssrn.3886142","url":null,"abstract":"The ability to confront new questions, opportunities, and challenges is of fundamental importance to human progress and the resilience of human societies, yet the capacity of science to meet new demands remains poorly understood. Here we deploy a new measurement framework to investigate the scientific response to the COVID-19 pandemic and the adaptability of science as a whole. We find that science rapidly shifted to engage COVID-19 following the advent of the virus, with scientists across all fields making large jumps from their prior research streams. However, this adaptive response reveals a pervasive \"pivot penalty\", where the impact of the new research steeply declines the further the scientists move from their prior work. The pivot penalty is severe amidst COVID-19 research, but it is not unique to COVID-19. Rather it applies nearly universally across the sciences, and has been growing in magnitude over the past five decades. While further features condition pivoting, including a scientist's career stage, prior expertise and impact, collaborative scale, the use of new coauthors, and funding, we find that the pivot penalty persists and remains substantial regardless of these features, suggesting the pivot penalty acts as a fundamental friction that governs science's ability to adapt. The pivot penalty not only holds key implications for the design of the scientific system and human capacity to confront emergent challenges through scientific advance, but may also be relevant to other social and economic systems, where shifting to meet new demands is central to survival and success.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74165103","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 COVID-19 pandemic highlighted vulnerabilities in upstream pharmaceutical supply chains (PSC) associated with the manufacture of essential active pharmaceutical ingredients (APIs). The need to develop health countermeasures provided new impetus to supporting advanced manufacturing technologies such as process intensification through continuous manufacturing (CM). Recent advanced manufacturing developments suggest potential advantages in adopting CM over traditional batch technologies. However, at an early stage of evaluation detailed quantitative information is limited, and selecting specific reactor technologies based on multiple, conflicting criteria is challenging. To address these early-stage manufacturing technology selection challenges, this paper applies an Analytical Hierarchy Process approach, integrating multiple managerial and engineering criteria. The analysis focuses on reactor technologies in upstream PSC manufacturing. Findings suggest that microreactor technologies outperform alternatives all things considered. However, PSC managerial considerations introduce nuances in specific therapeutic areas e.g., antivirals where a tension between complex chemistry and the need for flexibility in unit operations may favour batch manufacturing. For analgesics the need to exploit the existing manufacturing base whilst addressing inventory reduction favour technologies that incorporate elements of batch and CM. Research enriches previous conceptual frameworks predicated on volume-variety considerations, providing an empirical workflow for the multi-faceted evaluation of alternative CM reactor technologies in PSC.
{"title":"Multi-Criteria Assessment of Continuous Manufacturing Reactor Technologies in Upstream Pharmaceutical Supply Chains","authors":"Parminder Kaur Aulakh, E. Settanni, J. Srai","doi":"10.2139/ssrn.3884025","DOIUrl":"https://doi.org/10.2139/ssrn.3884025","url":null,"abstract":"The COVID-19 pandemic highlighted vulnerabilities in upstream pharmaceutical supply chains (PSC) associated with the manufacture of essential active pharmaceutical ingredients (APIs). The need to develop health countermeasures provided new impetus to supporting advanced manufacturing technologies such as process intensification through continuous manufacturing (CM). Recent advanced manufacturing developments suggest potential advantages in adopting CM over traditional batch technologies. However, at an early stage of evaluation detailed quantitative information is limited, and selecting specific reactor technologies based on multiple, conflicting criteria is challenging. To address these early-stage manufacturing technology selection challenges, this paper applies an Analytical Hierarchy Process approach, integrating multiple managerial and engineering criteria. The analysis focuses on reactor technologies in upstream PSC manufacturing. Findings suggest that microreactor technologies outperform alternatives all things considered. However, PSC managerial considerations introduce nuances in specific therapeutic areas e.g., antivirals where a tension between complex chemistry and the need for flexibility in unit operations may favour batch manufacturing. For analgesics the need to exploit the existing manufacturing base whilst addressing inventory reduction favour technologies that incorporate elements of batch and CM. Research enriches previous conceptual frameworks predicated on volume-variety considerations, providing an empirical workflow for the multi-faceted evaluation of alternative CM reactor technologies in PSC.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83260134","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 platform age, copyright-protected contents are primarily disseminated over the internet. This model poses various challenges to the copyright regime that was mainly designed in and for the analog age. One of these challenges is related to the fair balance between the interests of rightsholders and other members of society. Copyright norms try to guarantee this balance by granting a high level of protection for rightsholders and preserving some flexibility for end-users. Regulation by platforms’ end-user license agreements might also be relevant to preserve that balance. The present paper focused on how these private norms allow for or diminish the exercise of user flexibilities. We collected, analyzed, and compared seventeen private ordering practices of service providers grouped in four main categories. Our empirical examination demonstrated that intermediaries offer substantive flexibilities for their consumers, on the one hand, and they meaningfully limit the possibilities and decrease the expectations of end-users by restricting certain uses and providing limited access to contents, on the other hand. We measured the flexibility of the selected platforms, and we provided for the state of the art of platform flexibilities in the period preceding the implementation deadline of the EU’s CDSM Directive.
{"title":"End-User Flexibilities in Digital Copyright Law – An Empirical Analysis of End-user License Agreements","authors":"Péter Mezei, István Harkai","doi":"10.2139/ssrn.3879740","DOIUrl":"https://doi.org/10.2139/ssrn.3879740","url":null,"abstract":"In the platform age, copyright-protected contents are primarily disseminated over the internet. This model poses various challenges to the copyright regime that was mainly designed in and for the analog age. One of these challenges is related to the fair balance between the interests of rightsholders and other members of society. Copyright norms try to guarantee this balance by granting a high level of protection for rightsholders and preserving some flexibility for end-users. Regulation by platforms’ end-user license agreements might also be relevant to preserve that balance. The present paper focused on how these private norms allow for or diminish the exercise of user flexibilities. We collected, analyzed, and compared seventeen private ordering practices of service providers grouped in four main categories. Our empirical examination demonstrated that intermediaries offer substantive flexibilities for their consumers, on the one hand, and they meaningfully limit the possibilities and decrease the expectations of end-users by restricting certain uses and providing limited access to contents, on the other hand. We measured the flexibility of the selected platforms, and we provided for the state of the art of platform flexibilities in the period preceding the implementation deadline of the EU’s CDSM Directive.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86989171","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}
Artificial intelligence (AI) has been increasingly integrated into the process of matching between workers and employers requesting job tasks on a gig-economy platform. Unlike the conventional wisdom that adopting AI in the matching process always benefits the platform by assigning better-matched jobs (employers) to workers, we discover unintended but possible revenue-decreasing consequences for the AI-adopting platform. We build a stylized game theoretical model that considers gig workers’ strategic participation behavior. We find that while the matching enhancement effect of AI can increase the platform’s revenue by improving matching quality, AI-assigned jobs can also reveal information about the uncertain labor demand to workers and thus unfavorably change workers’ participation decisions, resulting in revenue loss for the platform. We extend our model to the cases where (1) the share of revenue between workers and platform is endogenous and (2) the workers compete for the job tasks, and find consistent results. Furthermore, we examine two approaches to mitigate the potential negative effect of AI-enabled matching for the platform and find that under certain conditions, the AI-adopting platform can be better off by revealing the labor demand or competition information directly to workers. Our results shed light on both the intended positive and unintended negative roles of utilizing AI to facilitate matching, and highlight the importance of thoughtful development, management, and application of AI in the gig economy.
{"title":"The Coin of AI Has Two Sides: Matching Enhancement and Information Revelation Effects of AI on Gig-Economy Platforms","authors":"Yi Liu, Xinyi Zhao, Bowen Lou, Xinxin Li","doi":"10.2139/ssrn.3877868","DOIUrl":"https://doi.org/10.2139/ssrn.3877868","url":null,"abstract":"Artificial intelligence (AI) has been increasingly integrated into the process of matching between workers and employers requesting job tasks on a gig-economy platform. Unlike the conventional wisdom that adopting AI in the matching process always benefits the platform by assigning better-matched jobs (employers) to workers, we discover unintended but possible revenue-decreasing consequences for the AI-adopting platform. We build a stylized game theoretical model that considers gig workers’ strategic participation behavior. We find that while the matching enhancement effect of AI can increase the platform’s revenue by improving matching quality, AI-assigned jobs can also reveal information about the uncertain labor demand to workers and thus unfavorably change workers’ participation decisions, resulting in revenue loss for the platform. We extend our model to the cases where (1) the share of revenue between workers and platform is endogenous and (2) the workers compete for the job tasks, and find consistent results. Furthermore, we examine two approaches to mitigate the potential negative effect of AI-enabled matching for the platform and find that under certain conditions, the AI-adopting platform can be better off by revealing the labor demand or competition information directly to workers. Our results shed light on both the intended positive and unintended negative roles of utilizing AI to facilitate matching, and highlight the importance of thoughtful development, management, and application of AI in the gig economy.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"47 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90914594","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}
Pub Date : 2021-06-30DOI: 10.21303/2313-8416.2021.001926
I. Kartuzov
An objective of this effort is a quick recap to assess the underpin barriers of transfer of technologies appeared in Ukraine after acquiring the Independence and those developed of today and to highlight and evaluate an impact of political, historical, mental and other factors affecting the science and as a consequence leakage of technologies abroad. Of importance is also a question if a current COVID-19 pandemic will join these factors if it initiates an illicit transfer of dual use (DU) technologies from Ukraine as it was in 1990s and how it affects an efficient and proper functioning and optimization of transfer of technologies process, and that is quite a challenge nowadays. Investigated problem. The process of technology transfer and specifically that one of DU as a whole is neither simple nor systematic and far from being that perfect, especially when it deals with dual-use technologies and at present reduced to a short relationship between supplier/recipient only. The experience and practice show that it is a rather complicated, multi-leveled and multi-players process which is impacted and follows several factors and conditions that determine its success and/or failure at the end. The main scientific results. The development of dual use technologies continues in a quagmire of conflicting interests and technology transfer export control rationales. There are historical, mental and political-military considerations where a state’s decision to develop weapon systems or related applications can be assessed not only as a function of perceived levels of threat to its security, but also as a need to respond and/or step forward to potential technological innovations; and second, the fundamental conceptual differences in appreciation among countries of the right to possess different advanced weapons systems for defensive or offensive purposes. The result of this endeavor makes a solid ground floor for further debates in terms of political science, export control regulations and factors affecting transfer of sensitive technologies.
{"title":"Four Factors are in Force Pandemic Joints to Initiate an Illicit Dual Use Technologies Transfer from Ukraine","authors":"I. Kartuzov","doi":"10.21303/2313-8416.2021.001926","DOIUrl":"https://doi.org/10.21303/2313-8416.2021.001926","url":null,"abstract":"An objective of this effort is a quick recap to assess the underpin barriers of transfer of technologies appeared in Ukraine after acquiring the Independence and those developed of today and to highlight and evaluate an impact of political, historical, mental and other factors affecting the science and as a consequence leakage of technologies abroad. Of importance is also a question if a current COVID-19 pandemic will join these factors if it initiates an illicit transfer of dual use (DU) technologies from Ukraine as it was in 1990s and how it affects an efficient and proper functioning and optimization of transfer of technologies process, and that is quite a challenge nowadays. Investigated problem. The process of technology transfer and specifically that one of DU as a whole is neither simple nor systematic and far from being that perfect, especially when it deals with dual-use technologies and at present reduced to a short relationship between supplier/recipient only. The experience and practice show that it is a rather complicated, multi-leveled and multi-players process which is impacted and follows several factors and conditions that determine its success and/or failure at the end. The main scientific results. The development of dual use technologies continues in a quagmire of conflicting interests and technology transfer export control rationales. There are historical, mental and political-military considerations where a state’s decision to develop weapon systems or related applications can be assessed not only as a function of perceived levels of threat to its security, but also as a need to respond and/or step forward to potential technological innovations; and second, the fundamental conceptual differences in appreciation among countries of the right to possess different advanced weapons systems for defensive or offensive purposes. The result of this endeavor makes a solid ground floor for further debates in terms of political science, export control regulations and factors affecting transfer of sensitive technologies.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"79 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75157600","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}
Pub Date : 2021-06-30DOI: 10.15587/1729-4061.2021.235948
O. Zinchenko, Olesya Finahina, L. Pankova, Ievgen Buriak, Yu. O. Kovalenko
The relevance of the issue, related to building an information infrastructure of technology transfer, is predetermined by the transformation of information into the most important resource of technological cooperation. At the same time, its effective functioning requires investment support on a regular basis. This paper addresses the establishment of regularities in the process of investing in the development of the information infrastructure of technology transfer and determining the rational volumes of these investments. This study was carried out in the context of the regional market, which is due to the territorial specificity of market processes, the peculiarity of information interaction among economic agents in a separate market. The study results have identified the following patterns: the lower the transaction costs of technology transfer participants, the more productive the functioning of the information infrastructure; the more active the cooperation between the participants of technology transfer, the more investment revenues in the development of this infrastructure. Taking into consideration these patterns, a simulation model of the process of investing in the development of the information infrastructure of technology transfer has been built. The proposed model was tested using an example of the real estate market in the Prydniprovskyi economic region of Ukraine. As a result of the simulation experiment, the optimal level of costs for the development of the information infrastructure for technology transfer has been established. It makes up 20 % of all available investment funds in this market. The proposed model could be adapted for other regional markets. The results of this study could be useful for the system of state and regional management since they substantiate the directions of innovation policy formation and promote the development of technology transfer under the conditions of certain territorial systems.
{"title":"Investing in the Development of Information Infrastructure for Technology Transfer Under the Conditions of a Regional Market","authors":"O. Zinchenko, Olesya Finahina, L. Pankova, Ievgen Buriak, Yu. O. Kovalenko","doi":"10.15587/1729-4061.2021.235948","DOIUrl":"https://doi.org/10.15587/1729-4061.2021.235948","url":null,"abstract":"The relevance of the issue, related to building an information infrastructure of technology transfer, is predetermined by the transformation of information into the most important resource of technological cooperation. At the same time, its effective functioning requires investment support on a regular basis. This paper addresses the establishment of regularities in the process of investing in the development of the information infrastructure of technology transfer and determining the rational volumes of these investments. This study was carried out in the context of the regional market, which is due to the territorial specificity of market processes, the peculiarity of information interaction among economic agents in a separate market. The study results have identified the following patterns: the lower the transaction costs of technology transfer participants, the more productive the functioning of the information infrastructure; the more active the cooperation between the participants of technology transfer, the more investment revenues in the development of this infrastructure. Taking into consideration these patterns, a simulation model of the process of investing in the development of the information infrastructure of technology transfer has been built. The proposed model was tested using an example of the real estate market in the Prydniprovskyi economic region of Ukraine. As a result of the simulation experiment, the optimal level of costs for the development of the information infrastructure for technology transfer has been established. It makes up 20 % of all available investment funds in this market. The proposed model could be adapted for other regional markets. The results of this study could be useful for the system of state and regional management since they substantiate the directions of innovation policy formation and promote the development of technology transfer under the conditions of certain territorial systems.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84862639","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}
James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert C. Seamans
Artificial intelligence (“AI”)-enabled products are expected to drive economic growth. Training data are important for firms developing AI-enabled products; without training data, firms cannot develop or refine their algorithms. This is particularly the case for AI startups developing new algorithms and products. However, there is no consensus in the literature on which aspects of training data are most important. Using unique survey data of AI startups, we find that startups with access to proprietary training data are more likely to acquire venture capital funding.
{"title":"The Role of Data for AI Startup Growth","authors":"James Bessen, Stephen Michael Impink, Lydia Reichensperger, Robert C. Seamans","doi":"10.2139/ssrn.3896463","DOIUrl":"https://doi.org/10.2139/ssrn.3896463","url":null,"abstract":"Artificial intelligence (“AI”)-enabled products are expected to drive economic growth. Training data are important for firms developing AI-enabled products; without training data, firms cannot develop or refine their algorithms. This is particularly the case for AI startups developing new algorithms and products. However, there is no consensus in the literature on which aspects of training data are most important. Using unique survey data of AI startups, we find that startups with access to proprietary training data are more likely to acquire venture capital funding.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82489116","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}
Hyoungmin Han, Jeong-gon Kim, Doyeon Kim, Sung Hee Lee, Jonghun Pek
A startup refers to a company with ideas and innovative technologies, which have a short period of experience. Recently, startups are leading the fourth industrial technological innovation and affecting job creation and industrial productivity growth, so that its economic importance is increasing. In particular, India is emerging as a startup powerhouse based on its fast-growing economy and relatively cost-efficient excellent talent pool. Also, global investment towards the Indian startup market is increasing. While the number of Korean companies entering the Indian startup market is increasing, only a few have made stable inroads into the market. Based on quantitative data, literature analysis, corporate case analysis, surveys, and in-depth interviews, we objectively identified the Indian startup ecosystem and drew policy implications to increase the accessibility of Korean firms to the Indian market.
{"title":"The Indian Startup Ecosystem and Policy Implications","authors":"Hyoungmin Han, Jeong-gon Kim, Doyeon Kim, Sung Hee Lee, Jonghun Pek","doi":"10.2139/ssrn.3885453","DOIUrl":"https://doi.org/10.2139/ssrn.3885453","url":null,"abstract":"A startup refers to a company with ideas and innovative technologies, which have a short period of experience. Recently, startups are leading the fourth industrial technological innovation and affecting job creation and industrial productivity growth, so that its economic importance is increasing. In particular, India is emerging as a startup powerhouse based on its fast-growing economy and relatively cost-efficient excellent talent pool. Also, global investment towards the Indian startup market is increasing. While the number of Korean companies entering the Indian startup market is increasing, only a few have made stable inroads into the market. Based on quantitative data, literature analysis, corporate case analysis, surveys, and in-depth interviews, we objectively identified the Indian startup ecosystem and drew policy implications to increase the accessibility of Korean firms to the Indian market.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78675019","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 raíz de la crisis financiera surgida en el sector inmobiliario de los Estados Unidos de América en 2008-2009, que desencadenó una grave falta de liquidez, y con ello, un efecto dominó que alcanzó otros aspectos de la economía global, y que generó crisis también en el mercado bursátil y a nivel alimentario, los mercados han tenido que aprender y evolucionar. Ante este escenario, las técnicas de Liquidity-Adjusted Value-at-Risk (LVaR) se han convertido en herramientas críticas para monitorear y pronosticar el riesgo de mercado y liquidez de portafolios de inversión. La principal ventaja de estos modelos LVaR es que su enfoque está basado en el riesgo de los resultados de rentabilidad negativa.
{"title":"Innovación en modelos de inversión y finanzas para tiempos de crisis","authors":"Mazin A. M. Al Janabi","doi":"10.2139/ssrn.3840331","DOIUrl":"https://doi.org/10.2139/ssrn.3840331","url":null,"abstract":"A raíz de la crisis financiera surgida en el sector inmobiliario de los Estados Unidos de América en 2008-2009, que desencadenó una grave falta de liquidez, y con ello, un efecto dominó que alcanzó otros aspectos de la economía global, y que generó crisis también en el mercado bursátil y a nivel alimentario, los mercados han tenido que aprender y evolucionar. Ante este escenario, las técnicas de Liquidity-Adjusted Value-at-Risk (LVaR) se han convertido en herramientas críticas para monitorear y pronosticar el riesgo de mercado y liquidez de portafolios de inversión. La principal ventaja de estos modelos LVaR es que su enfoque está basado en el riesgo de los resultados de rentabilidad negativa.","PeriodicalId":14586,"journal":{"name":"IO: Productivity","volume":"8 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83618111","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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