To what extent does high-growth entrepreneurship depend on skilled human capital? We estimate the impact of the inflow of inventors into a region on the founding of high-growth firms, instrumenting mobility with the county-level share of millions of inventor surnames in the 1940 U.S. Census. Inventor immigration increases county-level high-growth entrepreneurship; estimates range from 29-55 immigrating inventors for each new high-growth firm, depending on the region and model. We also find a smaller but significant negative effect of inventor arrival on entrepreneurship in nearby counties.
{"title":"Skilled Human Capital and High-Growth Entrepreneurship: Evidence from Inventor Inflows","authors":"B. Balsmeier, L. Fleming, M. Marx, S. R. Shin","doi":"10.3386/w27605","DOIUrl":"https://doi.org/10.3386/w27605","url":null,"abstract":"To what extent does high-growth entrepreneurship depend on skilled human capital? We estimate the impact of the inflow of inventors into a region on the founding of high-growth firms, instrumenting mobility with the county-level share of millions of inventor surnames in the 1940 U.S. Census. Inventor immigration increases county-level high-growth entrepreneurship; estimates range from 29-55 immigrating inventors for each new high-growth firm, depending on the region and model. We also find a smaller but significant negative effect of inventor arrival on entrepreneurship in nearby counties.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130340380","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 Kauffman Indicators of Early-Stage Entrepreneurship is a set of measures that represents new business creation in the United States, integrating several high-quality, timely sources of information on early-stage entrepreneurship. This report presents four indicators tracking early-stage entrepreneurship for the years 1996–2019: rate of new entrepreneurs reflects the number of new entrepreneurs in a given month, opportunity share of new entrepreneurs is the percentage of new entrepreneurs who created their businesses out of opportunity instead of necessity, startup early job creation is the total number of jobs created by startups per capita, startup early survival rate is the one-year average survival rate for new employer establishments. National and state level trends are reported for all four indicators. In addition, demographic trends are reported for the rate of new entrepreneurs and opportunity share of new entrepreneurs. National Trends in Early-Stage Entrepreneurship in 2019: • Nationally, the rate of new entrepreneurs in 2019 was 0.31 percent, meaning that an average of 310 out of every 100,000 adults became new entrepreneurs in a given month. - The rate of new entrepreneurs was 0.23 percent among women and 0.38 percent among men, reflecting a slight decline for men and an essentially no change for women from the previous year. - In 2019, the rate of new entrepreneurs was the highest among Latinos (0.44 percent) and lowest among African Americans (0.24 percent). It decreased for Latinos and decreased slightly for Asians, but remained constant for African Americans and whites. - The rate of new entrepreneurs was 0.44 percent for immigrants, which is substantially higher than for native-born Americans (0.28 percent). Immigrants started businesses at a lower rate than they did in the previous year. - The rate of new entrepreneurs was highest among Americans aged 45–54 (0.36 percent) and lowest among Americans aged 20–34 (0.24 percent). It declined slightly in 2019 among all age groups except for the aged 20–34 group. • The opportunity share of new entrepreneurs nationally in 2019 was 86.9 percent. - The opportunity share of new entrepreneurs increased for women and remained roughly constant for men in 2019. - African Americans and Asians experienced increases in the opportunity share of new entrepreneurs in 2019, continuing upward trends over the past few years. The opportunity share for Latinos and whites remained roughly constant but showed a similar general positive trend over the past few years. - The opportunity share of new entrepreneurs increased for immigrants in 2019. - All age groups, except ages 45–54, experienced increases in the opportunity share, continuing upward trends since the Great Recession. • National startup early job creation in 2019 was 5.2 jobs, meaning that the average startup that hired would hire a little over 5 jobs for every 1,000 people. • Startup early survival rate was 79.6 percent in 2019, meaning that
{"title":"2019 Early-Stage Entrepreneurship in the United States: National and State Report","authors":"R. Fairlie, S. Desai","doi":"10.2139/ssrn.3607936","DOIUrl":"https://doi.org/10.2139/ssrn.3607936","url":null,"abstract":"The Kauffman Indicators of Early-Stage Entrepreneurship is a set of measures that represents new business creation in the United States, integrating several high-quality, timely sources of information on early-stage entrepreneurship. This report presents four indicators tracking early-stage entrepreneurship for the years 1996–2019: rate of new entrepreneurs reflects the number of new entrepreneurs in a given month, opportunity share of new entrepreneurs is the percentage of new entrepreneurs who created their businesses out of opportunity instead of necessity, startup early job creation is the total number of jobs created by startups per capita, startup early survival rate is the one-year average survival rate for new employer establishments. National and state level trends are reported for all four indicators. In addition, demographic trends are reported for the rate of new entrepreneurs and opportunity share of new entrepreneurs. National Trends in Early-Stage Entrepreneurship in 2019: • Nationally, the rate of new entrepreneurs in 2019 was 0.31 percent, meaning that an average of 310 out of every 100,000 adults became new entrepreneurs in a given month. - The rate of new entrepreneurs was 0.23 percent among women and 0.38 percent among men, reflecting a slight decline for men and an essentially no change for women from the previous year. - In 2019, the rate of new entrepreneurs was the highest among Latinos (0.44 percent) and lowest among African Americans (0.24 percent). It decreased for Latinos and decreased slightly for Asians, but remained constant for African Americans and whites. - The rate of new entrepreneurs was 0.44 percent for immigrants, which is substantially higher than for native-born Americans (0.28 percent). Immigrants started businesses at a lower rate than they did in the previous year. - The rate of new entrepreneurs was highest among Americans aged 45–54 (0.36 percent) and lowest among Americans aged 20–34 (0.24 percent). It declined slightly in 2019 among all age groups except for the aged 20–34 group. • The opportunity share of new entrepreneurs nationally in 2019 was 86.9 percent. - The opportunity share of new entrepreneurs increased for women and remained roughly constant for men in 2019. - African Americans and Asians experienced increases in the opportunity share of new entrepreneurs in 2019, continuing upward trends over the past few years. The opportunity share for Latinos and whites remained roughly constant but showed a similar general positive trend over the past few years. - The opportunity share of new entrepreneurs increased for immigrants in 2019. - All age groups, except ages 45–54, experienced increases in the opportunity share, continuing upward trends since the Great Recession. • National startup early job creation in 2019 was 5.2 jobs, meaning that the average startup that hired would hire a little over 5 jobs for every 1,000 people. • Startup early survival rate was 79.6 percent in 2019, meaning that ","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122975962","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}
Many technology companies struggle to fill all their positions and to achieve gender parity in their ranks. One explanation for gender disparities is the possibility that men and women differ in their willingness to work under competitive organizational environments of tech firms. To investigate this question, this paper reports on a large platform-based field experiment in which 97,696 U.S. university-educated individuals were given the opportunity to join a tech-related product development activity. Individuals were randomly assigned to treatments emphasizing either competitive or collaborative interactions with other participants. We find that (1) in non-STEM fields, the competition treatment leads to a 27% drop in participation for females in comparison to males. However, in our main finding, (2) in STEM fields, we find no statistical differences in men and women’s responses to competition. The patterns are consistent with (3) men in non-STEM fields exhibiting overconfidence in their likelihood of succeeding under competition. We also find that, while participation in highest in STEM fields, (4) the ratio of female to male participation in a field is better predicted by whether the field is male- or female-dominated, than it is by whether it is a STEM field or not. We discuss theoretical interpretations and implications for organizations.
{"title":"The Gender Gap in Tech & Competitive Work Environments? Field Experimental Evidence from an Internet-of-Things Product Development Platform","authors":"K. Boudreau, Nilam Kaushik","doi":"10.3386/w27154","DOIUrl":"https://doi.org/10.3386/w27154","url":null,"abstract":"Many technology companies struggle to fill all their positions and to achieve gender parity in their ranks. One explanation for gender disparities is the possibility that men and women differ in their willingness to work under competitive organizational environments of tech firms. To investigate this question, this paper reports on a large platform-based field experiment in which 97,696 U.S. university-educated individuals were given the opportunity to join a tech-related product development activity. Individuals were randomly assigned to treatments emphasizing either competitive or collaborative interactions with other participants. We find that (1) in non-STEM fields, the competition treatment leads to a 27% drop in participation for females in comparison to males. However, in our main finding, (2) in STEM fields, we find no statistical differences in men and women’s responses to competition. The patterns are consistent with (3) men in non-STEM fields exhibiting overconfidence in their likelihood of succeeding under competition. We also find that, while participation in highest in STEM fields, (4) the ratio of female to male participation in a field is better predicted by whether the field is male- or female-dominated, than it is by whether it is a STEM field or not. We discuss theoretical interpretations and implications for organizations.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131261462","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}
Contributions from various tourism SMEs to improve socio-economic development in developed countries include employment creation, improved living standards and increased family income. Despite this, you have great deals on the direct link between job creation, but there is also some controversy over who creates jobs and how they do it. Various documents say that Tourism SMEs play an important role in training young people, covering the labour deficit and generating benefits to the efficiency of the economy, innovation and overall growth. Therefore, this study will help us build the evidence needed to create Tourism SME policies and understand the core operational values of SMEs that maximize results in terms of achieving basic objectives such as job creation, increasing employee productivity and what are the financial challenges facing tourism SMEs. Policy initiatives to encourage the financial sector to be more proactive in securing tourism financing SMEs can also be envisaged, including taking steps to improve the knowledge and understanding of the tourism sector.
{"title":"SME: Apparently Small but of Great Derivative Value! Literature Review of Tourism SMEs to Create Employment and Access to Finance","authors":"G. Nure, E. Bazini, F. Madani","doi":"10.5296/ber.v10i2.16574","DOIUrl":"https://doi.org/10.5296/ber.v10i2.16574","url":null,"abstract":"Contributions from various tourism SMEs to improve socio-economic development in developed countries include employment creation, improved living standards and increased family income. Despite this, you have great deals on the direct link between job creation, but there is also some controversy over who creates jobs and how they do it. Various documents say that Tourism SMEs play an important role in training young people, covering the labour deficit and generating benefits to the efficiency of the economy, innovation and overall growth. Therefore, this study will help us build the evidence needed to create Tourism SME policies and understand the core operational values of SMEs that maximize results in terms of achieving basic objectives such as job creation, increasing employee productivity and what are the financial challenges facing tourism SMEs. Policy initiatives to encourage the financial sector to be more proactive in securing tourism financing SMEs can also be envisaged, including taking steps to improve the knowledge and understanding of the tourism sector.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"207 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114393456","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 Kauffman New Employer Business Indicators series has been compiled in an effort to provide information on new employer businesses, a subset of all entrepreneurial activity. The series provides users with measures to track trends in the emergence of these businesses, their representation in the population and among all firms, and the time it takes these businesses to become employers. This report presents indicators for the United States and all 50 states and Washington, D.C., beginning in 2005 and through the most recent year of data available for each metric. Rate of new employer business actualization: This indicator reflects the proportion of all new business applications that become employer businesses within eight quarters. In 2018, the national rate of new employer business actualization was 11.33%, meaning that for every 100 new business applications, about 11 businesses made a first payroll within eight quarters. For the same year, the value of this indicator ranged from 6.59% in Delaware to 17.36% in Washington, with a median of 11.30% across states. Rate of new employer businesses: The rate of new employer businesses reflects new employer businesses in the population. The national rate of new employer businesses was 0.12 in 2018, meaning there were 120 new employer businesses for every 100,000 people. This ranged from 0.07 in West Virginia to 0.31 in Wyoming in 2018, with a median of 0.12 across states. New employer business velocity: New employer business velocity is the average amount of time it takes, in quarters, for a new business application to become an employer, assuming it does so within eight quarters. In 2014, the national new employer business velocity was 1.92, indicating that, on average, approximately six months pass between business application and first payroll. For the same year, the value of this indicator ranged from 1.46 in North Dakota to 2.37 in Washington, D.C., with a median of 1.83. Employer business newness: Employer business newness captures new employer businesses as a share of employer firms, regardless of age. In 2016, national employer business newness was 6.8%, meaning that almost 7 out of every 100 employer businesses were new businesses that made a first payroll within the first eight quarters. This ranged from 4.44% in Washington, D.C. to 8.67% in Nevada in 2016, with a median of 5.99%. We also calculate the New Employer Business Actualization Speed (NEBAS) Index, a snapshot reflecting both the emergence (actualization) and speed (velocity) of new employer businesses. In 2014 (the most recent year for which data are available), the national NEBAS index was 0.76. The value of this measure in 2014 ranged from 0.60 in Washington, D.C., to 0.93 in South Dakota, with a median of 0.79 across states. The Kauffman New Employer Business Indicators series has been compiled in an effort to provide information on new employer businesses and provides users with measures to track trends in th
{"title":"2018 New Employer Business Report: National and State Trends","authors":"S. Desai, B. T. Howe, Hayden Murray","doi":"10.2139/ssrn.3375009","DOIUrl":"https://doi.org/10.2139/ssrn.3375009","url":null,"abstract":"The Kauffman New Employer Business Indicators series has been compiled in an effort to provide information on new employer businesses, a subset of all entrepreneurial activity. The series provides users with measures to track trends in the emergence of these businesses, their representation in the population and among all firms, and the time it takes these businesses to become employers. This report presents indicators for the United States and all 50 states and Washington, D.C., beginning in 2005 and through the most recent year of data available for each metric. \u0000 \u0000Rate of new employer business actualization: This indicator reflects the proportion of all new business applications that become employer businesses within eight quarters. In 2018, the national rate of new employer business actualization was 11.33%, meaning that for every 100 new business applications, about 11 businesses made a first payroll within eight quarters. For the same year, the value of this indicator ranged from 6.59% in Delaware to 17.36% in Washington, with a median of 11.30% across states. \u0000 \u0000Rate of new employer businesses: The rate of new employer businesses reflects new employer businesses in the population. The national rate of new employer businesses was 0.12 in 2018, meaning there were 120 new employer businesses for every 100,000 people. This ranged from 0.07 in West Virginia to 0.31 in Wyoming in 2018, with a median of 0.12 across states. \u0000 \u0000New employer business velocity: New employer business velocity is the average amount of time it takes, in quarters, for a new business application to become an employer, assuming it does so within eight quarters. In 2014, the national new employer business velocity was 1.92, indicating that, on average, approximately six months pass between business application and first payroll. For the same year, the value of this indicator ranged from 1.46 in North Dakota to 2.37 in Washington, D.C., with a median of 1.83. \u0000 \u0000Employer business newness: Employer business newness captures new employer businesses as a share of employer firms, regardless of age. In 2016, national employer business newness was 6.8%, meaning that almost 7 out of every 100 employer businesses were new businesses that made a first payroll within the first eight quarters. This ranged from 4.44% in Washington, D.C. to 8.67% in Nevada in 2016, with a median of 5.99%. \u0000 \u0000We also calculate the New Employer Business Actualization Speed (NEBAS) Index, a snapshot reflecting both the emergence (actualization) and speed (velocity) of new employer businesses. In 2014 (the most recent year for which data are available), the national NEBAS index was 0.76. The value of this measure in 2014 ranged from 0.60 in Washington, D.C., to 0.93 in South Dakota, with a median of \u00000.79 across states. \u0000 \u0000The Kauffman New Employer Business Indicators series has been compiled in an effort to provide information on new employer businesses and provides users with measures to track trends in th","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116576095","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 online platform firms are reorganizing the geography of how value is created, who captures it, and where. This essay argues that economic geographers have underestimated the power of platform and the firms that control them. We further demonstrate the remarkable concentration of these firms on the U.S. West Coast even while they organize global ecosystems. We suggest that a new spatial fix for the core of the global capitalist economy is emerging. We build upon a taxonomy of platform economy labor types and the location of the various types of labor and the implications of the ability of platforms to extract value from this labor. To illustrate, the impact on the geography of value creation, we undertake cases studies of two platforms, Amazon and Google Maps to explicate their effects upon the location of economic activity. Platforms are increasingly reorganizing labor and the location of value creation We argue that platforms are a new organizational form that is the result of an asymmetric power relationship between a platform and an ecosystem of complementers and users that interact and transact through platform. These platform leaders have the largest data sets and have created enormous teams of the best AI, machine learning researchers, and, finally, have enormous reservoirs of capital with which to capture new technologies that may threaten them.
{"title":"The Platform Economy and Geography: Restructuring the Space of Capitalist Accumulation","authors":"M. Kenney, J. Zysman","doi":"10.2139/ssrn.3497978","DOIUrl":"https://doi.org/10.2139/ssrn.3497978","url":null,"abstract":"Digital online platform firms are reorganizing the geography of how value is created, who captures it, and where. This essay argues that economic geographers have underestimated the power of platform and the firms that control them. We further demonstrate the remarkable concentration of these firms on the U.S. West Coast even while they organize global ecosystems. We suggest that a new spatial fix for the core of the global capitalist economy is emerging. We build upon a taxonomy of platform economy labor types and the location of the various types of labor and the implications of the ability of platforms to extract value from this labor. To illustrate, the impact on the geography of value creation, we undertake cases studies of two platforms, Amazon and Google Maps to explicate their effects upon the location of economic activity. Platforms are increasingly reorganizing labor and the location of value creation We argue that platforms are a new organizational form that is the result of an asymmetric power relationship between a platform and an ecosystem of complementers and users that interact and transact through platform. These platform leaders have the largest data sets and have created enormous teams of the best AI, machine learning researchers, and, finally, have enormous reservoirs of capital with which to capture new technologies that may threaten them.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124015895","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 growing body of literature finds that a healthy corporate culture is associated with superior financial performance. A separate stream of research has found that a firm’s adoption of management “best practices” is correlated with higher efficiency and productivity. To date, the cultural and management practices literatures have proceeded in parallel, with few studies considering the relationship between an organization’s processes and its culture. This paper uses data from a carefully-designed survey of 370 organizations and nearly ten thousand managers to simultaneously measure corporate culture and management practices. Our key finding is that the quality of a company’s management practices and health of its corporate culture are highly correlated. This implies that studies which measure either culture or processes in isolation are likely to overstate their impact on performance. We also provide suggestive evidence that management practices may cause changes in corporate culture, or at least that this effect is stronger than the reverse.
{"title":"The Close Relationship Between Management Practices and Corporate Culture","authors":"D. Sull, Hyosuk Kang, Neil C. Thompson","doi":"10.2139/ssrn.3462116","DOIUrl":"https://doi.org/10.2139/ssrn.3462116","url":null,"abstract":"A growing body of literature finds that a healthy corporate culture is associated with superior financial performance. A separate stream of research has found that a firm’s adoption of management “best practices” is correlated with higher efficiency and productivity. To date, the cultural and management practices literatures have proceeded in parallel, with few studies considering the relationship between an organization’s processes and its culture. This paper uses data from a carefully-designed survey of 370 organizations and nearly ten thousand managers to simultaneously measure corporate culture and management practices. Our key finding is that the quality of a company’s management practices and health of its corporate culture are highly correlated. This implies that studies which measure either culture or processes in isolation are likely to overstate their impact on performance. We also provide suggestive evidence that management practices may cause changes in corporate culture, or at least that this effect is stronger than the reverse.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127755386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates how business creation, earnings, and survival are related to incorporation and personal bankruptcy codes. In theory, individual debtor protection might either affect entrepreneurship or just prevent the incorporation of household firms. To examine this issue, I exploit the bankruptcy reform of 2005 as an exogenous reduction in the protection granted by homestead exemptions. Generous exemptions are found to encourage low-skilled entrepreneurs to sustain unincorporated firms. However, these exemptions also encourage high-skilled entrepreneurs to undertake profitable ventures. The evidence is consistent with new entrepreneurs often relying on unincorporated forms as the stepping-stone to a successful business.
{"title":"Business Creation, Incorporation, and the Role of Personal Bankruptcy Protection: Evidence from the BAPCPA","authors":"Rafael P. Ribas","doi":"10.2139/ssrn.3461785","DOIUrl":"https://doi.org/10.2139/ssrn.3461785","url":null,"abstract":"This paper investigates how business creation, earnings, and survival are related to incorporation and personal bankruptcy codes. In theory, individual debtor protection might either affect entrepreneurship or just prevent the incorporation of household firms. To examine this issue, I exploit the bankruptcy reform of 2005 as an exogenous reduction in the protection granted by homestead exemptions. Generous exemptions are found to encourage low-skilled entrepreneurs to sustain unincorporated firms. However, these exemptions also encourage high-skilled entrepreneurs to undertake profitable ventures. The evidence is consistent with new entrepreneurs often relying on unincorporated forms as the stepping-stone to a successful business.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115390567","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}
Although artificial intelligence (AI) promises to spur economic growth, there is widespread concern that it may replace human labor. We investigate the link between AI and labor by creating a new measure that we call the AI Occupational Impact (AIOI). The AIOI measure links advances in specific applications of AI, such as image recognition, translation, or the ability to play strategic games, to workplace abilities and occupations. We use this measure to study the relationship between AI and wages, employment, and labor market polarization. We provide evidence that, on average, occupations impacted by AI experience a small but positive change in wages, but no change in employment. We also provide evidence that the positive correlation with wages is driven primarily by occupations with higher software skill requirements, and that higher-income occupations have a strong positive relationship between our measure of AI impact and both employment and wages. These findings suggest that access to complementary skills and technologies may play an important role in determining the impact of AI, and that AI has the potential to exacerbate labor market polarization.
{"title":"The Occupational Impact of Artificial Intelligence: Labor, Skills, and Polarization","authors":"E. Felten, Manav Raj, Robert C. Seamans","doi":"10.2139/ssrn.3368605","DOIUrl":"https://doi.org/10.2139/ssrn.3368605","url":null,"abstract":"Although artificial intelligence (AI) promises to spur economic growth, there is widespread concern that it may replace human labor. We investigate the link between AI and labor by creating a new measure that we call the AI Occupational Impact (AIOI). The AIOI measure links advances in specific applications of AI, such as image recognition, translation, or the ability to play strategic games, to workplace abilities and occupations. We use this measure to study the relationship between AI and wages, employment, and labor market polarization. We provide evidence that, on average, occupations impacted by AI experience a small but positive change in wages, but no change in employment. We also provide evidence that the positive correlation with wages is driven primarily by occupations with higher software skill requirements, and that higher-income occupations have a strong positive relationship between our measure of AI impact and both employment and wages. These findings suggest that access to complementary skills and technologies may play an important role in determining the impact of AI, and that AI has the potential to exacerbate labor market polarization.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121576467","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 integrate the results of a social network survey and a forecast information sharing experiment to examine the roles of trust and trustworthiness in impacting high-ranking executives’ decisions in supply chain interactions. The members of our executive sample have, on average, 17 years of work experience. A significant portion of them holds positions at the C-level in world-leading organizations that span a wide range of industries. By examining the roles of trust and trustworthiness in the decision making of high-ranking executives, we find strong external validation for as well as demonstrate how these nonpecuniary, behavioral factors impact the outcomes of business interactions. We employ a multimethod research design that allows us to investigate the extent to which the executives’ trust beliefs toward a relevant network of exchange partners (which we define as their “network trust”) impact their trust behaviors when engaging in business interactions with members of this network. We determine the conditions pertaining to the executives’ professional experiences that strengthen or weaken the impact of network trust on the executives’ trust behaviors in supply chain interactions. For example, executives with more diverse professional experiences rely more on network trust to shape their trust behaviors. Conversely, executives with prior positive trust experiences rely less on network trust in their trusting behaviors. We quantify that improved trust and trustworthiness can yield up to 41%, 6%, and 5% gain in the expected profit of the supplier, the retailer, and the supply chain. Our results offer tangible implications for how organizations can better leverage executives’ knowledge about how much to rely on network trust in business interactions to achieve better outcomes. This paper was accepted by Serguei Netessine, operations management.
{"title":"Network Trust and Trust Behaviors Among Executives in Supply Chain Interactions","authors":"Emily W. Choi, Ö. Özer, Yanchong Zheng","doi":"10.2139/ssrn.3256571","DOIUrl":"https://doi.org/10.2139/ssrn.3256571","url":null,"abstract":"We integrate the results of a social network survey and a forecast information sharing experiment to examine the roles of trust and trustworthiness in impacting high-ranking executives’ decisions in supply chain interactions. The members of our executive sample have, on average, 17 years of work experience. A significant portion of them holds positions at the C-level in world-leading organizations that span a wide range of industries. By examining the roles of trust and trustworthiness in the decision making of high-ranking executives, we find strong external validation for as well as demonstrate how these nonpecuniary, behavioral factors impact the outcomes of business interactions. We employ a multimethod research design that allows us to investigate the extent to which the executives’ trust beliefs toward a relevant network of exchange partners (which we define as their “network trust”) impact their trust behaviors when engaging in business interactions with members of this network. We determine the conditions pertaining to the executives’ professional experiences that strengthen or weaken the impact of network trust on the executives’ trust behaviors in supply chain interactions. For example, executives with more diverse professional experiences rely more on network trust to shape their trust behaviors. Conversely, executives with prior positive trust experiences rely less on network trust in their trusting behaviors. We quantify that improved trust and trustworthiness can yield up to 41%, 6%, and 5% gain in the expected profit of the supplier, the retailer, and the supply chain. Our results offer tangible implications for how organizations can better leverage executives’ knowledge about how much to rely on network trust in business interactions to achieve better outcomes. This paper was accepted by Serguei Netessine, operations management.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125837333","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：