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  1. The perfect match
    the role of categorical fit between venture capitalists and their startup investments
    Author: Arnold, Jan-Frederik
    Published: 2018

    This dissertation sheds light on how the categorical fit between venture capitalists and startups affect the matching process before a funding round. The study uses market categories to measure new venture’s distinctiveness and the cultural distance... more

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    Universitätsbibliothek Braunschweig
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    Universitätsbibliothek Clausthal
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    Fachhochschule Erfurt, Hochschulbibliothek
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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Universitäts- und Landesbibliothek Sachsen-Anhalt / Zentrale
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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
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    Technische Universität Hamburg, Universitätsbibliothek
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    Bibliothek im Kurt-Schwitters-Forum
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    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Zentrale Hochschulbibliothek Lübeck
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    Leuphana Universität Lüneburg, Medien- und Informationszentrum, Universitätsbibliothek
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    Hochschule Magdeburg-Stendal, Hochschulbibliothek
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    Hochschule Osnabrück, Bibliothek Campus Westerberg
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    Hochschule Magdeburg-Stendal, Standort Stendal, Bibliothek
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    UB Weimar
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    This dissertation sheds light on how the categorical fit between venture capitalists and startups affect the matching process before a funding round. The study uses market categories to measure new venture’s distinctiveness and the cultural distance between venture capitalists and new ventures. The empirical analysis of 11 years of venture capital investment data in the USA confirms that experienced and high status investors prefer more distinctive new ventures and that the negative effect of cultural distance on the investment probability is mitigated by venture capitalists portfolio diversification and status. Die Dissertation analysiert den Effekt von Kategorischem-Fit zwischen Venture Capital Firmen und Startups auf den Finanzierungsprozess. Die Arbeit nutzt Marktkategorien für die Messung des Startup-Neuigkeitswert und der kulturellen Distanz zwischen Venture Capital Firmen und Startups. Die Analyse von Finanzierungsdaten über einen 11 Jahreszeitraum bestätigt, dass erfahrene und mit hohem Status versehene Venture Capital Firmen einen höheren Neuigkeitswert bevorzugen und kulturelle Distanz weniger relevant ist für die Finanzierungsentscheidung, wenn die Venture Capital Firmen ein diversifiziertes Portfolio und einen hohen Status haben.

     
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    Source: Union catalogues
    Contributor: Ihl, Christoph (AkademischeR BetreuerIn); Spaeth, Sebastian (AkademischeR BetreuerIn)
    Language: English
    Media type: Dissertation
    Format: Online
    Other identifier:
    hdl: 11420/1622
    Subjects: entrepreneurship; venture capital; investment; startup; categories; fit
    Scope: 1 Online-Ressource (xiii, 183 Seiten), Diagramme, Illustrationen
    Notes:

    Dissertation, Technische Universität Hamburg-Harburg, 2018
  2. Uberland
    How Algorithms Are Rewriting the Rules of Work
    Author: Rosenblat, Alex
    Published: [2018]; ©2018
    Publisher:  University of California Press, Berkeley, CA

    Silicon Valley technology is transforming the way we work, and Uber is leading the charge. An American startup that promised to deliver entrepreneurship for the masses through its technology, Uber instead built a new template for employment using... more

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    Bibliotheks-und Informationssystem der Carl von Ossietzky Universität Oldenburg (BIS)
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    Universitätsbibliothek Osnabrück
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    Silicon Valley technology is transforming the way we work, and Uber is leading the charge. An American startup that promised to deliver entrepreneurship for the masses through its technology, Uber instead built a new template for employment using algorithms and Internet platforms. Upending our understanding of work in the digital age, Uberland paints a future where any of us might be managed by a faceless boss. The neutral language of technology masks the powerful influence algorithms have across the New Economy. Uberland chronicles the stories of drivers in more than twenty-five cities in the United States and Canada over four years, shedding light on their working conditions and providing a window into how they feel behind the wheel. The book also explores Uber’s outsized influence around the world: the billion-dollar company is now influencing everything from debates about sexual harassment and transportation regulations to racial equality campaigns and labor rights initiatives. Based on award-winning technology ethnographer Alex Rosenblat’s firsthand experience of riding over 5,000 miles with Uber drivers, daily visits to online forums, and face-to-face discussions with senior Uber employees, Uberland goes beyond the headlines to reveal the complicated politics of popular technologies that are manipulating both workers and consumers

     
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  3. The value of publicly available, textual and non-textual information for startup performance prediction
    Author: Kaiser, Ulrich; Kuhn, Johan M.
    Published: March 2020
    Publisher:  IZA - Institute of Labor Economics, Bonn, Germany

    Can publicly available, web-scraped data be used to identify promising business startups at an early stage? To answer this question, we use such textual and non-textual information about the names of Danish firms and their addresses as well as their... more

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    Can publicly available, web-scraped data be used to identify promising business startups at an early stage? To answer this question, we use such textual and non-textual information about the names of Danish firms and their addresses as well as their business purpose statements (BPSs) supplemented by core accounting information along with founder and initial startup characteristics to forecast the performance of newly started enterprises over a five years' time horizon. The performance outcomes we consider are involuntary exit, above-average employment growth, a return on assets of above 20 percent, new patent applications and participation in an innovation subsidy program. Our first key finding is that our models predict startup performance with either high or very high accuracy with the exception of high returns on assets where predictive power remains poor. Our second key finding is that the data requirements for predicting performance outcomes with such accuracy are low. To forecast the two innovation-related performance outcomes well, we only need to include a set of variables derived from the BPS texts while an accurate prediction of startup survival and high employment growth needs the combination of (i) information derived from the names of the startups, (ii) data on elementary founder-related characteristics and (iii) either variables describing the initial characteristics of the startup (to predict startup survival) or business purpose statement information (to predict high employment growth). These sets of variables are easily obtainable since the underlying information is mandatory to report upon business registration. The substantial accuracy of our predictions for survival, employment growth, new patents and participation in innovation subsidy programs indicates ample scope for algorithmic scoring models as an additional pillar of funding and innovation support decisions.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/216341
    Series: Discussion paper series / IZA ; no. 13029
    Subjects: startup; performance; prediction; text as data
    Scope: 1 Online-Ressource (circa 24 Seiten), Illustrationen
  4. The value of publicly available, textual and non-textual information for startup performance prediction
    Author: Kaiser, Ulrich; Kuhn, Johan M.
    Published: 2020
    Publisher:  ZEW - Leibniz Centre for European Economic Research, Mannheim, Germany

    Can publicly available, web-scraped data be used to identify promising business startups at an early stage? To answer this question, we use such textual and non-textual information about the names of Danish firms and their addresses as well as their... more

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    DS 15
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    Universitätsbibliothek Mannheim
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    Can publicly available, web-scraped data be used to identify promising business startups at an early stage? To answer this question, we use such textual and non-textual information about the names of Danish firms and their addresses as well as their business purpose statements (BPSs) supplemented by core accounting information along with founder and initial startup characteristics to forecast the performance of newly started enterprises over a five years' time horizon. The performance outcomes we consider are involuntary exit, above{average employment growth, a return on assets of above 20 percent, new patent applications and participation in an innovation subsidy program. Our first key finding is that our models predict startup performance with either high or very high accuracy with the exception of high returns on assets where predictive power remains poor. Our second key finding is that the data requirements for predicting performance outcomes with such accuracy are low. To forecast the two innovation-related performance outcomes well, we only need to include a set of variables derived from the BPS texts while an accurate prediction of startup survival and high employment growth needs the combination of (i) information derived from the names of the startups, (ii) data on elementary founder-related characteristics and (iii) either variables describing the initial characteristics of the startup (to predict startup survival) or business purpose statement information (to predict high employment growth). These sets of variables are easily obtainable since the underlying information is mandatory to report upon business registration. The substantial accuracy of our predictions for survival, employment growth, new patents and participation in innovation subsidy programs indicates ample scope for algorithmic scoring models as an additional pillar of funding and innovation support decisions.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/215671
    Series: Discussion paper / ZEW ; no. 20, 012 (03/2020)
    Subjects: startup; performance; prediction; text as data
    Scope: 1 Online-Ressource (22 Seiten)
  5. The development of the Central and Eastern European venture capital market in Europe
    Author: Karsai, Judit
    Published: [2023]
    Publisher:  Institute of Economics, Centre for Economic and Regional Studies, Budapest

    The working paper examines the role and development of the Central and Eastern European venture capital sector in the five years between 2016 and 2020. This period includes both the end of the recovery after the economic crisis in 2008 and the... more

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    The working paper examines the role and development of the Central and Eastern European venture capital sector in the five years between 2016 and 2020. This period includes both the end of the recovery after the economic crisis in 2008 and the downturn due to the coronavirus crisis in 2019. A statistical analysis of venture capital funds and investments in the CEE region confirms that, while the overall position of the region in Europe did not change over the period under review, the differences between countries in the region increased sharply. The northern part of the region rivals the most developed countries in Europe, the central part is driven by an abundance of public resources, while the venture capital sector in the south is only in its infancy. The size of the venture capital funds in the region is far below the European average, so the start-ups only have a chance to become successful if they are involved in the international flow of venture capital. The role of the government in the funds in the region is extremely high, but the selection between companies is therefore not based solely on market considerations. Rent-seeking behaviour goes against the essence of venture capital. As a result of the deterioration of the global political and economic situation, the entire Central and Eastern European region is losing its ability to attract capital.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/282244
    Series: KRTK KTI working papers ; KRTK KTI WP - 2023, 23 (August 2023)
    Subjects: venture capital; private equity; acquisition; entrepreneurship; startup; innovation
    Scope: 1 Online-Ressource (circa 26 Seiten)
  6. Policy and regulatory changes for a successful startup revolution
    experiences from the startup action plan in India
    Author: Singh, Vijay Kumar
    Published: [2020]
    Publisher:  Asian Development Bank Institute, Tokyo, Japan

    In January 2016, the Government of India launched the Startup India initiative, which has transformed the way in which the markets, potential entrepreneurs, and investors view startups. This transformation included a slew of policy measures intended... more

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    DS 188
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    In January 2016, the Government of India launched the Startup India initiative, which has transformed the way in which the markets, potential entrepreneurs, and investors view startups. This transformation included a slew of policy measures intended to promote a startup culture and allow younger population members to take risk with their ideas and become "job creators" rather than "job seekers." India's demographic dividend required a suitable channelization of human resources. The Startup Action Plan (SAP) of 2016 proposed to address three key areas for empowering potential startups: (i) handholding and simplification; (ii) funding support and incentives; and (iii) incubation and industry-academia partnership. Emerging as the third-largest startup ecosystem of the world, India has potential for enormous growth. There have been several policies at all levels of government, industry, and academia to promote a startup culture. However, it is important to examine these initiatives and determine whether they move beyond the subsidy/tax holiday mindset and work on the root corrections necessary for a robust startup ecosystem. There are several issues that require consideration from the policy and regulatory perspective for a successful startup revolution. This paper explores these initiatives that the Government of India has taken and identifies the gaps that require attention from stakeholders. The paper also investigates the major challenges and potential solutions arising from the Indian experience of initiatives in the startup revolution.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/238503
    Series: ADBI working paper series ; no. 1146 (June 2020)
    Subjects: startup; legal compliance; financing; investors; global partnerships; entrepreneurship; incubation
    Scope: 1 Online-Ressource (circa 29 Seiten), Illustrationen
  7. One for all
    resolving tensions between heterogeneous investors in a startup
    Author: Chen, Shiqi; Lambrecht, Bart M.
    Published: 17 June 2023
    Publisher:  Centre for Economic Policy Research, London

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    Universitätsbibliothek Mannheim
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Array ; DP18227
    Subjects: investment; payout; startup; risk preferences; group policy
    Scope: 1 Online-Ressource (circa 48 Seiten)