From Single to Scale: Essays on Social Media, Artificial Intelligence and Start-Up Scaling- [electronic resource]
From Single to Scale: Essays on Social Media, Artificial Intelligence and Start-Up Scaling- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214100118
- ISBN
- 9798379750947
- DDC
- 005
- 저자명
- Wang, Xiaoning.
- 서명/저자
- From Single to Scale: Essays on Social Media, Artificial Intelligence and Start-Up Scaling - [electronic resource]
- 발행사항
- [S.l.]: : University of Pennsylvania., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(211 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
- 주기사항
- Advisor: Wu, Lynn.
- 학위논문주기
- Thesis (Ph.D.)--University of Pennsylvania, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약This dissertation, comprised of three essays, examines the influence of nascent information technologies including social media and artificial intelligence on facilitating the scaling process of entrepreneurial ventures. Through large-scale empirical analyses, this dissertation studies how social media and artificial intelligence can help start-ups improve financing outcomes, institutional environments and product performances, and whether such nascent information technologies will mitigate or exacerbate the existing disparities in the domain of entrepreneurship.In the first essay, we examine whether social media use can improve funding outcomes for start-up firms, especially those founded by women and by other people also lacking connections to the investor network. Using Twitter data and start-up investment data from Crunchbase, we show that social media can mitigate some disparities in financing experienced by these firms through improving information access. We find this effect is stronger for first-time entrepreneurs than for experienced ones, stronger for attracting new investors than repeat ones, and stronger in more competitive markets.In the second essay, using comprehensive start-up data in China, we find that social media activities can help companies that possess few political connections to obtain institutional resources. They are more likely to receive administrative approvals from the government to conduct their primary business activities. They are also more likely to receive positive media coverages. We find that social media can not only help these companies broadcast quality signals, but also direct public opinion and mobilize public support, all of which are essential to establish public legitimacy.In the third essay, we investigate the role of the lean start-up method (LSM) in explaining the impact of AI capability on product innovations in start-ups. We find that companies that adopt general AI capability create more innovative products every year, including both novel and incremental products. We also find that AI investments complement LSM in product innovations, and the complementarities depend on the type of product innovations and the type of AI used.
- 일반주제명
- Web studies.
- 키워드
- Scaling
- 키워드
- Social media
- 키워드
- Start-up method
- 키워드
- AI capability
- 기타저자
- University of Pennsylvania Operations Information and Decisions
- 기본자료저록
- Dissertations Abstracts International. 84-12B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520240214100118
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■020 ▼a9798379750947
■035 ▼a(MiAaPQ)AAI30423178
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a005
■1001 ▼aWang, Xiaoning.
■24510▼aFrom Single to Scale: Essays on Social Media, Artificial Intelligence and Start-Up Scaling▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of Pennsylvania. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(211 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 84-12, Section: B.
■500 ▼aAdvisor: Wu, Lynn.
■5021 ▼aThesis (Ph.D.)--University of Pennsylvania, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aThis dissertation, comprised of three essays, examines the influence of nascent information technologies including social media and artificial intelligence on facilitating the scaling process of entrepreneurial ventures. Through large-scale empirical analyses, this dissertation studies how social media and artificial intelligence can help start-ups improve financing outcomes, institutional environments and product performances, and whether such nascent information technologies will mitigate or exacerbate the existing disparities in the domain of entrepreneurship.In the first essay, we examine whether social media use can improve funding outcomes for start-up firms, especially those founded by women and by other people also lacking connections to the investor network. Using Twitter data and start-up investment data from Crunchbase, we show that social media can mitigate some disparities in financing experienced by these firms through improving information access. We find this effect is stronger for first-time entrepreneurs than for experienced ones, stronger for attracting new investors than repeat ones, and stronger in more competitive markets.In the second essay, using comprehensive start-up data in China, we find that social media activities can help companies that possess few political connections to obtain institutional resources. They are more likely to receive administrative approvals from the government to conduct their primary business activities. They are also more likely to receive positive media coverages. We find that social media can not only help these companies broadcast quality signals, but also direct public opinion and mobilize public support, all of which are essential to establish public legitimacy.In the third essay, we investigate the role of the lean start-up method (LSM) in explaining the impact of AI capability on product innovations in start-ups. We find that companies that adopt general AI capability create more innovative products every year, including both novel and incremental products. We also find that AI investments complement LSM in product innovations, and the complementarities depend on the type of product innovations and the type of AI used.
■590 ▼aSchool code: 0175.
■650 4▼aWeb studies.
■653 ▼aArtificial intelligence
■653 ▼aScaling
■653 ▼aSocial media
■653 ▼aStart-up method
■653 ▼aAI capability
■653 ▼aNascent information technologies
■690 ▼a0310
■690 ▼a0454
■690 ▼a0646
■690 ▼a0800
■71020▼aUniversity of Pennsylvania▼bOperations, Information and Decisions.
■7730 ▼tDissertations Abstracts International▼g84-12B.
■773 ▼tDissertation Abstract International
■790 ▼a0175
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16931787▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
