SwePub
Sök i LIBRIS databas

  Utökad sökning

onr:"swepub:oai:DiVA.org:uu-497864"
 

Sökning: onr:"swepub:oai:DiVA.org:uu-497864" > Using machine learn...

Using machine learning to create and capture value in the business models of small and medium-sized enterprises

Costa-Climent, Ricardo, 1972- (författare)
Uppsala universitet,Informationssystem,University of Economics and Human Sciences, Okopowa 59, 01-043 Warsaw, Poland
Haftor, Darek M., 1969- (författare)
Uppsala universitet,Informationssystem,University of Economics and Human Sciences, Okopowa 59, 01-043 Warsaw, Poland
Staniewski, Marcin W. (författare)
 (creator_code:org_t)
Elsevier, 2023
2023
Engelska.
Ingår i: International Journal of Information Management. - : Elsevier. - 0268-4012 .- 1873-4707. ; 73
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Start-ups have revolutionised many economic ecosystems, becoming innovation pioneers around the world. Most are based on data-driven business models, particularly relying on machine learning technologies. However, not all start-ups that use machine learning technologies manage to create and capture value. The existing literature on the use value enabled by information technologies does not take into account the unique capabilities of machine learning. The theory of data network effects offers a promising explanation of how to create value using machine learning. However, it does not explicitly describe how to capture value using machine learning. In contrast, business model theory explains how companies use technologies to create and capture value, but not specifically through the use of machine learning technology. Therefore, this study aims to improve the theoretical understanding of the key drivers of value creation and capture in start-ups with business models driven by this kind of technology. Statistical techniques are used in a sample of 122 start-ups to explore the theoretical relationships between these two theories. The analysis reveals the link between specific value creation and capture factors of the two theories, such as efficiency, novelty, and performance expectancy. The study also provides evidence of the need to adopt a co-evolutionary perspective of value creation and capture through the use of machine learning.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)
SAMHÄLLSVETENSKAP  -- Ekonomi och näringsliv -- Företagsekonomi (hsv//swe)
SOCIAL SCIENCES  -- Economics and Business -- Business Administration (hsv//eng)

Nyckelord

Machine learning
Start-up
Data network effect
Business model
Twitter

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Sök utanför SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy