Combining big data and lean startup methods for business model evolution

Name: Combining big data and lean startup methods for business model evolution
Author: Seggie, S. H., Soyer, Emre, Pauwels, K. H.

İsim	Combining big data and lean startup methods for business model evolution
Yazar	Seggie, S. H., Soyer, Emre, Pauwels, K. H.
Basım Tarihi:	2017-12
Basım Yeri	- Springer
Konu	Big data, Build-measure-learn-loop, Business model, Confirmation bias, Innovation, Innovation accounting, Lean startup
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1869-814X
Kayıt Numarası	a1e8b4bd-6abe-4459-ae02-beb701b4ee42
Lokasyon	Business Administration
Tarih	2017-12
Örnek Metin	The continued survival of firms depends on successful innovation. Yet, legacy firms are struggling to adapt their business models to successfully innovate in the face of greater competition from both local and global startups. The authors propose that firms should build on the lean startup methodology to help adapt their business models while at the same time leveraging the resource advantages that they have as legacy corporations. This paper provides an integrated process for corporate innovation learning through combining the lean startup methodology with big data. By themselves, the volume, variety and velocity of big data may trigger confirmation bias, communication problems and illusions of control. However, the lean startup methodology has the potential to alleviate these complications. Specifically, firms should evolve their business models through fast verification of managerial hypotheses, innovation accounting and the build-measure-learn-loop cycle. Such advice is especially valid for environments with high levels of technological and demand uncertainty.
DOI	10.1007/s13162-017-0104-9
Cilt	7

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Combining big data and lean startup methods for business model evolution

Yazar Seggie, S. H., Soyer, Emre, Pauwels, K. H.

Basım Tarihi 2017-12

Basım Yeri - Springer

Konu Big data, Build-measure-learn-loop, Business model, Confirmation bias, Innovation, Innovation accounting, Lean startup

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1869-814X

Kayıt Numarası a1e8b4bd-6abe-4459-ae02-beb701b4ee42

Lokasyon Business Administration

Tarih 2017-12

Örnek Metin The continued survival of firms depends on successful innovation. Yet, legacy firms are struggling to adapt their business models to successfully innovate in the face of greater competition from both local and global startups. The authors propose that firms should build on the lean startup methodology to help adapt their business models while at the same time leveraging the resource advantages that they have as legacy corporations. This paper provides an integrated process for corporate innovation learning through combining the lean startup methodology with big data. By themselves, the volume, variety and velocity of big data may trigger confirmation bias, communication problems and illusions of control. However, the lean startup methodology has the potential to alleviate these complications. Specifically, firms should evolve their business models through fast verification of managerial hypotheses, innovation accounting and the build-measure-learn-loop cycle. Such advice is especially valid for environments with high levels of technological and demand uncertainty.

DOI 10.1007/s13162-017-0104-9

Cilt 7