Analysis of big data enabled business models using a value chain perspective

Oleksandr Sadovskyi, Tobias Engel, Robert Heininger, Markus Böhm, Helmut Krcmar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

This paper evaluates the current state-of-the-art in big data research through conducting an analysis of currently available publications. It describes characteristics of big data, evaluates trends in research and defines the best practices and challenges in adoption of big data-driven business models in organizations. Reflecting on the available showcases and case studies, it is shown how key industries in the private and public sectors innovate with big data. We describe in detail in which value chain activities big data is used to gain competitive advantage, showing a research gap in the logistics field. We conclude with a discussion on necessary research fields and research agenda in order to stimulate big data-oriented approaches for the creation of new business models.

Original languageEnglish
Title of host publicationTagungsband Multikonferenz Wirtschaftsinformatik 2014, MKWI 2014
EditorsDennis Kundisch, Lars Beckmann, Leena Suhl
PublisherUniversity of Paderborn
Pages1125-1137
Number of pages13
ISBN (Electronic)9783000453113
StatePublished - 2014
EventMultikonferenz Wirtschaftsinformatik, MKWI 2014 - Multi-Conference on Business Informatics, MKWI 2014 - Paderborn, Germany
Duration: 26 Feb 201428 Feb 2014

Publication series

NameTagungsband Multikonferenz Wirtschaftsinformatik 2014, MKWI 2014

Conference

ConferenceMultikonferenz Wirtschaftsinformatik, MKWI 2014 - Multi-Conference on Business Informatics, MKWI 2014
Country/TerritoryGermany
CityPaderborn
Period26/02/1428/02/14

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