Capturing value from big data – a taxonomy of data-driven business models used by start-up firms

Philipp Max Hartmann (Department of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany)
Mohamed Zaki (Department of Engineering, Cambridge University, Cambridge, UK)
Niels Feldmann (Department of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany)
Andy Neely (Department of Engineering, Cambridge University, Cambridge, UK)

International Journal of Operations & Production Management

ISSN: 0144-3577

Publication date: 3 October 2016

Abstract

Purpose

The purpose of this paper is to derive a taxonomy of business models used by start-up firms that rely on data as a key resource for business, namely data-driven business models (DDBMs). By providing a framework to systematically analyse DDBMs, the study provides an introduction to DDBM as a field of study.

Design/methodology/approach

To develop the taxonomy of DDBMs, business model descriptions of 100 randomly chosen start-up firms were coded using a DDBM framework derived from literature, comprising six dimensions with 35 features. Subsequent application of clustering algorithms produced six different types of DDBM, validated by case studies from the study’s sample.

Findings

The taxonomy derived from the research consists of six different types of DDBM among start-ups. These types are characterised by a subset of six of nine clustering variables from the DDBM framework.

Practical implications

A major contribution of the paper is the designed framework, which stimulates thinking about the nature and future of DDBMs. The proposed taxonomy will help organisations to position their activities in the current DDBM landscape. Moreover, framework and taxonomy may lead to a DDBM design toolbox.

Originality/value

This paper develops a basis for understanding how start-ups build business models capture value from data as a key resource, adding a business perspective to the discussion of big data. By offering the scientific community a specific framework of business model features and a subsequent taxonomy, the paper provides reference points and serves as a foundation for future studies of DDBMs.

Keywords

Citation

Philipp Max Hartmann, Mohamed Zaki, Niels Feldmann and Andy Neely (2016) "Capturing value from big data – a taxonomy of data-driven business models used by start-up firms", International Journal of Operations & Production Management, Vol. 36 No. 10, pp. 1382-1406

Download as .RIS

DOI

: https://doi.org/10.1108/IJOPM-02-2014-0098

Publisher

:

Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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