Legality of Cannabis by U.S. Jurisdiction

Authors
Philipp Max Hartmann, Mohamed Zaki, Niels Feldmann, Andy Neely
Publication date
2016/10/3
Journal
International Journal of Operations & Production Management
Volume
36
Issue
10
Pages
1382-1406
Publisher
Emerald Group Publishing Limited
Description
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 …
Total citations
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Scholar articles
PM Hartmann, M Zaki, N Feldmann, A Neely - International Journal of Operations & Production …, 2016