skip to primary navigationskip to content

Cambridge Service Alliance

At the forefront of service transformation in the digital era

Studying at Cambridge

 

Business Ecosystems: Towards a Classification Model

last modified Apr 20, 2017 01:46 PM
April 2017 Paper on 'Business Ecosystems: Towards a Classification Model' by Florian Urmetzer, Andy Neely and Veronica Martinez

This paper contributes to the business ecosystem literature by offering a classification model, allowing the differentiation of inter-company connections. The problem arose for the researchers that the definition of a business ecosystem lacks separation in the types of connection between companies. Business ecosystems are found to differentiate significantly, starting from loosely coupled to highly regulated and organised company relationships. Some may even result in newly founded business ventures. The authors are proposing a classification model for business ecosystems to allow further classifications in studies. 

[paper]

RSS Feed Latest news

'Using AI to Track How Customers Feel — In Real Time' published in the Harvard Business Review

May 13, 2021

The paper 'Using AI to Track How Customers Feel — In Real Time' by Mohamed Zaki, Janet R. McColl-Kennedy and Andy Neely has been published in Harvard Business Review.

Industry Day 2020 | What we learnt

Dec 06, 2020

What is the future of services in the new pandemic-driven era? This was the topic explored at our 2020 Industry Day by senior executives from L'Oréal, Microsoft Research, Manchester United and start-up, Fairjungle.

Understanding business models in the construction sector

Nov 25, 2020

What’s standing in the way of offsite manufacturing? For decades, the construction sector has been hailing it as the next big thing but we have yet to see it really taking off. Why is that, when the technologies and processes already exist? Dr Zakaria Dakhli believes it is due to a fundamental incompatibility between business models and it is only when this has been fully understood that the long-awaited transformation can take place.

A machine learning approach to quality control

Nov 14, 2020

Most of the products we take for granted contain huge numbers of components assembled in multiple stages by different manufacturers. Quality control is vital throughout the assembly process with rigorous testing required at every step.

View all news