Innovation Management Strategies and Practices to Accelerate the Commercialisation Process in the Biotechnology Industry

Grant Type

Australian Research Council Linkage Project

Start Date

July 2003

Brief Project Description

The innovation cycle is a complex and misunderstood area of management, particularly in the Biotechnology Industry where the innovation cycle can take up to 15 years. The management literature provides anecdotal information, however lacks theoretical models that provide guidance to managers on how to shorten the innovation process.

Therefore the aim of this PhD research, which is “a world first”, is to develop and test an innovation cycle model through quantitative and qualitative research.

The results of this research provide a theoretical and practical understanding to Australian managers on the complex relationships between innovation management practices and innovation performance in the biotechnology industry. This knowledge can assist managers to make more effective decisions on the allocation of scarce resources and complex project management. Australian companies will need to develop and implement strategic long-term plans in order to compete more effectively in increasingly competitive markets.

Research Partners

Assoc. Prof. Dr. Mile Terziovski-Chief Investigator

Prof. Danny Samson-Co. Chief Investigator

John Morgan- PhD Student

Industry Partner

AusBiotech Ltd - www.ausbiotech.org

Whitehorse Strategic Group Ltd - www.whitehorsestrategic.com

Work completed to date

The project is in the final stage of completion.

The study has completed stage 1 (literature review) by examining existing knowledge, and developing a detailed and comprehensive framework of innovation management.

Secondly, the project has accomplished the following case studies:

1. Prana Biotechnology Ltd
2. IDT Australia
3. Intercell AG
4. Ingeneon
5. Maize Technologies International
6. DSM

Stages 3 and 4 have been concluded through the development of a web-based survey to benchmark world-class innovation management practices, followed by analysis of the data.