Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104547
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Title: Cluster-based performance measurement system for emerging technology-based ventures
Authors: Ng, AW 
Wang, WM 
Cheung, BCF 
Ma, R
Or, YY 
Issue Date: 2017
Source: International journal of entrepreneurship and innovation management, 2017, v. 21, no. 6, p. 485-508
Abstract: Performance assessment of technology-based ventures requires consideration of the nature of their businesses and the dynamics of their emerging industries. This paper explores the development of a cluster-based and quantitative measurement system for science and technology parks to evaluate the performance of technology-based ventures. The proposed method incorporates technique for order preference by similarity to ideal solution (TOPSIS) and weight allocation. It ranks the technology-based ventures in different technological clusters, based on a range of indicators pertinent to productivity, research and development (R&D) effort, R&D personnel percentage, time to market and financial performance. This method has been implemented through a trial study conducted within the Hong Kong Science and Technology Parks Corporation. The results indicate that R&D spending has a strong impact on a company's performance ranking. The performance of technology-based ventures should be measured with respect to their R&D investments and their pertinent efforts to commercialise products.
Keywords: Performance measurement system
R&D
Resource allocation
Technology clusters
Technology-based ventures
Publisher: Inderscience Publishers
Journal: International journal of entrepreneurship and innovation management 
ISSN: 1368-275X
EISSN: 1741-5098
DOI: 10.1504/IJEIM.2017.086939
Rights: Copyright © 2017 Inderscience Enterprises Ltd.
This is the accepted manuscript of the following article: Ng, A. W., Wang, W. M., Cheung, B. C. F., Ma, R., & Or, Y. Y. (2017). Cluster-based performance measurement system for emerging technology-based ventures. International Journal of Entrepreneurship and Innovation Management, 21(6), 485–508, which has been published in final form at https://doi.org/10.1504/IJEIM.2017.086939.
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