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http://hdl.handle.net/10397/104547
| 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. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Ng_Cluster-Based_Performance_Measurement.pdf | Pre-Published version | 1.08 MB | Adobe PDF | View/Open |
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