Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104547
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dc.contributorSchool of Professional Education and Executive Developmenten_US
dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorNg, AWen_US
dc.creatorWang, WMen_US
dc.creatorCheung, BCFen_US
dc.creatorMa, Ren_US
dc.creatorOr, YYen_US
dc.date.accessioned2024-02-05T08:50:59Z-
dc.date.available2024-02-05T08:50:59Z-
dc.identifier.issn1368-275Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/104547-
dc.language.isoenen_US
dc.publisherInderscience Publishersen_US
dc.rightsCopyright © 2017 Inderscience Enterprises Ltd.en_US
dc.rightsThis 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.en_US
dc.subjectPerformance measurement systemen_US
dc.subjectR&Den_US
dc.subjectResource allocationen_US
dc.subjectTechnology clustersen_US
dc.subjectTechnology-based venturesen_US
dc.titleCluster-based performance measurement system for emerging technology-based venturesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage485en_US
dc.identifier.epage508en_US
dc.identifier.volume21en_US
dc.identifier.issue6en_US
dc.identifier.doi10.1504/IJEIM.2017.086939en_US
dcterms.abstractPerformance 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.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of entrepreneurship and innovation management, 2017, v. 21, no. 6, p. 485-508en_US
dcterms.isPartOfInternational journal of entrepreneurship and innovation managementen_US
dcterms.issued2017-
dc.identifier.scopus2-s2.0-85031015808-
dc.identifier.eissn1741-5098en_US
dc.description.validate202402 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0851-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextPolyUen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS20739829-
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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