GIS-Based Approach to Analyze the Spatial Opportunities for Knowledge-Intensive Businesses

Mei Lin Yeo, Saad Saleem Bhatti, Elisabete A. Silva

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Knowledge-intensive businesses (KIBs) are one of the fastest developing subsectors that play an integral role in the world’s economy; they have been outperforming the total economy in terms of economic and regional growth and job creation recently. The KIBs are usually driven by qualified and skilled workers capable of contributing to the creativity and innovation in a particular business sector. The location preferences of KIBs, therefore, are significantly different from other product-driven businesses. This study uses spatial analysis in a geographical information system (GIS) together with a multicriteria decision-making (MCDM) process to examine the spatial opportunities for growth of KIBs by integrating spatial data with the decision-makers’ opinion collected through questionnaire survey. The proposed approach was tested by applying to a case study area of Cambridge, the United Kingdom, which has a large number of knowledge-based firms. Two major sectors, biotechnology and computer technology, were analyzed using 11 factors; the data on companies’ perception regarding importance of location and other variables was collected through questionnaire survey of 17 firms and discussion with the field experts. We applied an “analytic hierarchy process,” which consists of a MCDM method, in order to obtain the relative importance of each factor contributing to the location of new firms. After this step, all spatial and aspatial data were translated to spatial coverages in order to build a GIS-based model to identify the areas suitable for biotechnology and computer technology businesses. The results indicated that KIBs prefer to be located close to research and development centers and Cambridge University Departments, which fuel these businesses by providing skilled workforce. The proposed approach presents robust results and provides the flexibility to integrate the variables fitting well to the local context to generate more realistic and accurate results.
LanguageEnglish
Title of host publicationComprehensive Geographic Information Systems
PublisherElsevier
Pages83-100
ISBN (Print)978-0-12-804793-4
DOIs
Publication statusPublished - 2018

Fingerprint

Geographical information system
Computer technology
Biotechnology
Questionnaire survey
Factors
Multicriteria decision-making
Skilled workers
Build-to-order
New firms
Job creation
Analytic hierarchy process
Decision-making process
Decision maker
Creativity
Regional growth
Integral
Economic growth
Business sector
Innovation
Knowledge-based

Keywords

  • Analytic hierarchy process (AHP)
  • Biotechnology
  • Cambridge (UK)
  • Creative/knowledge-intensive industries/businesses
  • Computer technology
  • Location preference
  • Multicriteria decision-making (MCDM)
  • Questionnaire survey
  • Site suitability
  • Spatial analysis

Cite this

Yeo, M. L., Bhatti, S. S., & Silva, E. A. (2018). GIS-Based Approach to Analyze the Spatial Opportunities for Knowledge-Intensive Businesses. In Comprehensive Geographic Information Systems (pp. 83-100). Elsevier. https://doi.org/10.1016/B978-0-12-409548-9.09687-1
Yeo, Mei Lin ; Bhatti, Saad Saleem ; Silva, Elisabete A. / GIS-Based Approach to Analyze the Spatial Opportunities for Knowledge-Intensive Businesses. Comprehensive Geographic Information Systems. Elsevier, 2018. pp. 83-100
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GIS-Based Approach to Analyze the Spatial Opportunities for Knowledge-Intensive Businesses. / Yeo, Mei Lin; Bhatti, Saad Saleem; Silva, Elisabete A.

Comprehensive Geographic Information Systems. Elsevier, 2018. p. 83-100.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - GIS-Based Approach to Analyze the Spatial Opportunities for Knowledge-Intensive Businesses

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AU - Bhatti, Saad Saleem

AU - Silva, Elisabete A.

PY - 2018

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M3 - Chapter

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PB - Elsevier

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