Fuzzy AHP approach to evaluate incentive factors of high-tech talent agglomeration
Expert Systems with Applications
; 212, 2023.
Article
in English
| Scopus | ID: covidwho-2245155
ABSTRACT
To compete with the speedy revolution of high technological innovation and restarted economy for the post-COVID-19 period in China, governments and organizations should be active in attracting high-tech talent to enhance independent and indigenous R&D capability. Talent agglomeration effectiveness is the strongest endogenous force pushing competitiveness for regional economy and industrial development. Due to the complexity of high-tech talent agglomeration, there are still considerable gaps to evaluate the incentive factors. This study evaluates the influential indicator system by using a hybrid fuzzy set theory extended Analytic Hierarchy Process (AHP) approach for proximity to reality from individual, organizational and environmental dimensions. The statistical analysis is adopted to verify the results of fuzzy AHP analysis. This research explores the founding that individual incentives are more important than environmental factors, and environmental incentives are more influential than organizational incentives. Job satisfaction, welfare system, and geographical location are the highest ranking factors. High-tech start-ups should give priority to combine geographical location with political support to reserve site selection or firm relocation for a great effectiveness of high-tech talent agglomeration. © 2022 Elsevier Ltd
Competition; Fuzzy set theory; Hierarchical systems; Job satisfaction; Regional planning; Site selection; Fuzzy analytic hierarchy; Fuzzy analytic hierarchy process, industrial cluster; Geographical locations; High tech; Incentive factor; Industrial cluster; Organisational; Process approach; Talent agglomeration; Technological innovation; Analytic hierarchy process; Fuzzy AHP, Industrial clusters; High-tech; Incentive factors
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
Expert Systems with Applications
Year:
2023
Document Type:
Article
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