Purpose
Over recent decades, talent agglomeration has emerged as a critical topic for scholars, businesses and government officers. Innovative ability is a core competition for high-tech talents. In China, low innovation is the bottleneck, as the high-tech industry usually cannot provide sufficient support for the continuous needs of innovative talents. To enhance the continuous support of talents, it is important to obtain the mechanisms of talent evaluation and flow in high-tech industry. Exploring the incentive factors influencing the scientific and technological personnel, adjust the layout of talents and promote the rational agglomeration. It’s significant to realize the regional economic development.
Design/methodology/approach
This study proposes an assessment model using the multi-criteria decision-making method of analytical hierarchy process (AHP) to determine the weights of incentive factors and a nonlinear programing model, from micro, meso and macro perspectives of individual, organizational and social incentives by adopting Maslow’s hierarchy of needs theory, Kurt Lewin’s field theory and Lee’s push-pull theory. After the literature review and interviews with 14 experts, this study produced a research framework and a pairwise comparison questionnaire. In addition, the relative quantitative weights of 3 main categories and 15 indicators are identified and ranked based on the AHP method.
Findings
The results demonstrate that the most important dimension is the individual, and the top three highest weighted factors are job satisfaction, sense of working accomplishment and interpersonal relationships. The discussion in this study showed that the proposed model is rational and acceptable to motivate high-tech innovation talent (HTIT) agglomeration for high-tech enterprises, universities, government and start-ups.
Research limitations/implications
The pairwise comparison using the AHP method is limited to expert opinions, which are considered comparatively subjective. The number of incentive factors should be increased, as some indicators may have been omitted from the AHP model.
Practical implications
According to the results, some suggestions can be recommended to corporate executives, HR managers and government officers to attract and retain high-tech talents and further to improve industrial clusters and economic development.
Originality/value
This paper derives a relative ranking of importance based on the opinions of experienced HR specialists, high-tech talent, scholars and government official, and assesses the consistency of results. The ordering represents the importance of indicators and sub-indicators of two levels from respondents’ perspectives in an industry cluster background. The study, focusing on the high-tech industry in China (which is a developing country), offers a unique view, as earlier studies mainly collect data from developed countries.
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