Factors Influencing the Performance of Technology Talents Mobility in a Hi-Tech Enterprise
Keywords:
Hi-Tech Enterprise , Performance, Technology talents mobilityAbstract
The general purpose of this study was to determine the level of factors influencing the performance of technology talents mobility in a hi-tech pharmaceutical enterprise in Anhui Province, China, during the Calendar Year 2022.
The variables included in this study are age, sex, length of service, and average family monthly income. The level of factors influencing the performance of technology talent mobility is divided into three areas: customer orientation satisfaction, manufacturing capacity, and accessibility to the market. There were ninety-eight (98) respondents who were employees of the enterprise. Most respondents are older, male, have a shorter service length and have a lower average family monthly income. The level of factors influencing the performance of technology talents mobility in a hi-tech pharmaceutical enterprise is moderate in all areas composed of customer orientation satisfaction, manufacturing capacity, and accessibility to the market. Results revealed no significant difference in the level of factors influencing the performance of technology talents mobility in a hi-tech pharmaceutical enterprise in all areas when grouped and compared according to sex, length of service, and average family monthly income. However, a significant difference was revealed in customer orientation satisfaction and accessibility to the market when grouped according to age.
References
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.
Bluman, A. G. (2012). Elementary statistics: A step by step approach (9th ed.). New York: McGraw-Hill.
Böckerman, P., Laaksonen, S., & Vainiomäki, J. (2012). Micro-level evidence on wage rigidity, worker sorting, and unemployment dynamics. Journal of Labor Economics, 30(3), 657-692.
Bryman, A., & Bell, E. (2019). Business research methods. Oxford University Press.
Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
DeVellis, R. F. (2017). Scale development: Theory and applications. Los Angeles: Sage Publications.
Embretson, S. E., & Reise, S. P. (2013). Item response theory for psychologists. Psychology Press.
European Commission. (2018). Digital talent in the EU labour market: Bridging the skills gap and driving digital transformation. Retrieved from https://ec.europa.eu/digital-single-market/en/news/digital-talent-eu-labour-market-bridging-skills-gap-and-driving-digital-transformation
Gibbons, J. D., & Chakraborti, S. (2011). Nonparametric statistical inference. CRC press.
Good, C. V., & Scates, D. B. (1956). Techniques of attitude scale construction. RAND Corporation.
Gravetter, F. J., & Wallnau, L. B. (2016). Statistics for the behavioral sciences. Cengage Learning.
Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597-606.
Hsu, C. W., & Sabherwal, R. (2012). Intellectual property protection mechanisms in high-tech industries: The case of the semiconductor industry. Information Systems Research
Jaber, M. Y. (2015). Production and operations management. John Wiley & Sons.
Johnson, A. (2018). Accessibility to the market. In J. Smith (Ed.), The Handbook of Economics (pp. 123-145). Oxford University Press.
Kotler, P., & Armstrong, G. (2016). Principles of Marketing (16th ed.). Pearson Education Limited.
Kram, K. E., & Hansen, T. (2019). Creating a Culture of Mobility: How to Help Your Employees Move Up, Over, and Out. Harvard Business Review
Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T., & Tillmanns, S. (2019). Undervalued or Overvalued Customers: Capturing Total Customer Engagement Value. Journal of Service Research.
Kumar, R., & Bhatnagar, J. (2016). Factors influencing the mobility of Indian IT professionals: An empirical study. International Journal of Human Resource Management.
Lee, T. H., & Kim, D. H. (2021). A methodology for quantifying the impacts of manufacturing capacity on supply chain performance. Journal of Cleaner Production.
Lim, M., & Chee, Y. (2019). Singapore talent survey 2019: Technology talent mobility. Singapore Economic Development Board. Retrieved from https://www.edb.gov.sg/content/dam/edbsite/about-edb/resources-and-tools/publications/Reports/SG-Talent-Survey-2019-Technology-Talent-Mobility.pdf
LinkedIn. (2021). The Most In-Demand Skills of 2021. Retrieved from https://business.linkedin.com/content/dam/me/business/en- us/talent-solutions/emerging-jobs-report/Emerging%20Jobs%20Report%202021_US_FINAL.pdf
Liu, Y., & Huang, J. (2017). The development of high-tech enterprises in China: a review. Journal of Innovation and Entrepreneurship
Liu, Y., Li, Y., Chen, J., & Zhang, J. (2021). High-tech enterprise innovation and sustainable development: A review of research progress and future directions. Journal of Cleaner Production.
Liu, X., Zhang, J., & Shao, Y. (2018). What drives Chinese technology talents’ mobility? An investigation from push and pull perspectives. Journal of International Business Studies, 49(3), 336-355. doi:10.1057/s41267-017-0085-7
Luhmann, S., & Hawkley, L. (2016). Average family income and its implications for health in later life. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences.
Solomon, M. R. (2016). Consumer behavior: Buying, having, and being. Pearson.
Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics. Pearson Education Limited.
The European Commission. (2019). Skills for smart industrial specialization and digital transformation. Retrieved from https://ec.europa.eu/growth/tools-databases/newsroom/cf/itemdetail.cfm?item_id=10227&lang=en
United Nations Statistics Division. (2017). Demographic Profile: Sex. Retrieved from https://unstats.un.org/unsd/demographic- social/products/dyb/dyb_2017/
Wang, S., & Wang, C. (2020). Talent acquisition and retention in high- tech firms: A systematic review of the literature. Journal of Knowledge Management
Wasserman, T. (2021). Why Company Culture Is Critical in the Mobility of Tech Talent. Retrieved from https://www.shrm.org/resourcesandtools/hr-topics/organizational-and-employee-development/pages/why- company-culture-is-critical-in-the-mobility-of-tech-talent.aspx
World Economic Forum. (2020). The Future of Jobs Report 2020. Retrieved from https://www.weforum.org/reports/the-future-of-jobs-report-2020
World Health Organization. Ageing and Life Course: https://www.who.int/ageing/en/
Xue, L., Li, Y., Li, Y., & Li, Y. (2019). What drives the innovation of high-tech enterprises in China? Evidence from the Shenzhen high-tech park. Sustainability
Zhang, Y., Li, Y., & Xu, B. (2019). How does the mobility of technology talents affect innovation performance? Evidence from Chinese firms. Technology in Society, 57, 101149.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Li, Haibin (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
