JOB SATISFACTION SCALE FOR TECH WORKERS: IMPLEMENTATION COMPASS
Abstract
Tech workers are not just employees but ubiquitous architects and drivers of the imminent digitalized future. Tech worker’s wellbeing is, therefore, crucial for global prosperity – necessitating their continuous monitoring and management in the workplace. Although a cross-cultural job satisfaction scale has been specifically developed and validated to help gauge the wellbeing of tech workers, christened JSST, it lacked an implementation guideline. This lack of implementation guidelines for the JSST questionnaire can stifle its practicality and, by extension, the wellbeing of Tech workers. The aim of this study, therefore, is to design an implementation guideline for JSST. The implementation guideline was designed using descriptive statistics and algorithmic specification. Adopting a self-assessment online survey on the original Five-point Likert JSST Questionnaire, this study also demonstrated the implementation of the guideline. 276 valid Tech workers’ job satisfaction self-assessment data solicited globally using the JSST questionnaire was employed to demonstrate the guideline’s feasibility. Overall, the job satisfaction index of the global tech workers has been estimated to fall into the third quartile of satisfaction, Q3, which is low. This low satisfaction index may account for the high turnover and turn-away in the global Tech industry. A notable outcome of this study is the seamless JSST implementation scheme, which is not only effective but also highly adaptable. This scheme can be tailored for the implementation of any multi-faceted psychometric scale, making it a versatile tool for assessing employee wellbeing. The automation for web accessibility of the JSST implementation scheme is encouraged.
References
Abiona, B. G., Adenuga, O. O., Adeosun, K. G., Fapojuwo, O. E., & Roseje, T. O. (2023). Assessment of job satisfaction among employees of Animal Care Services Consult Limited, Ogbere Remo, Ogun State, Nigeria. FUDMA Journal of Sciences, 7(3), 257-265. https://doi.org/10.33003/fjs-2023-0703-1813 DOI: https://doi.org/10.33003/fjs-2023-0703-1813
Asenahabi, B. M., & Ikoha, P. A. (2023). Scientific research sample size determination. The International Journal of Science & Technology, 11(7), 8-12. http://dx.doi.org/10.24940/theijst/2023/v11/i7/ST2307-008 DOI: https://doi.org/10.24940/theijst/2023/v11/i7/ST2307-008
Azash, S. M. D., & Thirupalu, N. (2017). Scale for measuring job satisfaction: A review of literature. International Journal of Economic and Business Review, 5(3), 114-123. URL: http://www.eprawisdom.com
Bernhard, U., Porten-Cheé, P., & Schultze, M. (2015). Survey research online. In Political communication in the online world: Theoretical approaches and research designs (pp. 218-232). Routledge https://doi.org/10.4324/9781315707495-15 DOI: https://doi.org/10.4324/9781315707495-15
Ehigbochie, A. I., & Ekuobase, G. O. (2024). A job satisfaction scale for tech workers: Development and validation in the global context. Human Behavior and Emerging Technologies. DOI: https://doi.org/10.1155/2024/8873743 DOI: https://doi.org/10.1155/2024/8873743
Ferreira, C., Pedrosa, I., & Calheiros, A. (2021). Turnover in Portuguese technology companies: A literature review. CRISTI - Revista Ibérica de Sistemas e Tecnologias de Informação, 2021(E42), 212-227. URL: http://www.risti.xyz
Gomez Gandia, S.A., Gavrila, S.G., Ancillo, A, D,L., & Val, T.D. (2024). RPA as a challenge beyong technology: self-learning and attitude needed for successful RPA implementation in the workplace. Journal of knowledge economy. https://doi.org/10.1007/s13132-024-01865-5 DOI: https://doi.org/10.1007/s13132-024-01865-5
Guobadia, F. E., & Ekuobase, G. O. (2024). An estimation of digital learning culture index of secondary education in Nigeria. Education Research International, 2024(16). https://doi.org/10.1155/2024/6671155 DOI: https://doi.org/10.1155/2024/6671155
Memon, M. A., Tings, H., Cheahs, J. H., Thurasamy, R., Chuah, F., & Cham, T. H. (2020). Sample size for survey research: Review and recommendations. Journal of Applied Equation Modeling, 4(2). https://doi.org/10.47263/JASEM.4(2)01 DOI: https://doi.org/10.47263/JASEM.4(2)01
Muwanguzi, E. (2022). Job satisfaction: A literature review. Journal of Research in Humanities and Social Science, 10(10), 165-172. URL: http://www.questjournals.org
Oguntayo, S. A., Unegbu, V. E., & Alegbeleye, G. O. (2023). Analysis of professional competencies and job satisfaction of Liberians in private universities in south-west Nigeria. FUDMAN Journal of Sciences, 7(6), 382-390. https://doi.org/10.33003/jjs-2023-0706-2218 DOI: https://doi.org/10.33003/fjs-2023-0706-2218
Oehlhorn, C. E., Maier, C., & Weitzel, T. (2020). Turnover and turnaway of IT workers: A person-environment fit perspective. SIGMIS-CPR '20, 103-104. http://dx.doi.org/10.1145/3378539.3393838 DOI: https://doi.org/10.1145/3378539.3393838
Robinson, M. A. (2018). Using the multi-item psychometric scales for research and practice in human resource management. Human Resource Management, 739-750. https://doi.org/10.1002/hrm.21852 DOI: https://doi.org/10.1002/hrm.21852
Segal, D. L., Colidge, F. L., O’Riley, A., & Heinz, B. A. (2006). Structured and semi-structured interviews. In Clinician's handbook of adult behavioral assessment,121-144. https://doi.org/10.1016/B978-012343013-7/50007-0 DOI: https://doi.org/10.1016/B978-012343013-7/50007-0
Statista. (2023). Number of ICT professionals worldwide 2019-2023, by share of website. Retrieved from https://www.statista.com/statistics/1126677/it-employment-worldwide/
Wei, L., Wongvanichtawee, C., & Tang, C.-H. (2024). The role of transformational leadership in mitigating employee turnover: Insights from China’s high-tech industry. Journal of Infrastructure, Policy and Development, 8(9), 7830. https://doi.org/10.24294/jipd.v8i9.7830 DOI: https://doi.org/10.24294/jipd.v8i9.7830
Wu, M. J., Zhao, K., & Fils-Aime, F. (2022). Response rates of online surveys in published research: A meta-analysis. Computers and Human Behavior Reports, 7, 100206. https://doi.org/10.1016/j.chbr.2022.100206 DOI: https://doi.org/10.1016/j.chbr.2022.100206
Yanchovska, I. (2022). Scales for measuring employee satisfaction. Academic Journal of Mechanics, Transport Communications, 11(10), 31-38. URL: http://www.mtc-aj.com
Zhang, X., Kuchinke, L., Woud, M. L., Veltin, J., & Margraf, J. (2017). Survey method matters: Online/offline questionnaires and face-to-face or telephone interviews differ. Computers in Human Behavior, 71, 172-180. https://doi.org/10.1016/j.chb.2017.02.006 DOI: https://doi.org/10.1016/j.chb.2017.02.006
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