IMPACT OF EMERGING TECHNOLOGY ADOPTION ON SAFETY PERFROMANCE OF MANUFACTURING COMPANIES IN NIGERIA
Abstract
This paper examined the impact of emerging technologies adoption on workplace safety in manufacturing industries in Nigeria. Six emerging technologies were explored. workplace safety was evaluated using safety outcomes, safety participations and safety compliance. Cross-sectional research design was adopted. Stratified random sampling technique was used. Sample sizes was 345 determined using Taro Yamane’s sample size determination formula. Data were collected using structured questionnaire based on 5-point Likert scale. SPSS version 24 was used for data analyses; percentages and weighted mean scores (WMS) were computed using descriptive statistics and regression analysis. Results of descriptive statistics revealed emerging technology adoption was low in Nigeria manufacturing firms (WMS=2.94<3.00). There is moderate level of safety outcome, compliance and participation in manufacturing firms in Nigeria (WMS=3.00, 3.21, and 3.26>3.00). Results of regression analysis showed that emerging technology adoption has positive and significant impact on safety outcome (B=1.198, p-value<0.0001) while its impact on safety compliance (B=0.064, p-value<0.073)) and safety participation (B=0.068, p-value<0.651) were positive but insignificant. Conclusively, emerging technology adoption improved workplace safety moderately in manufacturing firms in Nigeria. Therefore, stakeholders in manufacturing sector in developing countries like Nigeria should provide infrastructure and regulatory framework required for adequate adoption of emerging technology for workplace safety in the sector.
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Afolabi, A. O., Ojelabi, R. A., Bukola, A., Akinola, A., & Afolabi, A. (2018). Statistical exploration of dataset examining key indicators influencing housing and urban infrastructure investments in megacities. Data in Brief, 18, 1725–1733. https://doi.org/10.1016/j.dib.2018.04.089
Ajayi, A.O., Oyedele, L.O., Akinadé, O.O., Bilal, M., Owolabi, H.A., Àkànbí, L.A., & Delgado, J.M. (2020). Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations. Safety Science, 125, 104656.
Attih, G. E., Ugbebor, J., & Ugwoha, E. (2022). Health risks prevalent among workers in tank farms in Niger Delta, Nigeria. World Journal of Innovative Research (WJIR), 12(3), 07-12. https://doi.org/10.31871/WJIR.12.3.6
Ayantoyinbo, B., & Adepoju, O. (2018). Analysis of solid waste management logistics and its attendant challenges in Lagos Metropolis. Logistics, 2(2), 11. https://doi.org/10.3390/logistics2020011
De Merich, D., Gnoni, M., Malorgio, B., Micheli, G., Piga, G., Sala, G., & Tornese, F. (2020). A Cloud-Based Tool for Integrating Occupational Risk Assessment Within Management Systems for SMEs. Safety. https://doi.org/10.3390/safety6040047
Donisi, L., Cesarelli, G., Pisani, N., Ponsiglione, A. M., Ricciardi, C., & Capodaglio, E. (2022). Wearable sensors and artificial intelligence for physical ergonomics: A systematic review of literature. Diagnostics, 12(12), 3048.
Flor-Unda, O., Fuentes, M., Dávila, D., Rivera, M., Llano, G., Izurieta, C., & Acosta-Vargas, P. (2023). Innovative technologies for occupational health and safety: A scoping review. Safety, 9(2), 35. https://doi.org/10.3390/safety9020035
Fraboni F, Brendel H, Pietrantoni L. (2023). Evaluating Organizational Guidelines for Enhancing Psychological Well-Being, Safety, and Performance in Technology Integration. Sustainability, 15(10):8113. https://doi.org/10.3390/su15108113
Galaz, V., Centeno, M. A., Callahan, P. W., Causevic, A., Patterson, T., Brass, I., Baum, S., Farber, D., Fischer, J., Garcia, D., McPhearson, T., Jimenez, D., King, B., Larcey, P., & Levy, K. (2021). Artificial intelligence, systemic risks, and sustainability. Technology in Society, 67, 101741. https://doi.org/10.1016/j.techsoc.2021.101741
Goel, P., Jain, P., Pasman, H. J., Pistikopoulos, E., & Datta, A. (2020). Integration of data analytics with cloud services for safer process systems, application examples and implementation challenges. Journal of Loss Prevention in the Process Industries, 68, 104316. https://doi.org/10.1016/j.jlp.2020.104316
Hajar, A.L., Ahmed, N., & Karim, C. (2023). Deployment of Safety Predictive Analytics to Prevent Workplace Incidents and Promote Event Reduction: A Machine Learning Approach Towards a Data-Driven Safety System. 2023 Third International Conference on Digital Data Processing (DDP), 175-179.
Huang, Y. (2021). Technology innovation and sustainability: challenges and research needs. Clean Techn Environ Policy, 23, 1663–1664. https://doi.org/10.1007/s10098-021-02152-6
Hulsegge, G., Van Der Torre, W., Verbiest, S., & Oeij, P. (2022). De impact van technologie op de taken, skills en kwaliteit van de arbeid. Tijdschrift Voor Arbeidsvraagstukken, 38(2), 169–191. https://doi.org/10.5117/tva2022.2.004.huls
Laha, S. R., Pattanayak, B. K., & Pattnaik, S. (2022). Advancement of environmental monitoring system using IoT and Sensor: A Comprehensive analysis. AIMS Environmental Science, 9(6), 771–800. https://doi.org/10.3934/environsci.2022044
Li, R.Y.M., & Poon, S.W. (2013). Supply of Safety Measures in Developing and Developed Countries: A Global Perspective. In: Construction Safety. Risk Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35046-7_3
Lowe, G. S. (2010). Creating healthy organizations: How vibrant workplaces inspire employees to achieve sustainable success. University of Toronto Press.
Masi, D., & Cagno, E. (2015). Barriers to OHS interventions in Small and Medium-sized Enterprises. Safety Science, 71, 226–241. https://doi.org/10.1016/j.ssci.2014.05.020
Muralidhar P; Sai Prashanth A; Pavan Kumar K; Rani C; Rajesh Kumar M (2023). Accident prevention for autonomous vehicle. In 2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) (pp. 1-5). https://doi.org/10.1109/ViTECoN58111.2023.10157414
Musarat, M., Khan, A., Alaloul, W., Blas, N., & Ayub, S. (2024). Automated monitoring innovations for efficient and safe construction practices. Results in Engineering. https://doi.org/10.1016/j.rineng.2024.102057.
Niu, Y., Fan, Y., & Ju, X. (2024). Critical review on data-driven approaches for learning from accidents: Comparative analysis and future research. Safety Science, 171, 106381. https://doi.org/10.1016/j.ssci.2023.106381
Nwankwo, O. K., Muku, J. S., Amosa, M. K., Ike, C. B., & Ogionwo, E. (2020). Assessment of safety case compliance in the Nigerian oil and gas industry. Paper presented at the SPE Nigeria Annual International Conference and Exhibition, Virtual. https://doi.org/10.2118/203604-MS
Ogunbare, B. A. (2020). Socio-economic importance of bus rapid transit: A panacea to sustainable transport development in Nigeria. International Journal of Research in Geography, 6(1), 29-41. http://dx.doi.org/10.20431/2454-8685.0601004
Patel, V., Chesmore, A., Legner, C. M., & Pandey, S. (2022). Trends in workplace wearable technologies and connected‐worker solutions for next‐generation occupational safety, health, and productivity. Advanced Intelligent Systems, 4(1), 2100099.
Popescu, S. M., Mansoor, S., Wani, O. A., Kumar, S. S., Sharma, V., Sharma, A., Arya, V. M., Kirkham, M. B., Hou, D., Bolan, N., & Chung, Y. S. (2024). Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management. Frontiers in Environmental Science, 12. https://doi.org/10.3389/fenvs.2024.1336088
Shah, I. A., & Mishra, S. (2024). Artificial Intelligence in advancing the Occupational Health and Safety: An encapsulation of developments. Journal of Occupational Health, 66(1). https://doi.org/10.1093/joccuh/uiad017
Shah, I. A., & Mishra, S. (2024). Artificial Intelligence in advancing the Occupational Health and Safety: An encapsulation of developments. Journal of Occupational Health, 66(1). https://doi.org/10.1093/joccuh/uiad017
Shalender, K., Singla, B., & Sharma, S. (2023). Emerging Technologies and Their Game-Changing Potential: Lessons from Corporate World. In Grima, S., Sood, K., & Özen, E. (Eds.), Contemporary Studies of Risks in Emerging Technology, Part A (pp. 61-70). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80455-562-020231005
Trost, A. (2020). Human resources strategies. Cham: Springer International Publishing.
Unnikrishnan, S., Iqbal, R., Singh, A., & Nimkar, I. M. (2015). Safety management practices in small and medium enterprises in India. Safety and Health at Work, 6(1), 46–55. https://doi.org/10.1016/j.shaw.2014.10.006
Waqdan, M., Louafi, H., & Mouhoub, M. (2023). An IoT Security Risk Assessment Framework for Healthcare Environment. 2023 International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar, 2023, pp. 01-08. https://doi.org/10.1109/ISNCC58260.2023.10324002
Welter, F., & Schröder, C. (2016). Digitalisierung ja – Industrie 4.0 bislang unter Vorbehalt. Zeitschrift für Wirtschaftspolitik, 65, 059 - 065. https://doi.org/10.1515/zfwp-2016-0004
Yang, J. R., Tan, F. H., & Tan, A. H. (2017). The ancient construction materials and methods: The Great Wall of China in Jinshanling as a case study. Journal of Construction Engineering and Project Management, 7, 37-49.
Yap, J. B. H., Skitmore, M., Lam, C. G. Y., Lee, W. P., & Lew, Y. L. (2024). Advanced technologies for enhanced construction safety management: Investigating Malaysian perspectives. International Journal of Construction Management, 24(6), 633-642.
Ye, Z., Yang, J., Zhong, N., Tu, X., Jia, J., & Wang, J. (2020). Tackling environmental challenges in pollution controls using artificial intelligence: A review. The Science of the Total Environment, 699, 134279. https://doi.org/10.1016/j.scitotenv.2019.134279
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