Combined effect of climate change and labor relation on optimally managing labor productivity under uncertainty
Vol 8, Issue 9, 2024
VIEWS - 110 (Abstract) 155 (PDF)
Abstract
Heat stress amplified by climate change causes excessive reductions in labor capacity, work injuries, and socio-economic losses. Yet studies of corresponding impact assessments and adaptation developments are insufficient and incapable of effectively dealing with uncertain information. This gap is caused by the inability to resolve complex channels involving climate change, labor relations, and labor productivity. In this paper, an optimization-based productivity restoration modeling framework is developed to bridge the gap and support decision-makers in making informed adaptation plans. The framework integrates a multiple-climate-model ensemble, an empirical relationship between heat stress and labor capacity, and an inexact system costs model to investigate underlying uncertainties associated with climate and management systems. Optimal and reliable decision alternatives can be obtained by communicating uncertain information into the optimization processes and resolving multiple channels. Results show that the increased heat stress will lead to a potential reduction in labor productivity in China. By solving the objective function of the framework, total system costs to restore the reduction are estimated to be up to 248,700 million dollars under a Representative Concentration Pathway of 2.6 (RCP2.6) and 697,073 million dollars under RCP8.5 for standard employment, while less costs found for non-standard employment. However, non-standard employment tends to restore productivity reduction with the minimum system cost by implementing active measures rather than passive measures due to the low labor costs resulting from ambiguities among employment statuses. The situation could result in more heat-related work injuries because employers in non-standard employment can avoid the obligation of providing a safe working environment. Urgent actions are needed to uphold labor productivity with climate change, especially to ensure that employers from non-standard employment fulfill their statutory obligations.
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Bastian, N. D., Lunday, B. J., Fisher, C. B., et al. (2020). Models and methods for workforce planning under uncertainty: Optimizing U.S. Army cyber branch readiness and manning. Omega, 92, 102171. https://doi.org/10.1016/j.omega.2019.102171
Borba, B. S. M. C., Fortes, M. Z., Bitencourt, L. A., et al. (2019). A review on optimization methods for workforce planning in electrical distribution utilities. Computers & Industrial Engineering, 135, 286–298. https://doi.org/10.1016/j.cie.2019.06.002
Borg, M. A., Xiang, J., Anikeeva, O., et al. (2021). Occupational heat stress and economic burden: A review of global evidence. Environmental Research, 195, 110781. https://doi.org/10.1016/j.envres.2021.110781
Chen, Y., Guo, F., Wang, J. et al. (2020). Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100. Scientific Data, 7, 83. https://doi.org/10.1038/s41597-020-0421-y
Chen, C. H., Yan, S., & Chen, M. (2010). Short-term manpower planning for MRT carriage maintenance under mixed deterministic and stochastic demands. Annals of Operations Research, 181(1), 67–88. https://doi.org/10.1007/s10479-010-0689-y
China National Bureau of Statistics. (2021). China Statistics Yearbook. China Statistics Press.
Day, E., Fankhauser, S., Kingsmill, N., et al. (2018). Upholding labour productivity under climate change: an assessment of adaptation options. Climate Policy, 19(3), 367–385. https://doi.org/10.1080/14693062.2018.1517640
De Feyter, T., Guerry, M. A., & Komarudin. (2016). Optimizing cost-effectiveness in a stochastic Markov manpower planning system under control by recruitment. Annals of Operations Research, 253(1), 117–131. https://doi.org/10.1007/s10479-016-2311-4
Di Francesco, M., Díaz-Maroto Llorente, N., Zanda, S., et al. (2016). An optimization model for the short-term manpower planning problem in transhipment container terminals. Computers & Industrial Engineering, 97, 183–190. https://doi.org/10.1016/j.cie.2016.04.012
Dimitriou, V. A., & Georgiou, A. C. (2019). Introduction, analysis and asymptotic behavior of a multi-level manpower planning model in a continuous time setting under potential department contraction. Communications in Statistics—Theory and Methods, 50(5), 1173–1199. https://doi.org/10.1080/03610926.2019.1648827
Fischereit, J., & Schlünzen, K. H. (2018). Evaluation of thermal indices for their applicability in obstacle-resolving meteorology models. International Journal of Biometeorology, 62(10), 1887–1900. https://doi.org/10.1007/s00484-018-1591-6
Foley, M. (2017). Factors underlying observed injury rate differences between temporary workers and permanent peers. American Journal of Industrial Medicine, 60(10), 841–851. https://doi.org/10.1002/ajim.22763
Gao, C., Kuklane, K., Östergren, P. O., et al. (2017). Occupational heat stress assessment and protective strategies in the context of climate change. International Journal of Biometeorology, 62(3), 359–371. https://doi.org/10.1007/s00484-017-1352-y
Hatvani-Kovacs, G., Belusko, M., Skinner, N., et al. (2016). Drivers and barriers to heat stress resilience. Science of The Total Environment, 571, 603–614. https://doi.org/10.1016/j.scitotenv.2016.07.028
Kjellstrom, T., Freyberg, C., Lemke, B., et al. (2017). Estimating population heat exposure and impacts on working people in conjunction with climate change. International Journal of Biometeorology, 62(3), 291–306. https://doi.org/10.1007/s00484-017-1407-0
Lan, T., Goh, Y. M., Jensen, O., et al. (2022). The impact of climate change on workplace safety and health hazard in facilities management: An in-depth review. Safety Science, 151, 105745. https://doi.org/10.1016/j.ssci.2022.105745
Liu, X., Tang, Q., Zhang, X., et al. (2018). Projected Changes in Extreme High Temperature and Heat Stress in China. Journal of Meteorological Research, 32(3), 351–366. https://doi.org/10.1007/s13351-018-7120-z
Lohrey, S., Chua, M., Gros, C., et al. (2021). Perceptions of heat-health impacts and the effects of knowledge and preventive actions by outdoor workers in Hanoi, Vietnam. Science of The Total Environment, 794, 148260. https://doi.org/10.1016/j.scitotenv.2021.148260
Ma, R., Zhong, S., Morabito, M., et al. (2019). Estimation of work-related injury and economic burden attributable to heat stress in Guangzhou, China. Science of The Total Environment, 666, 147–154. https://doi.org/10.1016/j.scitotenv.2019.02.201
Matsumoto, K. (2019). Climate change impacts on socioeconomic activities through labor productivity changes considering interactions between socioeconomic and climate systems. Journal of Cleaner Production, 216, 528–541. https://doi.org/10.1016/j.jclepro.2018.12.127
Nunfam, V. F., Adusei-Asante, K., Van Etten, E. J., et al. (2018). Social impacts of occupational heat stress and adaptation strategies of workers: A narrative synthesis of the literature. Science of The Total Environment, 643, 1542–1552. https://doi.org/10.1016/j.scitotenv.2018.06.255
Nunfam, V. F., Oosthuizen, J., Adusei-Asante, K., et al. (2019). Perceptions of climate change and occupational heat stress risks and adaptation strategies of mining workers in Ghana. Science of The Total Environment, 657, 365–378. https://doi.org/10.1016/j.scitotenv.2018.11.480
Pogačar, T., Casanueva, A., Kozjek, K., et al. (2018). The effect of hot days on occupational heat stress in the manufacturing industry: implications for workers’ well-being and productivity. International Journal of Biometeorology, 62(7), 1251–1264. https://doi.org/10.1007/s00484-018-1530-6
Schwatka, N. V., Atherly, A., Dally, M. J., et al. (2016). Health risk factors as predictors of workers’ compensation claim occurrence and cost. Occupational and Environmental Medicine, 74(1), 14–23. https://doi.org/10.1136/oemed-2015-103334
Shakerian, S., Habibnezhad, M., Ojha, A., et al. (2021). Assessing occupational risk of heat stress at construction: A worker-centric wearable sensor-based approach. Safety Science, 142, 105395. https://doi.org/10.1016/j.ssci.2021.105395
Wang, S., & Zhu, J. (2019). Amplified or exaggerated changes in perceived temperature extremes under global warming. Climate Dynamics, 54(1–2), 117–127. https://doi.org/10.1007/s00382-019-04994-9
Xiang, J., Hansen, A., Pisaniello, D., et al. (2018). Correlates of Occupational Heat-Induced Illness Costs. Journal of Occupational & Environmental Medicine, 60(9), e463–e469. https://doi.org/10.1097/jom.0000000000001395
Yan, M., Xie, Y., Zhu, H., et al. (2022). The exceptional heatwaves of 2017 and all-cause mortality: An assessment of nationwide health and economic impacts in China. Science of The Total Environment, 812, 152371. https://doi.org/10.1016/j.scitotenv.2021.152371
Yu, I. T., Yu, W., Li, Z., et al. (2017). Effectiveness of participatory training in preventing accidental occupational injuries: a randomized-controlled trial in China. Scandinavian Journal of Work, Environment & Health, 43(3), 226–233. https://doi.org/10.5271/sjweh.3617
Zhang, P., Deschenes, O., Meng, K., et al. (2018). Temperature effects on productivity and factor reallocation: Evidence from a half million Chinese manufacturing plants. Journal of Environmental Economics and Management, 88, 1–17. https://doi.org/10.1016/j.jeem.2017.11.001
Zhao, Y., Sultan, B., Vautard, R., et al. (2016). Potential escalation of heat-related working costs with climate and socioeconomic changes in China. Proceedings of the National Academy of Sciences, 113(17), 4640–4645. https://doi.org/10.1073/pnas.1521828113
Zhu, J., Wang, S., & Fischer, E. M. (2021). Increased occurrence of day-night hot extremes in a warming climate. Climate Dynamics, 59(5–6), 1297–1307. https://doi.org/10.1007/s00382-021-06038-7
Zhu, J., Wang, S., & Huang, G. (2019). Assessing Climate Change Impacts on Human‐Perceived Temperature Extremes and Underlying Uncertainties. Journal of Geophysical Research: Atmospheres, 124(7), 3800–3821. https://doi.org/10.1029/2018jd029444
Zhu, J., Wang, S., Wang, D., et al. (2021). Upholding labor productivity with intensified heat stress: Robust planning for adaptation to climate change under uncertainty. Journal of Cleaner Production, 322, 129083. https://doi.org/10.1016/j.jclepro.2021.129083
Zhu, J., Wang, S., Zhang, B., et al. (2021). Adapting to Changing Labor Productivity as a Result of Intensified Heat Stress in a Changing Climate. GeoHealth, 5(4). https://doi.org/10.1029/2020gh000313
DOI: https://doi.org/10.24294/jipd.v8i9.5080
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