Factors Improving Childbearing Intention among Young Adults in the Context of Low Birth Rate in China: ISM Approach
DOI:
https://doi.org/10.17576/ebangi.2025.2201.24Keywords:
Interpretive Structural Modelling (ISM), childbearing intention, young adults, critical success factors, low birth rateAbstract
: In the context of China’s low fertility rate, critical success factors (CSFs) to enhance young adults’ childbearing intentions are considered an important means to achieve sustainable population development in China. The aim of this paper is to propose a methodology to identify critical success factors (CSFs) for enhancing young adult’s childbearing intentions in China. A total of 21 critical success factors (CSFs) were identified through a literature review and input from academic and industry practitioners. This paper adopts an Interpretative Structural Modeling (ISM) approach to establish the interrelationships among these factors, which not only helps to understand the relative relationships among the critical success factors, but also identifies their interdependencies in practical applications. In addition, the importance of the factors in enhancing childbearing intentions was identified through analysis based on their drivers and dependencies. It was found that improvement of fertility perception is the direct influential factor that motivates young adults to increase their childbearing intentions. This paper demonstrates the application of the proposed model in practice, using Chinese young adults as an example. The study can help academics, government regulators and practitioners to emphasize the implementation of measures to increase childbearing intentions.ReferencesAbendroth, A.-K. (2022). Transitions to parenthood, flexible working and time-based work-to-family conflicts: A gendered life course and organisational change perspective. JFR-Journal of Family Research, 34(4), 1033-1055. https://doi.org/10.20377/jfr-730Aguliera, E., & Nightengale-Lee, B. (2020). Emergency remote teaching across urban and rural contexts: perspectives on educational equity. Information Learning Sciences, 121(5/6), 471-478. https://doi.org/10.1108/ILS-04-2020-0100Bae, S. H., Pen, M., Sinn, C., Kol, S., An, B., Yang, S. J.,…Bae, S. (2022). Work hours and overtime of nurses working in Cambodian hospitals. International Nursing Review, 69(2), 150-158. https://doi.org/10.1111/inr.12720Beaujouan, E., & Berghammer, C. (2019). The gap between lifetime fertility intentions and completed fertility in Europe and the United States: A cohort approach. Population Research and Policy Review, 38(1), 507-535. https://doi.org/10.1007/s11113-019-09516-3Bhende, P., Mekoth, N., Ingalhalli, V., & Reddy, Y. (2020). Quality of work life and work–life balance. Journal of Human Values, 26(3), 256-265. https://doi.org/10.1177/0971685820939380Bi, M. (2024). Influencing factors and coping strategies of women's fertility intention under the guidance of China's development policy. Journal of Education, Humanities Social Sciences, 32, 29-34. https://doi.org/10.54097/8qeyne69Bose, B., Raub, A., Sprague, A., Martin, A., Bhuwania, P., Kidman, R., & Heymann, J. (2024). Do tuition-free lower secondary education policies matter for antenatal care among women in sub-saharan African countries? BMC Pregnancy Childbirth, 24(1), 250-261. https://doi.org/10.1186/s12884-024-06406-1Bueno, X. (2020). Fertility decisions in transition: young adults’ perceptions on fertility three decades apart in Spain. The History of the Family, 25(3), 386-405. https://doi.org/10.1080/1081602X.2019.1686049Chen, M., & Yip, P. S. (2017). The discrepancy between ideal and actual parity in Hong Kong: Fertility desire, intention, and behavior. Population Research Policy Review, 36(4), 583-605. https://doi.org/10.1007/s11113-017-9433-5Cheng, Y. h. A., & Hsu, C. H. (2020). No more babies without help for whom? Education, division of labor, and fertility intentions. Journal of Marriage Family, 82(4), 1270-1285. https://doi.org/10.1111/jomf.12672Delbaere, I., Verbiest, S., & Tydén, T. (2020). Knowledge about the impact of age on fertility: a brief review. Upsala Journal of Medical Sciences, 125(2), 167-174. https://doi.org/10.1080/03009734.2019.1707913Du, H., Hui, E. C.-m., & Chen, L. (2024). Do long commutes discourage fertility intentions among young public housing renters in Guangzhou, China? Housing Policy Debate, 34(4), 574-601. https://doi.org/10.1080/10511482.2024.2328142Fang, Y., & Chan, K. L. G. (2024). Review of literature on women employment discrimination in China. e-BANGI Journal, 21(3), 37-50. https://doi.org/10.17576/ebangi.2024.2103.04Feng, Y. (2024). The impact of maternity benefit policies on women’s willingness to have a second child in Shanghai. Studies in Social Science Humanities, 3(1), 38-58. https://doi.org/10.56397/SSSH.2024.01.05Finlay, J. E. (2021). Women’s reproductive health and economic activity: A narrative review. World Development, 139, 105313. https://doi.org/10.1016/j.worlddev.2020.105313Hart, R. K., & Galloway, T. A. (2023). Universal transfers, tax breaks and fertility: Evidence from a regional reform in Norway. Population Research Policy Review, 42(3), 49. https://doi.org/10.1007/s11113-023-09793-zHisham, B., & Akqmie, N. (2024). Hallyu stars mediated fandom: understanding mediatisation of non-k-pop consumption among Malaysian youth. e-BANGI Journal, 21(3), 613-624. https://doi.org/10.17576/ebangi.2024.2103.47Jing, W., Liu, J., Ma, Q., Zhang, S., Li, Y., & Liu, M. (2022). Fertility intentions to have a second or third child under China’s three-child policy: a national cross-sectional study. Human Reproduction, 37(8), 1907-1918. https://doi.org/10.1093/humrep/deac101Kim, Y., & Hong, S. (2021). Profiles of working moms’ daily time use: Exploring their impact on leisure. International Journal of Environmental Research Public Health, 18(5), 2305. https://doi.org/10.3390/ijerph18052305Kumar, R., & Goel, P. (2022). Exploring the domain of interpretive structural modelling (ISM) for sustainable future panorama: a bibliometric and content analysis. Archives of Computational Methods in Engineering, 29(5), 2781-2810. https://doi.org/10.1007/s11831-021-09675-7Lallement, R., Vergely, J.-L., Valette, B., Puspitarini, L., Eyer, L., & Casagrande, L. (2014). 3D maps of the local ISM from inversion of individual color excess measurements. Astronomy Astrophysics, 561, A91. https://doi.org/10.1051/0004-6361/201322032Lappegård, T., Kristensen, A. P., Dommermuth, L., Minello, A., & Vignoli, D. (2022). The impact of narratives of the future on fertility intentions in Norway. Journal of Marriage Family, 84(2), 476-493. https://doi.org/10.1111/jomf.12822Lardou, I., Chatzipapas, I., Chouzouris, M., Xenos, P., Petrogiannis, N., Tryfos, D.,…Michala, L. (2021). Fertility awareness and intentions among young adults in Greece. Upsala Journal of Medical Sciences, 126(4), e8148. https://doi.org/10.48101/ujms.v126.8148Liu, J., Xing, C., & Zhang, Q. (2020). House price, fertility rates and reproductive intentions. China Economic Review, 62(2), 101496. https://doi.org/10.1016/j.chieco.2020.101496Martins, M. V., Koert, E., Sylvest, R., Maeda, E., Moura-Ramos, M., Hammarberg, K., & Harper, J. (2024). Fertility education: recommendations for developing and implementing tools to improve fertility literacy. Human Reproduction, 39(2), 293-302. https://doi.org/0000-0001-6489-0290Mathiyazhagan, K., Govindan, K., NoorulHaq, A., & Geng, Y. (2013). An ISM approach for the barrier analysis in implementing green supply chain management. Journal of Cleaner Production, 47, 283-297. https://doi.org/10.1016/j.jclepro.2012.10.042Miller, R., Liu, K., & Ball, A. F. (2020). Critical counter-narrative as transformative methodology for educational equity. Review of Research in Education, 44(1), 269-300. https://doi.org/10.3102/0091732X20908501Otovescu, C., & Otovescu, A. (2019). The Depopulation of Romania–Is It an Irreversible Process? Revista De Cercetare Si Interventie Sociala, 65, 370-388. https://doi.org/10.33788/rcis.65.23Raute, A. (2019). Can financial incentives reduce the baby gap? Evidence from a reform in maternity leave benefits. Journal of Public Economics, 169(1), 203-222. https://doi.org/10.1016/j.jpubeco.2018.07.010Sarkar, P. K., Singh, P., Dhillon, M. S., Singh, A., & Bhattacharya, S. (2021). Impact of two intervention packages on the health and fitness of ante-and post-natal women attending in a teaching hospital. Journal of Family Medicine and Primary Care, 10(10), 3738-3747. https://doi.org/10.4103/jfmpc.jfmpc_427_21Singh, R., & Bhanot, N. (2020). An integrated DEMATEL-MMDE-ISM based approach for analysing the barriers of IoT implementation in the manufacturing industry. International Journal of Production Research, 58(8), 2454-2476. https://doi.org/10.1080/00207543.2019.1675915Thakkar, J., Deshmukh, S., Gupta, A., & Shankar, R. (2006). Development of a balanced scorecard: An integrated approach of interpretive structural modeling (ISM) and analytic network process (ANP). International Journal of Productivity Performance Management, 56(1), 25-59. https://doi.org/10.1108/17410400710717073Ullah, I., & Narain, R. (2021). Analyzing the barriers to implementation of mass customization in Indian SMEs using integrated ISM-MICMAC and SEM. Journal of Advances in Management Research, 18(2), 323-349. https://doi.org/10.1108/JAMR-04-2020-0048VenkatesaNarayanan, P. T., & Thirunavukkarasu, R. (2021). Indispensable link between green supply chain practices, performance and learning: An ISM approach. Journal of Cleaner Production, 279, 123387. https://doi.org/10.1016/j.jclepro.2020.123387Vinodh, S. (2021). Development of a structural model based on ISM for analysis of barriers to integration of leanwith industry 4.0. The TQM Journal, 33(6), 1201-1221. https://doi.org/10.1108/TQM-07-2020-0151Wagner Bernardes, J., & Marin, A. H. (2023). Individual and relational factors associated to the childbearing intentions of Brazilian women and men. Marriage Family Review, 59(6), 412-437. https://doi.org/10.1080/01494929.2023.2175101Wang, T., Wang, C., Zhou, Y., Zhou, W., & Luo, Y. (2019). Fertility intentions for a second child among urban working women with one child in Hunan Province, China: A cross-sectional study. Public Health, 173(1), 21-28. https://doi.org/10.1016/j.puhe.2019.05.006Wesolowski, K. J. J. o. F. I. (2020). It’s all about the money? Family policies, individual gender-role attitudes, and childbearing intentions in an international perspective. Journal of Family Issues, 41(11), 2065-2089. https://doi.org/10.1177/0192513X19896047Yadav, S., Luthra, S., & Garg, D. (2022). Internet of things (IoT) based coordination system in Agri-food supply chain: development of an efficient framework using DEMATEL-ISM. Operations management research, 15(1), 1-27. https://doi.org/10.1007/s12063-020-00164-xYearBook, C. S. (2016-2022). National Bureau of Statistics of China. China Statistical Publishing House. Retrieved 27-06 from https://scholar.google.com.hk/scholar?q=related:XhbzFDx197AJ:scholar.google.com/&scioq=&hl=zh-CN&as_sdt=0,5Yu, V. F., Bahauddin, A., Ferdinant, P. F., Fatmawati, A., & Lin, S.-W. (2023). The ISM method to analyze the relationship between blockchain adoption criteria in university: An Indonesian case. Mathematics, 11(1), 1-17. https://doi.org/10.3390/math11010239Zhang, C., Wei, L., Zhu, Y., Teng, L., Zhang, W., Xu, J.,…Wong, L. P. (2022). Fertility intentions among young people in the era of China’s three–child policy: a national survey of university students. BMC Pregnancy Childbirth, 22(1), 637-649. https://doi.org/10.1186/s12884-022-04873-yZhang, Y. (2023). Time spent on private tutoring and sleep patterns of Chinese adolescents: Evidence from a national panel survey. Children, 10(7), 1231-1241. https://doi.org/10.3390/children10071231Zhu, C., Yan, L., Wang, Y., Ji, S., Zhang, Y., & Zhang, J. (2022). Fertility intention and related factors for having a second or third child among childbearing couples in shanghai, China. Frontiers in Public Health, 10(1), 879672. https://doi.org/10.3389/fpubh.2022.879672Downloads
Additional Files
Published
2025-02-28
Issue
Section
Article