Hostname: page-component-848d4c4894-5nwft Total loading time: 0 Render date: 2024-05-21T19:10:31.664Z Has data issue: false hasContentIssue false

Linking enterprise information systems success to female employees’ work–family enrichment in China

Published online by Cambridge University Press:  21 February 2024

Wenhao Deng
Affiliation:
School of Management and Economics, Beijing Institute of Technology, Beijing, China Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, China Yangtze River Delta Research Institute, Beijing Institute of Technology, Jiaxing, China
Tianan Yang
Affiliation:
School of Management and Economics, Beijing Institute of Technology, Beijing, China Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, China Yangtze River Delta Research Institute, Beijing Institute of Technology, Jiaxing, China
Xuemei Ju
Affiliation:
School of Management and Economics, Beijing Institute of Technology, Beijing, China Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, China
Jianwei Deng*
Affiliation:
School of Management and Economics, Beijing Institute of Technology, Beijing, China Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, China Yangtze River Delta Research Institute, Beijing Institute of Technology, Jiaxing, China
*
Corresponding author: Jianwei Deng; Email: dengjianwei2006@163.com

Abstract

The spread and application of enterprise information systems (EISs) has provided scholars and managers with a new perspective to enhance the work–family enrichment. Based on the work–family enrichment theory, this research aims to examine the ability of female employees to enhance their work–family enrichment by applying the resources accumulated through the use of EISs by combining the technology acceptance model with the DeLone & McLean Information Systems Success Model. The findings based on a survey of 823 full-time female employees in China indicated that the information systems quality factors (including information quality, system quality, and service quality) were positively associated with female employees’ work–family enrichment. In addition, the chained mediating effect of perceived ease of use and perceived usefulness was examined. The results can help female employees to perform positively in both work and family spheres and provide positive support for the promotion of the social fertility policies.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press in association with Australian and New Zealand Academy of Management.

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abab, S. A., Wakjira, F. S., & Negash, T. T. (2021). Determinants of the land registration information system operational success: Empirical evidence from Ethiopia. Land, 10(12), .CrossRefGoogle Scholar
Ahn, T., Ruy, S., & Han, I. (2004). The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405420.CrossRefGoogle Scholar
Ahn, T., Ryu, S., & Han, I. (2007). The impact of web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263275.CrossRefGoogle Scholar
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843858.CrossRefGoogle Scholar
Anderson, S. E., Coffey, B. S., & Byerly, R. T. (2002). Formal organizational initiatives and informal workplace practices: Links to work–family conflict and job-related outcomes. Journal of Management, 28, 787810.Google Scholar
Anderson, J. C., & Gerbing, W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 27(1), 524.Google Scholar
Aryee, S., Srinivas, E. S., & Tan, H. H. (2005). Rhythms of life: Antecedents and outcomes of work-family balance in employed parents. Journal of Applied Psychology, 90(1), 132146.CrossRefGoogle ScholarPubMed
Ashforth, B. E., & Fugate, K. M. (2000). All in a day’s work: Boundaries and micro role transitions. Academy of Management Review, 25(3), 472491.CrossRefGoogle Scholar
Asmussen, C. B., & Moller, C. (2020). Enabling supply chain analytics for enterprise information systems: A topic modelling literature review and future research agenda. Enterprise Information Systems, 14(5), 563610.CrossRefGoogle Scholar
Bardoel, E. A., & Drago, R. (2016). Does the quality of information technology support affect work–life balance? A study of Australian physicians. International Journal of Human Resource Management, 27(21), 26042620.CrossRefGoogle Scholar
Bostrom, R. P., & Heinen, J. S. (1977). MIS problems and failures: A socio-technical perspective. MIS Quarterly, 1(3), 1732.CrossRefGoogle Scholar
Brandon-Jones, A., & Kauppi, K. (2018). Examining the antecedents of the technology acceptance model within e-procurement. International Journal of Operations and Production Management, 38(1), 2242.CrossRefGoogle Scholar
Butts, M. M., Casper, W. J., & Yang, T. S. (2013). How important are work-family support policies? A meta-analytic investigation of their effects on employee outcomes. Journal of Applied Psychology, 98(1), 125.CrossRefGoogle ScholarPubMed
Carlson, D. S., Ferguson, M., Kacmar, K. M., Grzywacz, J. G., & Whitten, D. (2011). Pay it forward: The positive crossover effects of supervisor work-family enrichment. Journal of Management, 37(3), 770789.CrossRefGoogle Scholar
Carlson, D. S., Grzywacz, J. G., & Kacmar, K. M. (2010). The relationship of schedule flexibility and outcomes via the work-family interface. Journal of Managerial Psychology, 25(3-4), 330355.CrossRefGoogle Scholar
Carlson, D. S., Kacmar, K. M., & Williams, L. J. (2000). Construction and initial validation of a multidimensional measure of work–family conflict. Journal of Vocational Behavior, 56(2), 249276.CrossRefGoogle Scholar
Casper, W. J., Harris, C., Taylor-Bianco, A., & Wayne, J. H. (2011). Work–family conflict, perceived supervisor support and organizational commitment among Brazilian professionals. Journal of Vocational Behavior, 79(3), 640652.CrossRefGoogle Scholar
Chen, H. J. (2010). Linking employees’ e-learning system use to their overall job outcomes: An empirical study based on the IS success model. Computers and Education, 55(4), 16281639.CrossRefGoogle Scholar
Cheng, Y. M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research, 22(3), 361390.CrossRefGoogle Scholar
Chen, R. F., & Hsiao, J. L. (2012). An empirical study of physicians’ acceptance of hospital information systems in Taiwan. Telemedicine and e-Health, 18(2), 120125.CrossRefGoogle ScholarPubMed
Chiou, Y. W., & Fang, G. D. (2005). A study of web portal user behavior. Web Journal of Chinese Management Review, 8(1), 4360.Google Scholar
Chung, B., Skibniewski, M. J., & Kwak, Y. H. (2009). Developing ERP systems success model for the construction industry. Journal of Construction Engineering and Management, 135(3), 207216.CrossRefGoogle Scholar
Cooklin, A. R., Westrupp, E. M., Strazdins, L., Giallo, R., Martin, A., & Nicholson, J. M. (2014). Fathers at work: Work–family conflict, work–family enrichment and parenting in an Australian cohort. Journal of Family Issues, 37(11), 125.Google Scholar
Daniel, S., & Sonnentag, S. (2016). Crossing the borders: The relationship between boundary management, work-family enrichment and job satisfaction. International Journal of Human Resource Management, 27(4), 407426.CrossRefGoogle Scholar
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.Google Scholar
Dehgani, R., & Navimipour, N. J. (2019). The impact of information technology and communication systems on the agility of supply chain management systems. Kybernetes, 48(10), 22172236.CrossRefGoogle Scholar
Delone, W. H., & Mclean, E. R. (2003). The Delone and Mclean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 930.Google Scholar
Ebnehoseini, Z., Tabesh, H., Deghatipour, A., & Tara, M. (2022). Development an extended-information success system model (ISSM) based on nurses’ point of view for hospital EHRs: A combined framework and questionnaire. BMC Medical Informatics and Decision Making, 22(1), 117.CrossRefGoogle ScholarPubMed
Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12(1), 122.CrossRefGoogle ScholarPubMed
European Foundation for the Improvement of Living and Working Conditions. (2007). Fifteen years of working conditions in the EU: Charting the trends. Retrieved from www.eurofound.europa.eu/ewcoGoogle Scholar
Fisher, G. G., Bulger, C. A., & Smith, C. S. (2009). Beyond work and family: A measure of work/nonwork interference and enhancement. Journal of Occupational Health Psychology, 14(4), 441456.CrossRefGoogle Scholar
Fried, Y., & Ferris, G. R. (1987). The validity of the job characteristics model: A review and meta-analysis. Personnel Psychology, 40(2), 287322.CrossRefGoogle Scholar
Goel, L., Zhang, J. Z., & Williamson, S. (2023). Work-to-home cybersecurity spillover: Construct development and validation. Information Systems Management, 40(3), 290300.CrossRefGoogle Scholar
Goodhue, D. L., Kirsch, L. J., Quillard, J. A., & Wybo, M. D. (1992). Strategic data planning: Lessons from the field. MIS Quarterly, 16(1), 1134.CrossRefGoogle Scholar
Greenhaus, J., & Powell, G. (2006). When work and family are allies: A theory of work-family enrichment. Academy of Management Review, 31(1), 7292.CrossRefGoogle Scholar
Grzywacz, J. G., & Marks, N. F. (2000). Reconceptualizing the work–family interface: An ecological perspective on the correlates of positive and negative spillover between work and family. Journal of Occupational Health Psychology, 5, 111126.CrossRefGoogle ScholarPubMed
Hair, J. F. (2022). Reflections on SEM: An introspective, idiosyncratic journey to composite-based structural equation modeling. SIGMIS Database 52, SI (December 2021), 101113.Google Scholar
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) using R. Cham: Sage publications.CrossRefGoogle Scholar
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139151.CrossRefGoogle Scholar
Halpern, D. F. (2006). How organizations can alleviate the traffic jam at the intersection of work and family. American Behavioral Scientist, 49(9), 11471151.CrossRefGoogle Scholar
Ho, K. F., Ho, C. H., & Chung, M. H. (2019). Theoretical integration of user satisfaction and technology acceptance of the nursing process information system. PLoS One, 14(6), .CrossRefGoogle ScholarPubMed
Hung, S. Y., Liang, T. P., & Chang, C. M. (2005). A meta-analysis of empirical research using TAM. Journal of Information Management, 12(4), 211234.Google Scholar
Jiang, N., Tian, E. L., Malayeri, F. D., & Balali, A. (2020). A new model for investigating the impact of urban knowledge, urban intelligent transportation systems and IT infrastructures on the success of SCM systems in the distributed organizations. Kybernetes, 49(11), 27992818.CrossRefGoogle Scholar
Ji, M. T., Genchev, G. Z., Huang, H. Y., Xu, T., Lu, H., & Yu, G. J. (2021). Evaluation framework for successful artificial intelligence-enabled clinical decision support systems: Mixed methods study. Journal of Medical Internet Research, 23(6), .CrossRefGoogle ScholarPubMed
Kibelloh, M., & Bao, Y. K. (2014). Perceptions of international female students toward e-learning in resolving high education and family role strain. Journal of Educational Computing Research, 50(4), 467487.CrossRefGoogle Scholar
Kim, T. G., Lee, J. H., & Law, R. (2008). An empirical examination of the acceptance behaviour of hotel front office systems: An extended technology acceptance model. Tourism Management, 29(3), 500513.CrossRefGoogle Scholar
Kozanoglu, D. C., & Abedin, B. (2020). Understanding the role of employees in digital transformation: Conceptualization of digital literacy of employees as a multi-dimensional organizational affordance. Journal of Enterprise Information Management, 34(6), 16491672.CrossRefGoogle Scholar
Kuo, C. S., Kang, Y. W., & Yang, H. L. (2023). Investigating the determinants of continuance intention on cloud ERP systems adoption. Advances in Mechanical Engineering, 15(4), .CrossRefGoogle Scholar
Laumer, S., Maier, C., & Weitzel, T. (2017). Information quality, user satisfaction, and the manifestation of workarounds: A qualitative and quantitative study of enterprise content management system users. European Journal of Information Systems, 26(4), 333360.CrossRefGoogle Scholar
Lee, S. H., Fogliasso, C. E., Jung, S. H. Y., Shin, M. M., & Shum, C. (2023). User psychological states and enterprise information systems adoption: Evidence from the United States, Zimbabwe, South Korea, and Paraguay. Service Business, 17(2), 477497.CrossRefGoogle Scholar
Lee, S., & Kim, B. G. (2017). The impact of qualities of social network service on the continuance usage intention. Management Decision, 55(4), 701729.CrossRefGoogle Scholar
Leidner, D. E., & Kayworth, T. (2006). Review: A review of culture in information systems research: Toward a theory of information technology culture conflict. MIS Quarterly, 30(2), 357399.CrossRefGoogle Scholar
Lemmer, K., Jahn, K., Chen, A. D. L., & Niehaves, B. (2023). One tool to rule? – A field experimental longitudinal study on the costs and benefits of mobile device usage in public agencies. Government Information Quarterly, 40(3), .CrossRefGoogle Scholar
Le, H., Newman, A., Menzies, J., Zheng, C., & Fermelis, J. (2020). Work–life balance in Asia: A systematic review. Human Resource Management Review, 30(4), .CrossRefGoogle Scholar
Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioural intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers and Education, 51(2), 864873.CrossRefGoogle Scholar
Lin, C. S., & Wu, S. (2002). Exploring the impact of online service quality on portal site usage. Proceedings of the 35th Hawaii International Conference on System Sciences, 7(206), 26542661.CrossRefGoogle Scholar
Liu, C., & Arnett, K. P. (2000). Exploring the factors associated with web site success in the context of electronic commerce. Information & Management, 38(1), 2333.CrossRefGoogle Scholar
Li, Y. X., & Wang, J. H. (2021). Evaluating the impact of information system quality on continuance intention toward cloud financial information system. Frontiers in Psychology, 12, .Google ScholarPubMed
Matthews, R. A., & Barnes-Farrell, J. L. (2010). Development and initial evaluation of an enhanced measure of boundary flexibility for the work and family domains. Journal of Occupational Health Psychology, 15(3), 330346.CrossRefGoogle ScholarPubMed
Mcnall, L. A., Masuda, A. D., & Nicklin, J. M. (2009). Flexible work arrangements, job satisfaction, and turnover intentions: The mediating role of work-to-family enrichment. Journal of Psychology, 144(1), 6181.CrossRefGoogle Scholar
Mishra, A., Shukla, A., Rana, N. P., Currie, W. L., & Dwivedi, Y. K. (2023). Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach. International Journal of Information Management, 68, .CrossRefGoogle Scholar
Nelson, R. R., Todd, P. A., & Wixom, B. (2005). Antecedents of information and system quality: An empirical examination within the context of data warehousing. Journal of Management Information Systems, 21(4), 199235.CrossRefGoogle Scholar
Ngai, E. W., Poon, J. K. L., & Chan, Y. H. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48(2), 250267.CrossRefGoogle Scholar
Nicklin, J. M., & Mcnall, L. A. (2013). Work–family enrichment, support, and satisfaction: A test of mediation. European Journal of Work & Organizational Psychology, 22(1), 6777.CrossRefGoogle Scholar
Oktal, O., Alpu, O., & Yazici, B. (2016). Measurement of internal user satisfaction and acceptance of the e-justice system in Turkey. Aslib Journal of Information Management, 68(6), 716735.CrossRefGoogle Scholar
Pai, F. Y., & Huang, P. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650660.CrossRefGoogle Scholar
Pan, K., Nunes, M. B., & Peng, G. C. (2011). Risks affecting ERP post-implementation: Insights from a large Chinese manufacturing group. Journal of Manufacturing Technology Management, 22(1), 107130.CrossRefGoogle Scholar
Park, N., Rhoads, M., Hou, J., & Lee, K. M. (2014). Understanding the acceptance of teleconferencing systems among employees: An extension of the technology acceptance model. Computers in Human Behavior, 39, 118127.CrossRefGoogle Scholar
Petter, S., DeLone, W., & McLean, E. R. (2013). Information systems success: The quest for the independent variables. Journal of Management Information Systems, 29(4), 761.CrossRefGoogle Scholar
Podsakoff, P. M., Mackenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879903.CrossRefGoogle ScholarPubMed
Poelmans, S., Reijers, H. A., & Recker, J. (2013). Investigating the success of operational business process management systems. Information Technology & Management, 14(4), 295314.CrossRefGoogle Scholar
Powell, G. N., Francesco, A. M., & Ling, Y. (2009). Toward culture-sensitive theories of the work–family interface. Journal of Organizational Behavior, 30(5), 597616.CrossRefGoogle Scholar
Rahman, M. S., Hossain, M. A., Chowdhury, A. H., & Hoque, M. T. (2022). Role of enterprise information system management in enhancing firms competitive performance towards achieving SDGs during and after COVID-19 pandemic. Journal of Enterprise Information Management, 35(1), 214236.CrossRefGoogle Scholar
Russo, M., & Buonocore, F. (2012). The relationship between work–family enrichment and nurse turnover. Journal of Managerial Psychology, 27, 216236.CrossRefGoogle Scholar
Sabherwal, R., Jeyaraj, A., & Chowa, C. (2006). Information system success: Individual and organizational determinants. Management Science, 52(12), 18491864.CrossRefGoogle Scholar
Sarstedt, M., Hair, J. F., & Ringle, C. M. (2023). “PLS-SEM: Indeed a silver bullet” – Retrospective observations and recent advances. Journal of Marketing Theory and Practice, 31(3), 261275.CrossRefGoogle Scholar
Seddon, P. B. (1997). A re-specification and extension of the Delone and Mclean model of is success. Information Systems Research, 8(3), 240253.CrossRefGoogle Scholar
Seddon, P. B., & Kiew, M. (1996). A partial test and development of DeLone and McLean’s model of IS success. Australasian Journal of Information Systems, 4(1), 90109.CrossRefGoogle Scholar
Shen, Y., & Jiang, L. (2020). Labor market outcomes of professional women with two children after the one-child policy in China. Journal of Social Issues, 76(3), 632658.CrossRefGoogle Scholar
Shih, H. P. (2003). Extended technology acceptance model of internet utilization behavior. Information & Management, 41(6), 719729.CrossRefGoogle Scholar
Shockley, K. M., & Singla, N. (2011). Reconsidering work-family interactions and satisfaction: A meta-analysis. Journal of Management, 37(3), 861886.CrossRefGoogle Scholar
Sousa, R., & Voss, C. A. (2006). Service quality in multichannel services employing virtual channels. Journal of Service Research, 8(4), 356371.CrossRefGoogle Scholar
Spector, P. E., Allen, T. D., Poelmans, S. A. Y., Lapierre, L. M., Cooper, C. L., O’Driscoll, M., Sanchez, J. I., Abarca, N., Alexandrova, M., Beham, B., & Brough, P. (2007). Cross-national differences in relationships of work demands, job satisfaction and turnover intentions with work–family conflict. Personnel Psychology, 60(4), 805835.CrossRefGoogle Scholar
Sulaiman, T. T., Mahomed, A. S. B., Rahman, A. A., & Hassan, M. (2023). Understanding antecedents of learning management system usage among university lecturers using an integrated TAM-TOE model. Sustainability, 15(3), .CrossRefGoogle Scholar
Taheri, F., Asarian, M., & Shahhosseini, P. (2020). Workaholism and workplace incivility: The role of work–family enrichment. Management Decision, 59(2), 372389.CrossRefGoogle Scholar
Teo, T. S., & Wong, P. K. (1998). An empirical study of the performance impact of computerization in the retail industry. Omega, 26(5), 611621.CrossRefGoogle Scholar
Tian, F., & Xu, S. X. (2015). How do enterprise resource planning systems affect firm risk? Post-implementation impact. MIS Quarterly, 39(1), 3960.CrossRefGoogle Scholar
Turetken, O., Ondracek, J., & IJsselsteijn, W. (2019). Influential characteristics of enterprise information system user interfaces. Journal of Computer Information Systems, 59(3), 243255.CrossRefGoogle Scholar
Wang, P., & Walumbwa, F. O. (2007). Family-friendly programs, organizational commitment, and work withdrawal: The moderating role of transformational leadership. Personnel Psychology, 60(2), 397427.CrossRefGoogle Scholar
Wang, W. T., & Wang, C. C. (2009). An empirical study of instructor adoption of web-based learning systems. Computers & Education, 53(3), 761774.CrossRefGoogle Scholar
Wang, P., Wang, S. H., Yao, X., Hsu, I. C., & Lawler, J. (2019). Idiosyncratic deals and work‐to‐family conflict and enrichment: The mediating roles of fit perceptions and efficacy beliefs. Human Resource Management Journal, 29(4), 600619.CrossRefGoogle Scholar
Wang, Y. M., Wei, C. L., Chen, W. J., & Wang, Y. S. (2023). Revisiting the e-learning systems success model in the post-COVID-19 age: The role of monitoring quality. International Journal of Human-computer Interaction, 1, 116.Google Scholar
Wayne, J. H., Musisca, N., & Fleeson, W. (2004). Considering the role of personality in the work–family experience: Relationships of the big five to work–family conflict and facilitation. Journal of Vocational Behavior, 64(1), 108130.CrossRefGoogle Scholar
Wayne, J. H., Randel, A. E., & Stevens, J. (2006). The role of identity and work–family support in work–family enrichment and its work-related consequences. Journal of Vocational Behavior, 69(3), 445461.CrossRefGoogle Scholar
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85102.CrossRefGoogle Scholar
Wu, C., Hunter, E. M., & Sublett, L. W. (2021). Gaining affective resources for work-family enrichment: A multisource experience sampling study of micro-role transitions. Journal of Vocational Behavior, 125, .CrossRefGoogle Scholar
Wu, C. Y., Kuo, C. C., Lin, C.‐W., Hu, W. H., Wu, C. Y., & Cheng, S. (2020). How does benevolent leadership lead to work–family enrichment? The mediating role of positive group affective tone. Stress and Health, 36(4), 496506.CrossRefGoogle ScholarPubMed
Yoo, S., Lim, K., Jung, S. Y., Lee, K., Lee, D., Kim, S., … Hwang, H. (2022). Examining the adoption and implementation of behavioral electronic health records by healthcare professionals based on the clinical adoption framework. BMC Medical Informatics and Decision Making, 22(1), 19.CrossRefGoogle ScholarPubMed
Yuan, Y. H., Tsai, S. B., Dai, C. Y., Chen, H.-M., Chen, W.-F., Wu, C.-H., & Deng, Y. (2017). An empirical research on relationships between subjective judgement, technology acceptance tendency and knowledge transfer. PLoS One, 12(9), .CrossRefGoogle ScholarPubMed
Yu-Hsi, Y., Sang-Bing, T., Chien-Yun, D., Hsiao-Ming, C., Wan-Fei, C., & Chia-Huei, W. (2017). An empirical research on relationships between subjective judgement, technology acceptance tendency and knowledge transfer. PLoS One, 12(9), .Google Scholar
Zhu, Y., Li, Y., Wang, W., & Chen, J. (2010). What leads to post-implementation success of ERP? An empirical study of the Chinese retail industry. International Journal of Information Management, 30(3), 265276.CrossRefGoogle Scholar