Flexible Working Arrangements and Social Sustainability: Study on Women Academics Post-COVID-19

One of the main challenges faced by companies, scholars, and governments nowadays is achieving economic, environmental, and social sustainability. Remote working, reduced work weeks, and other types of flexible working time arrangements (FWAs) are the new characteristics that will shape the future of work to ensure social sustainability. In changing work patterns, working styles are changed to possibly improve women employees' mental health and life–work balance. However, recently, very few firms have succeeded in adopting these new FWA trends. The purpose of this paper is to investigate women's preferences towards FWAs in the academic sector as a social sustainability source. We investigate the effect of the COVID-19 pandemic on female faculty members' future job preferences. The data used in the research are collected from a survey given to female faculty members who work in a Saudi women's university and have already experienced FWAs during the COVID-19 period. The study uses mixed methods of research, combining a choice modeling (CM) method, one sample t-test, a paired sample t-test, cluster analysis, and probit models. Our results show that flexible working arrangements improve the wellbeing of women employees, which ensures sustainable social development. The findings also show that flexibility in location plays a significant role in the decision made by female faculty members when revealing their flexibility preferences. However, flexibility in time did not play a significant role in the decisions made by respondents. This study adds to the empirical evidence in the current literature on female academic staff preferences for FWAs in Saudi Arabia, using choice modeling conjoint analysis and mixed approaches. © 2022 by the authors.

Optimizing the Practice Environment for Medical Staff in the Post-pandemic Era: A Discrete Choice Experiment.

Objective: This study aimed to elicit the stated job preferences of Chinese medical staff in the post-pandemic era and identify the relative importance of different factors in the practice environment. Methods: We used an online discrete choice experiment (DCE) survey instrument to elicit the job preferences of medical staff (doctors and nurses) in tertiary hospitals in Anhui, China. Attributes and levels were generated using qualitative methods, and four attributes were considered: career development, workload, respect from society, and monthly income. A set of profiles was created using a D-efficient design. The data were analyzed considering potential preference heterogeneity, using the conditional logit model and the latent class logit (LCL) model. Results: A total of 789 valid questionnaires were included in the analysis, with an effective response rate of 73.33%. Career development, workload, respect from society, and monthly income were significant factors that influenced job preferences. Three classes were identified based on the LCL model, and preference heterogeneity among different medical staff was demonstrated. Class 1 (16.17%) and Class 2 (43.51%) valued respect from society most, whereas Class 3 (40.32%) prioritized monthly income. We found that when respect from society was raised to a satisfactory level (50-75% positive reviews), the probability of medical staff choosing a certain job increased by 69.9%. Conclusion: Respect from society was the most preferred attribute, while workload, monthly income, and career development were all key factors in the medical staff's job choices. The heterogeneity of the medical professionals' preferences shows that effective policy interventions should be customized to accommodate these drive preferences.

Tackling brain drain at Chinese CDCs: understanding job preferences of public health doctoral students using a discrete choice experiment survey.

BACKGROUND: Given the demands for public health and infectious disease management skills during COVID-19, a shortage of the public health workforce, particularly with skills and competencies in epidemiology and biostatistics, has emerged at the Centers for Disease Controls (CDCs) in China. This study aims to investigate the employment preferences of doctoral students majoring in epidemiology and biostatistics, to inform policy-makers and future employers to address recruitment and retention requirements at CDCs across China. METHODS: A convenience sampling approach for recruitment, and an online discrete choice experiment (DCE) survey instrument to elicit future employee profiles, and self-report of their employment and aspirational preferences during October 20 and November 12, 2020. Attributes included monthly income, employment location, housing benefits, children's education opportunities, working environment, career promotion speed and bianzhi (formally established post). RESULTS: A total of 106 doctoral epidemiology and biostatistics students from 28 universities completed the online survey. Monthly income, employment location and bianzhi was of highest concern in the seven attributes measured, though all attributes were statistically significant and presented in the expected direction, demonstrating preference heterogeneity. Work environment was of least concern. For the subgroup analysis, employment located in a first-tier city was more likely to lead to a higher utility value for PhD students who were women, married, from an urban area and had a high annual family income. Unsurprisingly, when compared to single students, married students were willing to forgo more for good educational opportunities for their children. The simulation results suggest that, given our base case, increasing only monthly income from 10,000 ($ 1449.1) to 25,000 CNY ($ 3622.7) the probability of choosing the job in the third-tier city would increase from 18.1 to 53.8% (i.e., the location choice is changed). CONCLUSION: Monthly income and employment location were the preferred attributes across the cohort, with other attributes then clearly ranked and delineated. A wider use of DCEs could inform both recruitment and retention of a public health workforce, especially for CDCs in third-tier cities where resource constraints preclude all the strategies discussed here.