In 2018, we carried forward the research design of 2017 and continued to measure, evaluate and analyze the overall organizational working conditions from four aspects: work time, workplace, work reward and employee participation. The following conclusions have been drawn from the statistical analysis mentioned above:

 1. The mean values of scale scores in terms of work time duration, irregular time, flexibility of work time and comprehensive quality index of aggregated work time for Chinese urban residents were 64, 68, 45 and 60, respectively, in 2018, falling into the “medium to high” category.

The index of work time quality is distributed unevenly across different groups: women have a better work time quality index than men; the index of middle- and older-aged group is higher than that of the young group; the index of migrant workers is lower than that of employees holding non-agricultural hukou (household register); residents holding a bachelor’s degree have the highest work time quality index while those holding high school or secondary technical school diplomas have the lowest. The distribution of work time quality index also varies across different types of jobs: while the bosses’ work time quality is the best, casual and dispatched workers have the worst work time quality; employees with intermediate or senior professional titles have a better work time quality in comparison with those without or with pending professional titles; the higher the power hierarchy of an employee, the higher his/her work time index. The distribution of work time quality index also varies across different types of organizations: party and political agencies have the best work time quality, while enterprise organizations have the worst. Residents’ autonomous organizations and the education industry have the best work time quality, while the handicraft industry have the worst. One of the objective social consequences of work time is job burnout felt by employees. Statistics shows that for every 1 percentile increase in work time quality index, the score of job burnout would decrease by 0.16. Thus, increasing employees’ work time quality can significantly reduce their job burnout.

2. The mean value of the environmental sub-scale of ambient physical risks for Chinese urban employees in 2018 is 93, the mean value of the sub-scale of man-machine engineering risks is 77, and the mean value of the composite index for physical working conditions is 86.

Physical working conditions vary across individual characteristics: women have better physical working conditions than men; migrant workers have a relative poorer physical working conditions index compared with employees with an urban hukou. The higher education an employee receives, the better his/her physical working conditions. The distribution of physical working conditions varies across different types of jobs: formal workers have the best physical working conditions while casual workers have the worst; workers with pending technical titles have the best physical working conditions while those with senior technical titles have the worst; frontline workers also have the worst physical working conditions. The distribution of physical working conditions also varies across different organizations and industries: party and political agencies and public institutions have the best physical working conditions, while self-employed business owners and collectively-owned enterprises have worse physical working conditions; consulting, financial and insurance industries have the best physical working conditions, in contrast with construction and agricultural product processing industries that have the worst. One of the objective social consequences caused by physical working conditions is the sub-health status among employees. For every 1 percentile increase in physical working conditions, the score of sub-health status will drop by 0.41, pointing to a significantly negative correlation. Thus, to relieve employees from sub-health status, more efforts should be done on improving employees’ physical working conditions.

3. The mean values of the effort and reward sub-scales for Chinese urban residents in 2018 are 56 and 54, respectively, with the mean value of the ERI_ratio being 1.06.

The distribution of ERI_ratio varies across different individual attributes: compared with mean, women have a higher ERI_ratio; compared with employees with non-agricultural hukou, migrant workers have a higher ERI_ratio. The higher education an employee receives, the lower his/her ERI_ratio is. Employees holding a bachelor’s or master's degree tend to be in a positively imbalanced state featuring low effort but high reward. The distribution of ERI_ratio also varies across different types of jobs: casual workers have the highest effort-reward imbalance, while formal workers and bosses tend to have a roughly fair effort-reward imbalance ratio; employees with pending technical titles have the highest ERI_ratio, those with a junior technical title tend to have a balanced effort-reward relationship, and those with an intermediate or senior technical title are usually in a positively imbalanced state featuring low effort but high reward; tier-2 managers tend to have a balanced effort-reward relationship, frontline workers are usually in a negatively imbalanced state featuring high effort but low reward, while middle and high-level managers are often in a positively imbalanced state featuring low effort but high reward. The distribution of ERI_ratio also varies across different organizations and industries: self-employed business owners have the highest ERI_ratio index, while party and political agencies, as well as social organizations, have the lowest ERI_ratio index; enterprise organizations tend to have a higher ERI_ratio index compared with public institutions. State and party agencies and social organizations have the best work reward, while handicraft, catering and service industries have the worst. Effort-reward imbalance also causes severe social and psychological consequences. The higher the ERI_ratio, the higher the employees’ turnover tendency, the lower their occupational loyalty and income satisfaction.

4. The mean values of sub-scales for participation in work-related decision-making and work affairs among Chinese urban employees in 2018 are 18 and 52, respectively, with the mean value of the composite index of employee participation being 35, indicating a relatively low participation level.

The distribution of employee participation and co-determination varies across different groups of individuals: compared with men, women have a lower participation level; compared with employees with a non-agricultural hukou (household register), migrant workers have a lower participation level; the group of CPC members exhibit the highest level of employee participation, while that of the ordinary masses is lower; employee participation significantly grows along with an increase with their educational level. The distribution of employee participation and co-determination varies across different types of jobs: while bosses have the highest participation level, casual workers have the lowest. The higher an employee's technical title, the stronger his/her employee participation; the higher the power hierarchy of an employee, the stronger his/her employee participation. The distribution of employee participation and co-determination also varies across different organizations and industries: employees from state, party and political agencies and social organizations have the highest level of employee participation, while self-employed workers have the lowest; the participation level in state, party and political agencies and social organizations is found to be the highest among the three major types of organizations. Employees from the mining industry show the best employee participation, while those from the handicraft industry have the worst. Employee participation affects employees’ effort and job satisfaction. The higher an employee's participation level, the large his/her effort devoted to work and thus job satisfaction.