This paper develops a novel hybrid Trigonometric Envelopment Analysis for Ideal Solutions (TEA-IS) model to assess the ecological efficiency of 248 Chinese cities for a 14-year period and employs a difference-in-difference approach to reveal the mechanism of the impact of low-carbon pilot city policies on ecological efficiency from the perspective of green technology innovation. This TEA-IS approach not only combines the advantageous features that exist in each individual model, but also allows an analysis of ecological efficiency in terms of the synergistic effects that may exist among correlated positive and negative criteria. Machine learning methods are also employed to predict high-low performance and synergistic Chinese cities in terms of the socio-economic and demographic context. Results indicate that ecological efficiency is generally low in Chinese cities. The low-carbon pilot city policy does help to improve ecological efficiency, which results from the mechanism of green technology innovation.

The aim of this study was to identify the facets influencing job satisfaction and intention to quit of nurses employed in Turkey. Using a non-probability sampling technique, 417 nurses from six large private hospitals were surveyed from March 2014 to June 2014. The nurses’ demographic data, their job-related satisfaction and turnover intentions were recorded through a self-administered questionnaire. In this study, descriptive and bivariate analyses were used to explore data, and multivariate analysis was performed using logistic regression. Nurses’ job satisfaction was found at a moderate level with 61% of the nurses intended to quit. Nevertheless, nurses reported a high satisfaction level with work environment, supervisor support, and co-workers among the selected nine facets of job satisfaction. They also reported a low satisfaction level with contingent reward, fringe benefits, and pay. The impact of demographic characteristics on job satisfaction and intention to quit was also examined. The study revealed a negative relationship between job satisfaction and intention to quit the existing employment. Moreover, satisfaction with supervisor support was the only facet that significantly explained turnover intent when controlling for gender, age, marital status, education, and experience. The implications for nurse management were also described for increasing nurses’ job satisfaction and retention. This study is beneficial for hospital management to ensure proper nursing care that would lead to a better quality healthcare service.