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Worktime reduction's effect on life satisfaction is an important issue but one that has not been fully studied. This article fills this gap and uses an ordered probit model to analyse the working time reduction impact on life satisfaction in Germany by using the European Social Survey data, the mediating effect of health and cross-partner effect are also explored. A significantly negative correlation between working time and life satisfaction are revealed, showing that a short working week can improve Germans' life satisfaction. Health is confirmed to be the important intermediate variable in the 'worktime–health–life satisfaction' nexus and about 28% of the satisfaction among German people is due to the change in health explained by working hours. Further, we find that high-earners prefer to work long hours whereas low-earners tend to work less; middle-earners show no personal preferences. Cross-partner effects are confirmed, as a male's short working week can satisfy their partner, while a female's long working hours can improve their partner's life satisfaction. In light of this, working hours should be restricted to avoid unsatisfaction induced by overtime work and overtime compensation regulations should be strictly implemented, policy-makers also need to take gender differences into consideration. [ABSTRACT FROM AUTHOR]

An evaluation indexing system based on the theory of coordination was constructed to estimate the urban carrying capacity (UCC) of the Beijing–Tianjin–Hebei (BTH) region with four subsystems: social, economic, environmental, and transportation. This indexing system revealed the interactions between "supply" and "demand." The improved entropy method was adopted to calculate the weight of 17 indicators and evaluate the comprehensive UCC of 13 cities in the BTH region using data covering the period 1990–2018. The results showed that two cities, Tangshan (UCC of − 0.0021) and Handan (UCC of − 0.0009), were "overloaded" in 2018, while the other 11 cities were "loadable." The social and transportation subsystems played the most crucial roles in the evaluation. Based on the results, Baoding achieved the highest UCC, while that of Tangshan was the lowest. The results could play a significant role in decision-making relating to the sustainable development of the BTH region. Three policy implications are proposed based on these findings: (i) the efficiency of resource utilization and scientific allocation should be enhanced and industrial optimization and upgrading should be promoted, (ii) the coordinated development of urbanization and environment in the region should be improved, and (iii) the integration of traffic decongestion measures should be faster, and industrial docking systems should be enhanced. [ABSTRACT FROM AUTHOR]

Most previous studies on comprehensive urban carrying capacity (UCC) have estimated UCC levels and comparatively analyzed the heterogeneity of the sample cities. Very few researchers have focused on the interaction effects between different categories of UCC based on synergetic theory. To fill this gap, we constructed a panel vector autoregressive (PVAR) model to study 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2016. The ultimate goal of this study is to improve comprehensive UCC levels by forming a virtuous circle of mutual reinforcement between the four types of carrying capacity. To do so, the interaction mechanisms of the four subsystems are examined. Results show that (a) only transportation and social carrying capacity had causality between them as per the Granger causality test; (b) all four carrying capacities can support themselves (i.e., the development of economic conditions helps to improve social carrying capacity and the improvement of social carrying capacity helps to improve environmental carrying capacity); and (c) both the four carrying capacities are mostly affected by their own fluctuations. Overall transportation carrying capacity is the most important driving force among the four subsystems that interact with each other; followed by economic carrying capacity, which has promotion effect on the social and environmental aspects; social carrying capacity poses impact on the environmental dimension but not vice versa. Policy suggestions and future research directions are highlighted in the final section. • The Guangdong-Hong Kong-Macao Greater Bay Area is examined for 2000–2016. • The mean squared deviation and panel vector autoregressive methods are employed. • Transportation carrying capacity is the most significant driving force. • Economic carrying capacity could impact on social and environmental counterparts. • Social carrying capacity impact on environmental dimension but not the opposite. [ABSTRACT FROM AUTHOR]