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This paper examines the effect of board reforms on managerial risk-taking incentive provision in state-owned enterprises (SOEs) whose managers are undue risk-averse.

We use the staggered implementation of board reforms in Chinese central government-controlled state-owned enterprises (CSOEs) as an exogenous shock to board governance. We collect data on board reforms for a set of pilot CSOEs during the period 2005 to 2020 from the State-owned Assets Supervision and Administration Commission (SASAC) website by hand. We use a generalized difference-in-difference (DID) design to test the effect of staggered board reform adoption on managerial risk-taking incentive provision.

We find a positive relationship between board reforms and risk-taking inventive provision, i.e. pay-performance sensitivity, promotion-performance sensitivity and performance target difficulty. The documented relationship is stronger when the value of risk-taking is higher. We also find that board reforms lead to greater risky but value-enhancing investments and that managerial risk-taking incentive provision acts as an important channel through which board reforms improve value-enhancing risk-taking.

Our findings suggest that board reforms that improve board governance are effective in addressing risk-related agency conflicts in emerging markets. The findings also highlight the importance of managerial risk-taking incentive provision in inducing risky but value-enhancing investments.

The collaborative filtering algorithm is a classical and widely used approach in product recommendation systems. However, the existing algorithms rely mostly on common ratings of items and do not consider temporal information about items or user interests. To solve this problem, this study proposes a new user-item composite filtering (UICF) recommendation framework by leveraging temporal semantics.

The UICF framework fully utilizes the time information of item ratings for measuring the similarity of items and takes into account the short-term and long-term interest decay for computing users’ latest interest degrees. For an item to be probably recommended to a user, the interest degrees of the user on all the historically rated items are weighted by their similarities with the item to be recommended and then added up to predict the recommendation degree.

Comprehensive experiments on the MovieLens and KuaiRec datasets for user movie recommendation were conducted to evaluate the performance of the proposed UICF framework. Experimental results show that the UICF outperformed three well-known recommendation algorithms Item-Based Collaborative Filtering (IBCF), User-Based Collaborative Filtering (UBCF) and User-Popularity Composite Filtering (UPCF) in the root mean square error (RMSE), mean absolute error (MAE) and F1 metrics, especially yielding an average decrease of 11.9% in MAE.

A UICF recommendation framework is proposed that combines a time-aware item similarity model and a time-wise user interest degree model. It overcomes the limitations of common rating items and utilizes temporal information in item ratings and user interests effectively, resulting in more accurate and personalized recommendations.

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

This study aims to explore the social networks and network interactions of bed-and-breakfast (B&B) entrepreneurs in rural China. In addition, it evaluates how such network interactions relate to rural resilience.

In-depth interviews were performed in two locations: Ningbo and Dujiangyan, China. Purposive sampling was combined with snowball sampling to select interviewees. The 154 interviews involved 29 B&B owners and relevant social actors. All codes and data were analyzed using the discourse analysis framework.

The B&B owners’ social networks were identified based on strategic goals, revealing a business operation network, business development network and business citizenship network. Challenges in seeking financial support for rural B&Bs during the pandemic were specified along with network interactions. The institutional adaptation approach was used to evaluate network interaction in rural B&B business. It was argued that other networks would react based on primary network members’ goal compatibility and the effectiveness of the primary network in addressing obstacles.

This study indicates that the rural B&B entrepreneurs’ interactions with various networks could influence on business resilience, community resilience as well as rural resilience.

By combining the institutional adaptation typology with social network theory, this study generates a new typology of network interactions for rural B&Bs. The typology helps to explain how and why B&B entrepreneurs make decisions and provides a broader scope of social networks involved in these business operations.