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Customer service is crucial for organizations' survival and competitiveness in the hospitality industry. The purpose of this study is to examine how and when servant leadership affects extra-role customer service.

The hypotheses were tested with a sample of 302 employees from a passenger transport company in China.

Results demonstrate that servant leadership was positively related to extra-role customer service and that this relation was mediated by relational identification. In addition, the mediating effect of relational identification in the relation between servant leadership and extra-role customer service was contingent on prosocial motivation.

The study is the first to explore the relation between servant leadership and extra-role customer service from the perspective of relational identification and the moderating role of prosocial motivation.

The visible time window (VTW) calculation of satellites to ground targets is significant for Earth observation satellites' operation management and control. With the improvement of satellite maneuvering capability and the complexity of on-orbit observation tasks, the traditional VTW calculation methods can no longer meet the demands of satellite operation management and control due to a large amount of calculation and low efficiency. The purpose of this study is to propose a fast VTW calculation method based on map segmentation named map segmentation method (MSM), to improve the calculation efficiency, and further solve this problem.

The main feature of the MSM method is to segment the map and subsatellite trajectories and traverse the subsatellite points within a specific range around the target, significantly reducing the search space and the amount of computation and improving computational efficiency.

Numerical simulations for two satellite orbits are implemented to verify the feasibility of the proposed VTW calculation method, and the traditional traversal method (TM) is also performed for comparative analysis. The results show that the proposed method can obtain the same VTW, using less calculation time than the TM. The computational efficiency is significantly improved, especially for many tasks. The calculation time of observing 500 targets is saved by more than 70%, indicating a broad application prospect.

This paper proposes an original VTW calculation method based on map segmentation to improve the calculation efficiency. The simulation scenarios are designed to verify the accuracy and effectiveness of the proposed method, and the observation targets are randomly distributed on the map. For comparative analysis, the TM is also performed under the same simulation conditions.

This paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.

The authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.

The study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.

The authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.

The authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

Prior research demonstrated that China's Outward FDI (OFDI) is aimed at sustaining long-term economic growth by promoting industrialization and technological upgrading in the country. However, empirical evidence on the effectiveness of this strategy remains scarce. This study intends to fill this gap by exploiting endogenous changes in industrial productivity stemming from OFDI to examine if China's new strategy to spur OFDI is economically beneficial for the industries involved.

The authors employed the two-step system-GMM and pooled mean group approaches on a panel dataset of 18 Chinese industries over the 2004–2017 period. The industrial sectors are further classified into the state dominated and non-state dominated ones to evaluate whether the productivity growth impact of OFDI varies by the level of ownership structure. Besides, the dataset is further decomposed into the ex ante and ex-post BRI era to test if this initiative has altered the underlying relationship.

The results provide robust evidence that China's OFDI through reverse spillover effects promotes productivity growth in the domestic industries, and such productivity gains are greater for the non-state dominated industries, and the OFDI in the BRI era. The findings suggest that OFDI can act as a catch-up strategy to release excess capacity and acquire technology and smart business practices.

This study is the first attempt to highlight the reverse productivity spillovers associated with OFDI at the industrial level. The study's findings guide the government officials and the practitioners of foreign investment to better understand the implications of their investment projects in terms of technology improvements and to optimize market opportunities.

The purpose of this study is to provide evidence that government financing behavior has an impact on the outward foreign direct investment (OFDI) of enterprises.

This paper uses debt data from local government financing vehicles to measure the local government debt in China. Based on the data of listed manufacturing firms in China from 2010 to 2018, this paper uses the Tobit model to verify the impact of local government debt and firms' OFDI.

The results indicate that local government debt impedes firms' OFDI, with a more pronounced impact on state-owned enterprises (SOEs) and those with higher political connections. Furthermore, our study suggests that the dampening effect of local governments on firms' OFDI is mitigated in regions following the implementation of the Local Government Debt Management Act.

This study verifies the negative impact of local government debt activity on firms' overseas investments. This is not due to debt crowding out, but rather to the fact that local governments prefer to keep resources locally to stimulate the economy. This paper offers novel insights into the theoretical mechanisms by which local government behavior influences firms' investment activities in emerging markets.

In this paper, the author examines the role of uncertainty due to pandemic on the predictability of sectoral stock returns in South Africa. This is motivated by the ongoing global pandemic, COVID-19, in predicting sector stock returns.

The study considers estimation of dynamic panel data with dynamic common correlated effects estimator and two pair-wise forecast measures, namely Campbell and Thompson (2008) and Clark and West (2007) tests in dealing with the nested predictive models.

The results show that pandemic uncertainty has a negative and statistically significant effect on the different sector returns, implying that sector stock returns decline as the pandemic outbreak becomes more pronounced. While the single predictor model consistently outperforms the historical average model both for in-sample and out-of-sample, controlling for other macroeconomic variables effect improves the forecast accuracy of infectious diseases uncertainty. These results are consistently robust to both the in-sample and out-of-sample forecast periods, outliers and heterogeneity. These results have implications for portfolio diversification strategies, which we set aside for future research.

The empirical literature is satiated with studies on how news can predict economic and financial variables, however, the role of uncertainty due to infectious diseases in the stock return predictability especially at the sectoral level is less understudied, this is the main contribution of the study.

This paper analyzes the effect of the Belt and Road Initiative (BRI) on firm green innovation upgrading using data on Chinese firms between 2009 and 2021.

The author adopts the staggered difference-in-difference (DID) method to estimate regressions, treating the proposal of the BRI in 2013 as a policy shock. Our analysis yields few findings.

The author yields few findings. First, the BRI can significantly promote Chinese firms green innovation upgrading. Specifically, the BRI can promote firm green innovation upgrading by 0.9%. Second, the BRI mainly promotes firms green innovation upgrading by promoting firms to increase green entrepreneurship, cooperative innovation and environmental investment. Finally, the BRI has a greater impact on the green innovation upgrading of firms in the digital industrialization industry rather than digital industry and firms with low pollution emissions rather than firms with high-pollution emissions. This research indicates that the BRI is not only an important platform for sustainable development and also an important opportunity for green entrepreneurship.

First, due to the low quality of data and the lack of detailed information on some firms' patents owned after 2018, fully applying data of all years for regression was not possible. Second, the author did not construct a theoretical model to explore the impact of the BRI on green innovation upgrading of firms from the perspective of outward foreign direct investment (OFDI), which is also the direction of future research. Finally, there are still some unexplored mechanisms of the BRI on firms green innovation upgrading, which should be further explored in the future.

First, from the micro perspective, the author measures the quality of firms' green patents, further measuring the firms' green innovation upgrading. Second, the author discusses the impact of the BRI on firm green innovation upgrading with the method of staggered DID, so that the policy effect of the BRI can be more accurately evaluated. Third, the author comprehensively analyzes the mechanism of cooperative innovation and green infrastructure investment, as well as analyzing the heterogeneity from the perspective of industry digital transformation and firm pollution emissions. Lastly, the author provides specific paths for firms to make high-quality investment from the green BRI construction.

The Belt and Road Initiative (BRI) is the most comprehensive and substantial international cooperation platform, creating a new market influenced by economic and political factors. In this paper, the authors aim to examine whether and how the BRI impacts the Chinese enterprises' corporate environmental responsibility (CER).

Based on China's listed firms' database from 2011 to 2018, the authors use the PSM-DID method, an econometrics method combined with propensity score matching (PSM) and difference-in-differences (DID), to conduct causal inference between the BRI and Chinese enterprises' CER and conduct a series of robustness analyses. Moreover, the authors explore the mechanisms underlying the main effect from both market and non-market perspectives.

The results suggest that the BRI significantly increases Chinese enterprises' CER. Further analyses show that market competition and government support are two possible mechanisms through which the BRI has an effect on the enterprises' CER.

The research study supplements existing work on the environmental effects of the BRI at a microlevel and adds to the literature on the drivers of CER. The findings offer valuable insights into governments and scholars by demonstrating that CER is a crucial tool for Chinese enterprises to gain a competitive advantage in the increasingly competitive markets along the BRI.