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This research addressed online customer-to-customer (C2C) incivility during digital service recovery.

To examine the effectiveness of managerial responses to online C2C incivility post a restaurant service failure, a 2 (Managerial response: general vs specific) x 2 (Failure severity: high vs low) quasi-experimental design was employed. A pretest was conducted with 123 restaurant consumers via Amazon Mechanical Turk, followed by a main study with 174 restaurant consumers. Taking a mixed-method approach, this research first asked open-ended questions to explore how participants perceived the restaurant’s motivation for providing a generic versus a specific response. Hayes’ (2013) PROCESS procedure was then performed for hypotheses testing.

The results revealed significant interaction effects of managerial responses and failure severity on perceived online service climate and revisit intention, mediated by trust with managerial responses.

This research yielded unique insight into C2C incivility management literature and industry practices in the context of digital customer service recovery.

The purpose of this paper is to explore carbon emission reduction of electric vehicles from the perspective of electricity consumption.

Electric vehicles (EVs) consume large amounts of electricity, thereby generating large amounts of carbon dioxide (CO2) emissions, so there is an urgent need to consider whether EVs have greater potential for reducing carbon emissions than other modes of transport. In this paper, the carbon emission reduction potential (CERP) coefficients of EVs are examined under three different scenarios from an interprovincial electricity trading perspective. Scenario analysis was used to quantify the CERP of EVs in 18 provinces in China.

The results show the following: (1) The higher the proportion of general-fuel vehicles in all transportation, the higher the CERP of EVs. (2) Interprovincial power trading affects the proportion of coal power consumed in a province, and the higher the proportion of clean power in the purchased power, the lower the proportion of coal power consumed in that province. (3) The proportion of coal power in the electricity consumption of a province is correlated negatively with the CERP of EVs in that province.

This paper quantifies the CERP of EVs compared with other modes of transport and gives provinces a more intuitive understanding of the CERP of EVs. Furthermore, we derive the carbon emission shift out of each province via the electricity trading paths among provinces, analyzing the impacts of the variability between different provinces on EV carbon emissions.

This study investigates how the complexity of sentiment in online reviews affects perceived helpfulness. Analyzed over 730,000 reviews from Tripadvisor.com, the research explores how information overload and increased cognitive load impact consumer decision-making.

This study applied the BERT deep learning model to analyze sentiment complexity in online reviews. Based on cognitive load theory, we examined two key factors: the number of attributes mentioned in a review and the variation in sentiment valence of across attributes to evaluate their impact on cognitive load and review helpfulness.

The results show that a higher number of attributes and greater variation in sentiment valence increase cognitive load, reducing review helpfulness. Reviewers’ expertise and review readability further moderate these effects, with complex or expert-written reviews worsening the negative impact.

This research introduces a method for measuring attribute-level sentiment complexity and its impact on review helpfulness, emphasizing the importance of balancing detail with readability. These findings provide a foundation for future studies on review characteristics and consumer behavior.

This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.

Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.

The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.

This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.

Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

This study aims to investigate the crevice corrosion behavior of carbon steel in neutral/alkaline environments utilizing a transient multi-physics field model.

The crevice corrosion of carbon steel with different solution pH and crevice width was modeled, incorporating mass transfer, homogeneous phase and localized electrochemical reactions. The extent of crevice corrosion was evaluated by the geometric deformation of the model mesh. The hydro-chemical state inside the crevice was discussed through the Cl⁻ concentration and potential distribution of the solution.

Results revealed that the formation of pitting corrosion near the crevice mouth was accelerated in a neutral solution. When pH = 8 and pH = 9, the carbon steel matrix was dissolved and the Cl⁻ content within the solution was significantly reduced due to the higher concentration of hydroxide ions (OH⁻).

The crevice corrosion behavior of carbon steel in neutral/alkaline environments is closely associated with solution pH rather than the crevice width. The inhibition of crevice corrosion in alkaline environments was proved by finite element simulation. These findings provide valuable insights that can be applied in engineering applications to prevent and mitigate crevice corrosion in neutral/alkaline environments.

Migrant workers play a vital role in the development of countries such as China. However, they often face greater barriers in entrepreneurship. Yet, few studies have focused on the effect of institutional factors on migrant workers' entrepreneurial behaviors. To address this gap, this study concentrates on the role of taxation.

This study takes the agricultural tax abolition reform implemented in rural China since 2004 as an exogenous shock and uses the difference-in-difference (DID) method to examine its effect on migrant workers' entrepreneurship based on longitudinal data from the China Health and Nutrition Survey (CHNS).

We find that the reform significantly improves the probability of migrant workers engaging in entrepreneurship. Heterogeneity analysis reveals that the reform exerts a notably more pronounced positive impact on male, younger and migrant workers in the Western region. Further analysis reveals that the three main mechanisms are increased household income, female human capital accumulation and increased social capital, including social networks and social trust.

This study is first to offers an institutional perspective on the determinants of migrant workers' entrepreneurship in China. Additionally, the study can provide insights for policymaking intended to support employment and entrepreneurship among low-skill migrant workers.

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 paper aims to conduct a comparative analysis of the scientific performance of distinguished young scholars in China during the pre-award and early stages of their research careers, aiming to provide insights into their growth pattern.

Spearman correlation was used to analyse the correlation between various academic ages and awarding age of the distinguished young scholars. The Wilcoxon matched pairs test was used to analyse variations in their scientific performance across different research stages.

The findings showed that: a) early successful research experiences significantly impact their emergence as outstanding scientists. While a low correlation exists between publication ages and awards, perseverance proves crucial for later-stage academic achievements; b) productivity increases before awards, with notable variations between first-author and non-first-authored publications; c) collaboration intensifies before awards, particularly in non-first author roles. However, discipline-specific variations highlight the importance of smaller teams and first-author roles, especially in the early career stage; d) the correlation between collaboration and productivity depends on research roles, emphasizing the evolving nature of collaboration dynamics as scholars progress in their careers.

This study could offer a reference for formulating well-founded talent training programs and reward mechanisms.