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This study aimed to develop a moderated mediation model to explain the relationship between perceived organizational justice and the counterproductive work behavior (CWB) of Chinese public servants. In this model, the authors assumed that job burnout mediates the relationship between perceived organizational justice and CWB and that moral identity moderates the relationship between job burnout and CWB.

A total of 210 public servants in China participated in this study, and their characteristics were measured by self-report tools. Hierarchical multiple regression analyses were used to test the moderated mediation model.

Analysis of the data demonstrated that perceived organizational justice, job burnout and moral identity influenced CWB. Moral identity moderated the relationship between job burnout and CWB, such that individuals with low moral identity are more likely to engage in CWB. Moreover, job burnout mediated the effect of perceived organizational justice on CWB, and the mediating effect of job burnout was moderated by moral identity. The indirect effect of perceived organizational justice on CWB through job burnout was significant among individuals with low moral identity but not among individuals with high moral identity.

The findings highlight the self-regulatory function of moral identity in preventing CWB.

The study offers several significant suggestions to reduce CWB in Chinese public sector administration, such as by improving organizational justice perception, recruiting and selecting individuals with reference to their moral identity and monitoring employees’ job burnout regularly.

The authors developed and verified a moderated mediated model on the relationship between perceived organizational justice and CWB. The study revealed that job burnout has a mediating effect on the perceived organizational justice–CWB relation, providing important insights into the processes through which perceived organizational justice affects CWB.

This study aims to analyse the potential impacts of free trade agreement (FTA) between Indonesia and Organisation of Islamic Cooperation (OIC) countries by eliminating import tariffs in the halal food sector on welfare, gross domestic product (GDP) and trade balance. OIC countries as the second-largest organisation after the United Nations are the potential markets for the halal food industry.

This study used the Global Trade Analysis Project database version 10 by adopting a computable general equilibrium (CGE) model for two scenarios. The first scenario stated that Indonesia should conduct an FTA with ten potential OIC countries as export destination, while the second one stated that it should be conducted with all OIC countries.

Indonesia is predicted to get the highest increase in welfare by making an FTA with all OIC countries. Scenario 2 showed that Indonesia had much higher changes in real GDP with a positive change of 0.0018%. Even though it is projected to experience a surplus in the trade balance in both scenarios, Indonesia is predicted to experience a decline in exports for the particular halal food sector. The findings contribute some new insights to the existing literature, revealing an alignment between economic integration and the concept of international trade in Islam.

The limitation of this study is the available data that cannot describe the population of all OIC countries. Only 31 countries out of a total of 56 OIC countries can be used in research. The scope of research is limited to analysing FTAs between Indonesia and OIC countries in the form of abolishing import tariffs and does not include non-tariff barrier issues such as halal certification.

The preferential trade agreement is considered relevant as Indonesia’s initial commitment to conduct a bilateral trade with ten selected OIC countries. The Indonesia Government, however, still needs to make several mitigation efforts in various sectors experiencing losses as a result of economic integration, such as by creating a more conducive business climate, supporting the sources of capital, facilitating bureaucratic affairs, as well as providing tax incentives.

This paper contributes to the literature by focusing on the critical aspects of the FTA’s impacts on halal food sectors by optimizing the reduction of import tariffs of OIC countries. Different from previous studies, this study applied a static CGE model to examine the impacts of FTA on macroeconomic indicators.

In the process of making agricultural production decisions in rural households, severe weather conditions, either extreme cold or heat, may squeeze the labor input in the agricultural sector, leading to a reallocation of labor between the agricultural and non-agricultural sectors. By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, reveal the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

This study utilizes data from Chinese meteorological stations and two waves of China Household Income Project to examine the impact and behavioral mechanism of extreme temperatures on rural labor reallocation.

(1) Extremely high and low temperatures had led to a reallocation of labor force from agricultural activities to non-farm employment, with a more pronounced effect from extreme high temperature events. (2) Extreme temperatures influence famers’ decision in abandoning farmland and reducing investment in agricultural machinery, thus creating an interconnected impact on labor mobility. (3) The reallocation effect of rural labor induced by extreme temperatures is particularly evident for males, persons that perceives economic hardship or labor in economically active areas.

By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, and reveals the mechanism of farmers’ adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

Evaluating the economic effects of climate change is a pivotal step for planning adaptation in developing countries. For Bangladesh, global warming has put it among the most vulnerable countries in the world to climate change, with increasing temperatures and sea-level rise. Hence, the purpose of this paper is to examine how climate change impacts the economy in Bangladesh in the case of climate scenarios.

Using a dynamic computable general equilibrium (CGE) model and three climate change scenarios, this paper assesses the economy-wide implications of climate change on Bangladesh’s economy and agriculture. It is clear from the examination of the CGE model that the impacts of climate change on agricultural sectors were felt more sharply, reducing output by −3.25% and −3.70%, respectively, and increasing imports by 1.22% and 1.53% in 2030 and 2050, compared to the baseline.

The findings reveal that, relative to baseline, agricultural output will decline by a range of −3.1% to −3.6% under the high climate scenario (higher temperatures and lower yields). A decrease in agricultural output results in declines in agricultural labor and household income. Household income falls in all categories, although it drops the most in urban less educated households with a range of −3.1% to −3.4%. On the other hand, consumption of commodities will fall by −0.11% to −0.13%, according to the findings. Although climate change impacts had a relatively small effect on gross domestic product, reducing it by −0.059% and −0.098% in 2030 and 2050, respectively.

As agricultural output, household consumption and income decline, it will impact the majority of the population’s health in Bangladesh by increasing malnutrition, hidden hunger, poverty, changing food environment, changing physical and mental health status and a changing health-care environment. Therefore, population health and food security will be a top socioeconomic and political concern for Bangladesh Government.

The examination of the dynamic CGE model is its originality. In conclusion, the evidence generated here can provide important information to policymakers and guide government policies that contribute to national development and the achievement of food security targets. It is also necessary to put more emphasis on climate change issues and address potential risks in the following years.

Utilizing the expectation states theory in sociology, this study probes into the influence of the board's informal hierarchy on the quality of enterprise innovation, originating from the perspective of internal directorial interactions, while analyzing the boundary effects exhibited by the nature of property rights and the intensity of geo-culture.

The study selects China's A-share listed companies from 2008 to 2021 as the research sample, employing the Tobit regression analysis method to scrutinize the hypotheses presented in the text.

The regression results demonstrate a positive correlation between the board's informal hierarchy and the enterprise innovation quality (EIQ). Upon introducing variables specific to property rights and geographical culture, the authors found that in comparison to non-state-owned enterprises (non-SOEs), the influence of the board's informal hierarchy on the quality of corporate innovation is diminished in SOEs. Conversely, the intensity of geo-culture across Chinese provinces enhances their mutual positive influence. In the additional analysis, the authors also found that the elevation of corporate risk tolerance is a significant pathway for the positive effect of the board's informal hierarchy on EIQ. Moreover, this positive influence is more profound in high-tech enterprises, businesses implementing equity incentive plans and companies that have subscribed to director and officer liability insurance.

The findings not only deepen the understanding of how the board's internal status characteristics influence corporate decision-making but also enrich the application scope of expectation states theory. Furthermore, this study offers valuable guidance for optimizing innovation decision-making by adjusting the personnel structures of corporate boards.

The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling (AAR) for unmanned aerial vehicle, which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.

Methods and techniques for marker detection, feature matching and pose estimation have been designed and implemented in the visual measurement system.

The simple blob detection (SBD) method is adopted, which outperforms the Laplacian of Gaussian method. And a novel noise-elimination algorithm is proposed for excluding the noise points. Besides, a novel feature matching algorithm based on perspective transformation is proposed. Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.

The visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.

The SBD method is used to detect the features and a novel noise-elimination algorithm is proposed. Besides, a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.

This study aims to investigate the influence of parent company personnel embedding on the stock price crash risk (SPCR) of listed companies, along with the moderating effect of disparate locations between parent and subsidiary companies and other major shareholders.

This research empirically tests hypotheses based on a sample of listed subsidiaries in China during the period between 2006 and 2021.

Our results demonstrate that personnel embeddedness in the parent company significantly alleviates SPCR in subsidiaries. This effect is even more substantial when the parent and subsidiary companies are in different places. However, other major shareholders in the subsidiary company weaken it. Our additional analysis indicates that, relative to executive embeddedness, director embeddedness exerts a stronger effect on the SPCR of the subsidiary. Mechanism examination reveals that the information asymmetry and the level of internal control (IC) within the subsidiary are significant channels through which the personnel embeddedness from the parent company influences the SPCR of the subsidiary.

This study expands the literature on how personnel arrangements in corporate groups within emerging countries influence SPCR. We have extended the traditional concept of interlocking directorates to corporate groups, thereby broadening the understanding of the governance effects of interlocking directors and executives from a group perspective.

When emergencies occur, the attention of the public towards emergency information on social media in a specific time period forms the emergency information popularity evolution patterns. The purpose of this study is to discover the popularity evolution patterns of social media emergency information and make early predictions.

We collected the data related to the COVID-19 epidemic on the Sina Weibo platform and applied the K-Shape clustering algorithm to identify five distinct patterns of emergency information popularity evolution patterns. These patterns include strong twin peaks, weak twin peaks, short-lived single peak, slow-to-warm-up single peak and slow-to-decay single peak. Oriented toward early monitoring and warning, we developed a comprehensive characteristic system that incorporates publisher features, information features and early features. In the early features, data measurements are taken within a 1-h time window after the release of emergency information. Considering real-time response and analysis speed, we employed classical machine learning methods to predict the relevant patterns. Multiple classification models were trained and evaluated for this purpose.

The combined prediction results of the best prediction model and random forest (RF) demonstrate impressive performance, with precision, recall and F1-score reaching 88%. Moreover, the F1 value for each pattern prediction surpasses 87%. The results of the feature importance analysis show that the early features contribute the most to the pattern prediction, followed by the information features and publisher features. Among them, the release time in the information features exhibits the most substantial contribution to the prediction outcome.

This study reveals the phenomena and special patterns of growth and decline, appearance and disappearance of social media emergency information popularity from the time dimension and identifies the patterns of social media emergency information popularity evolution. Meanwhile, early prediction of related patterns is made to explore the role factors behind them. These findings contribute to the formulation of social media emergency information release strategies, online public opinion guidance and risk monitoring.

This paper aims to analyze the characteristics of friction vibration signals and identify the vibration excitation source at the start and stop stage of microtextured end face of dry gas seals.

The friction pair consists of a diamond-like carbon (DLC) film microtextured seal ring and a spiral groove seal ring. Friction vibration signal feature extraction method based on harmonic wavelet packet and spectrum analysis was proposed. Signals were collected using acceleration sensor, acquisition card and LabVIEW software. Vibration acceleration signal was decomposed into 32 frequency bands using MATLAB wavelet packet transformation. The 32nd band coefficient was extracted for reconstruction, time-domain and spectral waveforms were obtained and spectra before/after denoising were compared.

The end face of the DLC film microtextured seal ring generates a good dynamic pressure effect, and the friction and vibration reduction effects are obvious. The harmonic wavelet packet can decompose the vibration signal conveniently and precisely. In the case of this experiment, the frequency of vibration of the seal ring is 7500 HZ.

The results show that the method is effective for the processing of friction vibration signal and the identification of vibration excitation source. The findings will provide ideas for the frictional vibration signal processing and basis for further research in the field of tribology of dry gas seal ring.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0084/

This paper aims to explore the trends in academic research on elder abuse from 1990 to 2023 using bibliometric analysis. It seeks to identify research trends, hotspots and gaps and proposes future research directions.

Using bibliometric analysis method, this study analyzes 2,404 documents related to elder abuse from the Scopus database. Visual analysis is conducted using VOSviewer software to reveal research trends, thematic clusters and their interrelationships.

The study shows a rising concern for elder abuse, especially in nursing homes, domestic settings and among dementia patients. However, research on prevention and intervention measures is lacking, despite increasing international collaboration. Yet, deeper exploration of cross-cultural and regional differences remains limited.

This study reveals that improving care conditions for nursing home residents and dementia patients requires increased funding, professional training for caregivers, the strengthening of regulations and the establishment of clear guidelines for reporting abuse. Additionally, promoting international cooperation, sharing best practices, raising public awareness and supporting ongoing research are essential measures to ensure the safety and dignity of older adults.

To the best of the authors’ knowledge, this study represents the first systematic review of elder abuse research using bibliometric analysis, providing researchers and policymakers with a comprehensive knowledge framework of the field’s development trends and research hotspots.