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The purpose of this study is to explore the impact of work-to-family conflict (WFC) on unethical pro-family behavior (UPFB) and work engagement (WE) among Chinese female leaders. In addition, this study investigates the mediating role of work-to-family guilt (WFG) and the moderating role of family centrality (FC) in these relationships.

A quantitative approach was adopted, involving the collection of data through online questionnaires administered at three time points. These data were analyzed using hierarchical regression and the bootstrapping method to test the proposed hypotheses.

WFC exhibited a significant positive correlation with UPFB and a negative correlation with WE; WFG played a mediating role in the relationships between WFC and both UPFB and WE; and FC had a significant moderating effect on the relationship between WFC and WE.

This study sheds light on a model of WFC and its related effects, reveals how WFC affects UPFB and WE and uncovers the mediating role of WFG and the moderating role of FC; pays attention to a unique organizational behavior, UPFB, which enriches research on the antecedents influencing such behaviors; and examines Chinese female leaders in organizations, their current experience of WFC and the resulting psychological and behavioral outcomes.

This paper aims to explore the effects of leadership style and trust in leadership on employees’ affective commitment under the epidemic situation.

A total of 580 valid questionnaires were collected online targeting the hospitality and tourism employees working from home during the particular period of the COVID-19 Coronavirus crisis. Structural equation modeling was used to analyze the data with AMOS software.

The findings indicated that perceived transformational leadership was a positive predictor of trust in leadership and affective commitment. In addition to the positive contribution to commitment, trust in leadership also mediated the relationship between transformational leadership and organizational commitment.

The current study contributes to the literature on leadership and organizational commitment. The results of this study may provide a valuable guide to organizations, leaders and young employees.

变革型领导对员工信任及员工情感承诺的影响研究

本文旨在研究在新冠疫情背景下, 变革型领导对员工信任度以及情感承诺的影响。

本文研究对象为旅游及酒店行业工作人员, 由于新冠疫情, 调查问卷通过线上的方式向居家办公的酒店工作人员进行发放, 调查结束共收集到580份有效问卷, 利用AMOS软件对收集到的数据进行结构方程分析。

本研究发现, 变革型领导对员工组织信任具有正向影响, 员工信任对员工的组织情感承诺具有正向影响, 变革型领导正向影响员工的组织情感承诺, 并且, 变革型领导通过增强员工信任度, 正向影响员工的组织情感承诺, 即员工信任在变革型领导和情感承诺中间起中介作用。

本研究为拓展企业管理领域研究做出了贡献, 本文研究结果验证了相关的领导理论及组织管理理论, 丰富了职业承诺领域的研究, 为组织、领导以及青年员工的职业发展提供了参考借鉴。

Investigación sobre la influencia del liderazgo transformacional en la confianza y el compromiso emocional de los empleados

Este artículo tiene como objetivo estudiar la influencia del liderazgo transformacional en la confianza y el compromiso emocional de los empleados bajo el impacto del Covid-19.

El objeto de investigación de este artículo es el personal del sector turístico y hotelero. Se recogieron un total de 580 cuestionarios válidos y se analizaron los datos recopilados mediante ecuación estructural utilizando el software AMOS.

Esta investigación encontró que el liderazgo transformacional tiene una influencia positiva en la confianza de los empleados, la confianza de los empleados tiene una influencia positiva en el compromiso emocional de los empleados, el liderazgo transformacional afecta positivamente el compromiso emocional de los empleados y la confianza de los empleados juega un papel intermediario entre el liderazgo transformacional y el compromiso emocional.

Esta investigación enriquece la investigación sobre la teoría del liderazgo y el compromiso organizacional, y proporciona una referencia para el desarrollo profesional de organizaciones, líderes y empleados jóvenes.

The purpose of this paper is to understand the applications of metaverse-related technologies in US urban libraries, explore excellent cases of US urban libraries' practices in using metaverse-related technologies to serve patrons and try to find the factor that may affect the application of metaverse-related technologies in libraries at this stage.

To gather information about how and whether libraries use metaverse-related technologies such as three-dimensional (3D) technology, radio frequency identification (RFID), virtual reality augmented reality (AR) and artificial intelligence (AI) in their services. Firstly, the authors visit 150 US urban library websites that are members of the Urban Libraries Council. Secondly, the authors calculate the proportion of services provided by urban libraries that use metaverse-related technologies and introduce outstanding cases. Lastly, the authors discuss the factors that influence the application of metaverse-related technologies in urban libraries in the United States based on data published by the Institute of Museum and Library Services.

Metaverse-related technologies have been widely used in US urban libraries, but there are differences in the popularity of the applications of different technologies. In all, 84% of libraries use 3D technology, mainly in 3D printing services and 3D model building services; 76% of libraries use virtual and augmented reality technologies in their services, mainly concentrated in head-mounted VR device experiences, AR device experiences, virtual tours and virtual exhibitions; 62% of libraries use Internet of things (IoT) technology, mainly in self-checkout machines and book location services. However, AI technologies are less used in libraries, with 28% of libraries mentioning the applications of AI in their services, mainly focusing on intelligent search, virtual assistants and robot librarians. In addition, this study finds that library operating expenditures and population served do not affect the application of metaverse-related technologies in libraries.

This paper provides updated statistical data on the use of metaverse-related technologies in US urban libraries and aims to help library managers understand the overall applications and best practices. With this as an inspiration, they could formulate corresponding development plans to better serve their communities with metaverse-related technologies.

Complex mechanical 3D computer-aided design (CAD) model embodies rich implicit design knowledge. Through discovering the key function parts and key function module in 3D CAD assembly model in advance, it can promote the designers’ understanding and reuse efficiency of 3D assembly model in design reuse.

An approach for discovering key function module in complex mechanical 3D CAD assembly model is proposed. First, assembly network for 3D CAD assembly model is constructed, where the topology structure characteristics of 3D assembly model are analyzed based on complex network centrality. The degree centrality, closeness centrality, betweenness centrality and mutual information of node are used to evaluate the importance of the parts in 3D assembly model. Then, a multi-attribute decision model for part-node importance is established, and the comprehensive evaluation for key function parts in 3D assembly model is accomplished by combining Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Subsequently, a community discovery of function module in assembly model-based Clauset–Newman–Moore (CNM)-Centrality is given in details. Finally, 3D CAD assembly model of worm gear reducer is taken as an example to verify the effectiveness and feasibility of proposed method.

The key function part in CAD assembly model is evaluated comprehensively considering assembly topology more objectively. In addition, the key function module containing key function part is discovered from CAD assembly model by using CNM-Centrality-based community discovery.

The approach can be used for discovering important design knowledge from complex CAD assembly model when reusing the assembly model. It can help designers capture and understand the design thinking and intent, improve the reuse efficiency and quality.

The paper first proposes an approach for discovering key function module in complex mechanical 3D CAD assembly model taking advantage of complex network theory, where the key function part is evaluated using node centrality and TOPSIS, and the key function module is identified based on community discovery.

Rising energy expenditures due to more intensive use of energy in modern agriculture and increasing energy prices may affect rural households’ agricultural incomes, particularly the incomes of the rural poor in developing countries. However, the exact link between energy costs and income among the rural poor needs further empirical investigation. The purpose of this paper is to develop a deeper understanding of the relationship between energy use and family income, using household-level panel data collected from 500 potato farmers in a poor region of Northern China, where eliminating poverty by 2020 is now the top government priority.

The paper uses household survey data collected from six counties in a poor region in northern China in 2013 to measure the relationship between energy cost and family income. A fixed effect model is employed to estimate the relationship.

The findings indicate that potatoes play an important role in the surveyed families’ incomes, and that the energy costs of potato production have a significant negative relationship with family income. However, this negative relationship is only significant for farmers with low economic standing, such as those living below or just above the poverty line. The negative relationship between energy costs and family income is only significant for those cultivating a certain size of potato-sown area; it is insignificant for those cultivating smaller areas.

These findings indicate that, in general, reducing energy costs helps the poor increase their income but is not necessarily helpful to those with high economic standing or a relatively small potato-sown area. If rural development policies are to support poverty reduction and energy savings (at least in major potato production regions), interventions aimed at energy cost reduction may be effective only for the poor whose family income depends, to a relatively high degree, on potato production.

The purpose of this paper is to present a clear path to securitize the longevity risk with two distinct swaps in order to inspire a new Chinese life market.

Studies on longevity risk securitization consist of three aspects, respectively, instrument design, pricing methodology and mortality projection. The swaps designed are referenced, respectively, to vanilla and complex survivor swaps (Dowd et al., 2006; Lin and Cox, 2005). Methods applied are RHH model and Gompertz law for mortality projection, as well as two-factor Wang transformation for pricing.

This paper figures out the market price of risk in Chinese annuity market, checks for the sensitivity of the price to parameters and tests the hedging effects by Monte Carlo simulation.

Based on the theoretical and numerical results, this paper suggests an effective way to possibly witness the birth of New Life Market in China.

The purpose of this paper is to examine the effect of adopting certified food production on chemical fertilizer and pesticide use in China.

The authors estimate fixed effect models to track the changes in agrochemical consumption at household level over time and evaluate the effect of certified food production, using an unbalanced panel data set covering 4,830 households in six provinces over the period 2005–2013.

On average, the authors do not find significant effects of certified food production on either chemical fertilizer or pesticide consumption among Chinese farmers. The effects are heterogeneous across villages, but the heterogeneous effects show no clear pattern that is consistent with different types of certification. The findings are robust to the use of alternative panel structure and certification indicators. The lack of knowledge about certification among farmers, the price premium and differences in regulation enforcement across regions may explain why the authors do not find negative effects on agrochemical use.

This study suggests that careful inspections and strong enforcement of certified food production is needed to ensure that the environmental goals of certified food production can be achieved and the reputation of certification in China can be improved. The inspection of certification producers and the enforcement of current regulations should be stricter for the further healthy development of certified food production in China.

This study is the first attempt to systematically evaluate the impact of food certification on the use of agrochemicals in Chinese agriculture.

With the end of the Cultural Revolution and the rise of Deng Xiaoping, China began a new era of economic and political reform. In 1978 the open door policy was initiated. In October of 1984, Deng Xiaoping set in motion an ambitious program of financial and industrial reform aimed at eventually restructuring China's economy into a vaguely defined market system. This “second revolution” has run into difficulties because the Chinese officials lacked experience controlling a supply and demand economy and because of the opposition from conservative factions within the Chinese bureaucracy.

The purpose of this study is to reveal the mechanism of humble leadership inducing abusive supervision from the low-status compensation perspective, examining the mediation role of leader perceived thread to status. Besides, the moderation effect of regulatory focus on the mediation path is discussed.

This study conducted a three-wave longitudinal survey. The data was collected from 438 leaders and their employees in five Chinese enterprises. This study used Mplus 7.4 and adopted a bootstrapping technique for data analysis.

Humble leadership has a positive effect on leader perceived threat to status. Leader perceived threat to status plays a mediation role between humble leadership and leader abusive supervision. Leader regulatory focus is the “gate valve” that humble leadership fosters leader abusive supervision. That is, when the leader promotion focus is high, leader perceived threat to status bred by humble leadership is low, resulting in less abusive supervision. When the leader prevention focus is high, humble leadership brings relatively more abusive supervision through perceived threat to status.

This study explores why humble leadership breeds abusive supervision behaviors and reveals the mechanism behind the negative effect of humble leadership based on low-status compensation theory. This study not only promotes the continuous development of the field of humble leadership research through empirical research but also provides guidance for effectively suppressing the negative effects of humble leadership, promoting strengths and avoiding weaknesses and suppressing inappropriate management behaviors in management practice.

According to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition, long short-term memory network and GM (1,1) model.

First, the empirical mode decomposition method is used to decompose the crude oil price series into several components with different frequencies. Then, each subsequence is classified and synthesized based on the specific periodicity and other properties to obtain several components with different significant characteristics. Finally, all components are substituted into a suitable prediction model for fitting. LSTM models with different parameters are constructed for predicting specific components, which approximately and respectively represent short-term market disturbance and long-term influences. Rolling GM (1,1) model is constructed to simulate a series representing the development trend of oil price. Eventually, all results obtained from forecasting models are summarized to evaluate the performance of the model.

The model is respectively applied to simulate daily, weekly and monthly WTI crude oil price sequences. The results show that the model has high accuracy on the prediction, especially in terms of series representing long-term influences with lower frequency. GM (1,1) model has excellent performance on fitting the trend of crude oil price.

This paper combines GM (1,1) model with LSTM network to forecast WTI crude oil price series. According to the different characteristics of different sequences, suitable forecasting models are constructed to simulate the components.