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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 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.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to calculate the workforce productivity changes of the US construction industry from 2006 to 2016, with the number of laborers as input and value of construction industry as output.

The present study introduced the data envelopment analysis (DEA) based Malmquist productivity index model to measure the workforce productivity of the US construction industry from 2006 to 2016.

The results indicated that the workforce productivity of the US construction industry experienced a continuous decline, except for the increases from 2011 to 2013 and from 2014 to 2015. It was also shown that there were gaps in the workforce productivity development level among all states and nine regions in the US construction industry. Besides, the relationship between workforce productivity and four aspects, including real estate price, workforce, climate distribution and economic factors, was analyzed.

The calculation of the productivity of the US construction industry is based on the premise that the external environment is fixed and unchanged from 2006 to 2016, but the multi-level DEA model for further calculation is required for obtaining more effective conclusions.

This paper measures the workforce productivity of the US construction industry over the past 11 years, which added latest analysis and knowledge into the construction industry, providing decision-makers with advice and data support to formulate policies to improve workforce productivity.

This study provided both government decision-makers and industrial practitioners with important macro background environment information, which will facilitate the improvement of workforce productivity in the construction industry in different regions of the US.

The purpose of this paper is to explore the impact of using computers to obtain information on the farm household’s production and consumption based on a field survey of farm households in the northern China.

The most important methods applied are instrumental variable (IV) method and propensity score matching (PSM) method. Estimators of IV, PSM and nearest neighborhood matching approaches are considered together to check the robustness of empirical results.

This paper careful impact evaluation results suggest that the use of computer not only improves the size of arable land rented in but also reduces family labor input intensity and the probability of selling agricultural outputs at farm-gate markets. Moreover, it also stimulates transportation, garment, housing and insurance expenditures per capita.

The database of this research comprises cross-section data, which does not support a cross-time comparison.

These results imply that it is vital to expand the coverage of computer use in rural areas. This may suggest that the importance of improving computer access is crucial for stimulating rural consumption increase. Furthermore, the need for the expansion of internet network coverage in western areas is also of importance.

First, the authors directly estimate computer usage impacts on a broader range of production and consumption indicators by including land-relative investments, variable investments, labor input and household’s expenditure and provide rigorous impact evaluations on the impact of access to computer. Second, the authors use IV and PSM methods to correct self-selection bias, going beyond the single equation approach in other studies. This enables us to identify the causal relationship between computer usage and farmer’s production and consumption decisions.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.