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The present study aims to ascertain the relationships between subordinate moqi and leader behaviors, by primarily discussing how and when subordinate moqi is associated with leadership empowerment.

A self-report study was conducted by recruiting 334 employees from 13 firms. All concepts were rated on a seven-point Likert-type response scale. Linear regression analysis (conducted in MPLUS 7) was conducted to verify the hypotheses.

First, subordinate moqi showed positive association with empowerment. Second, trust-in-supervisor mediated the relationships between subordinate moqi and empowerment. Third, subordinates' power distance orientation (PDO) could moderate the subordinate moqi – leader empowerment relationship. When subordinates reported higher PDO, the relationships between subordinate moqi and empowerment were more robust; likewise, subordinate moqi would have more significantly indirectly impacted empowerment via trust-in-supervisor.

Though researchers have discussed the impacts of subordinate moqi on subordinates' outcomes, the impact of subordinate moqi on supervisors' attitudes or behaviors remains unclear. The relationships between subordinate moqi and supervisor empowerment behaviors are empirically ascertained by emphasizing the leader-subordinate dyadic process. The findings here suggested that subordinate moqi boosted subordinates' trust-in-supervisor, and moqi would also predict the behaviors of leader empowerment. This study extended the PDO literature by identifying the moderating role of PDO in the subordinate moqi – leader empowerment behavior relationship.

The purpose of this paper is to explore the effect of ZnO on the structure and properties of micro-arc oxidation (MAO) coating on rare earth magnesium alloy under large concentration gradient.

The macroscopic and microscopic morphology, thickness, surface roughness, chemical composition and structure of the coating were characterized by different characterization methods. The corrosion resistance of the film was studied by electrochemical and scanning Kelvin probe force microscopy. The results show that the addition of ZnO can significantly improve the compactness and corrosion resistance of the MAO coating, but the high concentration of ZnO will cause microcracks, which will reduce the corrosion resistance to a certain extent.

When the concentration of zinc oxide is 8 g/L, the compactness and corrosion resistance of the coating are the best, and the thickness of the coating is positively correlated with the concentration of ZnO.

Too high concentration of ZnO reduces the performance of MAO coating.

The MAO coating prepared by adding ZnO has good corrosion resistance. Combined with organic coatings, it can be applied in corrosive marine environments, such as ship parts and hulls. To a certain extent, it can reduce the economic loss caused by corrosion.

The effect of ZnO on the corrosion resistance of MAO coating in electrolyte solution was studied systematically, and the conclusion was new to the common knowledge.

Recent years have witnessed an unexpected and astonishing rise of AI-generated (AIGC), thanks to the rapid advancement of technology and the omnipresence of social media. AIGCs created to mislead are more commonly known as DeepFakes, which erode our trust in online information and have already caused real damage. Thus, countermeasures must be developed to limit the negative impacts of AIGC. This position paper aims to provide a conceptual analysis of the impact of DeepFakes considering the production cost and overview counter technologies to fight DeepFakes. We will also discuss future perspectives of AIGC and their counter technology.

We summarize recent developments in generative AI and AIGC, as well as technical developments to mitigate the harmful impacts of DeepFakes. We also provide an analysis of the cost-effect tradeoff of DeepFakes.

The mitigation of DeepFakes call for multi-disciplinary research across the traditional disciplinary boundaries.

Government and business sectors need to work together to provide sustainable solutions to the DeepFake problem.

The research and development in counter-technologies and other mitigation measures of DeepFakes are important components for the health of future information ecosystem and democracy.

Unlike existing reviews in this topic, our position paper focuses on the insights and perspective of this vexing sociotechnical problem of our time, providing a more global picture of the solutions landscape.

This paper aims to explore the impact of green finance on the heterogeneity of enterprise green technology innovation and the underlying mechanism between them.

Using the data of China's A-share listed enterprises from 2008 to 2020 and the fixed effect model, the authors empirically explore the relationship and mechanism between green finance and green technology innovation by constructing the green finance index while considering both the quality and quantity of innovation.

The study suggests that green finance is positively related to the quality and quantity of enterprise green technology innovation, while green finance is more effective in stimulating the quality of green technology innovation than quantity. In addition, alleviating financial mismatch and improving the quality of environmental information disclosure are core mechanisms during the process of green finance facilitating green technology innovation. Furthermore, green finance exerts a more positive effect on the quality and quantity of green technology innovation with large-size enterprises, heavily polluting industries and enterprises in the eastern region.

This paper enriches the literature on green finance and green technology innovation and provides practical significance for green finance implementation.

The unitized curtain wall system (UCWS), a symbol of modern architecture, is gaining popularity among prefabricated components. Previous studies have focused on both construction technology advances and material selection strategies to facilitate the UCWS. However, the topic of client satisfaction, which drives industry development by targeting clients' demands, has gone unnoticed. Therefore, the current study aims to investigate client satisfaction with UCWS products in Hong Kong by finding its influential factors.

A systematic review was employed to first identify the influential factors. A semi-structured interview was employed to validate the reliability of the extracted factors. The machine learning algorithm Extreme Gradient Boosting (XGBoost) and the Pearson correlation were then employed to rank the importance and correlation of factors based on the 1–5 Likert scale scores obtained through a questionnaire survey.

The findings revealed that “reduction in construction time” and “reduction in construction waste” are the most important factors and have a strong positive influence on client satisfaction.

Unlike previous studies, the present study focused on a novel research topic and introduces an objective analysis process using machine learning algorithms. The findings contribute to narrowing the knowledge gap regarding client preference for UCWS products from both individual and collaborative perspectives, providing decision-makers with an objective, quantitative and thorough reference before making investments in the curtain wall management development.

Three-dimensional (3D) food printing is an innovative technology used to customize food products through the integration of digital technology and food ingredients. The purpose of this study is to assess the current state of research in the field of 3D food printing, identify trending topics and identify promising future research directions.

This bibliometric review systematically evaluates the field of 3D food printing using data from published literature in the Web of Science database. After reference screening, 812 articles were included in the analysis.

The result reveals that research in 3D food printing primarily focuses on the optimization and characterization of mechanical and rheological properties of food inks and that post-printing processing, such as laser treatment, has emerged recently as an important consideration in 3D food printing. However, extant works lack animal and human studies that demonstrate the functionality of 3D-printed food.

This sophisticated bibliometric analysis uncovered the most studied current research topics and the leading figures in the area of 3D food printing, providing promising future research directions.

The purpose of this paper is to conceptualize the indigenous concept of suzhi at individual and organizational levels, and identify its dimensions for human resource management (HRM) research and practice in China.

Based on a comprehensive review of suzhi literature, Chinese cultural and historical literature, as well as Western mainstream HRM research, a multidimensional suzhi framework is conceptualized.

As an indigenous expression, suzhi can be and has been adopted for Chinese HRM research and practice. As a multidimensional construct, one’s cognitive suzhi is jointly determined by corresponding moral suzhi, wenhua (knowledge-based) suzhi and zhuanye (professional) suzhi. Cognitive suzhi, in turn, determines one’s behavioral suzhi that drives employees to enhance organizational performance, and this relationship is moderated by psychological suzhi.

The proposed framework provides new insight for Chinese indigenous management research, particularly in developing suzhi measurement for different dimensions. It also informs HRM practices in recruiting, selection, performance analysis and employee career development.

The complexity of suzhi dimensions from an organizational HRM perspective is analyzed. The resulting suzhi framework offers new insight for HRM research and practices in China.

The purpose of this paper is to investigate firm behaviors on patent examination request under the deferred patent examination system in Korea. The authors examine firm decisions on whether and when to request patent examinations when they face both uncertainty about invention’s value and market competition.

The authors provide a simple theoretical model and test a couple of hypothesis using Korea patent data. The authors employ KIPO (Korean intellectual patent office) patent applications data during 2006–2009 and incorporate it with firm financial data retrieved from1 Korea investor service-financial analysis system (KIS-FAS) database in Korea. The authors use the variation in the probability of lapsed patent applications filed in the same year and in the same technology field (at the four-digit IPC class level) of a patent application i as a proxy for the value of uncertainty, and further use one minus a firm’s market share (at the three-digit SIC industry level) as an indicator of the market competition faced by the firm/applicant.

The authors find that the examination requests of firms in Korea have interesting bipolar distribution, and both uncertainty about an invention’s value and market competition have significant impacts on firm’s decision for examination request. Applicants tend to utilize option value of waiting when uncertainty is high, but market competition attenuates the option value: the higher the competition, the less likely applicants are to delay or forego examination.

The authors’ study makes interesting contributions to the literature on the optimal design of the patent system in general and the deferred patent examination request system in particular. By considering the roles of both uncertainty and market competition in firm decisions, it provides a more comprehensive perspective on the deferred patent examination system. The study also provides empirical evidences on the broader research topic regarding firm decision for irreversible investment when faced with both uncertainty and competition, for which a strand of theoretical literature exists but empirical literature is largely limited. This study, which explicitly takes into account uncertainty and market competition, extends this line of empirical literature and fills the gap in the literature.

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.