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This paper aims to examine the influence of the interplay between servant leadership behaviors and Machiavellianism on leader effectiveness.

Drawing on trait activation theory and motivation to lead theory, the authors hypothesize that the effect of servant leadership behaviors on perceived leadership effectiveness is manifested differently in teams with high-Machiavellian vs. low-Machiavellian leaders. In teams with low-Machiavellian leaders, servant leadership behaviors are expected to be associated with a cooperative way of handling team conflicts, which enhances employees' leader effectiveness ratings. In contrast, in teams with high-Machiavellian leaders, this mediation role vanishes due to the incongruency between Machiavellian traits and the cooperative context. The authors conducted a two-wave survey-based study and tested the hypotheses with a matched supervisor-employee sample from 310 employees and their leaders in 91 teams.

The results showed that servant leadership behaviors positively impact leadership effectiveness and that this effect takes place through cooperative team conflict management (TCM) without controlling for leaders' Machiavellian trait. Further analysis shows this mediation mechanism is only strong and significant in teams led by low-Machiavellian leaders, but not high-Machiavellian leaders.

To the authors’ best knowledge, this is the first study that examines the interplay of servant leadership behaviors and Machiavellianism on perceived leader effectiveness.

本文旨在探討僕人式領導行為與馬基雅維利主義之間的相互作用會如何影響領導效能。

我們根據特質激活理論和領導動機理論、建立了一個假設，這個假設就是： 僕人式領導行為對感知的領導效能所產生並顯示出來的影響、是會視乎團隊是高/強馬基雅維利主義，還是低/弱馬基雅維利主義而有所分別的。若團隊的領導者是低/弱馬基雅維利主義的話，僕人式領導行為大概會與使用合作的方式去處理團隊衝突有相互之關聯，這會提高僱員對領導效能的評分。與此相反，若團隊的領導者是高/強馬基雅維利主義的話，這調節作用和角色將會因馬基雅維利主義的特質與合作的環境之間存在著不協調而消失。我們進行了一個兩波的、以及基於調查的研究，在這研究中，我們利用管理者和員工相應的樣本來測試各個假設;這些樣本包括91個團隊內的310名員工及其領導者。

研究結果顯示、僕人式領導行為對領導效能會產生積極的影響，而這影響是透過以合作方式管理團隊衝突而產生的，亦沒有對領導者的馬基雅維利主義特質加以管控。我們進一步的分析顯示、這調節機制只會在由低/弱馬基雅維利主義的領導者領導的團隊內顯得強烈和顯著，但若領導者是高/強馬基雅維利主義的話，情況就不一樣了。

盡我們所知，本研究為首個研究、去探討僕人式領導行為與馬基雅維利主義之間的相互作用會如何影響感知的領導效能。

This article provides deeper insights into the measurement of servant leadership within the Chinese culture. Servant leadership is viewed as a responsible leadership style that is beneficial to organizations by awaking, engaging and developing employees and working from a sense of service and stewardship for the world with a long-term perspective.

The paper consists of a survey study that examines the relationships between 5 servant leadership measures translated into Chinese and outcome measures using a sample of 463 participants.

The authors' results show that the five measures are very comparable. Although some differences exist, the combined conclusions from internal consistency, intercorrelations and correlations to outcome variables and factor analysis confirmed their overall commonality. A core group of 11 items is introduced as a potential scale to represent the underlying variance of all 55 items.

This study validates how the five instruments are grounded in the core aspects of servant leadership described by Robert Greenleaf, the service aspect of choosing to become a leader and the importance for a leader to give attention to the followers' personal growth, meaningful work and well-being.

Two studies are designed to address the research questions including an experimental study and a field study. The experimental study manipulated Servant Leadership (SL vs. non-SL), leaders' Machiavellianism (H-Mach vs L-Mach), and leaders' gender (male vs. female), and measured leadership effectiveness. The second study is a survey study that collected data from employees regarding their interaction with supervisors and their perceptions of supervisors' leadership behaviors.

Leadership behaviors can correspond to or deviate from leaders' personality traits. This study aims to study the interplay of two seemingly opposite constructs in leadership – a power-pursuing and manipulation-oriented trait (i.e. Machiavellianism) and an other-oriented leadership style (i.e. servant leadership behaviors) by examining whether the effect of servant leadership behaviors on perceived leadership effectiveness varies across high and low levels of Machiavellian traits. Furthermore, built upon gender role congruency theory, the researchers pay particular attention to the (leader) gender's role in the paradox of Machiavellian traits and servant leadership behaviors.

Results from the two studies show that the relationship between servant leadership behaviors and followers' ratings of leaders' effectiveness varies with leaders' Machiavellian traits. More engagement in servant leadership behaviors serves as a remedy for high-Mach leaders to achieve leadership effectiveness, and this remedy effect tends to be greater for women leaders.

To the authors' best knowledge, this is one of the first attempts that examine the interplay of servant leadership behaviors and Machiavellianism on perceived leader effectiveness. The authors also contribute to the gender leadership literature by providing evidence for the contingencies of leaders' genders when employees evaluate leadership effectiveness with consideration for the dual demands for agency and communion from women leaders.

Although a laser profile sensor (LPS) can be used to measure dimensions, the “shadow region” generally degrades the accuracy and precision of width measurements. The accuracy and precision of such measurements should be improved.

In this paper, the authors propose herein a technique that combines high dynamic range (HDR) imaging with logistic fitting. First, a HDR image is composed of several images acquired with different exposure times, which augments the grayscale of the object profile and significantly reduces overexposure. Next, the profile is fit to a logistic function, which provides accurate and precise edge coordinates. Finally, given the edge coordinates, the object width is calculated.

To verify the stability of this logistic algorithm, the authors simulate different noise conditions and different degrees of incomplete edge data. In addition, the progressiveness of the algorithm is demonstrated by comparing the results with those of other algorithms and with the height measurement. Furthermore, the suitability of the system is verified experimentally.

Because of the limitation of the condition of laboratory, in the experimental section, this paper cannot represent perfectly the industrial situation. It makes this section limited in demonstration.

In this paper, the results show that the measurement accuracy and precision of the width is improved and exceeds that of the height measurement. The proposed HDR imaging method with logistic fitting may be applied to LPS width measurements, which should significantly aid the development of LPSs.

The purpose of this paper is to identify different automotive coatings using Confocal Raman microscope which could hardly be differentiated with Fourier transform infrared microscope (FTIR).

Raman spectroscopy was used to provide extra vibration information to infrared spectroscopy. Paints preparation was not necessary, and only 30 s was needed for each sample in an optimised method. Paints were first analysed by FTIR and then compared with Raman microscope.

Raman microscope was used to address the lack of ability of FTIR in discriminating four groups of paints in same colours. This study indicated that Raman microscopy is especially effective in sensing pigments and could successfully identify all pigments in the paints.

The two instruments in combination produce accurate results than when used individually, especially in complex and multi-layered paints analysis.

The method proved to be fast, accurate and non-destructive, and it could be easily applied to real cases.

With this method, scientists could discriminate some coating types which were hard to be discriminated by other techniques.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

The purpose of the research is to assess the risk of the financial market in the digital economy through the quantitative analysis model in the big data era. It is a big challenge for the government to carry out financial market risk management in the big data era.

In this study, a generalized autoregressive conditional heteroskedasticity-vector autoregression (GARCH-VaR) model is constructed to analyze the big data financial market in the digital economy. Additionally, the correlation test and stationarity test are carried out to construct the best fit model and get the corresponding VaR value.

Owing to the conditional heteroscedasticity, the index return series shows the leptokurtic and fat tail phenomenon. According to the AIC (Akaike information criterion), the fitting degree of the GARCH model is measured. The AIC value difference of the models under the three distributions is not obvious, and the differences between them can be ignored.

Using the GARCH-VaR model can better measure and predict the risk of the big data finance market and provide a reliable and quantitative basis for the current technology-driven regulation in the digital economy.

This study aims to thoroughly explore and visualize the trends and developments of digital twin (DT) literature in the construction field while revealing future research directions for further exploration and exploitation.

The research follows a three-stage methodology. First, the bibliographic data is acquired using the Web of Science database. Second, the bibliometric methods are defined to include co-authorship analysis, citation analysis, keywords co-occurrence, thematic mapping while the software tools include MS Excel, VOSviewer and Biblioshiny. Third, analysis and findings include yearly DT publication output, influential DT publications, leading DT contributors, top DT sources and science mapping of DT literature.

This study identifies top-cited DT publications (35 out of 320) in terms of citations score, local citations score and document average citations per year. Furthermore, the key contributors with respect to authors (58 out of 1147), organizations (55 out of 427) and countries (19 out of 51) are recognized in terms of productivity, influence, activeness and scientific value. Similarly, the major publishing sources (24 out of 58) are identified using the same measures. Regarding science mapping, the DT domain comprises four research frontiers, namely, deep learning and smart city, internet of things and blockchain, DT and building information modeling and machine learning and asset management.

Through a mixed-review strategy, this study introduces a comprehensive analysis of DT literature while avoiding the subjectivity/cognitive bias of traditional review approaches. Moreover, it illuminates the promising and rising DT themes for new/seasoned researchers, institutions, editorial boards and funding agencies.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

Despite the growing body of empirical research on leader anger expressions, the issue of how and when leader anger expressions shape newcomers’ proactive career behavior and work alienation in the construction industry has been largely overlooked. Building upon social information processing theory, this research identifies newcomers’ organization-based self-esteem as a mediator, and suggests that newcomers’ performance goal orientation could moderate the relationship.

A questionnaire study was conducted on the construction industry in China, and the PROCESS program developed by Hayes was used to test the hypothetical model with 215 valid cases.

The results suggest that leader anger expressions are negatively associated with newcomers’ organization-based self-esteem, and organization-based self-esteem mediated the link between leader anger expressions and newcomers’ proactive career behavior and work alienation. Furthermore, the newcomers’ performance goal orientation moderates the negative impact of leader anger expressions on newcomers’ organization-based self-esteem.

Due to the cross-sectional nature of this study, causal implications are difficult to draw. Moreover, all data we received was based on participant self-reports, which may raise concerns about common method variance.

In this paper, we contribute to a deeper understanding of the mediating mechanisms and boundary conditions by which leader anger expressions influence newcomers’ proactive career behavior and work alienation from social information processing perspective, in addition to providing valuable insights for management of newcomers in the construction industry.