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The vulnerability of multinational corporation (MNC) knowledge network is one of the major causes for the failure and even the death of MNCs in the fierce global market competition. Employee turnover and knowledge loss are the triggers for the MNC knowledge network vulnerability and a matter of serious concern in the evolution and development of MNC knowledge network. The purpose of this work is to propose a valid and quantitative measurement method to investigate the influence of employee loss and knowledge loss on the vulnerability of MNC knowledge network.

MNC knowledge network is inherently a heterogeneous network where there are mainly two types of units: employees and their knowledge. Therefore, this paper establishes a weighted super-network model for MNC knowledge network to depict its heterogeneous composition. On the basis of the weighted MNC knowledge super-network, the static and dynamic vulnerability measurement methods are further proposed to investigate and evaluate MNC knowledge network vulnerability.

A real case is given to illustrate the applicability of the proposed weighted MNC knowledge super-network model and the network vulnerability measurement methods. The results show the super-network model proposed in this paper can effectively embody the complex features of MNC knowledge network, and the vulnerability measurement methods can effectively investigate the influence of employee loss and knowledge loss on network vulnerability.

From the perspective of super-network, researchers and practitioners can get a more systematic and deeper understanding of the MNC knowledge network and its human and knowledge resource constitute which are vital for the evolution and development of MNC. Moreover, the MNC knowledge network vulnerability measurement methods can effectively measure and analyze the influence of resource loss on network vulnerability, which can provide a helpful decision support for monitoring and managing of MNC knowledge network vulnerability to reduce its adverse effects.

This study investigates the credit supervision issue in rural e-commerce. By studying the trading strategies of buyers and sellers under different credit supervision measures and the impact of different pricing strategies on the trading strategies of both parties, this paper proposes regulatory suggestions for the increasingly severe credit problems in rural e-commerce.

In the online agricultural product transaction between farmers and consumers, both parties' decision-making is a dynamic process. Using the copying dynamic model of the evolutionary game, this study establishes two evolutionary game models to explore the factors affecting credit supervision in the rural e-commerce transaction process. Then, the study provides corresponding countermeasures and suggestions.

First, credit supervision measures implemented by rural e-commerce platforms and the Government's legal system construction and infrastructure construction guarantees influence both parties' trust choices in rural e-commerce transactions. Second, price is a key factor affecting both parties' trading strategies. In the case of relatively fair prices, the higher the proportion of farmers who choose “low price” and “honest transaction” strategies, the easier that is for consumers to choose to trust farmers. In contrast, the higher the price, the higher the proportion of consumers who choose the “trust farmers” strategy, and the more willing farmers are to choose honest transactions.

This work develops a new approach for analyzing rural e-commerce credit supervision. Moreover, this study helps establish and improve the credit supervision mechanism of rural e-commerce and further realize the long-term sustainable development of the rural economy.

The purpose of this paper is to maraging 18Ni-300 steel fabricate by powder bed based selective laser melting (SLM) process. Microstructure and mechanical properties of the maraging steel part before and after heat treatment at a slow cooling rate were investigated.

The microstructure of the printed part was observed by optical microscopy and scanning electron microscopy. The phases were determined by X-ray diffraction. The surface roughness of the part was recorded by a profilometer. The tensile properties and microhardness of the parts before and after heat treatment were characterized by an electronic universal tensile testing machine and a Vickers hardness tester, respectively.

Maraging 18Ni-300 steel part comprised of the martensitic phase and a small fraction of austenite phase. After heat treatment, the volume fraction of austenite slightly increased. The surface roughness of the part was about 96 µm. The printed part was dense, but irregular pores were present. The yield strength, ultimate tensile strength (UTS), elongation and Young’s modulus of as-fabricated parts were 554.7 MPa, 1173.1 MPa, 10.9% and 128.9 GPa, respectively. The yield strength, UTS, elongation and Young’s modulus of as-treated parts were 2065 MPa, 2225 MPa, 4.2% and 142.5 GPa, respectively. The microhardness values of surface and cross-section of the as-fabricated part were 407.1 HV and 443.0 HV, respectively. After short-time heat treatment, the microhardness values of the surface and cross-section of the part were 542.7 HV and 567.3 HV, respectively. After long-time heat treatment, the microhardness values of the surface and cross-section of the part were 524.4 HV and 454.8 HV, respectively. The microhardness and tensile strength increased significantly with decreasing elongation due to the changes in phases and microstructure of the parts after heat treatment.

This work studied the effect of heat treatment at 550°C combined with a subsequent slow cooling rate on microstructure and mechanical properties of maraging 18Ni-300 steel obtained by the powder bed based SLM process.

Career plateau and employee silence are negative employee management phenomena that should be overcome but are challenging. However, relatively speaking, when employees reach a particular career stage, it is inevitable that the hierarchical plateau in the career plateau will occur, while the phenomena of employee silence have the chance to improve. This paper aims to study the influence mechanism of the career plateau on employee silence in an uncertain environment and then provides theoretical support for enhancing the organizational phenomenon of employee silence.

After considering the effects of career plateau and social desirability of employee silence, this paper obtained 313 samples based on the pilot survey, which were collected anonymously online and offline. Based on passing the data quality test, this experiment uses hierarchical regression, Bootstrap method, interaction graph and slope test to test the mediating variable

The results show a significant positive correlation between career plateau and employees' silent behavior. Affective commitment plays a partial mediating role between career plateau and employees' silent behavior. Organizational justice not only negatively moderated the relationship between career plateau and affective commitment but also negatively moderated the indirect effect of career plateau on silent behavior through affective commitment.

First, based on the theory of uncertainty management and social exchange theory, this paper develops a behavioral response to the organizational environment based on the principle of fair exchange when employees perceive an uncertain environment. This study innovatively applied the two theories together in one study, establishing a link between the two theories. Second, this study explores the influence of career plateau on employee silence and empirically tests the silent behavior based on the previous division of three dimensions of career plateau. The third study explores affective commitment, the black box of the relationship between career plateau and employee silence. This research also enriches the related research on affective commitment.

This study examines the serial mediation mechanism between paternalistic leadership and innovative work behavior through the leader–member exchange (LMX) and employee voice behavior. Particularly, this study utilized the social exchange theory to investigate the indirect effect of three distinct dimensions of paternalistic leadership style on innovative work behavior through LMX and employee voice behavior.

Self-reported questionnaires were used to collect data from 397 employees in Pakistan. Hypotheses were tested using structural equation modeling (SEM).

The two dimensions of paternalistic leadership were significantly related to LMX. LMX had a significant effect on employee voice behavior that was further related to innovative work behavior. The findings also support the mediating role of LMX between authoritarian and moral leadership and employee voice. Further, LMX and employee voice boosted the indirect relationship between moral leadership and innovative behavior. However, authoritarian leadership demonstrated a significant but negative indirect effect on innovative behavior through LMX and employee voice.

The organizational members need to encourage a high LMX and voice behavior to enhance the positive effects of benevolent and moral leadership styles on innovative employee behaviors. Contrarily, they need to discourage authoritarian leadership if they want to enhance innovative work behavior through LMX and employee voice. Furthermore, when leaders provide a safe environment to employees at the workplace, then they may feel secure to take risks and exhibit innovative work behavior, which ultimately contributes to increasing employee and organizational performance.

This study extended the existing literature on paternalistic leadership in two important ways. First, this study examined a serial mediation mechanism to test the effect of paternalistic leadership on innovative work behavior through LMX and voice behavior. Second, this is a key study to investigate which dimension of paternalistic leadership is effective to boost employees' innovative work behavior at the individual level in the Pakistani organizational context.

The problem of parameter identification for biaxial piezoelectric stages is still a challenging task because of the existing hysteresis, dynamics and cross-axis coupling. This study aims to find an accurate and systematic approach to tackle this problem.

First, a dual-input and dual-output (DIDO) model with Duhem-type hysteresis is proposed to depict the dynamic behavior of the biaxial piezoelectric stage. Then, a systematic identification approach based on a modified differential evolution (DE) algorithm is proposed to identify the unknown parameters of the Duhem-type DIDO model for a biaxial piezostage. The randomness and parallelism of the modified DE algorithm guarantee its high efficiency.

The experimental results show that the characteristics of the biaxial piezoelectric stage can be identified with adequate accuracy based on the input–output data, and the peak-valley errors account for 2.8% of the full range in the X direction and 1.5% in the Y direction. The attained results validated the correctness and effectiveness of the presented identification method.

The classical DE algorithm has many adjustment parameters, which increases the inconvenience and difficulty of using in practice. The parameter identification of Duhem-type DIDO piezoelectric model is rarely studied in detail and its successful application based on DE algorithm on a biaxial piezostage is hitherto unexplored. To close this gap, this work proposed a modified DE-based systematic identification approach. It not only can identify this complicated model with more parameters, but also has little tuning parameters and thus is easy to use.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

The determination of parameters of Duhem model that can describe piezoelectric hysteresis is usually a great challenge. The purpose of this paper is to find a way to identify the parameters of Duhem model by using a modified bee colony algorithm.

The promising bee colony algorithm has great potential to identify hysteresis nonlinearity, but has not yet been used to identify the Duhem-type hysteresis in the literatures. To explore this possibility, the classical bee colony algorithm is modified to enhance its performance regarding both searching capability and convergence speed. In the modification, the current optimal solution is used to guide the search direction, which can balance the local and global searching ability. Moreover, a new searching formula for scout bees is proposed to enhance the convergence ability of the algorithm.

Through a series of experiments, the modified algorithm can attain the optimal parameters with a 0.61 µm peak valley error and a 0.12 µm root-mean-square error. Compared to the particle swarm optimization and classical bee colony algorithms, the modified bee colony algorithm can reach higher parameter identification accuracy. Based on 50 trials, the robustness of the posed algorithm was also proved.

The well-performed modified bee colony algorithm is a good candidate in parameter identification of Duhem-type hysteresis nonlinear systems. As there is no work studying the parameter identification of Duhem model using a bee colony algorithm in the literatures, this work closed this gap and explored the ability of bee colony algorithm to identify piezoelectric hysteresis with superb accuracy and robustness.

The traditional Chinese culture has always emphasized the authority of leaders and their “top-down” influence over subordinates tangled with “bottom-up” management. Paternalistic leadership can both nurture and restrict growth in mega-construction projects, due to the unique consequences (i.e. positive vs negative implications) for project teams. Hence, the present study aimed to explore the impact of paternalistic leadership (PL), team members’ voice (TMV) and team resilience (TR) on the mega-construction project success (MPS) in China's Belt and Road Initiative (BRI).

A surveyed-based sample of project professionals (N = 563) directly linked with the BRI was employed for statistical estimations with partial least squares (PLS) structural equation modeling (SEM).

Paternalistic leadership styles, including authoritarian leadership (AL), moral leadership (ML) and benevolent leadership (BL), significantly influence the mega-construction project success in BRI. The findings empirically validated that both BL and ML increase the likelihood of mega-construction project success. However, AL could impose a threat through its underlying negative influence. In addition, leaders with benevolence and morality have a positive influence on TMV and TR, while leaders with authoritarianism signal a negative impact. Furthermore, both TMV and TR significantly and positively mediate the relationships between AL-MPS (Model-1), BL-MPS (Model-2) and ML-MPS (Model-3), respectively.

The present study is a groundbreaking endeavor that fills a crucial research gap by investigating mega-construction project success in the BRI through paternalistic leadership, project team members' voice and team resilience in a multi-mediation model. These novel findings offer valuable strategic insights for managing mega-construction projects in countries with paternalistic solid cultural foundations, enabling project managers to navigate cultural nuances and optimize megaproject outcomes.

The demand to reduce carbon emissions has become an increasingly important social factor due to the unprecedented impacts of climate change. However, most existing publications have focused on minimizing emissions during the operational phase of buildings. At the same time, there is a lack of comprehensive research conducted on carbon emissions, specifically during the construction phase. The purpose of this paper is to identify, review and classify current practices related to carbon emissions management in construction operations to gain greater insight into how to reduce and mitigate emissions and achieve more sustainable solutions.

This study reviewed the published literature on carbon emissions from construction. A total of 198 bibliographic records were extracted from the Scopus collection database and analyzed using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). PRISMA is used as a basis for reporting possible trends, research methods and strategies used in published literatures. A total of 99 papers related to carbon emissions in the construction operations were further reviewed and analyzed. This review paper draws on existing research and identifies current carbon management patterns in construction projects.

Data indicated an upward trend in the number of publications in carbon emissions research during the last few years, particularly in 2015, 2017 and 2019. The most significant contributions to the domain were reported from China, Europe and the USA. This paper found that most studies conduct the Life Cycle Assessment (LCA) method to estimate carbon emissions. This paper found that the primary studies have focused on construction machinery and equipment emissions. The strategies such as establishing uniform standards for carbon emissions policies and regulations, equipment and logistic planning and low carbon design material will potentially impact carbon emissions reductions.

This paper provides information that will be beneficial for the construction industry to design and manage construction operations. It will also be of interest to those looking to reduce or manage construction emissions.

Although there is a diversity of current thinking related to the practical estimation and management of carbon emissions in construction projects, there is no consolidated set of keys of standardized carbon emissions management in practice. By assessing the existing paradigms of carbon assessment methods and tactics in the construction industry, this study contributed to the existing knowledge base by providing insights into current techniques in the construction sector for monitoring and mitigating emissions.