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Silence is a commonly seen phenomenon at the workplace. However, little is known about the cause and effect of leader silence. Drawing on the affective events theory, we develop a moderated mediation model to examine the effect of subordinates’ creative deviance on leader's authoritative silence and test the moderating effect of subordinates’ political skills.

Our research adopts a novel bottom-up perspective to investigate the subordinates’ influence on leader silence. A two-wave survey study involving 196 corporate team leaders in China was employed.

We found that leader’s workplace anxiety mediated the relationship between subordinates' creative deviance and leader's authoritative silence and subordinates’ political skills moderated the mediating effect.

Our research contributes to the leader silence literature in three folds. First, we employ the AET framework to study leader silence from the emotional perspective. Second, this research adopts a bottom-up angle to reveal the influence of subordinates’ behavior on leader silence. Third, the political skills lens offers novel explanation of why the anxious emotions triggered by followers’ creative deviance vary among leaders.

The development of an effective corporate vision is a necessary issue for corporate performance, and it is a key issue for corporate sustainable development as well. The recognition of questions like “what is the role of corporate vision in corporate performance” is directly related to the attitude and practice of entrepreneurs and managers toward the development of corporate vision as well as the effectiveness of the corporate vision itself. To better answer the questions concerning the role of corporate vision development and effectively guide the practice of corporations, the authors study the pathways and mechanisms by which corporate visions operate to assist businesses in achieving high performance.

The article completes the construction of indicators to measure each dimension of the corporate vision in line with social cognitive theory and analyzes the relationship between corporate vision and corporate performance by combining qualitative comparative analysis (QCA) and necessary condition analysis (NCA) research methods. The article provides insights into the logic of constructing and adjusting corporate visions from a process perspective.

The mechanisms by which corporate visions can be articulated, accepted and transformed within the organization are also the means by which corporate visions can improve corporate performance. In a dynamic environment, the corporate vision setting and acceptance process integrates the requirements of various stakeholders, leading to the adjustment and acceptance of the corporate vision. As a result, the vision has continuous validity in a changing environment. Both start-ups and non-start-ups can benefit from the guidance provided by a strong corporate vision in overcoming a variety of issues and obstacles to produce strong business performance.

This is the first study that shows the relationship between corporate vision and corporate performance from a process perspective. The authors are interested in understanding which characteristics for building a corporate vision are more accepted by organizational members and, in turn, create high corporate performance. The authors also explore the conditions for corporate vision acceptance. This research has positive implications for shedding some light on the mechanisms by which corporate visions improve corporate performance.

This paper aims to develop a flexible manufacturing method for multimaterial sand molds to realize efficient additive manufacturing of multimaterial sand molds.

To study the influence of multimaterial sand laying process parameters on the quality of powder bed and optimize the design of multimaterial sand laying device. Numerical simulation and X-ray Computed Tomography are used to study the penetration behavior and curing morphology of resin in different sand particles.

The surface roughness and porosity of the multimaterial powder bed that meet the requirements of sand-based additive manufacturing can be obtained under the optimal printing process, that is, the sanding speed of 140.0 mm/s and sanding roller diameter of 15.0 mm. The resin penetration process of the multimaterial sand molds shows a pattern of transverse expansion and longitudinal penetration. In terms of the resin curing morphology, the maximum thickness of the resin film layer of zircon sand reaches 30.5 ± 1.0 µm, which has the best tensile property, followed by silica sand and the thinnest resin film layer of chromite sand.

In this work, a highly flexible integrated combined sand-laying device suitable for multimaterial sand-laying tests is developed, which can obtain a multimaterial powder bed that meets the needs of sand additive manufacturing. Subsequent casting print tests also verify that the program can meet the needs of multimaterial sand mold additive manufacturing.

In public firms, the largest shareholder can make decisions on cash dividends in favor of its own interests at the expense of other investors. While the second largest shareholder can actively participate in corporate governance and protect the interests of investors, its impact has not been fully understood. This research investigates how shareholding ratio and ownership type of the second largest shareholder moderate the relationship between controlling shareholder's shareholding ratio and cash dividends.

The authors conducted econometrics analysis based on a panel data of China's A-share listed companies from 2007 to 2017.

The authors find that the controlling shareholder's shareholding ratio has a significant negative impact on cash dividends. However, this influence is conditional on the shareholding ratio of the second largest shareholder. The negative impact is weakened when the second largest shareholder holds a large proportion of shares or when the shareholding gap between the second largest and the controlling shareholder is small.

This research extends the existing literature by highlighting the nuanced moderating effect of the second largest shareholder on the relationship between the controlling shareholder and cash dividends, thus making a unique contribution to the understanding of corporate governances in the emerging financial market in China.

Homophily, a prominent phenomenon in social networking, profoundly shapes user behaviors on social media but has not been well studied in the livestream commerce context. This study aims to investigate its moderation role in leveraging the effects of key livestream commerce factors – perceived expertise of live streamers and perceived interaction during live streaming – on audience trust, a critical determinant of purchase intentions.

A survey was conducted among livestream shoppers on Taobao. A sample of 313 responses was analyzed. SPSS (version 29) was used for general statistical analysis. The partial least squares structural equation modeling approach with SmartPLS 4.1 software was used to assess the research model and hypotheses.

The results reveal noteworthy differential effects of homophily: it negatively moderates the expertise–trust association but positively moderates the interaction–trust relationship. When the audience perceives strong homophily with live streamers, their trust in these live streamers becomes increasingly contingent on the level of interaction, whereas the effect of perceived expertise diminishes.

The insights on the differential effects of homophily are novel to the literature. These findings extend theoretical understanding of the homophily effect and provide valuable guidance for live streamers, marketers and platforms seeking to reinforce audience trust and drive purchase intentions in livestream commerce.

Manufacturing systems have undergone radical changes because of the implementation of physical and digital innovating technologies with high levels of connectivity, interoperability and autonomy. In this regard, the objective of this study was to investigate whether industrial engineers graduated in recent years in Brazil are prepared or not to work in companies and industries within the scope of Industry 4.0 technologies in a way that they positively contribute to the implementation and management of such technologies.

To achieve these objectives, a literature review and a survey on managers of the industrial sector acting in Brazil were carried out as the research strategies. The data collected were analyzed through a quantitative approach by means of the structural equations modeling method.

The hypothesis that the competencies of industrial engineers currently graduating in Brazil have a positive impact on the implementation and management of Industry 4.0 technologies has been confirmed. Predicting the evolution of production scenarios, understanding the interaction between organizations and their impacts on competitiveness and keeping abreast of technological advancements, organizing them and putting them to the service of business and societal demands were the competencies that obtained the highest factor loadings in the construct of industrial engineer competencies. In addition, cloud manufacturing, automation and robotization were the competencies that obtained the highest factor loadings in the industry 4.0 construct.

The analysis of skills development stands out as a source of competitive advantage for companies that intend to transition to a production system aligned with the principles of Industry 4.0, considering the training of professionals in an emerging economy context.

Based on the perspective of knowledge management, this study aims to discuss how to build cross-city emergency management collaboration mechanism in major emergencies and explore the important role of knowledge management in emergency management collaboration.

Based on the theoretical analysis of knowledge management and the typical case study of cross-city emergency management collaborative rescue, this study provides an in-depth analysis of how these cities achieve high emergency management performance through multidimensional and multilevel knowledge collaboration, thus revealing the mechanism of knowledge transfer, integration and sharing in achieving high emergency management performance.

Through analyzing typical cases, this study finds that building a smooth mechanism for multichannel emergency rescue information can promote the diversification of knowledge transfer methods, building a platform-based integration mechanism for emergency rescue information can enhance knowledge integration capabilities and building a linkage mechanism for emergency rescue materials between cities can promote knowledge-sharing level, thereby improving emergency management performance level.

This study has great significance for how to build cross-city emergency management collaboration mechanism in the digital era. In the future, the authors need to further discuss the following two aspects in depth: research on the impact of cross-city emergency management collaboration mechanism on improving the knowledge management capabilities of government emergency management departments; and research on the impact mechanism of knowledge management capabilities on city resilience.

Through case analysis of cross-city emergency management collaborative rescue for major emergencies in China in recent years, this study proposes three specific strategies for cross-city emergency management (smooth, integration and linkage mechanisms) and reveals that these three strategies are essentially aimed at improving the government’s knowledge management level.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

The objective of this study is to accurately predict the cost of green buildings to provide quantifiable criteria for investment decisions from investors.

This study proposes a hybrid prediction model ML-based for cost prediction of GBPs and obtains prediction parameters (PPs) associated with project characteristics through data mining (DM) techniques. The model integrates a principal component analysis (PCA) method to perform parameter dimensionality reduction (PDR) on a large number of raw variables to provide independent characteristic terms. Moreover, the support vector machine (SVM) algorithm is improved to optimize the prediction results and integrated with parameter dimensionality reduction and cost prediction.

The prediction results show that the mean absolute and relative errors of the hybrid prediction model proposed in this study are equal to 39.78 and 0.02, respectively, which are much lower than those of the traditional SVM model and MRA prediction model. Moreover, the hybrid prediction model with parameter dimensionality reduction also achieved better prediction accuracy (R² = 0.319) and superior prediction accuracy for different cost terms.

Theoretically, the hybrid prediction model developed in this study can reliably predict the cost while accurately capturing the characteristics of GBPs, which is a bold attempt at a comprehensive approach. Practically, this study provides developers with a new ML-based prediction model that is capable of capturing the costs of projects with ambiguous definitions and complex characteristics.

This paper aims to conduct research on the role of vertical interlocks of executives in blocking adverse loops between research and development (R&D) investment and the cost of equity capital and explore the action path of vertical interlocks of executives. This paper also analyzes the differences in the effect of vertical interlocks of chairman, vertical interlocks of chief executive officer (CEO) and vertical interlocks of CEO duality.

This paper uses 28,078 firm-year samples from Chinese A-share listed companies to study the impact of R&D investment on the cost of equity capital using univariate group analysis and multiple regression methods. This paper analyzes the role of vertical interlocks of executives in reducing the positive impact of R&D investment on the cost of equity capital by constructing interaction variables, by using group testing method to analyze the differences in the vertical interlocks of executives. This study also uses propensity score matching and instrumental variables to conduct robustness tests.

The vertical interlocks of executives can block adverse loops between R&D investment and the cost of equity capital. The role of executive vertical interlocks is more prominent in non-state-owned firms, mainly exerting the resource effect that supports the innovation of non-state-owned firms, including the information resource effect and the financial resource effect. Through heterogeneity analysis, this paper discovered that the role of vertical interlocks of chairman is greater than that of the CEO and the CEO duality.

Based on the perspective of the correlation effect generated by vertical interlocks of executives, this paper analyzes the path of promoting corporate innovation. This provides new empirical evidence for studying the collaborative governance effect of vertical interlocks of executives “supervision effect, financial resource effect and information resource effect.” This study provides useful insights for regulatory authorities to regulate and guide development of the vertical interlocks of executives.