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The metallic alloys and their components fabricated via laser powder bed fusion (LPBF) suffer from the microvoids formed inevitably due to the extreme solidification rate during fabrication, which are impossible to be removed by heat treatment. This paper aims to remove those microvoids in as-built AlSi10Mg alloys by hot forging and enhance their mechanical properties.

AlSi10Mg samples were built using prealloyed powder with a set of optimized LPBF parameters, viz. 350 W of laser power, 1,170 mm/s of scan speed, 50 µm of layer thickness and 0.24 mm of hatch spacing. As-built samples were preheated to 430°C followed by immediate pressing with two different thickness reductions of 10% and 35%. The effect of hot forging on the microstructure was analyzed by means of X-ray diffraction, scanning electron microscopy, electron backscattered diffraction and transmission electron microscopy. Tensile tests were performed to reveal the effect of hot forging on the mechanical properties.

By using hot forging, the large number of microvoids in both as-built and post heat-treated samples were mostly healed. Moreover, the Si particles were finer in forged condition (∼150 nm) compared with those in heat-treated condition (∼300 nm). Tensile tests showed that compared with heat treatment, the hot forging process could noticeably increase tensile strength at no expense of ductility. Consequently, the toughness (integration of tensile stress and strain) of forged alloy increased by ∼86% and ∼24% compared with as-built and heat-treated alloys, respectively.

Hot forging can effectively remove the inevitable microvoids in metals fabricated via LPBF, which is beneficial to the mechanical properties. These findings are inspiring for the evolution of the LPBF technique to eliminate the microvoids and boost the mechanical properties of metals fabricated via LPBF.

This paper aims to study whether the adoption of an entry mode that fits the social trust level contributes to the improvement of foreign subsidiary performance.

The authors used the Probit model, linear regression, strategic fit approach and instrumental variable regression. The sample was made up of 11,095 observations of Chinese multinational enterprises' foreign subsidiaries in 54 countries from 2005 to 2020.

The results suggest that a host country with a high level of social trust results in fewer difficulties for enterprises in gaining legitimacy, thus foreign subsidiaries are more likely to select the wholly owned entry mode. The results also show that the effect is contingent on the formal institutions of host countries. The results of the mechanism test suggest that social trust influences subsidiaries' entry mode choice by reducing information asymmetry, costs and uncertainty risks. This study further finds that selecting a fit entry mode based on social trust level substantially increases foreign subsidiary performance and this effect is more significant when multinational enterprises (MNEs) are state-owned enterprises (SOEs).

The main limitation of this paper is its only focus on foreign subsidiaries of Chinese MNEs, which may limit the generalizability of research findings.

This paper responds to the call for conducting more research on informal institutions. Findings highlight the critical role of informal institutions in helping foreign subsidiaries in gaining legitimacy in host countries and the essentialness of selecting a fit entry mode based on the informal institutions of host countries for the development of foreign subsidiaries.

This study aims to contribute to the existing institutional literature by examining the impact of regional social trust on foreign firm performance.

In this study, 10,286 annual observations of foreign firms in China from 2008 to 2020 are used to test the research hypotheses using an ordinary least square regression model.

Social trust can improve foreign firm performance by reducing operating costs and increasing risk-taking capacity, while formal institutions and economic policy uncertainty strengthen the positive relationship between social trust and foreign firm performance. Moreover, the results of the heterogeneity test show that the positive relationship is only manifested in the samples from the eastern region and is more pronounced in the samples of small- and medium-sized foreign firms and non-manufacturing foreign firms.

This study makes a theoretical contribution to the literature on institutional theory and foreign firm performance, as well as providing practical guidance to foreign firms on how to improve their performance.

When solving the cogging torque of complex electromagnetic structures, such as consequent pole hybrid excitation synchronous (CPHES) machine, traditional methods have a huge computational complexity. The notable feature of CPHES machine is the symmetric range of field-strengthening and field-weakening, but this type of machine is destined to be equipped with a complex electromagnetic structure. The purpose of this paper is to propose a hybrid analysis method to quickly and accurately solve the cogging torque of complex 3D electromagnetic structure, which is applicable to CPHES machine with different magnetic pole shapings.

In this paper, a hybrid method for calculating the cogging torque of CPHES machine is proposed, which considers three commonly used pole shapings. Firstly, through magnetic field analysis, the complex 3D finite element analysis (FEA) is simplified to 2D field computing. Secondly, the discretization method is used to obtain the distribution of permeance and permeance differential along the circumference of the air-gap, taking into account the effect of slots. Finally, the cogging torque of the whole motor is obtained by using the idea of modular calculation and the symmetry of the rotor structure.

This method is applicable to different pole shapings. The experimental results show that the proposed method is consistent with 3D FEA and experimental measured results, and the average calculation time is reduced from 8 h to 4 min.

This paper proposes a new concept for calculating cogging torque, which is a hybrid calculation of dimension reduction and discretization modules. Based on magnetic field analysis, the 3D problem is simplified into a 2D issue, reducing computational complexity. Based on the symmetry of the machine structure, a modeling method for discretized analytical models is proposed to calculate the cogging torque of the machine.

The purpose of this study was to investigate the effects of aging time on the microstructure, mechanical properties and fracture morphology of Cu/Zn160%SAC0307/Al solder joints produced through solid-state bonding.

Zn particles with a size of 1 µm and Sn-0.3Ag-0.7Cu (SAC0307) particles ranging from 20 to 38 µm were used to achieve Cu/Al micro-connections using ultrasonic assistance at a temperature of 180 °C, followed by aging treatment at 150 °C to enhance the quality of Cu/Al joints. Scanning electron microscopy was used for observing and analyzing the solder seam, interface microstructure, and fracture morphology. The structural composition was determined using energy dispersive spectroscopy, while a PTR-1102 bonding tester was used to measure the average shear strength.

The results indicated that the intermetallic compounds formed at the interface between Cu substrates and solder metal primarily consisted of smooth Cu5Zn8. The Al-side interface mainly comprises an Al-Sn-Zn solid solution, with Zn-Sn-Cu phases forming between SAC0307 particles at 180 °C. During the aging process, atomic diffusion was accelerated, leading to improved connection quality. The shear strength of the joints initially increased before decreasing as aging time progressed; it peaked at 32.92 MPa after 24 h – an increase of 76.8% compared to as-received joints. After reaching stability at 96 h, there was still a notable increase in shear strength by 48.4% relative to as-received joints.

This study further explores the strengthening mechanisms associated with solid-state bonded Cu/SACZ/Al joints through aging processes. Joints created via solid-state bonding demonstrate superior reliability compared to traditional soldered connections. It is anticipated that insights gained from this research will contribute valuable knowledge toward developing low-temperature soldering methodologies for heterogeneous materials.

The high-load operation of the engine crankshaft causes severe wear and fatigue. This study aims to prepare in situ textures with effective density and study their wear mechanism on the surface of ductile cast iron, which optimizes the tribological properties of engine crankshafts and reduces wear.

A new method was proposed based on the hardness difference in graphite removal to form an in situ texture. The friction performance was evaluated using a combination of computational fluid dynamics and tribological testings. The influence of the texture characteristic parameters on the bearing capacity of the oil film was analyzed. The surface wear morphology was studied by scanning electron microscopy.

The texture density significantly affected the oil film bearing capacity. The surface texture can reduce the average friction coefficient (COF) by more than 35% owing to the oil film bearing and storage capacity. Specifically, the 13% texture density exhibited the lowest wear rate and COF under all three experimental conditions. The reduction in abrasive particles in the wear area of the textured surface indicates that the surface texture can improve the lubrication mechanism.

This study systematically explored the influence of the weight of each model parameter on tribological properties. Subsequently, focusing on the critical parameter (texture density), detailed tribological testings were carried out to reveal the specific effect of texture density on the wear mechanism under different working conditions, and the optimal texture density to achieve the optimal tribological performance was determined accordingly.

Since the performance of vehicular users and cellular users (CUE) in Vehicular networks is highly affected by the allocated resources to them. The purpose of this paper is to investigate the resource allocation for vehicular communications when multiple V2V links and a V2I link share spectrum with CUE in uplink communication under different Quality of Service (QoS).

An optimization model to maximize the V2I capacity is established based on slowly varying large-scale fading channel information. Multiple V2V links are clustered based on sparrow search algorithm (SSA) to reduce interference. Then, a weighted tripartite graph is constructed by jointly optimizing the power of CUE, V2I and V2V clusters. Finally, spectrum resources are allocated based on a weighted 3D matching algorithm.

The performance of the proposed algorithm is tested. Simulation results show that the proposed algorithm can maximize the channel capacity of V2I while ensuring the reliability of V2V and the quality of service of CUE.

There is a lack of research on resource allocation algorithms of CUE, V2I and multiple V2V in different QoS. To solve the problem, one new resource allocation algorithm is proposed in this paper. Firstly, multiple V2V links are clustered using SSA to reduce interference. Secondly, the power allocation of CUE, V2I and V2V is jointly optimized. Finally, the weighted 3D matching algorithm is used to allocate spectrum resources.

This study aims to examine whether customer trust is influenced by the congruence and incongruence between customers' perceptions of two types of omnichannel integration—perceived transactional integration (PTI) and perceived relational integration (PRI). The authors further considered the perceived effectiveness of e-commerce institutional mechanisms (PEEIM) as the boundary condition of omnichannel integration's effect.

Drawing upon the stereotype content model, this study hypothesizes the influences of PTI and PRI on customer trust wherein PEEIM moderates the relationships. The research model was empirically examined based on the responses surface analysis of survey data collected from 311 omnichannel customers.

Results showed that when PTI and PRI are congruent, customers are inclined to trust brands that have high levels of PTI and PRI rather than low levels of PTI and PRI. Moreover, the incongruence between PTI and PRI is positively related to customer trust. PEEIM was found to weaken the congruence effect while strengthening the incongruence effect. The authors also examined customer distrust as another relational outcome to provide a robust check.

This study uncovers customer cognition of omnichannel integration and examines the influences on customer trust, therefore contributing to our understanding of omnichannel integration's effect from the customer perspective. Findings from this research provide insights for brand managers on deploying channel integration strategies and institutional mechanisms to manage customer trust.

The purpose of this paper is to examine the influence of intelligent manufacturing on audit quality and its underlying mechanism as well as the variation in this influence across different types of organizations.

This research utilizes a difference-in-differences (DID) method to examine how enterprises that apply intelligent manufacturing choose auditors and impact their audit work. The study is based on 15,228 observations of Chinese-listed A-shares from 2011 to 2020.

(1) There is a strong correlation between intelligent manufacturing and audit quality. (2) This positive correlation is statistically significant only in state-owned enterprises (SOEs), those that have steady institutional investors and where the roles of the CEO and chairman are distinct. (3) Enterprises that have implemented intelligent manufacturing are more inclined to employ auditors who possess extensive industry expertise. The auditor's industry expertise plays a crucial role in ensuring audit quality. (4) The adoption of intelligent manufacturing also leads to higher audit fees and longer audit delay periods.

This paper validates the beneficial impact of intelligent manufacturing on improving corporate governance. In addition, it is recommended that managers prioritize the involvement of skilled auditors with specialized knowledge in the industry to ensure the high audit quality and the transparency of information in intelligent manufacturing enterprises.

This study builds upon previous research that has shown the importance of artificial intelligence in enhancing audit procedures. It contributes to the existing body of knowledge by examining how enterprise intelligent manufacturing systems (IMS) enhance audit quality. Additionally, this study provides valuable information on how to improve audit quality in the field of intelligent manufacturing by strategically selecting auditors based on resource dependency theory.

This study aims to examine the effect of digitalization and sanitary measures during the COVID-19 pandemic on corporate social responsibility (CSR) in the African context. While CSR has traditionally been analyzed in developed markets, this paper explores how multinational subsidiaries can leverage CSR practices to create financial opportunities and market stability for themselves and their communities in Africa.

The authors use a panel of data from six listed African companies for the period ranking from January 2006–2022 to analyze the effect of financial performance (FP), digitalization and health measures on the social responsibility of these companies. The authors provide a robust test that improves the understanding of the impact of pandemics and innovation on CSR, using Machine Learning (ML) linear regression.

The results show that the social responsibility of African companies is highly dependent on FP and digitalization. On the other hand, the authors demonstrate that the moderating role of epidemic instability negatively affects social responsibility through FP, but on the other hand strengthens CSR in the presence of digitalization. The results of the initial analysis remain largely unchanged, demonstrating the validity and robustness of the empirical results through ML models. This article highlights some of the obstacles and opportunities for CSR adapted to the crisis context. The authors conclude that adjusting innovation strategies improves the forecasting performance of responsible companies, especially in a context of instability.

The paper clearly shows that CSR literature varies across different regions. Given that the financial market in Africa is characterized by a lack of opportunity for innovation as well as financial stability, this paper represents an important first step in the elaboration of a CSR development strategy. In light of the results presented above, the study makes an important contribution to the literature on CSR, in particular the CSR practices of multinationals in developing countries and also provides CSR managers with various insights into the types of support they will need to leverage and improve the internal underpinnings of their CSR strategies and collaboration.

The results of this study contribute to the understanding of digital transformation in responsible business, offering empirical evidence of its benefits in tackling the health crisis. In addition, the study highlights the role of an innovative approach in enhancing reputation and developing sustainable, trusting relationships with stakeholders.

This research pioneers the academic link between innovation and epidemic crisis in responsible business, filling a notable gap and introducing a new academic perspective. In concrete terms, it provides women entrepreneurs with actionable insights into the digital strategies essential to improving business performance in a context of instability. Methodologically, the study sets a benchmark for research innovation, using ML to provide a reproducible model for exposing robust results and for future research in this evolving field.