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Soy protein has been considered as a renewable and environmentally friendly source of adhesives. The purpose of this paper is to investigate a new approach for making a soy protein adhesive modified by SiO₂ nanoparticles.

The objective of this investigation was to evaluate the adhesive properties by determining the viscosity, wettability and shear strength of soy protein adhesive. The effects of nano‐SiO₂ content, wood surface roughness and processing pressure on shear strength between soy protein adhesive and wood were investigated. Four nano‐SiO₂ contents (0, 0.5, 1 and 2 percent), two wood surface roughness (40 and 280 grits), and two processing pressure (1 and 2 MPa) were tested. Adhesive performance was evaluated based on the maximum force required for shearing the adhesive bond between cherry wood pieces.

The modified soy protein adhesives by SiO₂ nanoparticles showed a significant enhancement in dry strength with nano‐SiO₂ content of 1 percent. The mechanism appears to be related to the increased interaction between adhesive and wood and the elimination of voids on the wood surface by SiO₂ nanoparticles.

The adhesive resins used in the present context was soy protein isolate, not from commercially available soy flour. The wet strength was not satisfactory. Further study is needed to solve this problem.

The method developed provided a simple and practical solution to improving the shear strength of soy protein adhesives.

The enhancement method for adhesion strength of soy protein was novel and could find numerous applications in wood industry, avoiding formaldehyde emission and reducing the dependence on petroleum products.

The purpose of this paper is to design a new type of magnetic suction wall-climbing robot suitable for the wall inspection of wind turbine towers to solve the problems in manual maintenance tasks.

By analyzing the shortcomings of existing wall-climbing robots, a magnetic suction integrated wheel structure is designed to effectively combine the adsorption structure and transmission structure. To enable the robot to adapt to the curvature of the wall surface of a wind turbine tower, a passive adaptive curvature structure is designed. The effects of the air gap, the thickness of the wheel plates on both sides, the size of permanent magnets and the size of aluminum rings on the adsorption force are studied. Through mechanical model analysis under different instability conditions, the magnetic circuit of the magnetic wheel is optimized and designed.

Applying the wall-climbing robot to engineering practice, experiments have shown that the developed wall-climbing robot can move safely and stably on the wall of the wind turbine tower. The robot can also carry a load of 20 kg, and the designed adaptive structure can cause the magnetic wheel to deflect up to 20° relative to the vehicle body, fully meeting the curvature requirements of the minimum diameter end of the wind turbine tower.

This paper proposes a magnetic suction integrated wheel structure through analysis of the working environment. And the parameters affecting the magnetic wheel adsorption performance were optimized. Meanwhile, a passive adaptive wind turbine tower curvature structure was proposed.

This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

This paper aims to solve the problem of uncertain position and attitude between unstructured terrain robot and grasped target and insufficient control accuracy in extreme environment, a grasping mechanism based on attraction domain relationship is proposed, which can realize autonomous positioning, capturing and grasping of robot under low control accuracy.

The grasping mechanism was designed, taking inspiration from fishing behavior this mechanism introduces attraction domains and flexible-elastic structures through the active and passive ends to achieve automatic positioning and capture. After the capture is completed, the grasping mechanism connects the active end and the passive end, simultaneously relying on the gravity of the target object to achieve locking and release between the robot and the target object. This paper adopts theoretical, simulation and experimental verification methods to conduct theoretical and simulation analysis on the autonomous positioning and grasping process of the mechanism, and produces grasping experimental prototypes with different positions and postures.

The experiment shows that the gripping mechanism designed in this paper can achieve automatic positioning capture and gripping of large deviation situations under low control accuracy, with a displacement deviation of up to 10 mm (about 1/6 diameter of the end of the mechanism) and an angle deviation of up to 3°. The scientific research task in the extremely high altitude environment has finally been successfully accomplished.

Inspired by fishing behavior, this paper proposes a positioning, capturing and grasping mechanism. The attraction area built with permanent magnets, coupled with the flexible connection, enables precise capture under low control, while the grasping mechanism can also rely on gravity to self-lock and release.

The purpose of this study is to put forward a high-strength bolt end-plate connection of prefabricated concrete beam-column joint and carry out the pseudo-static test.

ABAQUS finite element software is used to study the fire resistance performance of high-strength bolt end-plate prefabricated joint. This mainly considers the influence of axial compression ratio, screw preload, end-plate thickness and steel hoop thickness.

The results show that the thickness of end-plate and steel hoop has a certain effect on the fire resistance. The change of screw preload has little effect on the fire resistance limit. Compared with the cast-in-place concrete beam-column joint, the deformation trend of column-beam end of the fabricated joint is basically the same as that of cast-in-place joint.

To study the mechanical performance of this kind of joint more comprehensively, the finite element software is used to study the prefabricated concrete beam-column joint with end-plates, and the effects of axial compression ratio, screw preload, end-plate thickness and steel hoop thickness on the fire resistance of joints are mainly considered.

To present the detailed implementation processes of the IDEAL algorithm for two-dimensional compressible flows based on Delaunay triangular mesh, and compare the performance of the SIMPLE and IDEAL algorithms for solving compressible problems. What’s more, the implementation processes of Delaunay mesh generation and derivation of the pressure correction equation are also introduced.

Programming completely in C++.

Five compressible examples are used to test the SIMPLE and IDEAL algorithms, and the comparison with measurement data shows good agreement. The IDEAL algorithm has much better performance in both convergence rate and stability over the SIMPLE algorithm.

The detail solution procedure of implementing the IDEAL algorithm for compressible flows based on Delaunay triangular mesh is presented in this work, seemingly first in the literature.

By adopting learning theory and a guanxi perspective, this study aims to investigate the effects of interpersonal guanxi (interpersonal networks or connections) and relationship learning on companies’ business performance when operating in a large emerging market.

Using a sample of 294 sales managers and salespeople in the Chinese hotel sector, the authors empirically test the authors' arguments through a structural equation modeling (SEM) approach.

The authors' findings indicate that strong interpersonal guanxi tends to generate more positive business performance. Furthermore, the authors find that relationship learning plays a mediating role in the association between interpersonal guanxi and hotel companies’ business performance in a Chinese context. Finally, the authors empirically explore the moderating effect of inter-firm dependence on the contribution of interpersonal guanxi to relationship learning. Findings demonstrate that this effect varies significantly based on inter-firm dependence, with interpersonal guanxi exhibiting a greater positive impact if such dependence is high.

This study enriches our understanding of interpersonal guanxi and of how companies can enhance the companies' business performance in an emerging market context.

Despite the growing and widespread importance of exploring the primary factors facilitating global value chain (GVC) and supply chain management, this topic has received surprisingly little attention to date. Drawing upon the technology–organization–environment framework and the resource-based view, this study aims to fill these important gaps in the literature by theorizing and developing a comprehensive model to explain how a foreign subsidiary of multinational enterprises can improve the upgrading of the GVC and supply chain performance in a host market.

Using survey data collected from 266 foreign subsidiaries of multinational enterprises operating in the Chinese manufacturing sector, this study empirically examines the theoretical framework using a structural equation modeling approach.

The results demonstrated that the relative advantages of digital technology, supplier diversification and environmental uncertainty all contribute positively to the development of foreign subsidiaries’ supply chain management capabilities. Meanwhile, supply chain management capability plays a positive role in foreign subsidiaries facilitating GVC upgrading and enhancing supply chain performance.

The findings of this study provide many important implications and useful insights to foreign subsidiaries operating in an emerging host market by concentrating on how to develop and maintain their competitive advantages in the process of GVC reshaping and supply chain restructuring.

This study provides a useful guide to help firms better understand how they may develop and enhance their competitive advantages in upgrading their GVCs and implementing supply chain restructuring. In addition, this research generates important policy implications considering the recent trend toward creating more effective and sustainable global supply value chains.

Although extant research has provided vast knowledge on the determinants of new product development (NPD) success, prior work is generally bounded to the framework of developed economies. Thus, research dealing with NPD, specifically in the emerging-market context, is still in its infancy. The purpose of this paper is to advance our current understanding on the determinants of NPD performance of emerging-market multinationals (EMMs) by exploring how international knowledge exploration plays a part in the international NPD performance of these firms. Furthermore, it examines how such contribution is contingent on EMMs’ international networking effectiveness and environmental dynamism that draws on the “fit” concept.

To empirically test the theoretical model, the authors draw on a sample of 179 high-technology firms from China, which is the world’s largest emerging market.

Results strongly support the hypothesis that international knowledge exploration positively affects international NPD performance. The analyses of moderating effects indicate that EMMs that are more effective in networking with global network partners and experience a low level of environmental dynamism are likely to achieve better financial performance in NPD.

This study advances our understanding on how and under what conditions EMMs can overcome their knowledge-disadvantaged position and achieve NPD success in global markets by highlighting the important role of international knowledge exploration and possible contingencies. Thus, it contributes to the literature on EMM and innovation.

How much variance in firm performance can be attributed to firms’ corporate political activities (CPA)? Under what conditions does CPA contribute to firm performance? To theorize and empirically tackle these questions, we build on the resource-based view (RBV) to theorize how CPA might improve or hinder firm performance, and specifically examine the direct relationship between firms’ investments in lobbying activities and their performance. We also expect firm growth rate to moderate the relationship between lobbying and performance.

We empirically test our hypotheses using large-scale longitudinal panel data from publicly traded US firms from 2008 to 2018.

Our analyses support our predictions of the double-edged sword effect of lobbying on firm performance. Moreover, our results show that this effect is steeper for firms with higher growth rates.

Our study contributes meaningful insights to strategy scholarship on the influence of nonmarket strategies, highlighting the relevance of firm-specific conditions in shaping the performance outcomes of such strategies. In particular, we make a contribution by identifying a nonlinear relationship between lobbying and firm performance, which is amplified in fast-growing firms compared to stagnant ones.