Search results

In the knowledge-based view, knowledge is a valuable source of enterprise success. Its transfer through expatriates is a key mechanism in the value proposition of outward foreign direct investment by multinational enterprises (MNEs). Unfortunately, individuals are not always willing to share what they know. Expatriates are crucial players in knowledge transfer, and their knowledge-hiding behavior can significantly inhibit enterprise success. This paper thus aims to explore the patterns and antecedents of knowledge hiding, as well as the underlying mechanisms in the hiding process by expatriates within MNEs.

This paper focuses on expatriates assigned to emerging economies in Chinese MNEs. It is based on a systematic qualitative analysis of semi-structured interviews with 24 expatriates from 16 companies across 25 countries.

Not all knowledge hiding should be perceived as a negative behavior, as moderate rationalized hiding can fulfil a positive purpose. Antecedents of expatriates’ knowledge hiding were identified within a framework covering knowledge, individual, organizational and cultural features. Three main scenarios of knowledge-hiding process were also disclosed to illustrate the internal generative logic.

The comprehensive analysis of knowledge hiding presented in this paper enriches the existing literature on cross-border knowledge management and provides novel theoretical insights to better promote knowledge transfer by expatriates. A practical framework of knowledge transfer within MNEs is developed to guide the management of expatriates, even a broader spectrum of knowledge workers.

The aerodynamic load caused by high-speed train operation may lead to severe vibration of the pedestrian bridge, thus causing great safety hazards. Therefore, this study aims to investigate the aerodynamic loading characteristics of a pedestrian bridge when a high-speed train passes over the bridge, as well as to evaluate the vibration response of the aerodynamic loads on the bridge structure.

High-speed trains are operated at three different speeds. The aerodynamic pressure load characteristics of high-speed trains crossing a pedestrian bridge are investigated by combining a nonconstant numerical simulation method with a dynamic modeling test method, and the vibration response of the bridge is analyzed.

The results show that when a high-speed train passes through the pedestrian bridge, the pedestrian bridge interferes with the attenuation of the pressure around the train, so that the pressure spreads along the bridge bottom, and the maximum positive and negative pressure peaks appear in the center area of the bridge bottom, while the pressure fluctuations in the bridge entrance and exit areas are smaller and change more slowly, and the pressure attenuation of the bridge bottom perpendicular to the direction of the train’s operation is faster. In addition, the pressure fluctuation generated by the high-speed train will lead to a larger vertical response of the bridge structure in the mid-span position, and the main vibration frequency of the bridge structure ranges from 8 to 10 Hz, and the maximum value of the vertical deformation amplitude is located in the mid-span region of the bridge.

This paper analyzes the flow field distribution around the train and at the bottom of the bridge for the evolution of the flow field when the train passes through the bridge at high speed, and conducts a finite element dynamic analysis of the bridge structure to calculate the vibration response of the bridge when the train passes through at high speed, and to evaluate the comfort of the passengers passing through the high-speed railroad bridge.

This chapter examines the significant role of non-fungible tokens (NFTs) and blockchain technology in fostering a sustainable economy in the metaverse. Blockchain allows the saving and transfer of decentralized and secure data. As a primary component of the metaverse economy, NFTs are distinct and secure virtual assets saved on the blockchain. These assets facilitate possessing, trading, and monetizing digital assets. These advancing technologies have also revolutionized the method by which creators and artists test and exchange their digital work, introducing a novel period of ownership and value in the digital realm. However, the negative environmental effects of some blockchain technologies constitute a considerable constraint, pushing a shift to a sustainable economy. Platforms like The Sandbox have implemented initiatives to address environmental concerns. As a case study, The Sandbox play-to-earn model with tokenized assets showcases its ability to create value and encourage user participation. It shows the ability of NFTs and blockchain to support a sustainable economy.

The process of redesigning is one of the essential steps in upcycling, which comprises ideation, reconstruction and fitting. This paper aims to study the best practice of upcycling in the clothing industry. This study is an attempt to standardise upcycling/redesign process.

An exploratory approach was adopted to perform the research. This study draws on the multiple organisations involved in the upcycling of clothes. The organisations chosen for this study are located in Sweden and Romania using the snowball technique. Semi-structured interviews, direct and participatory observation approaches were used to collect information. The collected data are systematically analysed using NVivo 10 software.

This paper provides empirical insights into the diverse practices of upcycling. Process, product and demand-based were three fundamental approaches to performing the redesigning process. The fabric quality and durability, variations in size, colour and pattern, skills and efforts required in the extraction of parts and environmental consciousness and awareness were the main factors influencing upcycling process.

The use of the European case may miss best practices from the other region. This study may help scholars to understand the method of upcycling. A practitioner of upcycling can use the findings to improve and standardise the existing process. This research is beneficial for society, as this leads to the reduction of textile wastage.

This paper conceptualises some of the best practices of clothes redesign. This provides a good insight for the organisation for the improvement in the redesign business.

The purpose of this paper is to analyze and compare the mechanical properties of sintered nanosilver with different porosities at both the mesoscopic and macroscopic scales and to conduct a multiscale analysis of the porosity effect on the mechanical properties of sintered nanosilver.

This paper establishes a mesoscopic model for the uniaxial tension of sintered nanosilver and a macroscopic model for chips containing sintered silver layers. Using the finite element method, combined with crystal plasticity theory and unified creep plasticity theory, a multiscale analysis is conducted for the mechanical properties of sintered nanosilver. First, stress distribution characteristics under uniaxial tensile loading for different porosities in sintered nanosilver polycrystal models are analyzed at the mesoscopic scale. Second, at the macroscopic scale, the mechanical performance of sintered nanosilver layers with varying porosities in high-power chip models under cyclic loading is analyzed. Finally, the porosity influence on the damage evolution in sintered nanosilver is summarized, and simulations are conducted to explore the evolution of damage parameters in sintered nanosilver under different porosities.

In the mesoscopic model, the presence of mesoscale voids affects the stress distribution in sintered nanosilver subjected to tensile loading. Sintered nanosilver with lower porosity exhibits higher tensile strength. In the macroscopic model, sintered nanosilver layers with lower porosity correspond to a more uniform stress distribution, whereas higher porosity leads to faster accumulation of plastic strain in the sintered layer. During chip packaging processes, improving processes to reduce the porosity of sintered layers can delay the initiation of damage and the propagation of cracks in sintered nanosilver.

During chip packaging processes, improving processes to reduce the porosity of sintered layers can delay the initiation of damage and the propagation of cracks in sintered nanosilver.

This paper innovatively uses a mesoscopic crystal plasticity constitutive model and a macroscopic unified creep plasticity constitutive model to analyze the mechanical behavior of sintered nanosilver with different porosities. It comprehensively investigates and explains the influence of porosity on the mechanical performance of sintered nanosilver across multiple scales.

This study aims to investigate the effects and implications of overconfidence in a competitive game involving multiple newsvendors. This study explores how overconfidence influences system coordination, optimal stocking strategies and competition among newsvendors in the context of the well-known newsvendor stocking problem.

The study applies robust optimization theory and the absolute regret minimization criterion to analyze the competitive game of overconfident newsvendors. This study considers the asymmetric information held by newsvendors regarding market demand and obtains a closed-form solution for the competing game. The effects of overconfidence on system coordination and optimal stocking strategies are examined.

The results of the study indicate that overconfidence can act as a positive force in reducing the effects of overstocking caused by competition and asymmetric information among newsvendors. The analysis reveals that there exists an optimal level of overconfidence that coordinates the ordering system of multiple overconfident newsvendors, leading to first-best outcomes under certain conditions. Additionally, numerical examples confirm the obtained results. Furthermore, considering newsvendors' expected profit, the study finds that a higher degree of overconfidence does not necessarily result in lower actual expected profit.

Despite the significant contributions of this study to theoretical and managerial insights, this study does have certain limitations. First, in the establishment of the belief demand function, the substitution ratio, which quantifies the transfer, is assumed to be an exogenous variable. However, in reality, this is often influenced by factors such as the price of goods and the distance between stores. Therefore, one direction worth studying in the future is to explore the uncertainty associated with the demand substitution ratio and integrate that as an endogenous variable into the optimization model. Second, this study does not address the type of product and solely focuses on quantitatively analyzing the effect of salvage value on the optimal stocking strategy. Future studies can explore the effect of degree of perishability and selling period of the product on the stocking. Third, the focus of uncertainty in this study revolves around market demand, and the implications of this uncertainty are significant. A recent study (Rahbari et al., 2023) addressed an innovative robust optimization problem related to canned foods during pandemic crises. The recent study's findings highlighted the effectiveness of expanding canned food exports to neighboring countries with economic justification as the best strategy for companies amidst the disruptions caused by the coronavirus disease 2019 (COVID-19) pandemic. Incorporating the issue of disruptions into the authors' research would be interesting and challenging.

From a managerial perspective, the authors' study provides a research paradigm for game-theoretic inventory problems in scenarios where the market demand distribution is unknown. While most inventory problems are analyzed and solved based on expectation-based optimization criteria, which rely on an accurate distribution of market demand, obtaining this information in practice can often be challenging or expensive for decision-makers. Consequently, a discrepancy arises between real-world observations and theoretical identifications. This study aimed to complement previous research and address the inconsistency between observations and theoretical identification.

The authors' research contributes to the existing understanding of overconfidence and assists individuals in making appropriate stocking strategies based on the individuals' level of overconfidence. Diverging significantly from the traditional view of overconfidence as a negative bias, the authors' results show the view's potential positive impact within a competitive environment, resulting in greater actual expected profits for newsvendors.

This study contributes to the existing literature by examining the effects of overconfidence in a competitive game of newsvendors. This study extends the analysis of the well-known newsvendor stocking problem by incorporating overconfidence and considering the implications for system coordination and competition. The application of robust optimization theory and the absolute regret minimization criterion provides a novel approach to studying overconfidence in this context.

The purpose of this study is to examine the effect of trust on user adoption of artificial intelligence-generated content (AIGC) based on the stimulus–organism–response.

The authors conducted an online survey in China, which is a highly competitive AI market, and obtained 504 valid responses. Both structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) were used to conduct data analysis.

The results indicated that perceived intelligence, perceived transparency and knowledge hallucination influence cognitive trust in platform, whereas perceived empathy influences affective trust in platform. Both cognitive trust and affective trust in platform lead to trust in AIGC. Algorithm bias negatively moderates the effect of cognitive trust in platform on trust in AIGC. The fsQCA identified three configurations leading to adoption intention.

The main limitation is that more factors such as culture need to be included to examine their possible effects on trust. The implication is that generative AI platforms need to improve the intelligence, transparency and empathy, and mitigate knowledge hallucination to engender users’ trust in AIGC and facilitate their adoption.

Existing research has mainly used technology adoption theories such as unified theory of acceptance and use of technology to examine AIGC user behaviour and has seldom examined user trust development in the AIGC context. This research tries to fill the gap by disclosing the mechanism underlying AIGC user trust formation.

This study aims to get a better understanding of the impact of streamlined high-speed trains (HSTs) with geometric uncertainty on aerodynamic performance, as well as the identification of the key parameters responsible for this impact. To reveal the critical parameters, this study creates a methodology for evaluating the uncertainty and sensitivity of drag coefficient induced by design parameters of HST streamlined shapes.

Bézier curves are used to parameterize the streamlined shape of HSTs, and there are eight design parameters required to fit the streamlined shape, followed by a series of steady Reynolds-averaged Navier–Stokes simulations. Combining the preparation work with the nonintrusive polynomial chaos method results in a workflow for uncertainty quantification and global sensitivity analysis. Based on this framework, this study quantifies the uncertainty of drag, pressure, surface friction coefficient and wake flow characteristics within the defined ranges of streamline shape parameters, as well as the contribution of each design parameter.

The results show that the change in drag reaches a maximum deviation of 15.37% from the baseline, and the impact on the tail car is more significant, with a deviation of up to 23.98%. The streamlined shape of the upper surface and the length of the pilot (The device is mounted on the front of a train’s locomotive and primarily serves to remove obstacles from the tracks, thereby preventing potential derailment.) are responsible for the dominant factors of the uncertainty in the drag for HSTs. Linear regression results show a significant quadratic polynomial relationship between the length of the pilot and the drag coefficient. The drag declines as the length of the pilot enlarges. By analyzing the case with the lowest drag, the positive pressure area in the front of pilot is greatly reduced, while the nose tip pressure of the tail is enhanced by altering the vortices in the wake. The counter-rotating vortex pair is significantly attenuated. Accordingly, exerts the impacts caused by geometric uncertainty can be found on the wake flow region, with pressure differences of up to 900 Pa. The parameters associated with the shape of the upper surface contribute significantly to the uncertainty in the core of the wake separation region.

The findings contribute to a better understanding of the impact of streamlined HSTs with geometric uncertainty on aerodynamic performance, as well as the identification of the key parameters responsible for this impact. Based on this study, future research could delve into the detailed design of critical areas in the streamlined shape of HSTs, as well as the direction of shape optimization to more precisely and efficiently reduce train aerodynamic drag under typical conditions.

This study aims to improve the lubrication performance of molybdenum disulfide powders at textured surface of cemented carbide materials, a squeeze motion of vibration assistance method was introduced and investigated.

Surface texture was fabricated on YT15 cemented carbide samples using a laser marking machine. After that, a tribological experiment was carried out on a self-built friction testing machine under different amplitude and frequency of squeeze motion conditions. Moreover, a simulation model was also established to verify the principle of squeeze motion on the lubrication performance improving of MoS₂ particles at textured interfaces.

Analysis results indicated that surface texture on test sample can increase the storage ability of solid lubrication particles, and the lubrication film at the contact interface is more easily formed due to the reciprocating action. Squeeze motion can improve the storage ability of it due to an intermittent contact, which provides an opportunity for MoS₂ particles infiltration, and then a more uniform distribution and load-bearing properties of force chain are also established and formed simultaneously. Thus, a better tribological performance at the contact interface is obtained.

The main contribution of this work is to provide a reference for the molybdenum disulfide powder lubrication with textured surface of cemented carbide materials.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0166/

Achieve a lightweight design for a bogie frame while ensuring it meets strength requirements by conducting static and fatigue strength assessments and optimizing plate thickness.

Establish a finite element model and determine loads according to the UIC615-4 standard. Fatigue strength assessments are conducted using the structural stress method. Size optimization for plate thickness is performed with constraints on maximum static strength and total fatigue damage of the weld. Multi-objective optimization design is carried out using Isight software, with sensitivity analysis to identify key plates. The neural network model is chosen as the approximation model, and the NSGA-II multi-objective genetic algorithm is selected as the optimization algorithm.

The strength assessment reveals a significant margin. Through size optimization of plate thickness with constraints on static strength and fatigue damage, the frame’s mass is reduced by 9.59%, achieving a lightweight design while meeting strength requirements.

In many lightweight studies, the inclusion of fatigue assessment through the structural stress method in the optimization process is often overlooked. However, this paper addresses this gap by incorporating it and providing a detailed operational procedure. Such consideration holds reference value for the design of lightweight optimization, especially when fatigue strength is a critical consideration.