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Travel bragging, driven by impression management, is common on social media. However, straightforward bragging can create negative perceptions. To mitigate this, tourists often turn to humblebragging, but its effectiveness is unclear. This study aims to examine whether humblebragging elicits more positive responses from viewers than straightforward bragging.

Drawing on social comparison theory and compensation theory, this paper developed a moderated mediation model to explore the impact of bragging type (bragging vs humblebragging) on viewer behavior. The model was validated through two scenario-based experiments.

The results reveal the double-sword effect of humblebragging: Humblebragging elicits stronger benign and malicious envy than bragging. Benign envy mediates the relationship between bragging type and consumption intention, while malicious envy mediates between bragging type and avoidance/gossip. Perceived deservingness moderates the effect of bragging type on envy and the mediation processes. When viewers perceive the poster’s advantage as deserving, humblebragging elicits more benign envy than bragging. When perceived as undeserving, humblebragging leads to more malicious envy.

This study is innovative in validating the double-edged sword effect of humblebragging and identifying perceived deservingness as a boundary condition.

Bridge plans are a complicated grey system. It depends on various natural and social factors. The purpose of this paper is to provide a scientific method for optimization of bridge construction plan.

Grey relational analysis (GRA) is completely new analysis method has been proposed in the grey system theory. Grey relational order can be used to describe the relation between the related factors based on data series rather than linear relation and typical distribution. First, this paper describes the basic steps and formulae of GRA. Then provides an example to show how to select best bridge construction plan with the method. Specially discusses significant influence of weight selection on decision making for a bridge plan.

The optimization of bridge construction plan will be selected more reasonable and more objective with the method GRA.

This paper will be further studied on how to quantify indicators more objectively and how to decide weight factor more reasonably.

It has significant practical value to apply GRA to optimization of bridge plans and other engineering projects.

A scientific method‐GRA has been applied to the selection of bridge plans for seeking the best comprehensive result.

Reasonable risk sharing is the key to the smooth implementation of infrastructure public-private partnership (PPP) projects and the optimization of benefit distribution among the participants. This study aims to explore the risk redistribution ratio between the government and the private sector under different degree of fairness concern.

Renegotiation is a mechanism to provide flexibility and make up for incompleteness of PPP contracts. However, the threshold value of risk redistribution ratio and negotiation cost are not explicitly considered in previous studies. In addition, these studies do not consider the influence of the fairness concern psychology on the negotiation process. To address these gaps, based on risk-income equilibrium analysis, this paper established the bargaining optimization model of PPP projects renegotiation considering the fairness concerns of the negotiating parties. Furthermore, this study analyzed the influence of fairness concern degree on negotiation thresholds, negotiation results, and negotiation incomes under three scenarios.

The results showed that excessive focus on the fairness of incomes may exclude the risk redistribution ratio that is most beneficial to project incomes from the negotiation threshold. Moreover, the increase in the fairness concerns of negotiating parties can reduce the negotiation success period, but the net income may not necessarily be improved.

The main contribution of this paper is to propose a new risk renegotiation methodology based on the risk-income equilibrium analysis, which is helpful to develop risk management strategies in the construction field. The research results can provide government with reference about renegotiation in decision making and provide theoretical support for the practice of PPP renegotiation.

The low-temperature sintering of silica glass combined with additive manufacturing (AM) technology has brought a revolutionary change in glass manufacturing. This study aims to carry out in an attempt to achieve precious manufacturing of silicate glassy matrix through the method of slurry extrusion.

A low-cost slurry extrusion modelling technology is used to extrude silicate glassy matrix inks, composed of silicate glass powder with different amounts of additives. Extrudability of the inks, their printability window and the featuring curves of silicate glassy matrix are investigated. In addition, the properties of the low-temperature sintering green part as a functional part are explored and evaluated from morphology, hardness and colour.

The results showed that the particle size was mainly distributed from 1.4 µm to 5.3 µm, showing better slurry stability and print continuity. The parameters were set to 8 mm/s, 80% and 0.4 mm, respectively, to achieve better forming of three-dimensional (3D) samples. Besides, the organic binder removal step was concentrated on 200°C–300°C and 590°C–650°C was the fusion bonding temperature of the powder. The hardness values of 10 test samples ranged from 588 HL to 613 HL, which met the requirements of hard stones with super-strong mechanical strength. In addition, the mutual penetration of elements caused by temperature changes may lead to a colourful appearance.

The custom continuous AM technology enables the fabrication of a glass matrix with 3D structural features. The precise positioning technology of the glass matrix is expected to be applied more widely in functional parts.

Many cities implement freight traffic restriction policy (FTRP) intending to reduce traffic congestion and air pollution. At the same time, city distribution had some negative effects. The purpose of this paper is therefore to study the freight group behavior under FTRP, and to provide some recommendations for the government.

This paper establishes a city distribution system model built by a simulation method of Agent, which includes the complex adaptability of freight individual, event of restriction policy, the influence factor of freight group behavior and its changes from the perspective of restriction policy. The rules of microscopic freight group behavior to macroscopic freight group behavior, the effects on freight group behavior exerted by restriction policy and the dynamic mechanism of freight group behavior are all studied. The model is also simulated with the traffic data of Beijing in China.

Theoretical results ensure that restriction of the passport is not the sole reason that may produce illegal trucks, and other measures need to be taken to solve the traffic problems. And in the long run, increasing fines has a greater effect than strengthening supervision frequency on illegal trucks reduction.

From city distribution perspective, this paper studied freight group behavior under FTRP. This paper also applied the Agent modeling method to build a model of urban distribution system in the FTRP.

This paper aims to improve the scene sense of a virtual scene, the welding model of a virtual reality system of riser automatic equipment was constructed using Unity3D and UG software, which mainly included a welding car, welding guide rail, welding power supply, virtual camera and other equipment and the model was rendered.

The human-computer interaction page and simulation test of the system was produced using the user interface GUI system for creating a human-computer interaction scene. The operator could capture the welding status of the physical equipment accurately and in real-time so the virtual reality technology was very suitable for the remote monitoring operation integrated with the welding system.

Human-computer interaction design and collision detection were realized. In addition, the system simulation experiment was accomplished. With the continuous improvement and development of virtual reality technology real-time virtual simulation and monitoring, technology will become the main development trend.

Based on virtual reality, the monitoring system can capture the operation status of physical welding equipment in real-time and accurately, which is very suitable for remote monitoring operation integrated with the welding system and also conducive to improving the monitoring level of the welding process.

This technology is time-saving and money-saving, for the operators do not have to be in a real welding environment and therefore they can get away from dangerous places. Consequently, it can avoid unnecessary injuries and problems.

This technology can replace people to enter the dangerous and extreme environment to carry out welding operation, so it becomes the most effective means of nuclear power plant maintenance, space structure construction and marine engineering construction. In addition, it is time-saving and money-saving.

With the rapid development of virtual reality technology in recent years, it is a new research direction to apply virtual reality technology to the remote welding operation. This technology is different from the traditional way of welding for the operators can stay away from the welding scene especially some dangerous places.

This study empirically explores the intraday price discovery mechanism and volatility transmission effect between the dual-listed Indian Nifty index futures traded simultaneously on the onshore Indian exchange, National Stock Exchange (NSE) and offshore Singapore Exchange (SGX) and its spot market by using high-frequency data.

This study applies the vector error correction model to analyze the lead-lag relationship in price discovery among three markets. The contributions of individual markets in assimilating new information into prices are measured using various measures, Hasbrouck's (1995) information share, Lien and Shrestha's (2009) modified information share and Gonzalo and Granger's (1995) component share. Additionally, the Granger causality test is conducted to determine the causal relationship. Lastly, the BEKK-GARCH specification is employed to analyze the volatility transmission.

This study provides robust evidence that Nifty futures lead the spot in price discovery. The offshore SGX Nifty futures consistently ranked first in contributing to price discovery, followed by onshore NSE Nifty futures and finally by the spot. Empirical results also show unidirectional causality and volatility transmission from Nifty futures to spot, as well as bidirectional causal relationship and volatility spillovers between NSE and SGX Nifty futures. These novel findings provide fresh insights into the informational efficiency of the dual-listed Indian Nifty futures, which is distinct from previous literature.

These findings can potentially help market participants, policymakers, stock exchanges and regulators.

Unlike previous studies in this area, this is the first study that empirically examines the intraday price discovery mechanism and volatility spillover between the dual-listed futures markets and its spot market using 5-min overlapping price data and trivariate econometric models.

The purpose of this study is to investigate the microstructural evolution of high-strength 2024 Al alloy prepared by the laser powder bed fusion (L-PBF) additive manufacturing (AM) route. The high-strength wrought Al alloy has typically been unsuitable for AM due to its particular solidification characteristics such as hot cracking, porosity and columnar grain growth.

In this research work, samples were fabricated using L-PBF under various laser energy densities by varying laser power and scan speed. The microstructural features that developed during the solidification are correlated with operating laser parameters. In addition, finite element modelling (FEM) was performed to understand the experimentally observed results.

Microstructure evolution and defect formation have been assessed, quantified and correlated with operating laser parameters. Thermal behaviour of samples was predicted using FEM to support experimental observations. An optimised combination of intermediate laser power and scan speed produced the least defects. Higher energy density increased hot tearing along the columnar grain boundaries, while lower energy density promoted void formation. From the quantitative results, it is evident that with increasing energy density, both the top surface and side wall roughness initially reduced till a minimum and then increased. Hardness and compressive strength were found to decrease with increasing power density due to stress relaxation from hot tearing.

This research work examined how L-PBF processing conditions influence the microstructure, defects, surface roughness and mechanical properties. The results indicates that complete elimination of solidification cracks can be only achieved by combining process optimisation and possible grain refining strategies.

The purpose of this work is to explore predictive model approaches for selecting laser cladding process settings for a desired bead geometry/overlap strategy. Complementing the modelling challenges is the development of a framework and methodologies to minimize data collection while maximizing the goodness of fit for the predictive models. This is essential for developing a foundation for metallic additive manufacturing process planning solutions.

Using the coaxial powder flow laser cladding method, 420 steel cladding powder is deposited on low carbon structural steel plates. A design of experiments (DOE) approach is taken using the response surface methodology (RSM) to establish the experimental configuration. The five process parameters such as laser power, travel speed, etc. are varied to explore their impact on the bead geometry. A total of three replicate experiments are performed and the collected data are assessed using a variety of methods to determine the process trends and the best modelling approaches.

There exist unpredictable, non-linear relationships between the process parameters and the bead geometry. The best fit for a predictive model is achieved with the artificial neural network (ANN) approach. Using the RSM, the experimental set is reduced by an order of magnitude; however, a model with R2 = 0.96 is generated with ANN. The predictive model goodness of fit for a single bead is similar to that for the overlapping bead geometry using ANN.

Developing a bead shape to process parameters model is challenging due to the non-linear coupling between the process parameters and the bead geometry and the number of parameters to be considered. The experimental design and modelling approaches presented in this work illustrate how designed experiments can minimize the data collection and produce a robust predictive model. The output of this work will provide a solid foundation for process planning operations.

The dispute over the benefit of diversity on the transactive memory system (TMS) has attracted the attention with the development of global collaboration. This paper aims to discover how knowledge heterogeneity (KH), categorized as explicit and tacit KH, affects TMS and to test the mediation effect of innovation climate (IC).

Data from a 6-month field study of 207 research and development (R&D) members and 7 expertize observers were analyzed by partial least squares structure equation model. Robustness check and Barron and Kenny mediation test were used to evaluate the model and confirm the mediation effect.

Tacit KH of R&D team negatively influences the development of TMS. Furthermore, IC partially mediates tacit KHs’ negative influence on the development of TMS.

These results distinguish the different influence of explicit and tacit KH on TMS and explore the mediating role of IC that has been confirmed affecting the development of TMS.

These results could motivate practitioners to address more attention to tacit KH, IC and the development of TMS in the R&D team members composition.

This study contributes not only to elucidate the different influence of explicit and tacit KH on TMS but also to the appropriate members composition of R&D team by considering the relationships among KH, IC, TMS and innovation performance.