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In large-scale group decision-making (LSGDM) situations, existing TODIM group decision-making methods often fail to account for the influence of social network relationships and the bounded rationality of decision-makers (DMs). To address this issue, a new TODIM-based group decision-making method is proposed that considers the current trust relationships among DMs in a large-scale trust relationship network.

This method consists of two main stages. In the first stage, the large-scale group is partitioned into several sub-clusters based on trust relationships among DMs. The dominance degree matrix of each sub-cluster is then aggregated into the large-scale group dominance degree. In the second stage, after aggregating the large-scale group dominance degree, the consensus index is calculated to identify any inconsistent sub-clusters. Feedback adjustments are made based on trust relationships until a consensus is reached. The TODIM method is then applied to calculate the corresponding ranking results. Finally, an illustrative example is applied to show the feasibility of the proposed model.

The proposed method is practical and effective which is verified by the real case study. By taking into account the trust relationships among DMs in the core process of LSGDM, it indeed has an impact on the decision outcomes. We also specifically address this issue in Chapter Five. The proposed method fully incorporates the bounded rationality of DMs, namely their tendency to accept the opinions of trusted experts, which aligns more with their psychology. The two-stage consensus model proposed in this paper effectively addresses the limitations of traditional assessment-based methods.

This study establishes a two-stage consensus model based on trust relationships among DMs, which can assist DMs in better understanding trust issues in complex decision-making, enhancing the accuracy and efficiency of decisions, and providing more scientific decision support for organizations such as businesses and governments.

Drawing on conservation of resources theory, this study aims to investigate the impact of online customer engagement on brand love via dual mediating mechanisms, empowerment (bright side) and stress (dark side). The roles of perceived brand quality and extroversion as weakener and facilitator respectively on the dark side effect are also examined.

An online survey is conducted, targeting people who have experience in participating in online engagement activities. The dual mediation and moderation analysis are examined.

The results confirm the proposed dual mediating mechanisms. Perceived brand quality and extroversion also significantly moderate the engagement–stress link.

This study explains the mediating mechanisms between online customer engagement and brand love, with a focus on the fast-moving consumer goods industry. This calls for further research on other industries.

This study provides marketers with insights that online customer engagement strategies are not always good and that they should be more careful in formulating such strategies.

This study advances the understanding of the relationship between customer engagement and brand love in the virtual community especially in the social media context.

In order to give full play to the function of noise reduction of asphalt pavement, it is necessary to understand its internal sound absorption mechanism. Therefore, the purpose of this study is to establish a micro model of the pore structure of asphalt mixture with the help of finite element method (FEM), discuss the noise reduction mechanism of asphalt pavement from the micro perspective and analyze and evaluate the noise attenuation law of the pore structure.

The FEM was used to establish the microscopic model of the pore structure of asphalt mixture. Based on the principle of acoustics, the noise reduction characteristics of asphalt pavement were simulated. The influence of gradation and pore characteristics on the noise reduction performance of asphalt pavement was analyzed.

The results show that the open graded friction course-13 (OGFC-13) has excellent performance in noise reduction. The resonant sound absorption structure composed of its large porosity can effectively reduce the pavement noise. For asphalt concrete-13 (AC-13) and stone matrix asphalt-13 (SMA-13), the less resonant sound absorption structure makes them have poor sound absorption effect. In addition, the variation rules of noise transmission loss (TL) curve and sound absorption coefficient curve of three graded asphalt mixtures were obtained. At the same time, the peak noise reduction values of OGFC-13, AC-13 and SMA-13 were obtained, which were 650Hz, 1000Hz and 800Hz, respectively.

The results show that the simulation results can well reflect and express the experimental results. This will provide a reference for further exploring the sound absorption mechanism and its variation rule of porous asphalt pavement. It also has some positive significance for the application of low noise asphalt pavement.

To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions. However, the accuracy of perception is closely related to the performance of sensors configured on the vehicle. To enhance sensors’ performance further to improve the accuracy of environmental perception, this paper aims to introduce an obstacle detection method based on the depth fusion of lidar and radar in challenging conditions, which could reduce the false rate resulting from sensors’ misdetection.

Firstly, a multi-layer self-calibration method is proposed based on the spatial and temporal relationships. Next, a depth fusion model is proposed to improve the performance of obstacle detection in challenging conditions. Finally, the study tests are carried out in challenging conditions, including straight unstructured road, unstructured road with rough surface and unstructured road with heavy dust or mist.

The experimental tests in challenging conditions demonstrate that the depth fusion model, comparing with the use of a single sensor, can filter out the false alarm of radar and point clouds of dust or mist received by lidar. So, the accuracy of objects detection is also improved under challenging conditions.

A multi-layer self-calibration method is conducive to improve the accuracy of the calibration and reduce the workload of manual calibration. Next, a depth fusion model based on lidar and radar can effectively get high precision by way of filtering out the false alarm of radar and point clouds of dust or mist received by lidar, which could improve ICVs’ performance in challenging conditions.

The incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers’ responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.

Based on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of “network stage”, “consumer type”, and “resource type” to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.

The results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.

Under the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers > agent consumers > commenting consumers > potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.

This paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises’ customer relationship management and marketing decisions.

The purpose of this paper is to introduce a variable distance pneumatic gripper with embedded flexible sensors, which can effectively grasp fragile and flexible objects.

Based on the motion principle of the three-jaw chuck and the pneumatic “fast pneumatic network” (FPN), a variable distance pneumatic holder embedded with a flexible sensor is designed. A structural design plan and preparation process of a soft driver is proposed, using carbon nanotubes as filler in a polyurethane (PU) sponge. A flexible bending sensor based on carbon nanotube materials was produced. A static model of the soft driver cavity was established, and a bending simulation was performed. Based on the designed variable distance soft pneumatic gripper, a real-time monitoring and control system was developed. Combined with the developed pneumatic control system, gripping experiments on objects of different shapes and easily deformable and fragile objects were conducted.

In this paper, a variable-distance pneumatic gripper embedded with a flexible sensor was designed, and a control system for real-time monitoring and multi-terminal input was developed. Combined with the developed pneumatic control system, a measure was carried out to measure the relationship between the bending angle, output force and air pressure of the soft driver. Flexible bending sensor performance test. The gripper diameter and gripping weight were tested, and the maximum gripping diameter was determined to be 182 mm, the maximum gripping weight was approximately 900 g and the average measurement error of the bending sensor was 5.91%. Objects of different shapes and easily deformable and fragile objects were tested.

Based on the motion principle of the three-jaw chuck and the pneumatic FPN, a variable distance pneumatic gripper with embedded flexible sensors is proposed by using the method of layered and step-by-step preparation. The authors studied the gripper structure design, simulation analysis, prototype preparation, control system construction and experimental testing. The results show that the designed flexible pneumatic gripper with variable distance can grasp common objects.

The purpose of this paper is to investigate the friction and wear mechanisms in lubricated sliding conditions of additively manufactured SS316L parts. The different viscous oils 5W30, 15W40, 20W50 and SAE140 are used. These investigations provide a theoretical basis for the high performance of printed and postheattreated SS316L.

Tribological tests were carried out on selective laser melting-made SS316L printed specimens and heat-treated specimens. The parameters in 15 min of test duration are 20 N of load, 200 rpm, 8 mm of pin diameter, 25 mm length, 80 mm of track diameter and EN31 counter disc body. This work presented the phenomena of lubrication regimes and their characterization, as identified by the Stribeck curve, and these regimes affect the tribological properties of additively manufactured SS316L under the influence of industrial viscous lubricants. The results are observed using Scanning electron microscope (SEM), X-ray diffraction (XRD) and wear tests.

The observations indicate that additively manufactured SS316L shows a reduced coefficient of friction (COF) and specific wear rate (SWR). This is credited to the utilization of different viscous lubricants.

This exclusive research demonstrates how various viscous lubricants affect the COF and SWR of printed and post-heat-treated SS316L parts. Lambda (λ), lubricant film thickness (h₀), surface roughness and wear mechanisms are studied and reported.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0110/