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This study aims to investigate the advancement of place attachment within the bicycle tourism context. Specifically, this study seeks to ascertain whether the four attributes of bicycle tourism (tourism attractions, accessibility, amenities and complementary services) and enduring involvement can serve as predictors of tourists’ place attachment. Also, the research endeavors to examine the positive effects generated by the four attributes of bicycle tourism on enduring involvement. Additionally, the mediating role that enduring involvement plays in attribute–place attachment relationships will be clarified.

The final 547 samples are collected from five WeChat cycling groups in Shanghai, and the partial least squares structural equation modeling approach is used to analyze the data.

The results show that each of the four attributes has a positive impact on place attachment. Moreover, tourism attractions, accessibility and amenities can be the drivers of enduring involvement. Enduring involvement mediates the tourism attractions–place attachment relationship, the accessibility–place attachment relationship, as well as the amenities–place attachment relationship.

This paper, to the best of the author’s knowledge, pioneeringly introduces the concept of enduring involvement and place attachment into bicycle tourism research, and the findings contribute to providing practical implications for destination managers and government policymakers.

This is innovative work with a comprehensive and creative research framework for place attachment.

This study constructs the influence mechanism model of sustainable marketing activities (SMAs), event image, commemorative product perceived value and tourists’ behavioral intentions (TBIs) in the sports tourism context of the Beijing Winter Olympic Games. Additionally, the article discusses the role of event image and product perceived value in enhancing the SMAs’ effect on TBIs.

The research analyzed 315 valid questionnaires from tourists in the Chinese market by structural equation modeling.

The results indicate that SMAs positively impact sports tourism event image, tourists’ perceived commemorative product value and TBIs. Meanwhile, event image and product perceived value mediate the SMAs and TBIs relationship.

Considering SMAs as essential for sustainable development, this paper contributes to the strategic management discipline. Additionally, the research expands the analysis of event image and product perceived value in the brand theory and customer behavior research.

The article outlines the principal value of SMAs implementation in enhancing behavioral intentions. It also reveals that a favorable event image and good perceived value can enhance SMAs’ effectiveness toward positively influencing TBIs, especially purchase intentions. It provides a new vision for nonprofit organizations to prioritize SMAs’ implementation in marketing strategies.

It is pioneering work with a complex research framework for SMAs implementation in the sports tourism context.

This paper aims to present a method of optimal singularity-free motion planning under multiple objectives and multiple constrains for the 6-DOF parallel manipulator, which is used as an execution mechanism for the automated docking of components.

First, the distribution characteristics of the Jacobian matrix determinant in local workspace are studied based on the kinematics and a sufficient and necessary condition of singularity-free path planning in local workspace is proposed. Then, a singularity-free motion path of the end-effector is generated by a fifth-order B-spline curve and the corresponding trajectories of each actuator are obtained via the inverse kinematics. Finally, several objective functions are defined to evaluate the motion path and an improved multi-objective particle swarm optimization algorithm-based on the Pareto archive evolution is developed to obtain the optimal singularity-free motion trajectories.

If the initial pose and the target pose of the end-effector are both singularity-free, a singularity-free motion path can be planned in the local workspace as long as all the values of each pose elements in their own directions are monotonous. The improved multi-objective particle swarm optimization (IMPSO) algorithm is effective and efficient in the optimization of multi-objective motion planning model. The optimal singularity-free motion path of the end-effector is verified in the component docking test. The docking result is that the movable component is in alignment with the fixed one, which proves the feasibility and practicability of the proposed motion path method to some extent.

The proposed method has a certain novelty value in kinematic multi-objective motion planning of parallel manipulators; it also increases the application prospect of parallel manipulators and provides attractive solutions to component assembly for those organizations with limited cost and that want to find an option that is effective to be implemented.

Using typical structure of asphalt pavement in Harbin area of China, and the formula of generalized friction coefficient between base and surface layers of asphalt pavement in cold area is established.

Through structural characteristics analysis of asphalt pavement in cold area, the generalized formula of friction coefficient between base and surface layers of asphalt pavement in cold area is derived. The formula can quickly calculate the friction coefficient between layers of asphalt pavement.

Based on quantitative analysis to the contacting state between layers of asphalt pavement in cold area, the relationships between generalized friction coefficient and resilient modulus of asphalt mixtures, temperature shrinkage coefficient and temperature have been established.

The findings can enrich the description methods about the contacting state between layers of asphalt pavement, and have a certain theoretical and practical value. Through the application of the formula of generalized friction coefficient between layers, it can provide a technical basis for the asphalt pavement design, construction and maintenance in cold area.

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged robot. The autonomy of obstacle-surmounting is reflected in obstacle recognition based on multi-frame point cloud fusion.

In this paper, first, for the problem that the lidar on the robot cannot scan the point cloud of low-height obstacles, the lidar is driven to rotate by a 2D turntable to obtain the point cloud of low-height obstacles under the robot. Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping algorithm, fast ground segmentation algorithm and Euclidean clustering algorithm are used to recognize the point cloud of low-height obstacles and obtain low-height obstacle in-formation. Then, combined with the structural characteristics of the robot, the obstacle-surmounting action planning is carried out for two types of obstacle scenes. A segmented approach is used for action planning. Gait units are designed to describe each segment of the action. A gait matrix is used to describe the overall action. The paper also analyzes the stability and surmounting capability of the robot’s key pose and determines the robot’s surmounting capability and the value scheme of the surmounting control variables.

The experimental verification is carried out on the robot laboratory platform (BIT-6NAZA). The obstacle recognition method can accurately detect low-height obstacles. The robot can maintain a smooth posture to cross low-height obstacles, which verifies the feasibility of the adaptive obstacle-surmounting method.

The study can provide the theory and engineering foundation for the environmental perception of the unmanned platform. It provides environmental information to support follow-up work, for example, on the planning of obstacles and obstacles.

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.

Online retailers have become gradually popular to offer consumers installment payment services in the past few years. This paper aims to study how to determine the duration and rate of installment payment services, as well as the price of products to increase online retailers’ profits.

By modeling the utility functions, the behavior of consumers for strategic choosing the payment method and payment timing is analyzed. Thus, the market segments are obtained through the comparison of the consumer’s utilities. Combined with the given assumptions, the installment payment strategies for online retailers is investigated. This paper focuses on the impact of installment payment services on consumers’ purchasing behavior and online retailers’ profits by modeling and comparative analysis. No installment payment service as a benchmark, it is demonstrated whether online retailers can obtain more profits by offering installment payment services or what are the applicable conditions for installment payments.

If the installment payment service is offered, online retailers can gain more profits and need to adopt appropriate strategies based on different market conditions. During the depression or the peak shopping season, online retailers should take the strategy of free installment rate, and moderately increasing the product price of no installment service. When market demand is stable or during non-peak season, online retailers need to set a higher installment rate and maintain the product price without installment service. Finally, online retailers should determine the maximum duration of installments they can afford based on own risk control cost and allow consumers to freely choose the length of the installment within the duration limit.

First, the authors deeply analyze consumers’ payment and purchase behavior when the online retailer offers the installment payment service. Then, it is theoretically proved why many online retailers have offered installment payment services to consumers from a profit perspective. Finally, this paper proposes the optimal duration of installments, installment rate and product price in different market environments for online retailers, to provide theoretical basis and managerial insights for the development of installment payment service in online shopping.

In order to evaluate the rheological properties of asphalt more comprehensively and effectively, and to explore and discuss the practicability of relevant models in the evaluation of the rheological properties of asphalt.

Based on the rheological and viscoelastic theories, temperature scanning, frequency scanning and multiple stress creep recovery (MSCR) tests of different modified asphalt were carried out by dynamic shear rheometer (DSR) to obtain relevant viscoelastic parameters and evaluate the high temperature properties of different modified asphalt. Based on the time-temperature equivalence principle, the main curve was constructed to study the viscoelastic properties of asphalt in a wider frequency domain. The main curve was fitted with the CAM model, and the rheological properties of different modified asphalt were evaluated through the analysis of model parameters. The creep stiffness and creep velocity of different modified asphalt were obtained through the rheological test of bending beam (BBR), and the low-temperature performance of different modified asphalt was analyzed by using Burgers model to fit the creep compliance.

The results show that the high temperature rheological properties of several modified asphalt studied in the test are ranked from best to worst as follows: PE modified asphalt > SBS modified asphalt > SBR modified asphalt. Short-term aging can improve the high temperature performance of asphalt, and different types of modifiers can promote or inhibit this improvement effect. Based on BBR test and Burgers model fitting analysis, SBR modified asphalt has the best low temperature performance, followed by SBS modified asphalt, while PE modified asphalt has poor low temperature performance, so it is not suitable to be used as road material in low temperature area.

Combined with effective evaluation methods, the rheological properties of asphalt at different temperatures and angles were systematically evaluated, and the evolution of rheological properties of asphalt characterized by model parameters was further analyzed by advanced model simulation.

This paper aims to investigate the influences of dimple location on the heat transfer performance of a pin fin-dimpled channel with upright/curved/inclined pin fins under stationary and rotating conditions.

Numerical methods based on a realizable k-ε turbulent model are used to conduct this study. Three kinds of pin fins (upright, curved, inclined) and three dimple locations (front, middle, behind) are studied for Ro varying from 0 to 0.5.

On the whole, pin fin plays a dominated role in heat transfer performance compared to dimple. The heading path and interaction of the longitudinal secondary flow and jet-like flow critically affect heat transfer performance. The formation, development and impingement of jet-like flow and longitudinal secondary flow are significantly affected by dimple locations. Dimple at behind position shows the poorest heat transfer enhancement.

This study is an extend of another previous study in which an innovative curved pin fin is proposed. The originality of this paper is to evaluate the heat transfer performance for the combined cooling structure of dimple and pin fin, which will provide original and useful application and experience for turbine blade design.

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.