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External institutional policy and its impact on corporate social responsibility (CSR) have been widely discussed by researchers, but its effect still remains controversial. This study aims to use the minimum wage policy as an illustrative example to analyze its impact on the corporate social responsibility (CSR) of tourist enterprises. Furthermore, the research seeks to examine the boundary conditions that influence the minimum wage’s effect on CSR.

This paper takes the data of 42 listed tourism companies from 2010 to 2020 in China as samples and uses the mixed OLS regression method and the fixed effects panel model to examine the effect of the minimum wage on CSR.

Findings show that increasing wages has a significantly negative impact on their total CSR investment. Also, low-operating-capacity enterprises and private enterprises will react more adversely when faced with increasing minimum wages. And found that the increase of minimum wage has no significant negative impact on the strategic social responsibility of tourism enterprises; however, it has a significantly negative impact on their tactical social responsibility. In addition, as far as employees’ rights and interests are concerned, the minimum wage increase has effectively increased employee salaries, but the nonsalary benefits of the employees have significantly decreased.

The contribution of this paper not only expands the research on the antecedents and boundary mechanisms of CSR but also clarifies the specific effect of the rise of the minimum wage on corporate social responsibility; it further deepens the impact of institutional policy factors on CSR, which also opens new perspectives for policy evaluation and provides a theoretical basis for government policymakers.

Due to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the accuracy of dynamic model for n-Degree of Freedom (DOF) serial robot.

This paper exploits a combination of the link dynamical system and the friction model to create robot dynamic behaviors. A practical approach to identify the nonlinear joint friction parameters including the slip properties in sliding phase and the stick characteristics in presliding phase is presented. Afterward, an adaptive variable-step moving average method is proposed to effectively reduce the noise impact on the collected data. Furthermore, a radial basis function neural network-based friction estimator for varying loads is trained to compensate the nonlinear effects of load on friction during robot joint moving.

Experiment validations are carried out on all the joints of a 6-DOF industrial robot. The experimental results of joint torque estimation demonstrate that the proposed strategy significantly improves the accuracy of the robot dynamic model, and the prediction effect of the proposed method is better than that of existing methods.

The proposed method extends the robot dynamic model with friction compensation, which includes the nonlinear effects of joint stick motion, joint sliding motion and load attached to the end-effector.

The study aims to understand how cultural route heritage is conceptualized and managed in China by systematically reviewing the research literature on Chinese cultural route heritage (CRH). The study intends to inspire further discussion on the theoretical and practical development of cultural routes since the development is still at a liminal stage in China.

A total of 253 research articles related to Chinese cultural rote heritage from major Chinese and English research databases China National Knowledge Infrastructure (CNKI), Web of Science (WOS) and Scopus have been comprehensively identified and reviewed for the purpose of the study.

Four major themes of research on Chinese CRH have been identified: conceptual evaluation, list of the routes and characteristics of the routes, conservation and utilization. The results revealed that China has very rich resources in CRH, many of which were formed a long time ago, which exist across vast geographic regions and have assumed multiple functions and undergone dynamic reciprocal exchanges among diverse cultures and ethnicities.

The paper summarizes some major obstacles faced by CRH in China and proposes a strategic model to address the need for a more sustainable development of CRH in the Chinese context.

The paper offers a comprehensive overview of CRH in China and discusses practical issues in management and development of heritage great in size, number and complexity.

In general, the existing compressor design methods require abundant knowledge and inspiration. The purpose of this study is to identify an intellectual design optimization method that enables a machine to learn how to design it.

The airfoil design process was solved using the reinforcement learning (RL) method. An intellectual method based on a modified deep deterministic policy gradient (DDPG) algorithm was implemented. The new method was applied to agents to learn the design policy under dynamic constraints. The agents explored the design space with the help of a surrogate model and airfoil parameterization.

The agents successfully learned to design the airfoils. The loss coefficients of a controlled diffusion airfoil improved by 1.25% and 3.23% in the two- and four-dimensional design spaces, respectively. The agents successfully learned to design under various constraints. Additionally, the modified DDPG method was compared with a genetic algorithm optimizer, verifying that the former was one to two orders of magnitude faster in policy searching. The NACA65 airfoil was redesigned to verify the generalization.

It is feasible to consider the compressor design as an RL problem. Trained agents can determine and record the design policy and adapt it to different initiations and dynamic constraints. More intelligence is demonstrated than when traditional optimization methods are used. This methodology represents a new, small step toward the intelligent design of compressors.

The purpose of this paper is to design a soft robot for performing detection, by using a hybrid drive to reach the target point faster and enable the robot to perform the detection task at a relatively fast speed.

The soft robot is driven by a mixture of motors and pneumatic pressure, in which the pneumatic pressure is used to drive the soft actuator to bend and the motors to drive the soft robot forward. The careful design of the actuator is based on a finite element simulation using ABAQUS, which combines a constant curvature differential model and the D-H method to analyze the motion space of the soft actuator.

The soft robot’s ability to adapt to the environment and cross obstacles has been demonstrated by building prototypes and complex environments such as grass, gravel, sand and pipes.

This design can improve the speed and smoothness of the motion of the soft robot, while retaining the good environmental flexibility of the soft robot. And the soft robot has good environmental adaptability and the ability to cross obstacles. The soft robot proposed in this paper has broad prospects in fields such as pipeline inspection and field exploration.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

This paper aims to test the effects of social presence (SP) and other related factors, including trust, self-construal and brand familiarity, in affecting consumers’ purchase intention of live-streaming workout courses.

Three between-subjects, Web-based experimental studies were conducted. There were separately 108, 208 and 284 valid questionnaires collected in the three studies. Moderation and mediation analyses were performed to test the research hypotheses.

Users’ sense of SP when watching live-streaming courses positively affects their willingness to purchase courses, and users’ sense of trust plays a mediating role in the influence of users’ SP on their purchase intention. In addition, when users belong to dependent self-construal rather than independent self-construal, their trust in live-streaming courses plays a stronger mediating role in the influence of users’ SP on their purchase intentions. What is more, when users have high brand familiarity rather than low brand familiarity, their trust in online live-streaming plays a stronger mediating role in the influence of users’ SP on their purchase intentions.

This research delineates the effects of SP on the consumption of live-streaming courses, thus further adding to the understanding of the role of real-time interaction in determining consumer behavior. It also highlights the roles of self-construal and brand familiarity as mediating influences on the relationship between SP and consumer trust.

Through critically reflecting on existing research on information and communication technology (ICT) in hospitality, the purpose of this study is to propose recommendations for future research to further narrow the theory-practice gap.

Personal experiences along with evidence from the literature provide a foundation for discussion, which is further enriched by integrating industry practitioners’ points of view.

Single-perspective and technology adoption studies have dominated ICT research in the hospitality literature. Technology effectiveness has often been measured indirectly. Oversimplifying technological issues has limited the generalizability of research findings.

Future studies are suggested to go beyond examining technology adoption, embrace multi-perspective approaches and incorporate a wider range of situational and contextual factors.

Through a unique perspective, this study highlights the limitations of previous ICT research in the hospitality literature and provides suggestions for future research to better meet the needs of practitioners. The arguments presented are not purely from an academic standpoint, as they have been endorsed by senior industry executives.

While existing literature emphasizes the importance of empowerment in construction projects, the working mechanisms of empowering leadership in the project context are unclear. Based on conservation of resources (COR) theory, this study aimed to examine the relationship between empowering leadership and project performance, highlighting the mediation roles of creative self-efficacy and leadermember exchange and the moderation role of perceived overqualification.

The authors collected data from 287 project members in different projects and tested the integrated conceptual model through moderated mediation analysis with bootstrapping strategy.

The results revealed that empowering leadership was positively related to project performance through creative self-efficacy and leader–member exchange. Perceived overqualification served as significant moderator.

The findings contribute to the understanding of empowering leadership in projects by verifying and extending the resource acquisition and investment process in the project context. The results of this study also demonstrated that creative belief and social exchange facilitate the effectiveness of project members' task efforts and outcomes and that perceived overqualification might not exert a detrimental effect on project performance.

This paper aims to examine the relationship between workplace spirituality and employee creativity and check the mediating role of psychological empowerment on this relationship.

An online survey developed with SurveyMonkeyTM has been shared via LinkedIn to 750 software professionals working in Indian origin. For data analysis, partial least squares-structural equation modeling (PLS-SEM) has been used, and for testing the mediation among the variables, Preacher and Hayes (2008) method is used.

The PLS-SEM results have revealed a significant positive relationship between workplace spirituality and employee creativity. There is also a positive relationship between workplace spirituality and psychological empowerment. Preacher and Hayes (2008) mediation results have revealed that psychological empowerment partially mediates between workplace spirituality and employee creativity.

The present study has filled the gap, which has been not addressed till this date and may be considered to be first-of-its kind study, which directly tried to understand the association between workplace spirituality and employee creativity among employees of Indian origin.