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The advancements in generative artificial intelligence (GenAI) encourage disruptive transformation in the hospitality industry. Previous discussions predominantly focused on the impact of AI-powered agents on the labor force. This research extends previous studies by investigating the feasibility of GenAI as an information search agent in comparison to the predominant role of search engines.

Based on the Tourist Online Information Search Behavior framework, the authors proposed that consumers’ GenAI adoption may vary upon search purpose (search type), individual differences (travel motive) and situational differences (GenAI task-oriented customization level). Four studies with a total number of 813 participants were conducted.

Taking GenAI over traditional search engines for pre-trip information search significantly increased with a non-decision-based (vs decision-based) purpose. To enhance the adoption of GenAI in its less effective but more important decision-based situations, the authors proposed and confirmed the incremental effect of utilitarian travel motives and task-oriented customization levels.

This study highlights GenAI’s potential as an information communication technology (ICT). This encourages tourism and hospitality businesses to consider integrating GenAI to strengthen ICT services. Moreover, search type, travel motive and task-oriented customization level are important in deploying GenAI for ICT improvement.

This study deepens the understanding of GenAI adoption in the tourism and hospitality sector by elaborating on the GenAI-as-ICT perspective and offers fresh insights into AI for pre-trip or pre-consumption information search.

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea, wind energy has great potential to become the primary energy. As a critical part of the wind turbine, the gearbox of a wind turbine often bears a large external load. Especially at sea, due to the effects of ocean corrosion, waves and wind, the burden of the wind turbine gearbox is greater, which brings great challenges to its reliability analysis. This study aims to systematically review the reliability research in wind turbine gearboxes and guide future research directions and challenges.

This study systematically reviews some design requirements and reliability analysis methods for wind turbine gearboxes. Then, it summarizes previous studies on wind load uncertainty modeling methods, including the processing of wind measurement data and the summary of three different classifications of random wind speed prediction models. Finally, existing reliability analysis studies on two major parts of the gearbox are described and summarized.

First, the basic knowledge of wind turbine gearboxes and their reliability analysis is introduced. The requirements and reliability analysis methods of wind turbine gearboxes are explained. Then, the processing methods of wind measurement data and three different random wind speed prediction models are described in detail. Furthermore, existing reliability analysis studies on two common parts of wind turbine gearboxes, gears and bearings, are summarized and classified, including a summary of bearing failure modes. Finally, three possible future research directions for wind turbine gearbox reliability analysis are discussed, namely, reliability research under the influence of multiple factors on gears, damage indicators of bearing failure modes and quantitative evaluation criteria for the overall dynamic characteristics of offshore wind turbine gearboxes and a summary is also given.

This paper aims to systematically introduce the relevant contents of wind turbine gearboxes and their reliability analysis. The contents of wind speed data processing, predictive modeling and reliability analysis of major components are also comprehensively reviewed, including the classification and principle introduction of these contents.

Addressing users’ migration is a prerequisite for the sustainable development of the sharing economy. Ethical concerns that may lead to users’ migration are frequent in sharing economy platforms. Therefore, this study explores whether the long-term governance of sharing economy platforms can effectively mitigate users’ migration caused by ethical concerns.

Using a questionnaire survey of 549 participants, this study investigated the mechanism of users’ migration and governance strategies in the platform ecosystem based on trust theory.

The results indicate that users’ ethical concerns regarding the platform ecosystem significantly and positively influence their migration. Furthermore, users’ continued trust played a significant mediating role in the relationship between ethical concerns and users’ migration. The results also showed that future orientation and resilience significantly moderated the impact of users’ ethical concerns on their continued trust, thereby weakening this effect.

The author clarified the relationship between ethical concerns and users’ migration, identified the underlying mechanisms and provided guidance on how to mitigate migration behavior. However, users’ migration is influenced by various factors beyond ethical concerns. In addition to some factors that lead to migration, other factors make users stay on the platform. Future research should integrate multiple factors.

This study reveals the mechanism of action between users’ migration and ethical concerns in the platform ecosystem and sheds light on the output of long-term orientation practices of the platform.

Enterprises use social media for their daily work. The use of social media in the workplace is crucial for social connections, the growth and evolution of the enterprise, and it opens up new avenues for voice behavior. Employee voice involves the expression of ideas or opinions towards enterprise and is beneficial for employee work and enterprise development. Extant studies of voice behavior usually focus on the leadership and employee factors. However, the internal mechanism of voice behavior, especially the interrelationship between different kinds of social media use and voice behavior has not been well investigated. To fill that research gap, this study analyzes the internal mechanism of voice behavior, taking the effects of social media use and social capital into consideration.

Using structural equation model, this study collected data from employees using social media and analyzed the data using the software of Smartpls 3.0, SPSS and AMOS, in order to analyze the internal mechanism of voice behavior among employees.

Based on social capital theory, this study investigates the relationship between social media use, social capital and voice behavior, and provides some insights into the mechanism of voice behavior. The social media use, social capital and voice behavior are divided into several kinds in order to clarify the internal mechanism of voice behavior more comprehensively. The empirical results show that: (1) Social media use for both work and social-related purposes could positively affect employees’ promotive and prohibitive voice behaviors. (2) Social capital mediates the relationship between social media use and voice behavior. (3) In the process of social media use influencing employees’ voice behavior, employees of different genders and ages show significant differences in social capital and voice behavior.

This study explored the internal mechanism of voice behavior, which could help to elicit the relationship between social media use and voice behavior. By integrating the roles of social capital, individual differences, this study could uncover the deep internal mechanism of employee voice behavior more comprehensively, broadening social capital theory and enriching the researches of voice behavior among employees.

This paper aims to explore new variable separation solutions for a new generalized (3 + 1)-dimensional breaking soliton equation, construct novel nonlinear excitations and discuss their dynamical behaviors that may exist in many realms such as fluid dynamics, optics and telecommunication.

By means of the multilinear variable separation approach, variable separation solutions for the new generalized (3 + 1)-dimensional breaking soliton equation are derived with arbitrary low dimensional functions with respect to {y, z, t}. The asymptotic analysis is presented to represent generally the evolutions of rogue waves.

Fixing several types of explicit expressions of the arbitrary function in the potential field U, various novel nonlinear wave excitations are fabricated, such as hybrid waves of kinks and line solitons with different structures and other interesting characteristics, as well as interacting waves between rogue waves, kinks, line solitons with translation and rotation.

The paper presents that a variable separation solution with an arbitrary function of three independent variables has great potential to describe localized waves.

The roles of parameters in the chosen functions are ascertained in this study, according to which, one can understand the amplitude, shape, background and other characteristics of the localized waves.

The work provides novel localized waves that might be used to explain some nonlinear phenomena in fluids, plasma, optics and so on.

The study proposes a new generalized (3 + 1)-dimensional breaking soliton equation and derives its nonlinear variable separation solutions. It is demonstrated that a variable separation solution with an arbitrary function of three independent variables provides a treasure-house of nonlinear waves.

Revenue management (RM) is a significant technique to improve revenue with limited resources. With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China, it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.

This paper proposes the theory and framework of generalized RM of railway passenger transport (RMRPT), and the thoughts and methods of the main techniques in RMRPT, involving demand forecasting, line planning, inventory control, pricing strategies and information systems, are all studied and elaborated. The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT. The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.

The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.

The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.

Transporting hydrogen through natural gas pipelines in blended compositions has been proven to be a highly feasible solution in the short term. However, under hydrogen-rich environments, steel structures are prone to hydrogen-induced damage (HID). Additionally, uncertainties in various parameters can significantly impact the performance evaluation of hydrogen pipelines. Efficient reliability and sensitivity analyses of medium- to high-strength steel pipelines considering HID have become a challenge. Therefore, the primary aim of this study is to address this issue.

This study first establishes reliability analysis models for medium- to high-strength steels, represented by X65 and X80. In these models, the effect of HID is expressed by reduced stress, and its statistical parameters are calculated. Then, a highly efficient enhanced first order reliability method (FORM) is proposed for pipeline reliability analysis. This method overcomes the oscillation and convergence issues of traditional FORM when dealing with certain problems and can compute negative reliability indices. The proposed reliability analysis method is applied to solve the constructed reliability models. Finally, a reliability sensitivity analysis is conducted on the models to identify the key variables affecting the reliability of medium- to high-strength steel pipelines under HID.

First, two reliability analysis examples are used to validate the effectiveness of the proposed enhanced FORM. Then, using this method to solve the constructed reliability models for X65 and X80 steel pipelines under HID reveals that, for both types of steel, the reliability indices decrease significantly when considering HID compared to cases without HID. The decline is more pronounced for X80 steel than for X65 steel. As internal pressure increases, the reliability of both steels drops sharply, showing a concave parabolic trend. Moreover, the reliability sensitivity analysis shows that at a pressure of 10 MPa, for both X80 and X65, internal pressure, pipeline wall thickness and model error are the top three factors influencing reliability. As internal pressure increases, its influence becomes stronger, while the impact of other variables diminishes. Notably, for X80 steel, the presence of hydrogen amplifies the effect of internal pressure on pipeline reliability compared to when HID is not considered, but for X65, this trend is reversed.

Given the urgent need for safety evaluation studies on hydrogen transport through natural gas pipelines, this research provides new insights by constructing reliability models for X65 and X80 pipeline steels under HID and introducing an enhanced FORM method. The results of the reliability and sensitivity analyses of the models offer valuable insights and serve as a reference for engineering design.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

Green innovation (GI) in megaprojects has become a significant research topic that attracts both megaproject management scholars' and practitioners' attention. Green transformational leadership (GTL) is acknowledged as an important antecedent to GI in the permanent context. However, limited research investigates the mechanism and condition of how GTL effectively affects GI in the temporary (i.e. megaproject) context. This study seeks to examine the mechanism and condition of GTL in improving GI by assessing the mediating role of green knowledge sharing (GKS) and the moderating effect of innovation climate (IC).

Regression analysis was performed on data obtained from 303 experts who have been involved in megaprojects.

GTL has a significant positive impact on two aspects of GI, including green product innovation (GPDI) and green process innovation (GPCI). Besides, GKS mediates the relationship between GTL and the two aspects of GI. Moreover, IC plays a significantly positive moderating role in the relationship between GTL and GKS and the relationship between GKS and the two aspects of GI.

This study adds knowledge to the theory and practice by unveiling the “black box” between GTL and GI in the temporary (i.e. megaproject) context. First, this study extends the continuing discussion on the direct effect of GTL on GI to the temporary (i.e. megaproject) context. Second, this study facilitates the understanding of the mechanism to generate better GI performance considering the mediating role of GKS and the moderating effect of IC in the temporary (i.e. megaproject) context. The results can illuminate megaproject practitioners on generating better GI performance.

The study’s purpose is to investigate the constraints and facilitators influencing skiing participation in Beijing. This research includes three segments based on the frequency of skiing participation (i.e. non-, low-frequency-, and high-frequency skiers). By doing so, the study offers an enhanced understanding of the Chinese skiing market and unveils insights assisting industry professionals to effectively address their customers' diverse needs and expectations.

An online survey was developed based on prior research and consisted of four sections: (1) skiing participation; (2) constraints; (3) facilitators; (4) demographics. Items in the constraint and facilitator scale were measured using a 7-point Likert scale. A total of 409 participants completed the survey. The participants included 137 non-skiers, 134 low-frequency skiers, and 138 high-frequency skiers.

Through an exploratory factor analysis, three constructs emerged: general constraints, facilitators and learning constraints. As expected, facilitators were a positive predictor of skiing participation. Importantly, the emergent construct of learning constraints was a negative predictor of skiing and yet, the construct of general constraints was insignificant. Furthermore, the three segments differ significantly in household status, income, and education level.

These results support previous research noting the relevance in skiing participation of the dimensions: facilitators and learning constraints. The findings point to the need for ski resorts in Beijing to offer instructional sessions for beginners so they may become familiar with skiing fundamentals and enhance their confidence, particularly among nonskiers and low-frequency skiers.