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To develop electrode materials for supercapacitor with superior electrochemical performance and simple preparation process, the purpose of this study is to prepare flexible CC/NiS/a-NiS electrodes with self-supporting structure by loading hydrothermally synthesized a-NiS particles along with nano-NiS on carbon cloth by electroplating method.

The effects of current densities, temperatures and pH values on the loading amount and uniformity of the active substances during the plating process were investigated on the basis of optimization of surface morphology, crystalline structure and electrochemical evaluation as the cyclic voltammetry curves, constant current charge–discharge curves and AC impedance.

The a-NiS particles on CC/NiS/a-NiS were mostly covered by the plated nano-NiS, which behaved as a bulge and provided a larger specific surface area. The CC/NiS/a-NiS electrode prepared with the optimized parameter exhibited a specific capacitance of 115.13 F/g at a current density of 1 A/g and a Coulomb efficiency of 84% at 5 A/g, which is superior to that of CC/NiS electrode prepared by electroplating at a current density of 10 mA/cm², a temperature of 55°C and a pH of 4, demonstrating its fast charge response of the electrode and potential application in wearable electronics.

This study provides an integrated solution for the development of specifically structured NiS-based electrode for supercapacitor with simple process, low cost and high electrochemical charge/discharge performance, and the simple and easy-to-use method is also applicable to other electrochemically active composites.

For nanostores, striving to become the community group-buying leader is gaining prominence. This paper aims to construct Hotelling linear models to investigate whether nanostores should be registered as leaders and their decisions in a competitive environment.

This paper constructs three Hotelling linear models: neither nanostore registers as community leader, only one nanostore registers as community leader and both nanostores register as community leader. The competitive operation strategies of two general nanostores under three scenarios are solved.

The study finds that nanostores without a cost advantage may benefit from being the first leader. The nanostore's preferred decisions depend on the investment cost parameters of its own and competitors which may lead to market share competition. Furthermore, consumers' sensitivity to community group-buying service has a negative effect on nanostores' profit.

The study is one of the few to consider the competition between community leaders. Besides, the study considers that the utilities functions of consumers are concurrently impacted by the service decisions, along with the price in different nanostores. It can provide nanostores useful implications in the dynamic industry.

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.

Most prior studies treated human resource management (HRM) strength as a whole, while neglecting the dynamic interactions between distinct components (consensus, consistency and distinctiveness). The authors lack a deep understanding of how different components operate together to influence burnout. To address these gaps, this study aims to adopt signaling theory to investigate the interactions among different components and their impacts on employee burnout.

The authors collected time-lagged data from 231 full-time employees in manufacturing firms in Suzhou, China. The authors used the PROCESS Model 6 and hierarchical multiple regression to analyze the data.

This study found that HRM system consensus and consistency mitigate employee burnout, whereas HRM distinctiveness is not significantly related to burnout. Furthermore, the authors revealed that HRM system consistency (rather than distinctiveness) mediated the relationship between consensus and burnout. Moreover, the authors found the sequential mediating effects of HRM system distinctiveness and consistency on the association between consensus and burnout.

Considering that employees’ well-being problems may be debilitating and overwhelming during the COVID-19 pandemic, it is particularly ethical and timely for managers to direct attention to the role of HRM system strength in addressing employee burnout.

This study advances the HRM system literature by teasing out the interactions between the three pivotal components of HRM strength. Our study is among the first to empirically investigate the internal relationships between the meta-features of the HRM system and employee burnout. In doing so, the authors develop a more nuanced understanding of the collective nature of a strong HRM system that conveys a shared message about HRM to promote well-being.

Market evaluation of products is the basis for product innovation, yet traditional expert-based evaluation methods are highly dependent on the specialization of experts. There exist a lot of weak expert-generated texts on the Internet of their own subjective evaluations of products. Analyzing these texts can indirectly extract the opinions of weak experts and transform them into decision-support information that assists product designers in understanding the market.

In social networks, a subset of users, termed “weak experts”, possess specialized knowledge and frequently share their product experiences online. This study introduces a comparative opinion mining framework that leverages the insights of “weak experts” to analyze user opinions.

An automotive product case study demonstrates that evaluations based on weak expert insights offer managerial insights with a 99.4% improvement in timeliness over traditional expert analyses. Furthermore, in the few-shot sentiment analysis module, with only 10% of the sample, the precision loss is just 1.59%. In addition, the quantitative module of specialization weighting balances low-specialization expert opinions and boosts the weight of high-specialization weak expert views. This new framework offers a valuable tool for companies in product innovation and market strategy development.

This study introduces a novel approach to opinion mining by focusing on the underutilized insights of weak experts. It combines few-shot sentiment analysis with specialization weighting and AHP, offering a comprehensive and efficient tool for product evaluation and market analysis.

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.

The purpose of this paper is to explore the determinants of entrepreneurs’ subjective social status perception (SSP) on firm international behaviors based on the upper echelons theory and social class theory.

To test the hypotheses, the authors studied a large sample of 10,823 small- and medium-sized private Chinese enterprises from 2006 to 2014.

The results showed that entrepreneurs with higher status perception prefer international activity and firms have higher export intensity and intention. In addition, the social capital of entrepreneurs and institutional environment amplifies the positive relationship between SSP and international behavior.

This paper contributes to research on the upper echelon of management and extends our understanding of how managerial social characteristics influence international strategic decision-making. Besides, it also contributes to the emerging stream of social status research in international expansion studies and expand researchers’ limited understanding of the effects of social status in business settings.

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.

The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

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.