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This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g. Xiaohongshu and Weibo).

This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

User value co-creation behaviors are crucial for the sustainable development of Virtual Brand Communities. This research, grounded in social exchange theory, investigates the impact of community satisfaction and identification on customer value co-creation behaviors and further explores how the reciprocity norm moderates these relationships.

Our research data were collected from users across multiple brand communities, totaling 481 survey responses. Structural equation modeling was performed to test the research hypotheses.

These results provide in-depth insights into the nexus between user-community relationships and customer value co-creation behaviors. While community satisfaction and identification positively influence co-creation, their effects vary across different value co-creation behaviors. Notably, the reciprocity norm within the community dampens the relationship between community satisfaction and value co-creation behaviors.

Unlike previous studies focusing on customer value co-creation behaviors, our research emphasizes social exchange, unveiling the mechanisms behind customer value co-creation. Our findings not only enrich the body of knowledge on customer value co-creation but also deepen our understanding of online collective behavior and knowledge sharing, offering valuable insights for the development of virtual communities.

Two friction models of Fe-Fe and Diamond-like carbon (DLC)-Fe were established by molecular dynamics (MD) method to simulate the friction behavior of traditional fracturing pump plunger and new DLC plunger from atomic scale. This paper aims to investigate the effects of temperature and load on the friction behavior between sealed nitrile butadiene rubber (NBR) and DLC films.

In this study, MD method is used to investigate the friction behavior and mechanism of DLC film on plungers and sealing NBR based on Fe-Fe system and DLC-Fe system.

The results show that the friction coefficient of DLC-Fe system exhibits a downward trend with increasing load and temperature. And even achieve a superlubricity state of 0.005 when the load is 1 GPa. Further research revealed that the low interaction energy between DLC and NBR promoted the proportion of atoms with larger shear strain in NBR matrix and the lower Fe layer in DLC-Fe system to be much lower than that in Fe-Fe system. In addition, the application of DLC film can effectively inhibit the temperature rise of friction interface, but will occur relatively large peak velocity.

In this paper, two MD models were established to simulate the friction behavior between fracturing pump plunger and sealing rubber. Through the analysis of mean square displacement, atomic temperature, velocity and Interaction energy, it can be seen that the application of DLC film has a positive effect on reducing the friction of NBR.

As after-hours technology-mediated work (ATW) becomes common in organizations, the increased workload and interference to life caused by ATW has induced employee turnover. This research develops a mediated moderation model to explain how employees' intrinsic and extrinsic motivations for ATW affect their turnover intention through work–life conflict.

A survey was conducted to collect data of 484 employees from Chinese companies. Partial Least Square was used to perform data analysis.

The results show that intrinsic motivation for ATW has an indirect negative impact on turnover intention via work–life conflict, whereas extrinsic motivation for ATW has both a positive direct impact and a positive indirect impact (via work–life conflict) on turnover intention. This study also helps find that time spent on ATW can strengthen the positive impact of extrinsic motivation for ATW on turnover intention but has no moderation effect on the impact of intrinsic motivation for ATW. Furthermore, this study reveals that the interaction effect of time spent on ATW and extrinsic motivation on turnover intention is mediated by employees' perceived work–life conflict.

By discovering the distinct impact of employees' intrinsic and extrinsic motivations for ATW on turnover intention, this research provides a contingent view regarding the impact of ATW and offers guidance to managers regarding how to mitigate ATW-induced turnover intention through fostering different motivations.

The critical chain project buffer monitor process addresses uncertainty and variability in project duration. However, classical buffer monitor methods only consider buffer consumption, while the dynamic allocation of buffer zones and the buffer consumption trend of activities are ignored. This paper presents the innovative framework for dynamic monitoring of project buffer which covers the dynamic buffer allocation, predictive analytics of buffer utilization and a new monitoring technique based on control chart graph.

First, a dynamically buffer allocation model is framed, and buffer zones are given to the activities considering risks. Then, a predictive model amalgamating Bayesian Optimization, Convolutional Neural Networks, and Long Short-Term Memory networks (BO-CNN-LSTM) is framed. Finally, a new buffer monitor framework is constructed that takes into account historical information about buffer usage and utilizes two thresholds derived from control chart theory.

This approach is empirically tested on a representative agricultural website project in China. The results show that, first, the dynamic buffer allocation makes better use of the project buffer, reduces buffer waste and increases the possibility of timely completion of the project. Second, the BO-CNN-LSTM model predicts better than Long Short-Term Memory (LSTM) and Grey Neural Network Model (GNNM), providing project managers with new management insights and perspectives. Third, the novel monitoring procedure makes the leveraging of historical data possible in the control of the schedule deviations, allowing for more timely interventions in the course of the implementation of the project.

A new project buffer monitoring method suitable for uncertain project environments is proposed.

The purpose of this study is to examine the effect of collaborative innovation networks on new product development (NPD) performance in small and medium-sized enterprises (SMEs). It also investigates the mediating role of business model innovation and moderating role of collaboration experience and external information technology (IT) capability in the above relationship.

To test the research hypotheses about the relationships above, survey data were collected from 209 Chinese manufacturing SMEs. Multiple hierarchical regressions analysis was used to examine the hypotheses.

Results reveal that collaborative innovation networks have positive impacts on NPD performance in SMEs. Moreover, business model innovation mediates and collaboration experience and external IT capability positively moderate the relationship between collaborative innovation networks and NPD performance in SMEs.

This study paints a more complete picture of the relationship between collaborative innovation networks and NPD performance in SMEs and advances the understanding of how and when SMEs enhance their NPD performance through collaborative innovation networks.

The impact of digital technology in the wider travel field has been substantial and significant, changing both the competitive landscape of businesses and the behavior of travelers. However, we are now on the cusp of new digital developments encompassing cloud computing, blockchain, internet of things (IoT) and above all, artificial intelligence (AI), which are predicted to disrupt the business and consumer sides of several industries – travel included. This study aims to frame this upcoming digital transformation in travel within a human-centered approach where the critical understanding of digital humanism principles will enrich social scientists’ research agenda in the coming years.

The viewpoint follows a structure based on (i) setting the scene for the rise of digital transformation, (ii) the historical perspective on digital transformation in travel, (iii) the pandemic’s impact and (iv) future development and research agenda.

It is only by fostering a human-centered digital transformation perspective that social science researchers in travel can realize the “high-tech for high-touch” promise of fostering a human-to-human encounter empowered and possibly hampered, by digital technologies. This work proposes to start from the concepts of digital technology control, participation, education and ethics to design a research agenda with a 2050 horizon.

This work has been designed to shift the attention of researchers toward a human-centered digital transformation approach to reflect on the human-machine relationship for a better society. Due to its inner characteristics the travel field can foster a reflection on this topic by reaffirming the centrality of human beings and their authorship in the travel product creation.

数字技术在更广泛的旅游领域产生了巨大而显著的影响, 改变了企业的竞争图景和游客行为。然而, 我们现在正处于新的数字发展的风口浪尖, 包括云计算、区块链、物联网以及最重要的人工智能, 预计这些技术将颠覆包括旅游业在内的多个行业的企业端和消费端。这项研究建议将即将到来的旅行数字化转型纳入以人为本的方法, 对数字人文主义原则的批判性理解将丰富社会科学家未来几年的研究议程。

该观点遵循基于以下方面的一种结构, (i)为数字化转型的兴起设定场景, （ii）旅行数字化转型的历史视角, (iii)疫情的影响和（iv）未来发展和研究议程。

只有培养以人为中心的数字化转型视角, 旅游领域的社会科学研究人员才能实现“高科技换高品质”的承诺, 培养一种被数字技术赋能但也可能受到阻碍的人与人之间的接触。这项工作建议从数字技术控制、参与、教育和伦理的概念出发, 设计一个2050年的研究议程。

这项工作旨在将研究人员的注意力转移到以人为中心的数字化转型方法上, 以反思更美好社会的人机关系。由于旅游领域的内在特征, 它可以通过重申人在旅游产品创造中的中心地位和作者身份来促进对这一主题的反思。

El impacto de la tecnología digital en el ámbito de los viajes en general ha sido sustancial y significativo, cambiando tanto el panorama competitivo de las empresas como el comportamiento de los viajeros. Sin embargo, en la actualidad estamos en la cúspide de nuevos desarrollos digitales que abarcan la nube informática, blockchain, IoT y, sobre todo, la inteligencia artificial, que se prevé que alteren los aspectos comerciales y de consumo de varias industrias, incluidos los viajes. Esta investigación propone enmarcar esta próxima transformación digital en los viajes dentro de un enfoque centrado en el ser humano, donde la comprensión crítica de los principios del humanismo digital enriquecerá la agenda de investigación de los científicos sociales en los próximos años.

El presente trabajo presenta una estructura basada en (i) el establecimiento del escenario para el auge de la transformación digital, (ii) la perspectiva histórica de la transformación digital en los viajes, (iii) el impacto de la pandemia y (iv) el desarrollo futuro y líneas de investigación.

Únicamente si se fomenta una perspectiva de transformación digital centrada en el ser humano podrán los investigadores de las ciencias sociales en el ámbito de los viajes hacer realidad la promesa de “alta tecnología para un alto contacto”, promoviendo un encuentro entre seres humanos potenciado, y posiblemente obstaculizado, por las tecnologías digitales. Este trabajo propone partir de los conceptos de control de la tecnología digital, participación, educación y ética para diseñar una agenda de investigación con horizonte 2050.

Este trabajo ha sido diseñado para desplazar la atención de los investigadores hacia un enfoque de transformación digital centrado en el ser humano para reflexionar sobre la relación ser humano-máquina para una sociedad mejor. Por sus características internas, el ámbito de los viajes puede propiciar una reflexión sobre este tema reafirmando la centralidad del ser humano y su autoría en la creación del producto turístico.

How does the regional institutional environment of China’s transitional economy influence the relationship between a firm’s R&D investment intensity and innovation performance? Based on the resource-based view and institution-based view, an empirical study was executed to identify the moderating effects of institutional environment variables from the Marketization Index of China’s Provinces: National Economic Research Institute (NERI) Report on the relationship between a firm’s R&D investment intensity and innovation performance. This paper aims to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment.

Against the background of China’s transitional economy, the authors present empirical evidence from panel data covering 374 Chinese A-share listed high-tech manufacturing firms on the Shanghai and Shenzhen Stock Exchange to examine the relationship between R&D investment intensity and innovation performance.

Empirical results illustrate the following: The R&D investment intensity and innovation performance displayed an inverse U-shaped relationship, and R&D investment intensity had a lagged effect on R&D output according to the uncertainty and industrialization period of R&D activities. The level of financial market development can intensify the effects of R&D investment intensity on innovation performance. The degree of government intervention weakens the effect of R&D investment intensity on innovation performance.

Based on the background of China’s institutional environment during the transition period, combined with previous research and the Marketization Index of China’s Provinces: NERI Report, selecting financial market development, government intervention level and legalization level as moderating variables to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment. Due to the different ownership of firms during the transition period, the appropriate impact of the institutional environment on the relationship between R&D investment intensity and innovation performance will vary. Moreover, the level of legalization would impact on innovation insignificantly.

The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying solely on textual discrepancies between the title and content to distinguish between real and fake news has proven ineffective. The purpose of this paper is to develop a new approach called semantic enhancement network with content–title discrepancy (SEN–CTD), which enhances the accuracy of fake news detection.

The SEN–CTD framework is composed of two primary modules: the SEN and the content–title comparison network (CTCN). The SEN is designed to enrich the representation of news titles by integrating external information and position information to capture the context. Meanwhile, the CTCN focuses on assessing the consistency between the content of news articles and their corresponding titles examining both emotional tones and semantic attributes.

The SEN–CTD model performs well on the GossipCop, PolitiFact and RealNews data sets, achieving accuracies of 80.28%, 86.88% and 84.96%, respectively. These results highlight its effectiveness in accurately detecting fake news across different types of content.

The SEN is specifically designed to improve the representation of extremely short texts, enhancing the depth and accuracy of analyses for brief content. The CTCN is tailored to examine the consistency between news titles and their corresponding content, ensuring a thorough comparative evaluation of both emotional and semantic discrepancies.