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This article aims to explore the key role of community participation in the protection and development of national parks under the global trend of national park development and provide reference for the construction of China’s national park system by analyzing international successful cases and experiences.

The study on “International Experience of Community Support for National Park Development” integrates multimethods, from data mining reports, journals and policy docs from WB, UNEP, to case analyses. In-depth interviews with policymakers, academics and farmers reveal needs, challenges and best practices. Comparative analysis tailors findings to China’s context, offering recommendations for enhancing community support. This hybrid approach ensures practical insights for China’s application.

The results of this study underscore the paramount significance of community participation as a cornerstone in advancing sustainable development and safeguarding national parks amidst a growing global awareness of environmental stewardship. Through a thorough examination of international National Parks such as Yellowstone, Maasai Mara, Uluru-Kata Tjuta and Sanjiangyuan, we reveal a blueprint of success that hinges on robust policy support, empowerment of local communities, strategic economic incentives and multifaceted cross-sectoral collaborations. In the context of domestic hurdles, including inadequate legal frameworks, narrow participation avenues and resource scarcities, our analysis outlines actionable recommendations aimed at fortifying policy and legal frameworks, establishing efficient engagement modalities, bolstering community capacity-building initiatives and fostering economic sustainability. This comprehensive approach presents a visionary roadmap for World’s national park system, guiding it towards achieving an optimal equilibrium where ecological integrity and community prosperity coexist harmoniously.

The article underscores the originality in illuminating the pivotal role of community participation in national park protection and development amidst a global shift. By delving into international exemplars like Yellowstone, Maasai Mara, Uluru-Kata Tjuta, Sanjiangyuan and Panda, it uncovers novel insights on policy frameworks, community empowerment, economic incentives and collaborative models. This work contributes to the burgeoning discourse on balancing ecological conservation with socioeconomic development, providing a blueprint for sustainable national park management of all the world.

This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how product market competition moderates this relationship.

This research tests the hypotheses using the fixed effects model based on panel data of publicly listed enterprises in China from 2007–2020.

The empirical results validate the positive association between trade disputes and corporate research and development (R&D) intensity as well as the U-shaped relationship between trade disputes and radical innovation. Additionally, the moderating effect of product market competition is verified: a concentrated market with less competition flattens the U-shaped curve of radical innovation induced by trade disputes; as the market becomes more concentrated and less competitive, the U-shaped relationship eventually turns into an inverted U.

First, this study contributes to the corporate innovation and trade dispute literature by expanding the environmental antecedents of technological innovation and the firm-level consequences of trade disputes. Second, this study enriches the theoretical framework of the environment–innovation link through an integrated perspective of contingency theory and dynamic capabilities view. Third, instead of the traditional linear mindset which had led to contradictory results, this study explores a curvilinear effect in the environment–innovation relationship.

The purpose of this paper is to study the corrosion behavior of Q235 steel in saturated acidic red and yellow soils.

The corrosion behavior of Q235 steel in saturated red and yellow soils was compared by weight-loss, SEM/EDS, 3D ultra-depth microscopy and electrochemical measurements.

R_p of the steel gradually increases and i_corr gradually decreases in both the red and yellow soils with time. The R_p of the steel in the red soil is lower, but its i_corr is higher than that in the yellow soil. The uniform corrosion rate, diameter and density of the corrosion pit on the steel surface in the red soil are greater than those in the yellow soil. Lower pH, higher contents of corrosive anions and high-valence Fe oxides in the red soil are responsible for its higher corrosion rates and local corrosion susceptibility.

This paper investigates the difference in corrosion behavior of carbon steel in saturated acidic red and yellow soils, which can help to understand the mechanism of soil corrosion.

The precast concrete slab track (PST) has advantages of fewer maintenance frequencies, better smooth rides and structural stability, which has been widely applied in urban rail transit. Precise positioning of precast concrete slab (PCS) is vital for keeping the initial track regularity. However, the cast-in-place process of the self-compacting concrete (SCC) filling layer generally causes a large deformation of PCS due to the water-hammer effect of flowing SCC, even cracking of PCS. Currently, the buoyancy characteristic and influencing factors of PCS during the SCC casting process have not been thoroughly studied in urban rail transit.

In this work, a Computational Fluid Dynamics (CFD) model is established to calculate the buoyancy of PCS caused by the flowing SCC. The main influencing factors, including the inlet speed and flowability of SCC, have been analyzed and discussed. A new structural optimization scheme has been proposed for PST to reduce the buoyancy caused by the flowing SCC.

The simulation and field test results showed that the buoyancy and deformation of PCS decreased obviously after adopting the new scheme.

The findings of this study can provide guidance for the control of the deformation of PCS during the SCC construction process.

This study aims to use corporate social responsibility (CSR) reporting focused on poverty alleviation in China as a case to demonstrate a unique interplay between the state and private enterprises. It illustrates how CSR reporting has influenced both the mechanisms and outcomes of their interactive relationship, contributing to the construction of symbolic power.

Drawing on Bourdieu’s theory of symbolic power, this study explores how symbolic power has been constructed and reinforced between the state and private enterprises. It highlights the unique role of CSR reporting in facilitating an alignment between private enterprises objectives and state goals, ultimately reinforcing symbolic and social order. The empirical materials examined are the CSR reports prepared by the top 20 private enterprises in China from 2017 to 2022.

Major private business enterprises in China actively engage with the state’s objectives on poverty alleviation as reflected through their CSR reporting practices. This engagement is evidenced by shifts in keywords, dominant language and reporting structure, which closely align with the state’s stance on the issue. As a result, these enterprises receive heightened public recognition, which in turn helps reinforce the symbolic power and its influence on corporate behaviour.

This paper contributes to the CSR accounting literature by revealing a strategic role of CSR reporting that extends beyond conventional compliance levels commonly observed in Western liberal democratic societies. It serves as a function that facilitates interaction between the state and private enterprises in a symbolic power relationship, where both parties mutually benefit from the alignment of interests in poverty alleviation and social positioning.

This study aims to identify the key characteristics of tourism live streamers (TLSers) that influence target consumers and examine how these characteristics enhance destination brand value by stimulating consumer emotional engagement and value co-creation behaviors.

A questionnaire survey was conducted with 552 respondents who had viewed tourism live streaming in China. The data were analyzed using structural equation modeling.

The results revealed that TLSers’ expertise had the strongest influence on consumers and positively affected their attachment, trust, participation and citizenship behaviors and perceived destination brand value. Attractiveness and trustworthiness exerted positive but weaker effects on these variables.

This study contributes to the theoretical development of live-streaming research by demonstrating the distinct impacts of TLSer characteristics. Furthermore, this study expands the application of the social exchange theory and value co-creation in tourism research.

本研究旨在确定影响目标消费者的旅游直播主（TLSers）的关键特征, 并检验这些特征如何通过激发消费者情感参与和价值共创行为来增强目的地品牌价值。

对在中国观看过旅游直播的552名受访者进行了问卷调查, 采用结构方程建模分析数据。

研究结果显示, TLSers的专业知识对消费者影响最大, 并积极影响他们的情感依恋、信任、参与和公民行为, 以及感知的目的地品牌价值。吸引力和可信度对这些变量的影响较弱但也是积极的。

本研究通过展示TLSer特征的独特影响, 对直播研究的理论发展做出了贡献。此外, 本研究扩展了社会交换理论和价值共创在旅游研究中的应用。

Linear addition is commonly used to generate ensemble forecasts for decomposition ensemble models but traditionally treats individual modes with equal weights for simplicity. Using Taiwan air passenger flow as an empirical case, this study examines whether incorporating weighting for individual single-mode forecasts assessed by grey relational analysis into linear addition can improve the accuracy of the decomposition ensemble models used to forecast air passenger demand.

Data series are decomposed into several single modes by empirical mode decomposition, and then different artificial intelligence methods are applied to individually forecast these decomposed modes. By incorporating the correlation between each forecasted mode series and the original time series into linear addition for ensemble learning, a genetic algorithm is applied to optimally synthesize individual single-mode forecasts to obtain the ensemble forecasts.

The empirical results in terms of level and directional forecasting accuracy showed that the proposed decomposition ensemble models with linear addition using grey relational analysis improved the forecasting accuracy of air passenger demand for different forecasting horizons.

Accurately forecasting air passenger demand is beneficial for both policymakers and practitioners in the aviation industry when making operational plans.

In light of the significance of improving the accuracy of decomposition ensemble models for forecasting air passenger demand, this research contributes to the development of a weighting scheme using grey relational analysis to generate ensemble forecasts.

This paper attempts to combine the application of artificial intelligence in predicting and evaluating the classification of surrounding rock grades and provides guidance for subsequent support design and reinforcement support operations.

This paper discusses the use of BPNN as the primary tool, combined with three swarm bionic optimization algorithms (GA, PSO, GWO), to solve stability evaluation and grade prediction of surrounding rock in ultra-deep roadway excavation.

Taking the Great Wall ore group as the core and the Shanghaimiao mining area as the extension, the optimal model is applied to the classification of surrounding rock grade in ultra-deep roadway engineering. Prediction results show that the performance of BPNN models is excellent.

Due to the limitations of geological conditions and construction environment in deep coal mines, the period of roadway excavation is too long, resulting in less data collection.

The prediction results can provide guidance for the excavation method, support scheme correction and reinforcement support scheme design of deep coal mine roadway engineering.

It provides guidance for deep mining of coal mine (the premise of surrounding rock support stability), so as to ensure the economic and safety benefits of coal enterprises.

The neural network is applied to rock mechanics in a deep site for the first time, which is used to solve the prediction direction of surrounding rock grade evaluation. The index of the input layer is determined by combining the “three high and one disturbance” with the on-site construction situation, which is closer to the actual project. The swarm intelligent bionic algorithms are selected to optimize the hyperparameters of back propagation neural network, so as to improve the accuracy of the models. The classification and evaluation system of surrounding rock for the Great Wall ore group is constructed, which is the core of Shanghaimiao mining area in the northwest of China, guiding the dynamic adjustment of on-site excavation and support operations.

The purpose of this study is to investigate the impact of the negative expectation–performance gap on the internationalization speed as well as the moderating role of organizational slack, based on the performance feedback theory and the springboard perspective.

This paper takes the Chinese A-share listed companies engaged in outward foreign direct investment (OFDI) between 2010 and 2022 as the research sample. A two-way fixed effects model is employed to test the research hypotheses, using a dataset comprising 6,868 observations.

The findings show that there is a positive relationship between the negative expectation–performance gap and internationalization speed for Chinese multinational enterprises (CMNEs). In addition, this effect is stronger in private CMNEs. Furthermore, the relationship is negatively moderated by organizational slack. Additional findings suggest that that negative industry expectation-performance gap has a stronger impact on the internationalization speed. The moderating effect of unabsorbed slack resources is more pronounced.

When emerging market multinational enterprises (EMNEs) face the dilemma of underperforming, they may consider a rapid internationalization strategy as a solution to improve performance. However, EMNEs should be wary of falling into a resource trap. Organizational slack reduces managers’ incentives to identify issues associated with negative performance feedback, thereby diminishing the likelihood of addressing performance challenges through rapid internationalization. For state-owned EMNEs, optimizing organizational structure and improving the efficiency of responses to negative performance feedback are essential.

Unlike previous studies, this paper integrates performance feedback theory and the springboard perspective to explore in depth the relationship between performance feedback, internationalization speed and organizational slack within the context of managers’ cognitive and decision-making mechanisms. It also examines the distinct impacts of historical and industry negative expectation–performance gaps as well as the different moderating roles of absorbed and unabsorbed organizational slack, which have not been explored together before.

As China is on an inevitable march into the digital era, firms have accumulated abundant digital assets, such as algorithms and data. Facing the possibility of using digital assets as a new type input, besides traditional inputs such as capital and labor, would powerful managers perform better? Would managerial power help managers increase the efficiency of how a firm combines traditional and digital inputs and converts them into outputs? Thus, the purpose of this study is to investigate whether powerful managers promotes corporate productivity by using digital assets as a new input.

Using data from listed Chinese firms between 2008 and 2020, the authors constructed panel regressions with three-way fixed effects to examine whether and how managerial power influences corporate productivity in the current digital context, particularly under market uncertainty.

The findings reveal no consistent relationship between managerial power and corporate productivity. The results explain this from two contrasting effects: while managerial power promotes technological change it hinders technical efficiency – two components of total productivity. Moreover, this study identifies market uncertainty as a significant external contingency. In uncertain markets, strong managerial power positively impacts corporate productivity.

The results extend extant theoretical insights in the literature on how managerial power might influence corporate productivity.