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The purpose of this study is to investigate family tourists’ emotional responses at world heritage sites (WHSs) by using cognitive appraisal theory (CAT).

The online survey was conducted targeting the family tourists who had travel experience at Pingyao Ancient City, a United Nations Educational, Scientific and Cultural Organization world heritage destination in Northern China.

Data analysis with 347 family tourists to the site, via structural equation modeling analysis, revealed that existential authenticity (i.e. intrapersonal and interpersonal authenticity) and family interpersonal interaction help evoke emotional experience, which generates family cohesion and storytelling behavior as responses.

This study results contribute to an existing body of literature on the ability of CAT to illustrate how emotional experience forms in the context of family tourism at WHSs. The study also provides a clear understanding on how to elicit emotions among family tourists at heritage destinations.

旨在运用认知评价理论 (CAT) 探讨家庭游客在世界遗产地 (WHSs) 的情感反应。

这项线上调查的对象为游览过平遥古城的家庭旅游者, 平遥古城是一个位于中国北方的联合国教科文名录中的世界文化遗产地。

本研究通过结构方程模型对由347名家庭旅游者提供的数据进行分析显示, 存在的真实性（即个人内部和人际真实性）和家庭人际互动有助于唤起情感体验, 从而产生家庭凝聚力和故事讲述行为的情感反应。

本研究结果为有关认知评价理论（CAT）的现有文献做出贡献, 以说明在世界遗产旅游地家庭旅游的背景下情感体验是如何形成的。该研究也为在文化遗产目的地如何引发家庭游客的情绪提供了清晰的解释。

El propósito de este estudio es investigar las respuestas emocionales de los turistas familiares en los sitios del Patrimonio Mundial (WHS) mediante el uso de la teoría de evaluación cognitiva (CAT).

Se realizó una encuesta en línea dirigida a los turistas familiares que habían tenido una experiencia de viaje en la Ciudad Antigua de Pingyao, un destino de patrimonio mundial de la UNESCO en el norte de China.

El análisis de los datos con 347 turistas familiares, a través del análisis SEM, reveló que la autenticidad existencial (es decir, la autenticidad intrapersonal e interpersonal) y la interacción interpersonal familiar ayudan a evocar la experiencia emocional, lo que genera cohesión familiar y comportamiento narrativo como respuestas.

Los resultados de este estudio contribuyen a un cuerpo existente de literatura sobre la capacidad de CAT para ilustrar cómo se forma la experiencia emocional en el contexto del turismo familiar en las CHM. El estudio también proporciona una comprensión clara sobre cómo provocar emociones entre los turistas familiares en el destino de patrimonio.

In international business (IB), the discussion of COVID-19-related global value chain (GVC) models driving resilience has taken momentum since May 2020. The purpose of this study is to uncover insights that the pandemic provided as a unique research opportunity, holistically, revealing the significant role of non-lead firms in GVC outcomes and resilience. This allows to extend theory as the authors critically identify impact criteria and assess interdependence and valence, thus progressing the traditional (pre-pandemic) IB view of GVC governance and orchestration.

This study opts for an integrative review to help create a much-needed extension of IB theory by means of a critical perspective on GVC theory. The authors examine the extant body of IB literature as the relevant stock of collective IB knowledge prompted by the COVID-19 pandemic, uncovering contributions – with a focus on the role of non-lead firms in orchestration and resilience – that allows to clarify what was not evident pre-pandemic. With this, the authors move the theory from its efficiency focus to a better recognition of the interdependencies of power and profit outcomes stemming from asymmetries of interrelationships. By design, the authors focus on the unique research period of the pandemic and orchestration complexities along the development of configurational arguments beyond simple correlations (Fiss, 2011), revealing key dependencies as key themes. The authors highlight further research avenues following Snyder (2019) that are called upon to strengthen that understanding and that helps extend theory.

This research provides a critical perspective on the application of the traditional IB views for GVC governance (designed for efficiency, cost and proximity to markets with pre-dominance for just in time), which has shifted during the pandemic to accommodate for adaptation and adjustment to resilience and just in case considerations. The holistic review reveals not only the key country- and multinational enterprise (MNE)-dependencies with residual impact determining the balance between just-in-time and just-in-case. Also, the authors advance the understanding of the (un)balance of the traditional GVC – focused on just-in-case rather than just-in-time through a lead and non-lead GVC participation and power lens yet rarely observed. The authors find that governance should not be construed as “management” such that it resolves into decisions undertaken in lead firms for execution in subordinate GVC participants. Autonomy allows to subsidiary units by MNE lead firms and/or exercised by (mainly, innovative) non-subsidiary GVC participant firms, is uncovered as a key driver in this. Greater delegation capacity appears to help provide resilience to loss in profit, with a recognition that there may be a dynamic trade-off between power and profit. In addition, the authors are able to identify correlations with innovation, demand elasticity, digital uptake, investment and other, that the authors trust will set the scene for additional research deepening and extending the findings.

Integrative literature reviews include a problem formulation (i.e. that is limited to published topics around an emerging theme) and are hence very focused in nature and approach. This applies to this paper. Data analysis in this method is not typically using statistical methods in contrast to meta-analyses. Also, the authors limit the sample to a relatively short time period with 33 publications analysed, purposefully focusing on the most prompt and “acute” insights into GVCs during the pandemic.

The traditional GVC governance model is designed for efficiency, cost and proximity to markets with pre-dominance for just in time. The authors reveal dependencies that are instrumental to better understand lead and non-lead interaction and relative autonomy, with a focus on residual impact determining the balance between just-in-time and just-in-case that, if in the sought equilibrium and agile, can allow alignment with context and this resilience. This paper specifically provides practical insights and visualization that highlights stages/“ripple” effects and their impact and the questions to ask as stakeholders look for GVC resilience. This includes, int.al., firms and their role as strategic agents, prompting participants through the learnings from exogenous shock to realign their strategies, redistributed manufacturing of production across subsidiary and non-subsidiary non-lead firms, greater competition and hence power for suppliers leveraging resilience and innovation, greater understanding of localization and regionalization of production of essential supplies, interaction with governments, and of investment impacts abroad especially to secure GVC participation.

The insights provided through this extension of theory with its literature review reveal the importance of aligning IB research into GVCs to factors that became visible through alternative or unusual settings, as they have the power to reveal the limitations of traditional views. In this case, a mainly efficiency-led, just-in-time focused GVC governance model is reviewed through the literature that emanated during the pandemic, with a critical perspective, which helped uncover and underline the complexities and evolution of GVC governance, providing fundamental support to solutioning the continuing global supply chain challenges that started as a result of the pandemic and are yet again accelerated by the Ukraine and Middle Eastern wars and its impact with, int.al., concerns over possible severe global food, labour/migration and resources crises. IB holds a social responsibility to help identify critical challenges from the disciplinary perspective and help advance resilience for social benefit.

This paper supports the original IB theory development by extending GVC theory into the lead – non-lead dynamics that may, under certain conditions, provide a “Resilience wall” for GVCs. The value created through insights stemming from a unique period of time for GVC is significant. It allows us thus also to pave the way to an emerging and critical research adaption looking into equilibrium, nuancing demand elasticity, better understanding trade and investment impacts along GVCs and more. By examining views on the sources of pandemic risks in a possibly unique setting, the authors offer added value from extant IB research insights by combining them, revealing the importance for GVCs to investigate not only key dependencies between the exogenous shock, i.e. context, and the impacts assessed through this literature but to further use their inherent value to create a framework for further conceptualization and extension of the traditional IB view on GVC governance. This work illustrates the urgency and importance for IB to take a timely and possibly more critical approach to the investigation of governance models that have, to date, shown some significant limitations.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

The current study aims to investigate the factors that impact the feedback received on answers to questions in social Q&A communities and whether the expertise-required question influences the role of these factors on the feedback.

To understand the antecedents and consequences that influence the feedback received on answers to online community questions, the elaboration likelihood model (ELM) is applied in this study. The authors use web data crawling methods and a combination of quantitative analyses. The data for this study came from Zhihu; in total, 353,775 responses were obtained to 1,531 questions, ranging from 49 to 23,681 responses per question. Each answer received 0 to 113,892 likes and 0 to 6,250 comments.

The answers' cognitive and emotional components and the answerer's influence positively affect user feedback behavior. In addition, the expertise-required question moderates the effects of the answer's cognitive component and emotional component on the user feedback, moderating the effects of the answerer's influence on the user approval feedback.

This study builds upon a limited yet growing body of literature on a theme of great relevance to scholars, practitioners and social media users concerning the effects of the connotation of answers (i.e. their cognitive and emotional components) and the answerer's influence on user feedback (i.e. approval and collaborative feedback) in social Q&A communities. The authors further consider the moderating role of the domain expertise required by the question (expertise-required question). The ELM model is applied to explore the relationships between questions, answers and feedback. The findings of this study add a new perspective to the research on user feedback and have implications for the management of social Q&A communities.

The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

This paper aims to obtain a symmetrical step-down topology with lower equivalent capacity and wider step-down range under the condition of the same output. Two new symmetrical step-down topologies of star-connected autotransformers are proposed in this paper. Taking the equivalent capacity as the main parameter, the obtained topologies are modeled and analyzed in detail.

This paper adopts the research methods of design, modeling, analysis and simulation verification. First, the star-connected autotransformer is redesigned according to the design objective of symmetrical step-down topology. In addition, the mathematical model of two topologies is established and a detailed theoretical analysis is carried out. Finally, the theoretical results are verified by simulation.

Two symmetrical star-connected autotransformer step-down topologies are designed, the winding configurations of the corresponding topology are presented, the step-down ranges of these three topologies are calculated and the influence of step-down ratio on the equivalent capacity of autotransformer are analyzed. Through analysis, the target step-down topologies are obtained when the step-down ratio is [1.1, 5.4] and [1.1, 1.9] respectively.

Because the selected research object is only a star-connected autotransformer, the research results may lack generality. Therefore, researchers are encouraged to further study the topologies of other autotransformers.

This paper includes the implications of the step-down ratio on the equivalent capacity of autotransformers and the configuration of transformer windings.

The topologies designed in this paper enable star-connected autotransformer in the 12-pulse rectifier to be applied in step-down circumstances rather than situations of harmonic reduction only. At the same time, this paper provides a way that can be used to redesign the autotransformer in other multi-pulse rectifier systems, so that those transformers can be used in voltage regulation.

Postpandemic efforts to rebuild have steered the global economy toward a more sustainable trajectory. It is imperative to acknowledge the pressing need for further enhancements in the sustainable development of the tourism industry. This study aims to examine the influence of personal factors, including environmental concern, cultural interest, travel lifestyle and involvement, on tourist satisfaction and revisit intention, using the theory of planned behavior (TPB) as its framework.

The data was gathered through surveys conducted in three of Türkiye’s most famous slow travel destinations: Seferihisar, Gökçeada and Akyaka. The analysis was carried out using SPSS and SmartPLS software, with subsequent structural model testing.

This study presents an extended model that incorporates four individual factors, tourist satisfaction, TPB and revisit intention. All hypotheses have been rigorously tested, and the model accounts for 60.4% of the variance in revisit intention. The findings are comprehensively discussed in this article, supported by relevant theoretical frameworks.

Future research avenues could delve into the evolution of slow tourism in both developed and developing countries, assess disparities in revisit intentions between slow tourism and mass tourism destinations and investigate the prospects of sustainable tourism development in the postpandemic era.

The authors use the TPB to examine individual factors, tourist satisfaction and revisit intentions, aiming to build an extended model to gain a deeper understanding of the slow tourist decision-making process.

Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.

A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.

The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.

This study has positive implications for enriching the method system of multivariable grey prediction model.

The purpose of the study is to investigate the factors that influence the adoption of new sustainability reporting (SDG) and external assurance (EXTA) practices. This study also examines the relationship between sustainability reporting activity and corporate economic performance for a sample of 99 companies in Gulf Cooperation Council (GCC) countries that addressed SDGs in their sustainability reports published in 2019.

Using a two-stage analysis, this study examines how firms’ characteristics and corporate governance variables affect SDG and economic performance, as well as the firm’s decision to adopt EXTA statements for a sample of companies in that addressed SDGs in their sustainability reports published in 2019. The authors collected data from the Global Reporting Initiative’s (GRI) Sustainability Disclosure database and the Bureau van Dijk for Orbis database.

The results show that the variables firm size, profitability, big 4 auditors and government ownership significantly affect SDG and economic performance. The results also reveal that firms operating in the manufacturing sector are positively correlated with SDG and the firm’s decision to adopt EXTA statements. Furthermore, the results indicate that board independence positively affects SDGs and EXTA.

The results can be particularly relevant and timely in helping large GCC companies promote their engagement to sustainable development practices by adopting more sustainable long-term strategies and policies. The findings could also guide managers in the strategic direction to identify firms’ characteristics and corporate governance features essential to promote sustainability reporting, an increasingly important performance indicator for investors and to enhance their confidence in the capital market. The results may also have practical implications to policymakers and other regulators in GCC countries to define effective frameworks that promote sustainable development reports and the use of EXTA.

The results make significant contributions by providing new insights to the existing literature on sustainability reporting in emerging markets by examining a unique perspective on the influence of firms’ characteristics and corporate governance features on the adoption of new sustainability reporting practices. The authors further add to the previous literature on the relationship between a firm’s economic performance and sustainable reporting by providing evidence from large companies in GCC countries, which might benefit from the adoption of multiple conceptual lenses, in this case, legitimacy and stakeholder theories. Lastly, through the empirical findings, this study provides economic validity to the 2018 joint initiative of the GRI and the United Nations Global Compact to strengthen corporate actions to achieve the United Nations SDGs.

This study aims to investigate the rarefaction effects on flow and thermal performances of an equivalent sand-grain roughness model for aerodynamic thrust bearing.

In this study, a model of gas lubrication thrust bearing was established by modifying the wall roughness and considering rarefaction effect. The flow and lubrication characteristics of gas film were discussed based on the equivalent sand roughness model and rarefaction effect.

The boundary slip and the surface roughness effect lead to a decrease in gas film pressure and temperature, with a maximum decrease of 39.2% and 8.4%, respectively. The vortex effect present in the gas film is closely linked to the gas film’s pressure. Slip flow decreases the vortex effect, and an increase in roughness results in the development of slip flow. The increase of roughness leads to a decrease for the static and thermal characteristics.

This work uses the rarefaction effect and the equivalent sand roughness model to investigate the lubrication characteristics of gas thrust bearing. The results help to guide the selection of the surface roughness of rotor and bearing, so as to fully control the rarefaction effect and make use of it.