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Thermal failure and incomplete separation often occur in aviation wet friction clutches. The purpose of this study is to improve the performance and reliability of the clutch, considering the influence of lubricating oil, in this paper, the finite element method is used to simulate the friction pair of clutch with separation spring.

Considering the influence of lubricating oil, based on computational fluid dynamics principle and applying multiple reference frame method, simulation is carried out in FLUENT software to study the distribution of flow field and temperature field of clutch friction pair and separation spring under the condition of maximum relative speed of 3000 r/min.

The middle friction pair has more oil distribution, while the two sides have less oil distribution, and the highest oil volume exceeds that of the lowest by a factor of 3.49. Under the influence of lubricating oil distribution and component heat conduction, the temperature of the separation spring on both sides is higher than that of the separation spring in the middle. The axial temperature distribution law of the friction pair is the same as that of the separation spring, and the difference of the highest temperature between the friction pair is 136.41°C.

The heat generation of the clutch is studied to improve the performance of the clutch and ensure the safety of the helicopter.

By analyzing the temperature and flow field of a wet friction clutch with a separation spring, engineers can help provide the service life and reliability of the clutch friction pair.

This study aims to explore the extent to which Chinese multinational enterprises (MNEs) rely on supranational institution – the Belt and Road Initiative (BRI) – versus host country institutional quality to navigate their foreign location choice.

This study uses a conditional logit regression model using a sample of 1,302 greenfield investments by Chinese MNEs in 54 BRI participating countries during the period 2011–2018.

The results indicate that as a supranational institution, the BRI serves as a substitution mechanism to address the deficiencies in institutional quality in BRI participating countries, thereby attracting Chinese MNEs to invest in those countries. In addition, the BRI’s substitution effect on host country institutional quality is more pronounced for large MNEs, MNEs in the manufacturing industry and MNEs in inland regions.

This study expands the understanding of the BRI as a supranational institution for MNEs from emerging markets and reveals its substitution effect on the host country institutional quality. Furthermore, it highlights that MNEs with diverse characteristics gain varying degrees of benefits from the BRI.

The purpose of this paper is to systematically investigate the hydraulic fracture branching phenomena in porous media under different loading conditions and the stepwise phenomenon. The effect of the pore pressure in hydraulic fracturing branching is studied, and more evidence for the stepwise phenomenon with the peridynamics approach is provided.

A fully coupled fluid-filled explicit peridynamics model is developed to simulate the complex evolution of crack branching and stepwise phenomena in saturated porous media. Based on the peridynamics theory, an explicit time integration scheme is used to solve the coupled equation system including rock deformation, fluid flow and fracture propagation. Using the proposed model, a series of peridynamic computational tests are performed to examine two common kinds of phenomena observed in hydraulic fracturing: the crack branching phenomenon and the stepwise phenomenon.

For crack branching phenomenon, the results obtained indicate that sufficient loading is required in order to initiate the crack branching process. Compared with the stress applied on crack surfaces condition, crack branching is more easily induced with the stress applied on boundaries. In addition, for the fluid-driven crack (stress applied on crack surfaces), the existence of pore pressure will depress the growth and branching of the crack. For stepwise phenomena, the results obtained indicate that the peridynamics is a promising tool to study the stepwise phenomenon. The stepwise phenomenon is more distinct under mechanical loading conditions due to the solid behaviour. A sudden jump or crack extension will happen when enough energy is accumulated in the hydraulic fracturing system.

In this study, the explicit method is used, which means it is conditionally stable, and the critical time step needs to be decided. The reason to use the explicit method is for the study purpose; the explicit method is faster and has no need for matrix inversions.

This study helps to understand the effect of the pore pressure in hydraulic fracturing branching and provides more evidence for the stepwise phenomenon with peridynamics.

This investigation seeks to elaborate on how proactive market orientation (MO) and responsive MO motivate firms to conduct business model innovation (BMI) through the breadth of market knowledge search (BMKS) and the depth of market knowledge search (DMKS).

Based on the survey data of 259 high-tech firms in the industrial parks of the Yangtze River Delta, this study uses multiple hierarchical regressions to examine the hypotheses and conducts Sobel and bootstrapping methods to further test the mediating effects.

The findings indicate that the positive effects of proactive and responsive MO on BMI are mediated by BMKS and DMKS. It also shows that proactive MO has a greater impact on BMKS than responsive MO, while responsive MO has a stronger impact on DMKS than proactive MO.

Firms with different MOs can choose different types of market knowledge search to promote BMI, which reminds managers to give attention to the importance of bridging MOs with knowledge search strategies in BMI.

This study introduces a constructive theoretical framework by examining the roles of MO and market knowledge search on BMI. The findings reveal that MO as a key initiating factor and market knowledge search as an important conduit play vital roles in the experimental process of BMI and identify the differential effects of proactive and responsive MO on two types of market knowledge search.

Aside from grappling with technological advancements, enterprises in the industrial internet era are embracing business model innovation to align with the evolution of the industrial internet. However, a gap persists in the existing research regarding the strategies and methods available to small and medium-sized enterprises (SMEs) for executing business model innovation. Therefore, this paper aims to explore the connotation, characteristics and logic of business model innovation for SMEs in the industrial internet era.

To explore the business model innovation logic of small and medium-sized enterprises in the era of industrial internet, the paper adopts a longitudinal single-case study approach, with PAYA, a medium-sized enterprise in the electromechanical industry, serving as the subject of research. It systematically analyzes PAYA’s business model innovation, centering on four key elements of the business model: value proposition, value creation, value delivery and value capture.

The study proposes two types of business model innovation, namely, “Migration” and “Expansion”, and explains the logic of business model innovation for SMEs in the industrial internet era: faced with a rapidly changing market environment, entrepreneurs put forward the value proposition through the insight of the market environment, then enterprises conduct technological innovation to support the value creation by their own unique experience and knowledge, and then improve the legitimacy of the market by expanding the influence of market acceptance of the new business model to promote the value delivery, and finally capture the economic value and ecological value.

The types and logic of business model innovation proposed in this paper contribute to supplementing and developing the theory of business model innovation and meanwhile have important reference value for SMEs in the industrial internet era.

This study aims to explore the relationship between non-market strategies and organizational resilience, using a Chinese private enterprise as an example.

This study collected data through semi-structured interviews and analyzed them through grounded theory, using a three-step approach of open coding, axial coding and selective coding to analyze and construct a model of the mechanism of the impact of non-market strategies on organizational resilience.

The following conclusions were drawn from this study. (1) Stakeholders, internal and external environment and entrepreneurship are important motivations that influence private firms to implement non-market strategies to enhance organizational resilience, with entrepreneurship being the key driver. (2) Non-market strategies contain three dimensions, and different non-market behaviors have different mechanisms of action on the organizational resilience of firms. (3) Non-market strategies and organizational resilience form an interactive spiral relationship. This mutually reinforcing effect promotes firm growth and sustainable corporate development. The research results enrich the theoretical connotation of non-market strategies, construct a model of the mechanism of influence of non-market strategies on organizational resilience, and describe three explanatory paths for the relationship between the two–incentive mechanism, functional mechanism and transformation mechanism.

This study's single case is unique and based on the Chinese context. In addition, this study adopts a rooted qualitative research approach and although the coding and model construction strictly follow the steps of grounded theory research, a degree of subjectivity is inevitable. On this basis, future research can adopt quantitative analysis methods to test and improve the model.

This paper explores the important role of non-market strategies in the Chinese context under the impact of traditional market mechanisms, based on the perspective of Chinese private enterprises, and provides new insights and revelations for private enterprises to achieve sustainable development.

This study innovatively explores the formation mechanism of organizational resilience from the perspective of non-market strategies, adding a new perspective to the literature. Additionally, it examines the mechanisms between long-term non-market strategy and organizational resilience, particularly their relationship in times of crisis, utilizing a rooted approach that goes beyond static analysis.

Since 2013, China has implemented targeted poverty alleviation policies, successfully eradicating absolute poverty nationwide by 2021. The fiscal funds allocated for poverty alleviation have significantly contributed to reducing poverty in impoverished areas. However, to date, there has been a lack of scholarly research specifically examining the effects of these fiscal poverty alleviation funds on both poverty reduction and economic growth. This study aims to address two key questions: What role do fiscal poverty alleviation funds play in reducing poverty? Additionally, do these funds contribute to economic growth?

Provincial panel data in China from 2010 to 2020 are used to test the impact of fiscal poverty alleviation funds on poverty reduction and economic growth. The empirical study of this paper primarily employs panel data within difference and two-stage least squares (2SLS) estimation for causal identification.

Poverty alleviation funds positively influence China’s economic growth and significantly reduce the rural poverty rate. During the sample period, the contribution of poverty alleviation funds to economic growth reached 7.3%, and the contribution to the reduction of the poverty incidence rate was 8.4%.

The key contribution of this study lies in its novel approach of using empirical methods to probe the impacts of fiscal poverty alleviation funds on provincial economic growth. Additionally, this paper also empirically tests the mechanisms by which fiscal poverty alleviation funds promote growth and reduce poverty, mainly by improving the infrastructure development conditions in impoverished areas.

Fake news refers to intentionally fabricated or misleading information designed to deceive the public and manipulate opinions for personal, political or financial gain. Most existing detection methods primarily focus on capturing language features from news content. However, these methods neglect the varying importance of different news entities. Additionally, these methods tend to overlook the auxiliary role of external knowledge, resulting in an incomplete understanding of the entity. To address these issues, this paper aims to propose a Dual-layer Semantic Information Extraction Network with External Knowledge (DSEN-EK) for fake news detection.

This approach is proposed to comprise three parts: Dual-layer Semantic Information Extraction Network, Entity Integration Network with External Knowledge and Classifier. Specifically, Dual-layer Semantic Information Extraction Network is designed to enhance relationships between entities and the influence of important entity representations. The Entity Integration Network with External Knowledge is proposed to extract entity descriptions from external knowledge bases.

The DSEN-EK model performs well on the Liar, Constraint, Twitter15 and Twitter16 data sets, achieving accuracy of 98.02%, 94.61%, 90.09% and 93.65%, respectively. These results highlight its effectiveness in detecting fake news across different types of content.

The Dual-layer Semantic Information Extraction Network is proposed to capture the relationships between entities and enhance the continuous semantic information of the news. The Entity Integration Network with External Knowledge is designed to enrich entity descriptions, leading to a more comprehensive capture of semantic details.

In social media context, service failures become public domain, making them visible to vast audiences of customers who are virtually present. Thus, this study aims to discuss the roles of service failure type and management response on observers’ perceived helpfulness.

The authors conducted econometric analyses on a dataset incorporating 107,984 reviews and 34,641 management responses to negative reviews.

The results reveal that, for process failures, specifying a form of action (initiatives for solving the problem) is associated with more perceived helpfulness of reviews than accounts (explanation) or acknowledgments (recognition and acceptance), while responding to an outcome failure by providing an account is associated with increased perceived helpfulness of reviews.

For process failures, managers should make every effort to convince observers through specific actions that similar failures are less likely to occur in the future. For outcome failures, managers should strive to provide clear and fast explanations of the failure causes to restore observers’ evaluation of the firm’s capabilities.

The authors’ work extends sparse insights on observers and sheds new light on the effect of service failure type and response strategy on observers’ actual behaviors. The interplay between service failure type and response strategy provides guidance on how to use management responses to influence potential customers.

The purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.

This study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.

The study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.

The study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.

The results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.