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The purpose of this paper is to investigate the linkage between perceived overqualification and task i-deals via the mediating effect of prove goal orientation and the moderating effect of a climate for inclusion.

This study proposes and tests the mechanism of perceived overqualification in affecting task i-deals. Matched data were collected from a two-wave survey among 457 employees who work in two Chinese enterprises. The hypotheses were tested using hierarchical linear modeling and bootstrapping

The findings reveal that perceived overqualification has a significant positive impact on task i-deals. Prove goal orientation has a mediating role between perceived overqualification and task i-deals. Climate for inclusion moderates the relationship between prove goal orientation and task i-deals and the mediation effect of prove goal orientation, which has a moderated mediating effect.

This study reveals the influence mechanism of perceived overqualification on task i-deals from the perspective of self-verification, which not only enriches the results of being overqualified but also expands the antecedents of task i-deals. Moreover, the findings emphasize that contextual factors may strengthen the positive mediation effect of prove goal orientation.

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 purpose of this study is to explore the economic impact of financial restatements by major customers on the audit opinion of their suppliers, showing that non-financial information disclosure potentially helps auditors make better assessments.

Using a sample of China’s listed firms from 2007 to 2021, the authors aim to find the relationship between customers’ financial restatements and their suppliers’ audit opinions. Heckman selection model, placebo tests and other robustness checks are used as well.

The findings reveal that customers’ financial restatements have a significant effect on the likelihood of suppliers receiving modified audit opinions. This relationship is pronounced when suppliers face a higher level of financial constraints, exhibit poorer accounting conservatism or receive more negative media coverage. Additionally, this effect occurs through increased business risk and information risk, which heightens auditors’ perceived audit risk. Moreover, the study highlights the influence of switching costs, auditor expertise and restatement severity on this relationship.

Risks originating from customers can spread along the supply chain, emphasizing the necessity for auditors to give heightened attention to both the audited firms and their customer information. Moreover, regulators should carefully consider the important impact of customer information disclosures to maximize the protection of the interests of external information users.

This study not only confirms the crucial role of customer information disclosures in annual reports for stakeholders and auditors but also contributes to the existing literature on customer–supplier relationships.

The Belt and Road Initiative (BRI) is the most comprehensive and substantial international cooperation platform, creating a new market influenced by economic and political factors. In this paper, the authors aim to examine whether and how the BRI impacts the Chinese enterprises' corporate environmental responsibility (CER).

Based on China's listed firms' database from 2011 to 2018, the authors use the PSM-DID method, an econometrics method combined with propensity score matching (PSM) and difference-in-differences (DID), to conduct causal inference between the BRI and Chinese enterprises' CER and conduct a series of robustness analyses. Moreover, the authors explore the mechanisms underlying the main effect from both market and non-market perspectives.

The results suggest that the BRI significantly increases Chinese enterprises' CER. Further analyses show that market competition and government support are two possible mechanisms through which the BRI has an effect on the enterprises' CER.

The research study supplements existing work on the environmental effects of the BRI at a microlevel and adds to the literature on the drivers of CER. The findings offer valuable insights into governments and scholars by demonstrating that CER is a crucial tool for Chinese enterprises to gain a competitive advantage in the increasingly competitive markets along the BRI.

This study aims to better understand the morphological characteristics of single particle and the health risk characteristics of heavy metals in PM_2.5 in different functional areas of Handan City.

High resolution transmission electron microscopy was used to observe the aerosol samples collected from different functional areas of Handan City. The morphology and size distribution of the particles collected on hazy and clear days were compared. The health risk evaluation model was applied to evaluate the hazardous effects of particles on human health in different functional areas on hazy days.

The results show that the particulate matter in different functional areas is dominated by spherical particles in different weather conditions. In particular, the proportion of spherical particles exceeds 70% on the haze day, and the percentage of soot aggregates increases significantly on the clear day. The percentage of each type of particle in the teaching and living areas varied less under different weather conditions. Except for the industrial area, the size distribution of each type of particle in haze samples is larger than that on the clear day. Spherical particles contribute more to the small particle size segment. Soot aggregate and other shaped particles contribute more to the large size segment. The mass concentrations of hazardous elements (HEs) in PM_2.5 in different functional areas on consecutive haze pollution days were illustrated as industrial area > traffic area > living area > teaching area. Compared with the other functional areas, the teaching area had the lowest noncarcinogenic risk of HEs. The lifetime carcinogenic risk values of Cr and As elements in each functional area have exceeded residents’ threshold levels and are at high risk of carcinogenicity. Among the four functional areas, the industrial area has the highest carcinogenic and noncarcinogenic risks. But the effects of HEs on human health in the other functional areas should also be taken seriously and continuously controlled.

The significance of the study is to further understand the morphological characteristics of single particles and the health risks of heavy metals in different functional areas of Handan City. the authors hope to provide a reference for other coal-burning industrial cities to develop plans to improve air quality and human respiratory health.

By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.

First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.

Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.

This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns with risk limitations or lowering risks with expected returns for P2P lenders.

This paper used data from a leading online P2P lending platform in America. First, the authors constructed a logistic regression-based credit scoring model and a linear regression-based profit scoring model to predict the default probabilities and profitability of loans. Second, based on the predictions of loan risk and loan return, the authors constructed linear programming model to form the optimal loan portfolio for lenders.

The research results show that compared to a logistic regression-based credit scoring method, the proposed new framework could make more returns for lenders with risks unchanged. Furthermore, compared to a linear regression-based profit scoring method, the proposed new framework could lower risks for lenders without lowering returns. In addition, comparisons with advanced machine learning techniques further validate its superiority.

Unlike previous studies that focus solely on predicting the default probability or profitability of loans, this study considers loan allocation in online P2P lending as an optimization research problem using a new framework based upon modern portfolio theory (MPT). This study may contribute theoretically to the extension of MPT in the specific context of online P2P lending and benefit lenders and platforms to develop more efficient investment tools.

Sustainable consumption is a crucial route to sustainable tourism. Hence, the purpose of this study is to investigate the individual and combined effect of social learning and eco-labels on the green hotel selection.

This study used a between-subject online experimental method with 199 respondents, which is used only in around 15% of published tourism articles. Additionally, this method provided reliability and control features.

Social learning and eco-labels individually could not influence tourists to select green hotels. However, the interaction of positive performance social learning with eco-labels could potentially influence tourists' green hotel selection. Therefore, internalizing green hotel performance from trusted sources and external validation bring behavioral changes among tourists to select green hotels. This study offers a new social learning-based model for understanding sustainable consumption.

This study can use various other types of social influences and can be expanded to other green settings.

This study provides policy and promotion formulation insights to hotel managers and sustainable tourism promoters to market green hotels.

Away from the traditional theory, this study bridges the gap between social learning of performance from relatable sources, assurance from governing entities and sustainable consumption. The interaction effect of social influence and eco-label on green hotel selection is a novel finding. Also, this study introduces various levels of social learning to the discussion of sustainable consumption.

该研究对 199 名受访者使用了主题间在线实验方法, 仅在大约 15% 的已发表旅游文章中使用。此外, 这种方法提供了可靠性和控制功能。

可持续消费是可持续旅游的重要途径。因此, 本研究调查了社会学习和生态标签对绿色酒店选择的个体和综合影响。

单独的社会学习和生态标签不能影响游客选择绿色酒店。然而, 积极绩效社会学习与生态标签的相互作用可能会影响游客对绿色酒店的选择。因此, 从可信赖的来源和外部验证中内化绿色酒店绩效, 会带来游客选择绿色酒店的行为变化。该研究为理解可持续消费提供了一种新的基于社会学习的模型。

该研究可以使用各种其他类型的社会影响, 并可以扩展到其他绿色环境。

它为酒店经理和可持续旅游推广者提供了政策和促销制定的见解, 以推销绿色酒店。

与传统理论不同, 本文填补了相关来源的绩效社会学习、管理实体的保证和可持续消费之间的研究空白。社会影响和生态标签对绿色酒店选择的交互作用是一个新的发现。此外, 它还将不同层次的社会学习引入到可持续消费的讨论中。

El estudio utilizó un método experimental online entre sujetos con 199 encuestados, utilizado sólo en alrededor del 15% de los artículos de turismo publicados. Además, este método ofrecía características de fiabilidad y control.

El consumo sostenible es una vía crucial para el turismo sostenible. Por ello, este estudio investiga el efecto individual y combinado del aprendizaje social y las etiquetas ecológicas en la selección de hoteles ecológicos.

El aprendizaje social y las ecoetiquetas por separado no pudieron influir en los turistas para que seleccionaran hoteles ecológicos. Sin embargo, la interacción del aprendizaje social del rendimiento positivo con las ecoetiquetas podría influir potencialmente en la selección de hoteles ecológicos por parte de los turistas. Por lo tanto, la interiorización del rendimiento de los hoteles ecológicos a partir de fuentes de confianza y la validación externa provocan cambios de comportamiento entre los turistas para seleccionar hoteles ecológicos. El estudio ofrece un nuevo modelo basado en el aprendizaje social para entender el consumo sostenible.

El estudio puede utilizar otros tipos de influencias sociales y puede ampliarse a otros entornos ecológicos.

Proporciona ideas para la formulación de políticas y promociones a los directores de hoteles y a los promotores del turismo sostenible para comercializar hoteles ecológicos.

Se aleja de la teoría tradicional y tiende un puente entre el aprendizaje social de los resultados a partir de fuentes relacionadas, la garantía de las entidades gobernantes y el consumo sostenible. El efecto de la interacción entre la influencia social y la etiqueta ecológica en la selección de hoteles ecológicos es un hallazgo novedoso. Además, introduce varios niveles de aprendizaje social en el debate sobre el consumo sostenible.

This paper aims to explore the critical factors which affect the quality of preschool education service so that targeted and effective measures to improve service quality can be put forward.

Evidential theory is applied to aggregate experts’ knowledge, and a fuzzy cognitive map (FCM) model of preschool education service quality is established to further carry out a simulation for inference, thus figuring out the critical factors to improve service quality.

The simulation results show that the main body of supervision and environment of governments and policies are two critical factors affecting the quality of preschool education service. More emphasis should be put on these two aspects, and corresponding measures can be put forward so as to ensure the quality of preschool education service.

This paper proposes a new model based on FCM and evidential theory to study the factors affecting preschool education service quality.

The purpose of this paper is to present a new tool, business network information ecological chain (BNIEC) aiming to solve the current information problems in business network, make more profits to business websites and to maintain the sustainable development of the business network environment in Internet of Things (IoT) era.

From multi-disciplinary perspectives, learning from the knowledge in information ecology, economics, the IoT and system theory, this paper first analyzes the positioning of BNIEC in different subjects. Second, it proposes the definition, components and characteristics of BNIEC and designs the BNIEC concept map helping to understand the BNIEC system. Last, this paper builds the structural model and the information flow models of BNIEC.

The study first presents the concept of BNIEC and based on the trans-disciplinary point of view, builds the structure model of BNIEC from three aspects: nodes, relations among nodes and link modes and illustrates the model using the knowledge from the system theory. Also, it builds two kinds of the information flow models by the related information knowledge in IoT.

This paper aims to introduce not only a new tool but an ecological idea to business network companies, to create a pleasant network environment, more than that, to make more benefits for themselves. Meanwhile, it has important significance in the sustainable development of the business network environment, business websites, business network information resources and information technology. Especially in today’s IoT era, it shows an ecological thinking to solve the information problems in business network that we may face in the future.