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This study aims to explore the impact of supply chain governance (SCG) on supply chain resilience (SCR) in China, as well as the mediating role of supply chain finance (SCF) and the moderating role of digital technology adoption (DTA).

Based on resource orchestration theory (ROT), this paper constructs a theoretical model to examine the influence of SCG on SCR. Employing data collected from 312 Chinese firms, multiple regression is conducted to test the theoretical hypotheses.

The results indicate that both relational governance (RG) and contractual governance (CG) significantly enhance SCR and SCF. In addition, SCF plays a mediating role in the relationship between SCG and SCR. The study also finds that DTA has a positive moderating effect on the relationship between SCG and SCF.

First, based on ROT, this paper clarifies the nuanced driving effects of RG and CG on SCR. Second, SCF is introduced as an intermediary process between SCG and SCR, which reveals the inner mechanisms between SCG and SCR. Moreover, this study contributes to investigating the contingent role of DTA in the relationship between SCG and SCF.

As an effective tool to promote rational resource allocation and facilitate the development of green management practices such as enterprise digital innovation, the green credit policy has recently gained extensive attention. The purpose of this paper is to analyze the relationship between green credit policies and the digital innovation of enterprises, and to further explore the mechanism of action between them and their boundary conditions.

Based on micro-level data on Chinese firms from 2007 to 2019, this paper constructs a difference-in-differences (DID) model to investigate the impact and intrinsic mechanisms of green credit policies on firms' digital innovation and its boundary conditions, with the help of a quasi-natural experiment, i.e. the Green Credit Guidelines.

Green credit policies inhibit digital innovation and fail to compensate for innovation. The analysis of the mechanism shows that the implementation of green credit policies has a negative impact on digital innovation by increasing the financing constraints faced by firms, and has also a crowding-out effect on R&D investment, resulting in a disincentive to digital innovation. Further analysis reveals that the negative impact of green credit policies on digital innovation is more pronounced in state-owned enterprises, enterprises without financially experienced executives, and in the eastern regions of China.

This study provides empirical evidence to understand the effectiveness and mechanism of influence of green credit policies on enterprise digital innovation, providing also a basis to further improve green credit policies.

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.

Following the standard practice of using nutrition claims to denote food functionality, this study empirically explores Chinese consumers’ willingness-to-pay for functional processed meat products by using three nutrition claims (namely “increased calcium,” “containing omega-3”, and “reduced salt”) made on pork sausages. It also aims to outline the typical characteristics of Chinese consumer segments based on preferences.

A choice-based choice experiment is utilized to investigate Chinese consumers’ valuation on attributes of interest regarding functional sausage products. First-hand data was collected in the two cities of Xi'an and Beijing.

There are market potentials for domestic and/or imported functional processed meat products among Chinese consumers. Nutrition claims made on pork sausages are appealing to Chinese consumers, and therefore, monetarily rewarded by them. Being imported from a more developed country of origin could both positively and negatively impact consumers’ WTP for nutrition claims made on pork sausages. Furthermore, specific functional modification strategies should be taken into account when addressing different segments of the Chinese market. In addition, regional impacts between Xi'an and Beijing are implied in terms of consumers’ valuation for functional pork sausages.

Limitations in the current study are mainly two folds. First, the WTP estimation magnitudes are subject to a hypothetical bias by using a stated preference approach. Second, this study only focuses on pork sausages to explore consumers’ perceptions and selects three nutrition claims among many other relevant options.

Implications are provided for meat marketers and for Chinese official food policymakers, such that promoting meat products with a nutrition claim is an attractive marketing strategy for foreign food manufacturers in China, and more reformulated meat products with better nutritional compositions should be allowed in the Chinese market.

To the best of the author’s knowledge, this research is the first to fill in the literature blank on investigating the consumers’ valuation for functional meat in the emerging market of China. Because when taking Chinese consumers as a target market and evaluating their perceptions of food quality-related labeling and certifications, the existing literature is mainly limited to topics of product safety, organic/green products, and geographical origins. However, nutrition claims, as marketable credence attributes that associate closely to the main characteristics of the functional food products, have been explored to a much lesser extent among Chinese consumers.

Social media's role in engaging participants in sports events, particularly during the pandemic, is acknowledged. However, previous studies often utilized sports events for diverse objectives but overlooked brand equity's influence on sports event development. And very limited research explores social media's impact on brand equity in esports events, despite its significance. Therefore, this study aims to explore how social media affects esports event brand equity and participants' satisfaction and engagement with social media through brand equity's influence.

The study focused on League of Legends World Championships (LOLWC) participants, who completed a self-judged questionnaire online. The questionnaire included demographic details and latent constructs. Data analysis involved two steps: exploratory factor analysis (EFA) to assess measurement scale validity and structural equation modeling (SEM) to study relationships between traits.

The results reveal that, within the esports event context, controlled communication exerts a meaningful and dual impact – both directly and indirectly – on the fundamental components of brand equity. This, in turn, serves as a catalyst for increasing participant contentment and their posting intention.

This study applies brand equity theories to the esports domain, exploring participant-based brand equity concepts, user behavior and the influence of social media communication on event branding and engagement. It also recommends strategies for event improvement, emphasizes controlled communication for brand equity and highlights marketing's role in brand awareness, association and participant satisfaction. Additionally, it suggests government regulation to address cyber violence during esports events.

The purpose of this integrative literature review was three-fold: to explore the phenomenon of women’s career interruptions as revealed by publications in the past two decades, to propose a new career decision tree model (CDTM) and to outline an agenda for future research.

The authors adopted the integrative literature review approach proposed by Torraco (2005, 2016) and used a mind mapping application called MindMeister to synthesize 64 identified articles.

The proposed CDTM can assist those who are interested in exploring individuals’ career decisions to think systematically about career influencers at different levels.

The CDTM is significantly different from existing career models and theories in that it explains women’s career interruptions in a context-sensitive manner. This model can assist human resource development professionals in analyzing the influencers of women’s career decisions and tackling individual problems level by level.

Time headway (THW) is an essential parameter in traffic safety and is used as a typical control variable by many vehicle control algorithms, especially in safety-critical ADAS and automated driving systems. However, due to the randomness of human drivers, THW cannot be accurately represented, affecting scholars’ more profound research.

In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified.

In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified.

The results show that the proposed model has a 62.7% performance improvement over the distribution model with fixed parameters. Moreover, the parameter function of the distribution model can be regarded as a quantitative analysis of the degree of influence of the traffic flow state on THW.

This paper aims to study the effect of the establishment of bankruptcy courts on bond issuance market. This paper helps to predict that the introduction of bankruptcy courts in China can mitigate price distortions caused by the implicit government guarantees and promote the development of the high-risk bond market.

This paper exploits the staggered introduction of bankruptcy courts across cities to implement a differences-in-differences strategy on bond issuance data. Using bonds issued in China between 2018 and 2020, the impact of bankruptcy courts on the bond issuance market can be analyzed.

This paper reveals that bond issuance credit spreads increase and is more sensitive to firm size, profitability and downside risk of issuance entity after the introduction of bankruptcy courts. It also reveals a substantive increase in bond issuance quantity and a decrease in issuer credit ratings following the establishment of bankruptcy courts. In addition, the increase of credit spreads is more prominent for publicly traded bonds, those whose issuers located in provinces with lower judicial confidence, bonds issued by SOEs and bonds with stronger government guarantees. Finally, the role of bankruptcy courts is more pronounced in regions with higher marketization.

This paper relates to previous studies that investigate the impact of laws and institutions on external financing. It helps provide new evidence to this literature on how improvements of efficiency and quality in bankruptcy enforcements relate to the marketization of bond issuance. The results provide further evidence on legal institutions and bond financing.

1. To improve the causality analysis performance, a novel causality detector based on time-delayed convergent cross mapping (TD-CCM) is proposed in this work. 2. Identify the root cause of plant-wide oscillations in process control system.

A novel causality analysis framework is proposed based on denoising and periodicity-removing TD-CCM (time-delayed convergent cross mapping). We first point out that noise and periodicity have adverse effects on causality detection. Then, the empirical mode decomposition (EMD) and detrended fluctuation analysis (FDA) are combined to achieve denoising. The periodicities are effectively removed through singular spectrum analysis (SSA). Following, the TD-CCM can accurately capture the causalities and locate the root cause by analyzing the filtered signals.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. Simulation studies show that the proposed method is able to improve the causality analysis performance. 3. Industrial case study shows the proposed method can be used to analyze the root cause of plant-wide oscillations in process control system.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. The influences of noise and periodicity on causality analysis are investigated. 3. Simulations and industrial case shows that the proposed method can improve the causality analysis performance and can be used to identify the root cause of plant-wide oscillations in process control system.

Safety climate and its impact on safety performance is well established; however, researchers in this field suggest that the absence of a common assessment framework is a reflection of the state of development of this concept. The purpose of this paper is to propose a five-factor model that can be used to diagnose and measure safety climate in construction safety research and practice.

A systematic review was adopted, and following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 574 articles were selected at the start of the study based on a developed review protocol for investigating safety climate factors. While examining the factor analysis of different studies, data reliability and data validity of the individual research findings were considered and frequency of factors uploaded was used to determine the significance as a quantitative measure to develop the ranking of safety climate factors.

The review identified that, from the established measures of safety climate in construction, there is little uniformity on factor importance. However, management commitment safety system role of the supervisor; workers’ involvement and group safety climate were found to be the most common across the studies reviewed. It is proposed these factors are used to inform a five-factor model for investigating safety climate in the construction industry.

The findings of this study will motivate researchers and practitioners in safety to use the five-factor safety climate model presented in this paper and test it to develop a common factor structure for the construction industry. The fact that the model is comprised of five factors makes it easier to be used and implemented by small-to medium-sized construction companies, therefore enhancing its potential use.