Tolerance for corruption and descriptive social norm: An experimental study of embezzlement

Public tolerance for corruption within a society significantly influences the prevalence of corrupt practices, but less is known about how this tolerance evolves with social norms. This paper presents experimental evidences demonstrating that the descriptive social norm indicating widespread corruption can lead to increased tolerance for corruptive acts. We introduce an asymmetric information ultimatum game to simulate the interactions between embezzlers and citizens. Game theoretical analysis reveals that victims anticipating corruption will exhibit greater compliance with embezzlement when the offers are evaluated based on descriptive norms. To test the hypothesis, we employ a framing effect to induce variations in descriptive norms within a behavioral experiment. Although the treatment effect is significant only in the subgroup of student cadres, this subgroup demonstrated increased beliefs about embezzlement, greater tolerance for corruption, and a heightened propensity to embezzle when exposed to framings with hierarchical implications. This paper contributes to the corruption literature by examining the effects of descriptive norms on victims' responses to embezzlement. It offers a more comprehensive perspective on how social standards shape public opinions and corrupt actions, enhancing our understanding of the self-reinforcing nature of corruption.

The impact of digital inclusive financial development on local government expenditure: Evidence from China

This paper investigates the impact of digital inclusive financial development on local government expenditure incentives at the income level. It does so by constructing a multi-level government Dynamic Stochastic General Equilibrium (DSGE) model that incorporates the financial sector. By employing empirical methods that involve uncertainty shocks and counterfactual simulations, the research yields several key findings. Firstly, the development of digital inclusive finance contributes to breaking down the urban-rural dual financial structure, thus facilitating balanced economic development within regions. Secondly, it reduces the proportion of financially excluded areas, accelerates fiscal decentralization, leading to an increase in local government fiscal revenue, and, consequently, an expansion of local fiscal expenditures. Thirdly, at a certain stage of digital inclusive finance development, it tends to crowd out residents' investment and consumption. Therefore, the decentralization of fiscal power and the expansion of local government expenditure at this stage may paradoxically inhibit regional economic growth. The study's conclusions validate the significant impact of digital inclusive finance on local government incentives at the income level.

Constructing an evaluation model for the comprehensive level of sustainable development of provincial competitive sports in China based on DPSIR and MCDM

This study focuses on the objective assessment of sport development in socio-economic environments, considering the challenges faced by the industry. These challenges include disparities in regional investments, limited market participation, slow progress towards sports professionalization, and insufficient technological innovations. To tackle these challenges, we suggest implementing an integrated evaluation model that follows the DPSIR (Drivers, Pressures, States, Impacts, Responses) framework and incorporates comprehensive socioeconomic indicators. Subsequently, we utilized the Entropy power method and TOPSIS (Order Preference Technique for Similarity to an Ideal Solution, TOPSIS) analysis to comprehensively assess the progress of competitive sports development in 31 provinces and cities in China. Additionally, we recommended further developments in competitive sports and proposed precise strategies for promoting its growth. The framework and methodology developed in this paper provide an objective and scientifically based set of decision-making guidelines that can be adopted by government agencies and related industries in order to create successful plans that promote the sustainable growth of competitive sport. This is expected to bolster the nation's global influence, enhance social unity, and fuel economic expansion. The findings of this study offer policymakers valuable insights regarding competitive sports and can advance the development of the sports sector in China, thus making it a crucial driver of regional socio-economic progress.

Working-Together Normative Appeals to Promote Pro-Environmental Donations

Investigating the role of social norms in fostering pro-environmental behaviors is crucial for advancing human efforts toward environmental protection. This study employed a one-way, two-level, between-participants experimental design, focusing on the type of social norm as the independent variable and pro-environmental donations as the dependent variable. This study aimed to explore the impact of working-together normative appeals on pro-environmental donations and to understand the underlying mediating mechanism. In total, 128 Chinese university students participated in an online experiment. The findings indicated that working-together normative appeals significantly increased both the intention to donate and the actual amount of pro-environmental donations in the experimental group compared to those in the control group. Furthermore, the perceived behavioral control and intentions towards pro-environmental donations were identified as mediators in the relationship between social norm categorization and pro-environmental donations. Notably, intentions towards pro-environmental donations alone had a substantial mediating effect. These results underscore the positive influence of working-together normative appeals on pro-environmental donations and offer valuable insights into encouraging active participation in the creation of an eco-friendly society, particularly within a collectivist cultural context.

Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm

Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon price forecasting model integrated fuzzy dispersion entropy and deep learning paradigm, named ICEEMDAN-FDE-VMD-PSO-LSTM-EC. Initially, the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is used to primary decompose the original carbon price. Subsequently, the fuzzy dispersion entropy (FDE) is conducted to identify the high-complexity signals. Thirdly, the variational mode decomposition (VMD) and deep learning paradigm of particle swarm optimized long short-term memory (PSO-LSTM) models are employed to secondary decompose the high-complexity signals and perform out-of-sample forecasting. Finally, the error-corrected (EC) method is conducted to re-modify and strengthen the above-predicted accuracy. The results conclude that the forecasting performance of ICEEMDAN-type secondary decomposition models is significantly better than the primary decomposition models, the deep learning PSO-LSTM-type models have superiority in forecasting China carbon price, and the EC method for improving the forecasting accuracy has been proved. Noteworthy, the proposed model presents the best forecasting accuracy, with the forecasting errors RMSE, MAE, MAPE, and Pearson's correlation are 0.0877, 0.0407, 0.0009, and 0.9998, respectively. Especially, the long-term forecasting ability for 750 consecutive trading prices is outstanding. Those conclusions contribute to judging the carbon price characteristics and formulating market regulations.

Heterogeneity effects of environmental regulation policy synergy on ecological resilience: considering the moderating role of industrial structure

Given the great importance attached to ecological civilization and green development, exploring the heterogeneous effects of environmental regulation policy synergy on ecological resilience holds significance for improving environmental protection and the design of environmental policies. Based on the policy synergy perspective, this paper uses 30 provinces (municipalities and autonomous) in China as the research sample. Bayesian quantile regression is employed to explore the heterogeneous effects of environmental regulation policy synergy on ecological resilience from 2007 to 2021, and the moderating effect of the industrial structure is examined. The results indicate the following: (1) there is significant heterogeneity and variability in the effect of environmental regulation policy synergy on ecological resilience. Specifically, the effects of policy mixes 12, 13, and 23 on ecological resilience shows a U-shaped trend, while the impact of policy mix 123 on ecological resilience shows a positive effect. (2) There are significant differences in the effects of environmental regulation policy synergy under different quantiles of ecological resilience. Taking policy mix 12 as an example, we find that the effect of policy synergy on ecological resilience tends to decrease and then increase at a lower quantile. Additionally, the effect of policy synergy on ecological resilience tends to be positive at a higher quantile. (3) There are significant differences in the moderating effects of the industrial structure. Policy mix 12 can effectively enhance ecological resilience through industrial structure upgrading, while the moderating effects of alternative policy combinations are deemed insufficient. Finally, relevant policy recommendations are proposed to effectively improve ecological resilience.

An application of BWM for risk control in reverse logistics of medical waste

The pollution posed by medical waste complicate the procedures of medical waste logistics (MWL), and the increasingly frequent occurrence of public health emergencies has magnified the risks posed by it. In this study, the authors established an index of the factors influencing the risks posed by MWL along five dimensions: the logistics business, emergency capacity, equipment, personnel, and management. The best-worst case method was used to identify the critical risk-related factors and rank them by importance. Following this, we assessed the risk posed by MWL in four major cities in China as an example and propose the corresponding measures of risk control. The results showed that the linking of business processes was the most important factor influencing the risk posed by MWL. The other critical risk-related factors included the location of the storage site, the capacity for emergency transportation, measures to manage emergencies, and the safety of packaging. Of the cities considered, Beijing was found to be a high-risk city, and its MWL needed to be improved as soon as possible in light of the relevant critical risks. Shanghai, Guangzhou, and Shenzhen were evaluated as general-risk cities, which meant that the risks of MWL were not a priority in these areas, and the other goals of urban development should be comprehensively considered during the long-term planning for MWL in these municipalities.

Development and validation of the Chinese family environment influencing physical activity habits scale

Introduction

Adolescence represents a pivotal stage in the development of healthy behaviors, where establishing positive physical activity habits can have enduring effects on an individual's overall wellbeing. The ecological model highlights the influence of environmental factors on human behavior, with the family environment playing a significant role in shaping the physical activity habits of adolescents.

Methods

The aim of this scale is to develop a reliable and effective tool, customized for the unique societal context of China, to assess how family factors influence the physical activity habits of Chinese adolescents. Participants were recruited through stratified cluster sampling from 24 secondary schools in six Chinese provinces between October and November 2021, resulting in 1,061 participants. Analysis was conducted on 1,004 valid questionnaires, divided into two samples. Sample 1, consisting of 502 students (248 males and 254 females; Mage = 15.5), underwent item analysis and exploratory factor analysis. Sample 2, comprising 502 students (267 males and 235 females; Mage = 16.5), underwent confirmatory factor analysis and internal consistency reliability analysis.

Results

Through exploratory factor analysis, we extracted three factors comprising 15 items: "Family Environment Construction" (4 items), "Family Action Support" (6 items), and "Family Health Awareness" (5 items). The Cronbach's alpha values for these factors ranged from 0.890 to 0.894. Confirmatory factor analysis confirmed a satisfactory model fit (CMIN/DF = 1.45, SRMR = 0.027, GFI = 0.991, TLI = 0.989, RMSEA = 0.03).

Discussion

The scale demonstrated strong internal consistency and test-retest reliability, confirming its effectiveness in empirical research. This study holds significant implications for enhancing the physical activity levels of adolescents, promoting their physical and mental wellbeing, enriching their developmental experiences, and contributing to their overall sense of happiness.

Drivers and influencers of blockchain and cloud-based business sustainability accounting in China: Enhancing practices and promoting adoption

The field of sustainability accounting aims to integrate environmental, social, and governance factors into financial reporting. With the growing importance of sustainability practices, emerging technologies have the potential to revolutionize reporting methods. However, there is a lack of research on the factors influencing the adoption of blockchain and cloud-based sustainability accounting in China. This study employs a mixed-methods approach to examine the key drivers and barriers to technology adoption for sustainability reporting among Chinese businesses. Through a systematic literature review, gaps in knowledge were identified. Primary data was collected through an online survey of firms, followed by in-depth case studies. The findings of the study reveal a positive relationship between company size and reporting behaviors. However, size alone is not sufficient to predict outcomes accurately. The industry type also has significant but small effects, although its impact on reporting behaviors varies. The relationship between profitability and reporting behaviors is intricate and contingent, requiring contextual examination. The adoption of blockchain technology is positively associated with capabilities, resources, skills, and regulatory factors. On the other hand, cloud computing adoption is linked to resources, management support, and risk exposures. However, the specific impacts of industry on adoption remain inconclusive. This study aims to offer empirical validation of relationships, shedding light on the intricate nature of interactions that necessitate nuanced conceptualizations incorporating contextual moderators. The findings underscore the importance of providing customized support and adaptable guidance to accommodate the evolving practices in sustainability accounting. Moreover, the assimilation of technology and organizational changes highlights the need for multifaceted stakeholder cooperation to drive responsible innovation and address the challenges posed by digital transformations in this field.

How does the location of high-speed railway stations affect the emission reduction effect of industrial structure upgrading?

The opening of high-speed railway (HSR) has accelerated the reorganization and reallocation of regional production elements, and constantly promoted the adjustment and upgrading of industrial structure. The cleaner production effect produced by industrial structure upgrading is of great significance to industrial pollution reduction. As a bridge connecting resources within the city and elements outside the city, the location of HSR stations has become an important factor affecting the structural emission reduction effect. Based on the data of 285 prefecture level and above cities in China from 2004 to 2018, this paper investigates the structural emission reduction effects of HSR opening and the impact of HSR station location on it by employing difference-in-differences (DID) model combined with mediation effect method. The results demonstrate that the opening of HSR has significant structural emission reduction effect, and the upgrading of inter-industry structure and the intra-industry structure are important mechanisms for HSR to achieve industrial emission reduction. The structural emission reduction effect of HSR opening is closely related to the location of HSR stations. With the increase of the distance between HSR station and city center, the industrial structure upgrading effect will continue to weaken, thus inhibiting the exertion of structural emission reduction effect, of which 10 km away from the city center is the optimal site strategy for the HSR service to give full play to the structural emission reduction effect, and exceeding 50 km will be significantly detrimental to its role in promoting industrial structure upgrading.

Rest-in-Peace: Research on the Architectural Types and Design Ideas to Guide Design of Hospice Care Building

In the context of an aging population, the concept of peaceful end-of-life care has gained increasing significance as an essential component of individuals' fundamental well-being. This underscores the importance of researching and developing hospice care facilities and service systems dedicated to providing a tranquil resting environment. This study focuses on selected hospice care buildings, examining their service model evolution and architectural design. Through case analyses, it explores contemporary hospice care architecture, identifying various types and spatial design features that cater to the end-of-life needs of individuals. The findings guide the design of hospice care buildings in China, emphasizing patient-living areas, medical care zones, and auxiliary functional spaces. This comprehensive approach aims to enhance terminally ill patients' comfort, serenity, and dignity. Moreover, it aims to provide emotional and post-funeral support to terminally ill patients' families.

Production line balance problem identification and improvement based on decision tree: A case study of commercial air conditioner production line

In the production of air conditioners, there are various issues such as complex requirements, redundant stations, excessive man-hours, and low production line balance rate. This paper aims to address these problems by analyzing the historical data of H Company's commercial air conditioner production line. The data is categorized into five aspects: station, working hours, standard working hours, labor capacity, and presence of bottleneck processes. To optimize and improve the second production line, this paper applies the production line balance management method based on data mining. It utilizes the decision tree model in data mining and incorporates lean production knowledge from industrial engineering. The goal is to identify crucial factors that affect the balance of the production line and address the issues caused by these factors. The aim is to reduce and eliminate redundant working hours and enhance the balance rate of the production line. By implementing the approach outlined in this paper, the bottleneck time of the second production line was reduced from 96.67 s to 74.6 s, and the production line balance rate increased from 68% to 85%.

Assessing the role and driving mechanisms of the green financial reform on urban energy consumption and pollution emissions: a policy evaluation from the generalized synthetic control method

The Green Financial Reform and Innovation Pilot Areas (GFRIPA) policy is a key institutional arrangement that enables China's green finance to advance from theory to practice. Few studies have quantitatively evaluated the policy's environmental performance. This study uses a generalized synthetic control method (GSCM) alongside panel data from Chinese prefecture-level cities since 2007 to assess the effects of the GFRIPA policy on energy consumption and pollution emissions and to pinpoint the underlying mechanisms. Results show that establishing the GFRIPA significantly reduces energy consumption and pollution emissions, and that the effect emerges immediately in the policy's issuance year. Possible mechanisms consist of the increase in urban green innovation, the ease of financing constraints, the optimization of industrial structure, and the enhancement of environmental governance. Heterogeneity analyses reveal that policy effects are more profound in cities with a higher degree of marketization and a higher level of education. The findings provide valuable insights into consistently promoting the GFRIPA policy to meet environmental goals for energy conservation and pollution reduction and ultimately advance green economies in developing nations.

Synthesis of a Novel Dithiocarbamate Surfactant Derivative Adsorbent for Efficient Removal of Heavy Metal Ions

In this work, a novel heavy metal chelating agent (DTC-SDS) containing dithiocarbamate (DTC) was synthesized using sodium dodecyl sulfate (SDS), formaldehyde, and carbon disulfide. DTC-SDS has excellent trapping performance under pH 1-7 and initial concentrations 100-500 mg/L. With the increase in adsorbent dose, the adsorption amount of DTC-SDS increases and then decreases, and the optimized dosage of DTC-SDS is 0.02 g. The DTC-SDS adsorbent exhibits superior adsorption capacity (191.01, 111.7, and 79.14 mg/g) and high removal rates (97.99%, 98.48%, and 99.91%) for Mn2+, Zn2+, and Pb2+ respectively, in wastewater. Such remarkable adsorption performance could be attributed to the strong trapping effect on heavy metal ions by the C-S bond of DTC-SDS. The liquid adsorbent was in full contact with heavy metal ions, which further enhanced the complexation of heavy metal ions. The adsorption isothermal model showed that the adsorption process was typical of Langmuir monomolecular layer adsorption. Kinetic studies showed that the pseudo-second-order kinetic model fits the experimental adsorption data better than the pseudo-first-order kinetic model. In the ternary metal species system (Mn2+, Zn2+, and Pb2+), DTC-SDS preferentially adsorbed Pb2+ due to its highest covalent index. The main controlling step is the chemical interaction between the active groups of DTC-SDS and the heavy metal ions. This work provides valuable insights into the adsorption of heavy metal ions onto dithiocarbamate, which could guide the development of other heavy metal chelating agents and be beneficial for developing novel treatments of wastewater contaminated with heavy metals.

The spillover effect of after-hours electronic communication on nurses' cyberloafing: the mediating role of psychological contract breach

BACKGROUND

Considerable research has investigated the influencing factors of cyberloafing in the workplace. However, few studies have focused on the antecedents in non-work fields, especially for nurses. According to the effort-reward imbalance theory, this study aims to explore the spillover effect of after-hours electronic communication on nurses' cyberloafing, and the mediating role of psychological contract breach.

METHODS

A total of 282 nurses completed the online survey. PROCESS macro for SPSS was used to test how after-hour electronic communication affect nurses' cyberloafing.

RESULTS

After-hours electronic communication has a significant positive impact on nurses' cyberloafing, and psychological contract breach plays a mediating role in the relationship.

CONCLUSION

Psychological contract breach was the linchpin linking after-hours electronic communication to nurses' cyberloafing in workplace. This study provides a guide for healthcare organizations to reduce or manage inappropriate telework arrangements and strengthen nurses' psychological contracts.