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Written communication differences across cultures can set the tone for effective or disastrous business relationships. Although English has been the go-to language in business, managers from different countries can significantly differ in how they convey the firms' information. This study explored these differences by examining the documentation presented by foreign corporations as part of their initial public offering (IPO) in the USA, particularly Chinese firms.

This work examined cultural-related differences in written communications by looking at foreign corporations' descriptions of their strengths, strategies and challenges included in F-1 documents submitted to the Securities and Exchange Commission as part of the IPO process. The sample consisted of 97 American depositary receipts (ADRs) identified in the Bank of New York Mellon's ADR directory from 2003 to 2015.

This study found that Chinese firms significantly differ from other countries' firms in depicting their strengths, strategies and challenges.

Limitations have to do with the sample size. Future research may address this by considering other depositary markets, not just the USA.

The results will be significant for potential ADRs investors; they must be conscious of these differences in the written documentation submitted by Chinese firms compared to other foreign firms. The market should also be aware of these differences, as the Chinese seem less open to sharing information about the under spinning of their operations and financial prospects.

This research studies the behavior choice of key actors in the construction supply chain and constructs a model which includes the benefit function of the government, contractors and owners, aiming at improving the coverage of green buildings.

In this paper, tripartite dynamic game is studied and simulated based on duplicate dynamic equation. The tripartite game under government intervention is rarely considered, and government punishment measures are seldom introduced into the research.

According to the simulation results, the practical insights in line with the development of green supply chain are put forward. Rewards and punishments affect the development of the supply chain. New technologies and new materials accelerate the development of green supply chain and then improve the coverage of green buildings.

This paper constructs a dynamic model based on complete information rationality, which is difficult to realize in practice, for information is incomplete and human rationality is limited.

In fact, the government has not issued a punishment document to introduce a new variable adjustment model.

Premium subsidy rates were increased in 2019 and 2020 for livestock risk protection (LRP) insurance, which is price insurance for cattle producers. The authors examined if the LRP subsidy rate changes affected the LRP coverage levels purchased by feeder and fed cattle producers.

The authors collected the United States Department of Agriculture Risk Management Agency summary of business sales data for daily LRP purchases from 2015 to 2023. The authors estimated a multinomial logit model to determine if subsidy rate changes were associated with the likelihood of LRP policies being purchased at different coverage levels.

After the 2019 and 2020 subsidy rate changes, the likelihood of producers buying LRP-feeder cattle policies with coverage over 95% increased relative to the policies with coverage less than 89.99% but did not influence the likelihood of producers buying LRP-feeder cattle policies with coverage between 90 and 94.99% relative to policies with coverage less than 89.99%. Marginal effects show these subsidy rate changes increased the likelihood of buyers purchasing LRP-feeder cattle policies with greater than 95% coverage. The subsidy change did not affect the purchase of LRP-fed cattle policies.

The results demonstrate the influence of the recent LRP policy adjustments on insurance purchases, which could be important for agency officials and policy makers. This is the first study to explore the LRP policy purchases which provides the United States cattle industry insight into the LRP price insurance take-up, which can guide producer extension education on managing price risk.

This study explores whether religion plays an important role in corporate poverty alleviation. Religious atmosphere affects managers' attitude towards corporate social responsibility (CSR) and then influences corporate poverty alleviation. This study first examines the impact of religious atmosphere on corporate poverty alleviation and then investigates whether formal institutions, such as law enforcement environments and ownership, influence the relationship between religious atmosphere and corporate poverty alleviation behavior.

In 2016, the Chinese government initiated a nationwide campaign aiming to eliminate poverty in China by 2020. The authors conduct empirical tests with data on Chinese listed firms from 2016 to 2020. The religious atmosphere is measured by the number of Buddhist monasteries and Taoist temples within a certain radius around Chinese listed firms' registered addresses. The authors adopt the ordinary least squares (OLS) method for regression and take the two-stage least squares (2SLS) method to address the endogeneity issue.

The results show a positive relationship between religious atmosphere and corporate poverty alleviation donations. Law enforcement attenuates the positive association between the religious atmosphere and corporate poverty alleviation donations. Religion and corporate poverty alleviation donations have a more positive association for non-state-owned enterprises (non-SOEs) than for state-owned enterprises (SOEs).

The authors' findings have important implications. First, this study inspires incorporating the ethical value of traditional culture, such as religion, into CSR. Second, the findings imply that informal institutions have a greater impact on corporate decision-making when formal institutions are weak, suggesting that informal institutions should be emphasized when promoting CSR in countries where formal institutions are relatively weak. The study investigates only religious influence on corporate poverty alleviation based on Buddhism and Taoism, but the authors do not examine the impacts of other religions. Future research may examine the relationships between other religions and corporate poverty alleviation in China.

This study illustrates the positive role played by religion in promoting CSR by relating religious atmosphere to corporate poverty alleviation. It fills the research gap between religion and CSR and also contributes to the literature on determinants of corporate poverty alleviation.

Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.

The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.

There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.

The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.

Since 2000, China, along with the USA, UK, France, Japan and many other developed countries have drawn up new blueprints for the development of a marine economy. At present, international marine economics research has entered into a new period of development, and the research methods of ocean econometrics are becoming more complex and mature. The purpose of this paper is to review the progress of international marine econometrics research and gives the development direction of marine econometrics.

The Web of Science core collection database was utilized, harvesting data from 1996 to May 2018, measuring the marine economy research from 1,489 articles as its sample, using CiteSpace visualization analysis tools.

Mapping the knowledge map from annual international marine economic metrology, literature identification, keywords, involving disciplines and related journals, countries (regions) and research and analyzing the research status of reveals the research frontiers of international marine economy measurement (learning) by using CiteSpace.

The conceptions and characteristics of marine econometrics are defined and analyzed, and the theoretical method of marine econometrics is sorted out. Mapping the knowledge diagram of marine econometrics and discussing the research status of international marine economics, and clarifying the existing problems, future opportunities and challenges of international marine econometrics research.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

Through its advanced computational capabilities, cyber–physical systems (CPS) proffer solutions to some of the cultural challenges plaguing the effective delivery of facilities management (FM) mandates. This study aims to explore the drivers for the uptake of CPS for FM functions using a qualitative approach – the Delphi technique.

Using the Delphi technique, the study selected experts through a well-defined process entailing a pre-determined set of criteria. The experts gave their opinions in two iterations which were subjected to statistical analyses such as the measure of central tendency and interquartile deviation in ascertaining consensus among the experts and the Mann–Whitney U test in establishing if there is a difference in the opinions given by the experts.

The study’s findings show that six of the identified drivers of the uptake of CPS for FM were attributed to be of very high significance, while 12 were of high significance. Furthermore, it was revealed that there is no significant statistical difference in the opinions given by experts in professional practice and academia.

The study’s outcome provides the requisite insight into the propelling measures for the uptake of CPS for FM by organisations and, by extension, aiding digital transformation for effective FM delivery.

To the best of the authors’ knowledge, evidence from the literature suggests that no study has showcased the drivers of the incorporation of CPS for FM. Hence, this study fills this gap in knowledge by unravelling the significant propelling measures of the integration of CPS for FM functions.

Complex and exquisite patterns are sculpted on the surface to beautify the parts. Due to the thin-walled nature, the blank of the part is often deformed by the forming and clamping processes, disabling the nominal numerical control (NC) sculpting programs. To address this problem, a fast adaptive sculpting method of the complex surface is proposed.

The geometry of the blank surface is measured using on-machine measurement (OMM). The real blank surface is reconstructed using the non-uniform rational basis spline (NURBS) method. The angle-based flattening (ABF) algorithm is used to flatten the reconstructed blank surface. The dense points are extracted from the pattern on the image using the OpenCV library. Then, the dense points are quickly located on the complex surfaces to generate the tool paths.

By flattening the reconstructed surface and creating the mapping between the contour points and the planar mesh triangular patches, the tool paths can be regenerated to keep the contour of the pattern on the deformed thin-walled surface.

The proposed method can adjust the tool paths according to the deformation of the thin-walled part. The consistency of sculpting patterns is improved.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.