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Both issuing firms and underwriters shall benefit from the associations in underwriting contracts for seasoned equity offerings (SEOs). Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SEO underwriters, and thus these existing underwriters are able to maintain or gain greater market share. This study investigates how the clustering of percentage gross spreads affects the likelihood of underwriter switching.

Using the investment bank-underwritten SEOs in Hong Kong, the authors find that the percentage gross spreads of 40% of these SEOs are clustered at 2.5%. The seemingly unrelated bivariate probit model, Weibull survival mixed model and trivariate probit model are applied to analyse this phenomenon.

The authors' study provides first direct evidence that the clustering of percentage gross spreads lowers the likelihood of underwriter switching. Investment banks as underwriters can explicitly price underwriting contracts at a clustered level, more likely in periods of greater market volatility, and intentionally retain the banks' client firms using pricing arrangements. The authors' finding and approach offer more direct and distinct support that the issuer–underwriter association can be relationship-based.

Whilst the clustering of fees is interpreted as a type of anticompetitive price sitting, the authors contribute to literature by providing new empirical evidence on why percentage gross spreads as a price dimension are clustered. On top of contract efficiency and collusion, this study's new evidence provides a third view for the clustering of gross spreads.

The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them.

In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019.

The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities.

There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

This study aims to analyse what factors influence ethnic minority group (EMG) college students’ attitudes towards promoting online start-ups and how their different attitudes impact their final online start-up behaviours on the live streaming platform. Based on the COM-B behaviour changing model and the theory of liberal and conservative attitudes, the research model has been established in this study, and it divides influencing factors into the environmental opportunity unit and personal capability unit.

To test relationships among the environmental opportunity, personal capability and personal attitude units, the partial least squares path modelling and variance-based structural equation modelling have been applied on the SmartPLS. Meanwhile, this study considers the regional difference between China’s developed and less-developed regions and promotes multi-group analysis based on it.

Research results show that the online start-up opportunity and capability positively affect EMG college students’ liberal attitudes but reduce EMGs’ conservative attitudes. Meanwhile, this study finds four significant differences, such as the path between conservative attitude and EMG students’ online start-up behaviour and the path between online start-up capability and conservative attitude.

This paper analyses the relationship between influencing factors and EMG students’ online start-up attitudes based on the COM-B behaviour changing model, contributing to the theoretical implications. Meanwhile, considering the impact of regional differences, this paper promotes the multi-group analysis and compares EMG college students from developed regions and others from less-developed areas.

This paper aims to assess the quality management (QM) principles in facilities management (FM) service delivery for office buildings. This is to create a quality culture that will enhance the performance of FM service delivery towards meeting the users' requirements and needs.

This study adopts a quantitative methodology via a questionnaire survey for the data collection. In total, 24.41% of respondents from the registered FM companies in Malaysia attended the survey. SPSS 27.0 was used to interpret the collected data, which were then reviewed through descriptive and inferential analysis.

The study signifies that customer focus, leadership, improvement, evidence-based decision-making and relationship management indicate positive connections with FM service delivery in ensuring a cost-effective working process and meeting both user requirements and legal and regulatory corporate compliance. There are 18 elements of strategic, people and structural barriers that may hinder the implementation of QM in the FM service delivery. Correspondingly, the five main key enablers suggested being teamwork and participation, leadership, continuous improvement, process management and resources and competency development-based enablers.

The study was conducted during the pandemic crisis with limited access and response from participants. However, this in-depth study was still able to synthesize the imperative QM practice in FM among FM practitioners in Malaysia.

This study provides insight into the implementation of QM principles to cultivate a quality culture that will enhance the performance and productivity in FM service delivery specifically for office buildings in Malaysia. Prior to this study, there was a lack of research pertaining to these two themes: QM and FM.

This study aims to examine the association between globally responsible leadership (GRL) and pro-environmental behavior (PEB), specifically probing the mediating role of green management initiatives (GMI) in this relationship.

This study used a quantitative research design, using survey data from 390 participants working in manufacturing sector organizations in one of the emerging economies in the Asian region, namely, Pakistan. AMOS was used to test the hypothesized relationships.

The results reveal that GRL has a significant positive link with GMI and PEB. In addition, this study found that GMI mediates the association between GRL and PEB, suggesting that GRL indirectly promotes PEB through the implementation of GMI.

This study has several limitations, including its reliance on self-reported data, its cross-sectional design and its focus on participants from only one nation. Future research may benefit from using mixed-study designs and diverse samples from multiple industries and nations.

The results suggest that businesses can promote PEB among their staff by adopting GRL and implementing GMI. In doing so, businesses can demonstrate their commitment to sustainability, enhancing their credibility and competitive advantage.

This research contributes several new insights to the existing literature on sustainable leadership. First, it provides empirical evidence to support the hypothesis that GRL, GMI and PEB are interrelated. Second, it highlights the mediating role of GMI in this relationship.

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

With increasing complexity of construction projects and new construction processes and methods are adopted, more safety hazards are emerging at construction sites, requiring the application of the modern risk management methods. As an emerging technology, digital twin has already made valuable contributions to safety risk management in many fields. Therefore, exploring the application of digital twin technology in construction safety risk management is of great significance. The purpose of this study is to explore the current research status and application potential of digital twin technology in construction safety risk management.

This study followed a four-stage literature processing approach as outlined in the systematic literature review procedure guidelines. It then combined the quantitative analysis tools and qualitative analysis methods to organize and summarize the current research status of digital twin technology in the field of construction safety risk management, analyze the application of digital twin technology in construction safety risk management and identify future research trends.

The research findings indicate that the application of digital twin technology in the field of construction safety risk management is still in its early stages. Based on the results of the literature analysis, this paper summarizes five aspects of digital twin technology's application in construction safety risk management: real-time monitoring and early warning, safety risk prediction and assessment, accident simulation and emergency response, safety risk management decision support and safety training and education. It also proposes future research trends based on the current research challenges.

This study provides valuable references for the extended application of digital twin technology and offers a new perspective and approach for modern construction safety risk management. It contributes to the enhancement of the theoretical framework for construction safety risk management and the improvement of on-site construction safety.

Aqueous zinc-ion battery has broad application prospects in smart grid energy storage, power tools and other fields. Co₃O₄ is one of the ideal cathode materials for water zinc-ion batteries due to their high theoretical capacity, simple synthesis, low cost and environmental friendliness. Many studies were concentrated on the synthesis, design and doping of cathodes, but the effect of process parameters on morphology and performance was rarely reported.

Herein, Co₃O₄ cathode material based on carbon cloth (Co₃O₄/CC) was prepared by different temperatures hydrothermal synthesis method. The temperatures of hydrothermal reaction are 100°C, 120°C, 130°C and 140°C, respectively. The influence of temperatures on the microstructures of the cathodes and electrochemical performance of zinc ion batteries were investigated by X-ray diffraction analysis, scanning electron microscopy, cyclic voltammetry curve, electrochemical charging and discharging behavior and electrochemical impedance spectroscopy test.

The results show that the Co₃O₄/CC material synthesized at 120°C has good performance. Co₃O₄/CC nanowire has a uniform distribution, regular surface and small size on carbon cloth. The zinc-ion battery has excellent rate performance and low reaction resistance. In the voltage range of 0.01–2.2 V, when the current density is 1 A/g, the specific capacity of the battery is 108.2 mAh/g for the first discharge and the specific capacity of the battery is 142.6 mAh/g after 60 charge and discharge cycles.

The study aims to investigate the effect of process parameters on the performance of zinc-ion batteries systematically and optimized applicable reaction temperature.

This research examines the role of green, inclusive leadership, corporate social responsibility, and pro-environmental attitudes on proactive pro-environmental behaviour among hotel employees. It further examines the indirect effects of pro-environmental attitudes between green inclusive leadership, corporate social responsibility, and proactive pro-environmental behaviour, as well as the moderating role of psychological contract breach between pro-environmental attitudes and proactive pro-environmental behaviour.

The participants of this cross-sectional study were employees in the Malaysian hotel industry, and 374 usable questionnaires were used for data analysis. The data were analysed using Partial Least Squares – Structural Equation Modelling.

This study found that green, inclusive leadership, corporate social responsibility, and pro-environmental attitudes significantly influence proactive pro-environmental behaviour. For mediating effects, pro-environmental attitudes have been found to mediate the relationship between corporate social responsibility, green inclusive leadership and proactive pro-environmental behaviour.

The research proposes actionable measures to encourage environmentally friendly practices in the hotel sector. For companies to succeed, they must integrate green initiatives with their societal objectives. Pro-environmental mindsets are essential for implementing effective environmental policies, which in turn impact recruitment approaches. The advantages of fostering pro-environmental conduct encompass financial savings, enhanced standing, adherence to regulations, increased innovative thinking and improved workplace well-being.

Over time, environmental degradation has been contributed by individual behaviours and the combined actions of businesses and organisations. This study significantly contributed to a new model underpinned by the Self-determination Theory by including new constructs influencing proactive pro-environmental behaviour.