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This paper examines the effect of board reforms on managerial risk-taking incentive provision in state-owned enterprises (SOEs) whose managers are undue risk-averse.

We use the staggered implementation of board reforms in Chinese central government-controlled state-owned enterprises (CSOEs) as an exogenous shock to board governance. We collect data on board reforms for a set of pilot CSOEs during the period 2005 to 2020 from the State-owned Assets Supervision and Administration Commission (SASAC) website by hand. We use a generalized difference-in-difference (DID) design to test the effect of staggered board reform adoption on managerial risk-taking incentive provision.

We find a positive relationship between board reforms and risk-taking inventive provision, i.e. pay-performance sensitivity, promotion-performance sensitivity and performance target difficulty. The documented relationship is stronger when the value of risk-taking is higher. We also find that board reforms lead to greater risky but value-enhancing investments and that managerial risk-taking incentive provision acts as an important channel through which board reforms improve value-enhancing risk-taking.

Our findings suggest that board reforms that improve board governance are effective in addressing risk-related agency conflicts in emerging markets. The findings also highlight the importance of managerial risk-taking incentive provision in inducing risky but value-enhancing investments.

One of the crucial elements of addressing global climate challenges through urban tourism is the continuing existence of urban forests. The reasoning is that the ecological attraction of urban forests can impact visitors’ intention to conduct pro-environmental behavior, including low-carbon actions. Thus, more visitors to urban forests will positively affect enhancing the quality of the urban environment. However, the extent to which ecological attraction can influence pro-environmental behavior warrants further investigation due to the complexity of psychosocial factors that impact behavioral intention. The main objective of this research is to examine the effects of the ecological attractiveness of urban forests on the pro-environmental behavior of visitors by exploring motivation, ecological experience, perceived value and knowledge as mediators. Moreover, whether the nature of the urban forest and facilities attract visitors simultaneously is also studied.

Data were collected from 615 respondents who visited three urban forests in Bandung, the second-most populous city in Indonesia, by five-point Likert questionnaires. As an analytical tool, SEM PLS was applied to establish the effect of the ecological performance of the urban forest on the increase in environmentally conscious behavior among urban forest visitors.

The findings demonstrate that the attractiveness of an urban forest affects the growth of environmentally responsible behaviors. Nonetheless, the attractiveness of urban forests is dictated more by their infrastructure than their ecological function. On the contrary, the visitors’ knowledge level can improve their motivation, environmental experience and perceived environmental value. These findings show the significance of developing educational programs with an emphasis on the experience of the visitors so that their ecological performance can contribute to improved low-carbon behavior. In conclusion, this work contributes to the management of sustainable urban tourism.

This work also has some limitations. First, the medium R-square on intention behavior to low-carbon action suggests investigating other influential factors to produce a more robust conscious behavior. Mkono and Hughes (2020) mention that many complex factors that cause positive intention do not necessarily lead to environmental action. Thus, many psychosocial variables need to be explored in different models. Second, the convenient sampling used here does not represent the whole population, making generalization difficult. Thus, further work needs to apply more rigorous sampling techniques to validate the findings. Further investigations may also need to be conducted in other urban forests in another Asian country with a similar and different social context for benchmarking, as this study found that the type of attractive urban forest design is a more dense forest, which differs from other studies based in Europe. Exploring more influencing behavioral factors of pro-environmental action in the model is also suggested. Thus, we could contribute more to support recreational activities in urban forests.

As an implication for planning an urban forest to increase its recreational function, the authors illustrate the importance of producing educational programs. Although the improved knowledge of visitors has been shown to strengthen their commitment to perform pro-environmental actions, the mediating role of motivation, experience and perceived value reveals that some activities are required to achieve visitor motivation to actual behavior. Consequently, designing an urban forest requires not only the enhancement of eco-attractions and artificial elements for the convenience of visitors but also the development of an environmental education program that can improve visitors’ environmental experience and perception of ecological value. The designed educational program may use an experiential education approach incorporating objective knowledge of Earth’s current state. The urban forest education program must encourage visitors’ connection and participation with nature. Moreover, knowledge and information about Earth’s environmental quality can increase visitors’ perceived value, ensuring that their activities in the urban forest contribute to improved health, environmental quality and social environment. Thus, with well-managed and provided education, they are encouraged to adopt low-carbon action because it complements their contribution to a better quality environment.

The theoretical contribution of this research is generated through the role of urban forest attractiveness in the intention to conduct low-carbon action, which influences solutions to existing urban environmental problems. This work exhibits that both ecological attractiveness and attractiveness of artificial elements in urban forests can attract visitors and subsequently boost their outdoor recreation motivation, ecological experience and perceived value and then turn them to boost their intention to conduct low-carbon action. The physical characteristics of a site are behavioral stimuli that can increase a person’s motivation, experience and perception of the value of the environment, thereby increasing their intention to engage in low-carbon actions. This environment behavioral construction is fundamental in understanding that urban forests offer ecological benefits and influence the social quality of urban communities. Nevertheless, without visitor activity, urban forests are merely physical entities that become increasingly demanding to maintain. Due to this, an urban forest that is socially active and has an influence on promoting environmentally conscious behavior is needed, and its presence is becoming ever more crucial. This work shows the significance of integrating psychosocial approaches into managing tourism in urban forests.

This paper aims to demonstrate that, in line with the emerging trend of multifunctional yarn development, cotton yarn can effectively harness renewable solar energy to achieve photothermal conversion and thermochromism. This innovation not only maintains the comfort associated with natural fiber cotton yarn but also enhances its ultraviolet (UV) light resistance.

In this work, 4% zirconium carbide (ZrC) and thermochromic powder were adhered to cotton yarn through polyurethane (PU) by sizing coating method. After sizing, the two cotton yarns are twisted by ring spinning to obtain composite yarns with photothermal conversion and thermochromic functions.

The yarn obtained by cotton/6%PU/8% thermochromic dye single yarn and cotton/6%PU/4% ZrC single yarn composite is the best match. After 5 min of infrared light, the temperature of the composite yarn rose to the maximum, increasing by 36.1°C. The ΔE* value before and after irradiation of infrared lamp is 26.565, which proves that the thermochromic function is good. The yarn dryness unevenness was significantly reduced by 27.2%. The composite yarn has a UPF value of up to 89.22, and its performance characteristics remain stable after 100 minutes of washing.

The composite yarn’s photothermal conversion and thermochromism functions are mutually reinforcing. Using sunlight can simultaneously achieve heating and discoloration effects without consuming additional energy. The cotton yarn used in this application is versatile, and suitable for a wide range of uses including clothing, temperature visualization detection and other scenarios.

Powder bed additive manufacturing has recently seen substantial growth, yet consistently producing high-quality parts remains challenging. Recoating streaking is a common anomaly that impairs print quality. Several data-driven models for automatically detecting this anomaly have been proposed, each with varying effectiveness. However, comprehensive comparisons among them are lacking. Additionally, these models are often tailored to specific data sets. This research addresses this gap by implementing and comparing these anomaly detection models for recoating streaking in a reproducible way. This study aims to offer a clearer, more objective evaluation of their performance, strengths and weaknesses. Furthermore, this study proposes an improvement to the Line Profiles detection model to broaden its applicability, and a novel preprocessing step was introduced to enhance the models’ performances.

All found anomaly detection models have been implemented along with several preprocessing steps. Additionally, a new universal benchmarking data set has been constructed. Finally, all implemented models have been evaluated on this benchmarking data set and the effect of the different preprocessing steps was studied.

This comparison shows that the improved Line Profiles model established it as the most efficient detection approach in this study’s benchmark data set. Furthermore, while most state-of-the-art neural networks perform very well off the shelf, this comparison shows that specialised detection models outperform all others with the correct preprocessing.

This comparison gives new insights into different recoater streaking (RCS) detection models, showcasing each one with its strengths and weaknesses. Furthermore, the improved Line Profiles model delivers compelling performance in detecting RCS.

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.

The study aims to investigate the characteristics of the current situation of library programs and explore the possible reasons behind the low participation in Hong Kong. It focuses on the development of library programs in the era of digital technology, which can lead to discussion and reflections on the further development of library programs with innovative technology services.

This study applied a mixed-method research approach to investigate the current situation of library programming and the reasons for low participation in Hong Kong. The first part analyzes the characteristics of library programs offered by the Hong Kong Public Libraries (HKPL) through data collection from the HKPL website. The second part of this study investigated the reasons behind the low participation in library programs through quantitative research through an online survey.

The findings show that current library programs were dominated by reading activities and children's programs to a great extent, which both users and non-users are not very interested in. Further, most respondents expressed more interest in cultural and leisure events and hands-on activities (especially new technologies related) than traditional library programming. Many lapsed and non-users chose not to attend the library programs for boredom and uselessness. As a result, there is a need for HKPL to adjust its services to stay relevant to the needs and interests of local communities.

Scant studies explored the reasons behind non-users of public library programs, especially in Asia. This research contributes to the literature by analyzing and proposing the characteristics of the current situation of library programs and exploring the possible reasons behind the low participation in Hong Kong.

The purpose of this study is to investigate the potential of using computer vision and deep learning (DL) techniques for improving safety on construction sites. It provides an overview of the current state of research in the field of construction site safety (CSS) management using these technologies. Specifically, the study focuses on identifying hazards and monitoring the usage of personal protective equipment (PPE) on construction sites. The findings highlight the potential of computer vision and DL to enhance safety management in the construction industry.

The study involves a scientometric analysis of the current direction for using computer vision and DL for CSS management. The analysis reviews relevant studies, their methods, results and limitations, providing insights into the state of research in this area.

The study finds that computer vision and DL techniques can be effective for enhancing safety management in the construction industry. The potential of these technologies is specifically highlighted for identifying hazards and monitoring PPE usage on construction sites. The findings suggest that the use of these technologies can significantly reduce accidents and injuries on construction sites.

This study provides valuable insights into the potential of computer vision and DL techniques for improving safety management in the construction industry. The findings can help construction companies adopt innovative technologies to reduce the number of accidents and injuries on construction sites. The study also identifies areas for future research in this field, highlighting the need for further investigation into the use of these technologies for CSS management.

This study aims to examine whether the adoption of artificial intelligence (AI) by audit firms and their clients affects audit efficiency and audit quality.

This study empirically examines the abovementioned research question based on data from China for the years 2011 to 2020. It uses audit report lag as a proxy for audit efficiency and the likelihood of annual report restatement as a proxy for audit quality. It adopts the propensity score matching and the two-stage OLS regression model to address the endogeneity issue led by firms’ innate complicated functions.

The findings show that when audit firms and their clients use AI separately, there's a positive link between AI use and audit report lag. However, when audit firms and clients use AI together, there's a negative link between AI use and audit report delays that enhance overall audit efficiency. Next, the authors observe a negative link between AI use and the likelihood of a restatement. Finally, the authors find that the association between AI adoption and audit quality is driven by increased audit effort lag. Results are consistent and robust to endogeneity tests and sensitivity analyses.

Findings can complement the audit quality and corporate governance literature by clarifying that external audit must evolve through digitalization and the incorporation of newly developed digital tools, such as AI.

Steam explosions are a major safety concern in many modern furnaces. The explosions are sometimes caused by water ingress into the furnace from leaks in its high-pressure (HP) cooling water system, coming into contact with molten matte. To address such safety issues related to steam explosions, risk based inspection (RBI) is suggested in this paper. RBI is presently one of the best-practice methodologies to provide an inspection schedule and ensure the mechanical integrity of pressure vessels. The application of RBIs on furnace HP cooling systems in this work is performed by incorporating the proportional hazards model (PHM) with the RBI approach; the PHM uses real-time condition data to allow dynamic decision-making on inspection and maintenance planning.

To accomplish this, a case study is presented that applies an HP cooling system data with moisture and cumulated feed rate as covariates or condition indicators to compute the probability of failure and the consequence of failure (CoF), which is modelled based on the boiling liquid-expanding vapour explosion (BLEVE) theory.

The benefit of this approach is that the risk assessment introduces real-time condition data in addition to time-based failure information to allow improved dynamic decision-making for inspection and maintenance planning of the HP cooling system. The work presented here comprises the application of the newly proposed methodology in the context of pressure vessels, considering the important challenge of possible explosion accidents due to BLEVE as the CoF calculations.

This paper however aims to optimise the inspection schedule on the HP cooling system, by incorporating PHM into the RBI methodology, as was recently proposed in the literature by Lelo et al. (2022). Moisture and cumulated feed rate are used as covariate. At the end, risk mitigation policy is suggested.

In this paper, the proposed methodology yields a dynamically calculated quantified risk, which emphasised the imperative for mitigating the risk, as well as presents a number of mitigation options, to quantifiably affect such mitigation.

The study examines the IPO resilience grounded on the firm’s intrinsic factors.

We examine the association of IPO performance and post-listing firm’s performance with issuers' pre-listing financial and qualitative traits using panel data regression.

IPOs floated in the Indian market from July 2009 to March 31, 2022, evince the notable influence of issuers' pre-IPO fundamentals and legitimacy traits on IPO returns and post-listing earning power. Where the pandemic’s favorable impact is discerned on the post-listing year earning power of the issuer firms, the loss-making issuers appear to be adversely affected by the Covid disruption. Perhaps, the successful listing equipped the issuers with the financial flexibility to combat market challenges vis-à-vis failed issuers deprived of desired IPO proceeds.

High initial returns followed by a declining pattern substantiate the retail investors to be less informed vis-à-vis initial investors, valuers and underwriters, who exit post-listing after profit booking. Investing in the shares of the newly listed ventures post-listing in the secondary market can shield retail investors from the uncertainty losses of being uninformed. The IPO market needs stringent regulations ensuring the verification of the listing valuation, the firm’s credentials and the intent of utilizing IPO proceeds. Healthy development of the IPO market merits reconsidering the listing of ventures with weak fundamentals suspected to withstand the market challenges.

Given the tremendous rise in the new firm venturing into the primary market and the spike in IPOs countering the losses immediately post-opening, the study examines the loss-making and young firms IPOs separately, adding novelty to the study.