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This study aims to systematically review the literature in the fields of liquidity, informational efficiency and default risk. The authors outline the key research streams and provide possible pathways for future research.

The study adopts bibliographic mapping to identify the most influential studies in the research fields of liquidity, informational efficiency and default risk from 1984 to 2021.

The study identifies four key research themes that include efficiency and transparency of markets; corporate yield spreads; market interactions: bonds, stocks and cryptocurrencies; and corporate governance. By assessing publications published from 2018 to 2021, the authors also document seven key emerging research trends: cross markets, managerial learning and corporate governance, state ownership and government subsidies, international evidence, machine learning (FinTech approaches), environmental themes and financial crisis. Drawing on these emerging trends, the authors highlight the opportunities for future research.

Keyword searches have limitations since some studies might be overlooked if they do not match the specified search criteria, even though their relevance to the topic is under investigation. Adopt the R project to expand this review by incorporating more literature from other databases, such as the Scopus database could be a possible solution.

The four key research streams contribute to a comprehensive understanding of liquidity, informational efficiency and default risk. The emerging trends integrate existing knowledge and leave the chance for innovative research to expand the research frontier.

This study fulfills the systematic literature review streams in the fields of liquidity, informational efficiency and default risk, and provides fruitful opportunities for future research.

This study sheds new light on the personality trait and provides evidence regarding the relation between narcissism and desirable accounting practices, specifically the impact of CEO narcissism on accounting conservatism.

The authors test the relation between CEO narcissism and accounting conservatism for a sample of 907 US companies and their corresponding CEOs for the period between 2010 and 2018. The authors apply three established models of accounting conservatism and measure executives' narcissism using a non-intrusive approach ubiquitous in the literature.

The authors find that CEO narcissism is associated with speculative accounting practices in the form of timely recognition of positive news and more prudent financial reporting of anticipated negative news. The authors provide the first empirical evidence that, despite its well-known negative effects on corporate financial reporting, executive narcissism can also produce positive outcomes.

While managerial overconfidence has received much attention, the effects of executives' narcissism are still widely unexplored (Chatterjee and Hambrick, 2007). The authors thus contribute to the literature by investigating the relationship between CEOs' narcissism and accounting conservatism. The authors conjecture CEO narcissism should have a twofold effect on prudent financial reporting. On the one hand, CEOs' narcissism should be associated with low levels of unconditional conservatism due to excessively fast good news recognition. On the other hand, narcissistic executives should be associated with early recognition of negative news and hence with higher levels of conditional conservatism.

The significance of smart mobility practices in shaping cities from a smart perspective has grown in recent years, influencing policies and the choices made by inhabitants. This transformation has led to the emergence of novel services and strategies, creating a new, vibrant and highly personalised urban environment that caters to the needs and preferences of both local residents and visitors. The purpose of this study is to evaluate the influence of smart mobility practices on tourism flows in cities, considering the moderating effect of airport activities on this relationship.

Using a generalised method of moments estimation and focusing on 20 Italian cities over an eight-year period, the authors highlight the current relationship between smart mobility practices and tourism flows. Moreover, the authors demonstrate that the yearly advancement of airports positively moderates this relationship.

The findings indicate a significant relationship between smart mobility practices in modern cities and tourism inflows because they influence the development of tourism services and emerging trends such as smart tourism and smart destinations. Furthermore, airport activities as a proxy for city openness play a crucial role in this link. The study shows that airports have an incremental impact on tourism and on the relationship between tourism and sustainable practices.

The limitations of this quantitative approach include the focus on a single country, the challenge of measuring the development of smart mobility practices due to a lack of standardised variables and the need for future research to expand the sample to different countries in relation to tourism inflows.

This study has practical implications for policymakers and governance in their task of effectively coordinating internal smart mobility practices and managing incoming tourism flows.

This study has social implications, highlighting the need for policymakers and governance to address the societal impacts of smart mobility practices and tourism inflows, ensuring inclusive and sustainable outcomes for local communities.

This study contributes to the existing literature as one of the first attempts to examine the interplay between smart mobility practices in smart cities and tourism flows. Furthermore, it emphasises the role of airports in this relationship, highlighting how the interaction between these variables benefits both stakeholders.

The majority of existing studies about named entity recognition (NER) concentrate on the prediction enhancement of deep neural network (DNN)-based models themselves, but the issues about the scarcity of training corpus and the difficulty of annotation quality control are not fully solved, especially for Chinese ancient corpora. Therefore, designing a new integrated solution for Chinese historical NER, including automatic entity extraction and man-machine cooperative annotation, is quite valuable for improving the effectiveness of Chinese historical NER and fostering the development of low-resource information extraction.

The research provides a systematic approach for Chinese historical NER with a three-stage framework. In addition to the stage of basic preprocessing, the authors create, retrain and yield a high-performance NER model only using limited labeled resources during the stage of augmented deep active learning (ADAL), which entails three steps—DNN-based NER modeling, hybrid pool-based sampling (HPS) based on the active learning (AL), and NER-oriented data augmentation (DA). ADAL is thought to have the capacity to maintain the performance of DNN as high as possible under the few-shot constraint. Then, to realize machine-aided quality control in crowdsourcing settings, the authors design a stage of globally-optimized automatic label consolidation (GALC). The core of GALC is a newly-designed label consolidation model called simulated annealing-based automatic label aggregation (“SA-ALC”), which incorporates the factors of worker reliability and global label estimation. The model can assure the annotation quality of those data from a crowdsourcing annotation system.

Extensive experiments on two types of Chinese classical historical datasets show that the authors’ solution can effectively reduce the corpus dependency of a DNN-based NER model and alleviate the problem of label quality. Moreover, the results also show the superior performance of the authors’ pipeline approaches (i.e. HPS + DA and SA-ALC) compared to equivalent baselines in each stage.

The study sheds new light on the automatic extraction of Chinese historical entities in an all-technological-process integration. The solution is helpful to effectively reducing the annotation cost and controlling the labeling quality for the NER task. It can be further applied to similar tasks of information extraction and other low-resource fields in theoretical and practical ways.

Improving productivity and efficiency has always been crucial for industrial companies to remain competitive. In recent years, the topic of environmental impact has become increasingly important. Published research indicates that environmental and economic goals can enforce or rival each other. However, few papers have been published that address the interaction and integration of these two goals.

In this paper, we identify both, synergies and trade-offs based on a systematic review incorporating 66 publications issued between 1992 and 2021. We analyze, quantify and cluster examples of conjunctions of ecological and economic measures and thereby develop a framework for the combined improvement of performance and environmental compatibility.

Our findings indicate an increased significance of a combined consideration of these two dimensions of sustainability. We found that cases where enforcing synergies between economic and ecological effects were identified are by far more frequent than reports on trade-offs. For the individual categories, cost savings are uniformly considered as the most important economic aspect while, energy savings appear to be marginally more relevant than waste reduction in terms of environmental aspects.

No previous literature review provides a comparable graphical treatment of synergies and trade-offs between cost savings and ecological effects. For the first time, identified measures were classified in a 3 × 3 table considering type and principle.

Promoting clean heating in rural areas is crucial for achieving a low-carbon transition of energy consumption and China's dual-carbon target. The study aims to consider the energy stacking behavior in heating energy use, reveals the determinants that affect household cleaner heating choices under the winter clean heating plan (WCHP), and proposes policy recommendations for the sustainable promotion of clean heating.

With unique rural household survey data covering the clean heating pilot regions in northern China in 2020, this study estimates the relationship between driving factors and heating energy choices through binary and multivariate probit models.

The regression estimates show that the main drivers of heating energy choices include household income per capita, education level of household head, knowledge of the WCHP, access to heating subsidies and perception of indoor air pollution. There is energy stacking behavior in rural household heating energy use. Household decisions to adopt electricity or clean coal heating are correlated with firewood or soft coal use.

This study is one of the few to investigate the heating energy use of rural households by allowing for the adoption of multiple energy types. Combined with a unique microsurvey dataset, it could provide rich information for formulating proper energy transition planning. The findings also shed light on the importance of heating subsidies, households' knowledge of WCHP and awareness of environmental health in choosing clean heating energy, which has not been fully valued in related research.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

Online reviews derived from peer communications have been increasingly viewed as an important approach for consumers to gather pre-purchase information. This study aims to examine factors affecting online reviews adoption in social network communities and then indicates the underlying mechanism of this process based on an extended information adoption model (IAM).

Using the data collected from 242 users of a social network community via an online survey, the proposed model is empirically assessed by partial least squares-based structural equation model (PLS-SEM).

The results show that both perceived diagnosticity and perceived serendipity are drivers of online reviews adoption in social network communities. Meanwhile, community identification is not only an antecedent of diagnosticity and serendipity perceived by community members, but also motivates source credibility which, in turn, positively influences argument quality. Finally, the importance of argument quality and source credibility in reviews adoption process is also presented.

This study extends the IAM and enriches the literature regarding online reviews adoption. It deepens the understanding of serendipitous experiences and community identification in social networking context by addressing their important roles in the authors' extended IAM.

Based on the role theory and prosocial motivation literature, this research aims to explore the bright and dark side of socially responsible human resource management (SRHRM) on hotel employees' outcomes through the mediation of role conflict. Besides, this study examines the moderating effect of prosocial motivation between role conflict and volunteering and organizational citizenship behavior (OCB).

The authors collected 326 employee-supervisor dyads data in two waves from 12 hotels in the province of Wuhan, China. Besides, structural equation modeling (SEM) analysis was adopted to test the hypothesized model.

As expected, the result shows that SRHRM can increase employees' volunteering and decrease their OCB through the mediation of the role conflict. Further, prosocial motivation strengthens the linkage between role conflict and volunteering, but not the relationship between role conflict and OCB.

This result enables hotel managers to adopt SRHRM as a useful tool of carrying out suitable corporate social responsibility (CSR) activities. Additionally, this study highlights the vital role of employee in successful CSR implementation.

Although the hotel industry contributes a lot to global economic development, CSR research specifically focused on hotel industry has been unexplored. Therefore, this research brings SRHRM into hotel industry and establishes a model specifying both the bright side and dark side effect of SRHRM in the hotel industry.

This paper investigates the influence of political connections on sustainability disclosure in the context of China's Regulation 18.

The study employs a quasi-experimental approach, utilizing difference-in-difference (DiD) analysis, dynamic DiD and propensity score matching to analyze the effects of politically connected independent directors on sustainability disclosure following the implementation of Regulation 18.

Companies with politically connected independent directors show an improvement in sustainability disclosures after Regulation 18. This effect is stronger for firms facing high political pressure or lacking alternative political power. Additionally, the increase in value from sustainability disclosures compensates for the loss of politically connected independent directors, indicating a positive value impact of sustainability disclosures.

This study provides novel insights into the corporate disclosure policy in China by investigating the impact of politically connected directors on sustainability disclosure. Additionally, it sheds light on the limitations of political power and its substitution effects within companies.