Search results

This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.

Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.

This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.

This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.

The distinct characteristics of slow tourism compared to mass tourism determine the differences between slow travelers and mass travelers. This transformation is essential for potential tourists to transition into slow travelers when promoting slow tourism to them. Can travel vlogs, a “fast” way of promoting, achieve such a “slow” transformation? To address this question, the purpose of this paper is to introduce the resonance theory and investigate the impact of resonance with slow tourism vlogs on potential travelers’ destination image and travel intention.

Through the distribution of online questionnaires on site, this study collected a total of 349 valid questionnaires. Subsequently, the researcher used partial least squares structural equation modeling to analyze the data and test the hypotheses.

The research findings indicate that cognitive resonance only positively affected cognitive image, while emotional resonance was positively associated with both cognitive image and affective image. In addition, it was observed that cognitive image and affective image played a positive mediating role between resonance with slow tourism vlogs and travel intention.

This research is pioneering in quantitatively validating the structure linking resonance, destination image and travel intention in the context of slow tourism. By validating the second-order structure of cognitive and emotional resonance, this study underscores the crucial role of resonance in shaping tourists’ transition toward a slow mindset in slow tourism.

This study aims to identify the dimensions of satisfaction in the halal tourism literature by analyzing the identified antecedents and outcomes. The study aims to synthesize the current empirical findings in halal tourism. Additionally, this study provides a comprehensive understanding of the factors that lead to halal traveller satisfaction.

Using a meta-analysis approach, this paper synthesizes the fragmented and conflicting findings of 56 quantitative studies focusing on satisfaction and its antecedents and consequences in the halal tourism context. Data from 145 relationships representing an aggregate sample size of 21,173 were used. Additionally, this study extends the analysis by incorporating contemporary factors such as the impact of COVID-19, sample size and gender as moderators.

The findings indicate that both physical characteristics and psychological aspects are positively related to satisfaction. Further, this study reported that endorsement and revisit intention are the significant consequences of satisfaction. Lastly, this study identifies the significant moderating effect of the COVID-19 pandemic, sample size and gender on the relationship between satisfaction and its antecedents/consequences.

Global halal tourism industry caters to Muslim and non-Muslim tourists across the globe; this article identifies the contributing factors of satisfaction in the halal tourism context. Policymakers can adapt according to their needs and preferences.

This study provides cumulative evidence to the literature regarding the relationship between satisfaction and its antecedents/consequences in halal tourism. This is the first meta-analysis study on the mentioned topic, making significant theoretical, managerial and methodological contributions to halal tourism research.

This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

The objective of this research is to evaluate the influence of mineral additions on the mechanical performances of polymer concrete. This study aims to propose a novel approach formulation of polymer concrete based on reduction in the quantity of the binder and disposal of large quantities of industrial by-products and household waste such as the marble, the brick and silica fume whose valuation in polymer concrete could be an interesting ecological and economical alternative. The incorporation of a rate of 10% brick powder affects the distribution of pores inside polymer concrete, that is, the pore diameters become thinner and decrease and the porosity becomes evenly distributed. The recycled mineral brick powder addition in polymer concrete mix improved the mechanical properties.

This polymer concrete was prepared by using polyester resin and two different types of sand, following a new formulation based on an empirical method. Furthermore, the optimal binder percentage was of 20% resin and a mixture of 52% dune sand and 48% quarry sand according to the Abrams method. To achieve our objective, five rates (from 2% to 10%) of brick powder, marble powder and silica fume were examined. Afterwards, its mechanical characteristics were evaluated via a three-point flexural with compressive resistance. The findings indicated that the addition of brick, marble and silica fume to polymer concrete increases the flexural strength with 21.84%, 12.76% and 9.07%, respectively.

Concerning the compressive strength, the best resistance is that of polymer concretes based on brick powder, and this economic formulation of polymer concrete serves the optimal cost/resistance ratio criteria. It allows an improvement in the mechanical resistance of concrete are obtained by adding brick powder that exceed that of the reference concrete.

In the past few decades, there has been several contribution concerning the subject of the reduction of the binder quantity in polymer concretes and adding the industrial and household wastes. However, previous studies revolving around the same area disregarded the effect of the brick powder, which appears scientifically of great importance for enriching the literature.

This paper aims to explore recent advances in drift compensation algorithms for Electronic Nose (E-nose) technology and addresses sensor drift challenges through offline, online and neural network-based strategies. It offers a comprehensive review and covers causes of drift, compensation methods and future directions. This synthesis provides insights for enhancing the reliability and effectiveness of E-nose systems in drift issues.

The article adopts a comprehensive approach and systematically explores the causes of sensor drift in E-nose systems and proposes various compensation strategies. It covers both offline and online compensation methods, as well as neural network-based approaches, and provides a holistic view of the available techniques.

The article provides a comprehensive overview of drift compensation algorithms for E-nose technology and consolidates recent research insights. It addresses challenges like sensor calibration and algorithm complexity, while discussing future directions. Readers gain an understanding of the current state-of-the-art and emerging trends in electronic olfaction.

This article presents a comprehensive review of the latest advancements in drift compensation algorithms for electronic nose technology and covers the causes of drift, offline drift compensation algorithms, online drift compensation algorithms and neural network drift compensation algorithms. The article also summarizes and discusses the current challenges and future directions of drift compensation algorithms in electronic nose systems.

This paper looks at how stakeholders co-create value at mega-events from a service ecosystem perspective. Despite the growing interest, little is known about how value is co-created through such initiatives for individual stakeholders and the community.

Drawing on institutional and stakeholder theory, the study focuses on Cortina 2021, the World Ski Championships held in Italy in February 2021. It investigates how multiple actors co-create value within a service ecosystem through qualitative interviews with key stakeholders combined with the analysis of official documents and reports.

The research established that key stakeholders were willing to get involved with Cortina 2021 if they recognised the value which could be co-created. Such an ecosystem requires a focal organisation with a clear regulative and normative framework and a common cultural basis. The latter helped resilience in the extraordinary circumstances of Cortina 2021 and safeguarded long-term impacts, even though the expected short-term ones were compromised.

From a managerial point of view, the evidence from Cortina 2021 shows how a clear strategy with well-defined stakeholder engagement mechanisms can facilitate value co-creation in service ecosystems. Moreover, when regulative and normative elements are blurred because of an extraordinary circumstance, resource integration and value creation processes need to be entrusted to those cultural elements that characterise an ecosystem.

The study takes an ecosystemic approach to mega-events to explore value creation for the whole community at the macro level, not only at the individual or organisational level, even during a crisis, which greatly impaired the preparation and running of the event.

The study aims to analyze research trends and hotspots in the field of food and nutrition literacy to inform evidence-based policymaking, and promote the health and well-being of the general population.

The Scopus database was used to retrieve relevant research articles using specific keywords related to food or nutritional literacy.

The analysis included 341 research articles, predominantly authored by scholars from the USA. Growth pattern of publications indicated recent evolution of the food and nutrition literacy concepts. The research hotspots identified included the development of tools to assess literacy, assessing food and nutritional literacy competencies among school children and adolescents and finally, cross-sectional survey studies on various international cultures to assess food and nutritional literacy. The top cited articles in the field focused on the operational definition and difference between nutrition literacy and food literacy.

The findings underscore the need for comparative studies across countries, and advocacy for policy change to advance food and nutrition literacy among school students and vulnerable populations.

Policymakers, public health officials and practitioners can use the research findings to inform the development of evidence-based policy frameworks and interventions aimed at addressing the gaps in food and nutrition literacy.

By promoting and advocating for policy reforms, and addressing gaps in food and nutrition literacy, the study contributes to fostering global future public health.

The study provides insights into the evolving research landscape on food and nutrition literacy, emphasizing the growing scholarly interest in understanding the concept and its public health impact.

Adhesive bonding is critical to the effectiveness and structural integrity of 3D printed components. The purpose of this study is to investigate the effect of joint configuration on failure loads to improve the design and performance of single lap joints (SLJs) in 3D printed parts.

In this study, adherends were fabricated using material extrusion 3D printing technology with polyethylene terephthalate glycol (PETG). A toughened methacrylate adhesive was chosen to bond the SLJs after adherend printing. In this study, response surface methodology (RSM) was used to examine the effect of the independent variables of failure load, manufacturing time and mass on the dependent variable of joint configuration; adherend thickness (3.2, 4.0, 4.8, 5.6, 6.4, and 7.2 mm) and overlap lengths (12.7, 25.4, 38.1, and 50.8 mm) of 3D printed PETG SLJs.

The strength of the joints improved significantly with the increase in overlap length and adherend thickness, although the relationship was not linear. The maximum failure load occurred with a thickness of 7.2 mm and an overlap of 50.8 mm, whilst the minimum failure load was determined with a thickness of 3.2 mm and an overlap of 12.7 mm. The RSM findings show that the optimum failure load was achieved with an adherend thickness of 3.6 mm and an overlap length of 37.9 mm for SLJ.

This study provides insight into the optimum failure load for 3D printed SLJs, reducing SLJ production time and mass, producing lightweight structures due to the nature of 3D printing, and increasing the use of these parts in load-bearing applications.

The pedestrian dead reckoning (PDR) based on smartphones has been widely applied in continuous indoor positioning. However, when the position of the mobile phone and the walking patterns of the pedestrian are mixed, traditional PDR tends to become confused and thus degrade performance. To address this issue, this paper aims to propose an improved PDR scheme by focusing on gait pattern recognition and the impact of short-period but negative transitions on tracking.

The overall solution uses the inertial sensor integrated within the phone for positioning. A binary classifier-based change point detection algorithm is used to identify the transition points in pedestrian gait. Additionally, to enhance the accuracy of gait recognition, this paper presents a combined CNN-attention-based bi-directional long short-term memory(ABiLSTM) model, integrating convolutional neural networks (CNN), bi-directional long short-term memory (Bi-LSTM) and an attention mechanism, to recognize the current gait pattern. The outcomes of this gait pattern recognition are then applied to PDR. Based on distinct gait patterns, corresponding PDR strategies are devised to enable continuous tracking and positioning of pedestrians.

Through experimental verification, the CNN-ABiLSTM model achieves a gait recognition accuracy of 99.52% on the self-constructed data set. The pedestrian navigation estimation method proposed in this paper, which is based on gait recognition assistance, demonstrates a 32.56% improvement in accuracy over traditional positioning algorithms in multi-gait scenarios.

The improved PDR scheme algorithm significantly enhances the robustness and smoothness of pedestrian tracking, particularly during multiple gait transitions. This, in turn, provides strong support for the utilization of low-cost inertial sensors integrated within mobile phones for indoor positioning applications.