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Social media's role in engaging participants in sports events, particularly during the pandemic, is acknowledged. However, previous studies often utilized sports events for diverse objectives but overlooked brand equity's influence on sports event development. And very limited research explores social media's impact on brand equity in esports events, despite its significance. Therefore, this study aims to explore how social media affects esports event brand equity and participants' satisfaction and engagement with social media through brand equity's influence.

The study focused on League of Legends World Championships (LOLWC) participants, who completed a self-judged questionnaire online. The questionnaire included demographic details and latent constructs. Data analysis involved two steps: exploratory factor analysis (EFA) to assess measurement scale validity and structural equation modeling (SEM) to study relationships between traits.

The results reveal that, within the esports event context, controlled communication exerts a meaningful and dual impact – both directly and indirectly – on the fundamental components of brand equity. This, in turn, serves as a catalyst for increasing participant contentment and their posting intention.

This study applies brand equity theories to the esports domain, exploring participant-based brand equity concepts, user behavior and the influence of social media communication on event branding and engagement. It also recommends strategies for event improvement, emphasizes controlled communication for brand equity and highlights marketing's role in brand awareness, association and participant satisfaction. Additionally, it suggests government regulation to address cyber violence during esports events.

This study aims to adopt the microfoundation perspective to investigate undesirable knowledge rejection by individuals in organizations in the context of counterproductive knowledge behavior (CKB). The paper advances a conceptual framework of the conditions of knowledge rejection by individuals and their respective knowledge rejection behavior types.

This study reviews the limited literature on knowledge rejection and outline a set of antecedents leading to rejecting knowledge as well as a set of different types of knowledge rejection behaviors. This study reviews and synthesizes articles on knowledge rejection from a microfoundation perspective.

The proposed conceptual framework specifies four particular conditions for knowledge rejection and outlines four respective knowledge rejection behavior types resulting from these conditions. Recipients’ lack of capacity leads to ineptitude, lack of motivation leads to dismissal of knowledge, lack of alignment with the source leads to disruption and doubts about the validity of external knowledge lead to resistance. The authors treat these behaviors as variants of CKB, as they can hinder the productive use of knowledge resources in the organization.

Further investigation of both knowledge rejection causes and the resulting knowledge rejection behaviors will ensure a more thorough grasp of the relationships between them, both in terms of the inherent nature of these relationships and their dynamics that would likely be context-sensitive. Although this study focuses only on the individual level, future studies can conduct multi-level analyses of undesirable knowledge rejection, including team and organizational levels.

Practitioners can use the framework to identify, diagnose and manage knowledge rejection more meaningfully, accurately and purposefully in their organizations. This study offers valuable insights for managers facing undesirable knowledge rejection, and provides recommendations on how to address this behavior, improves the constructive use of knowledge resources and the effectiveness of knowledge processes in their organizations. Managers should be aware of undesirable knowledge rejection, its potential cost or concealed cost to their organizations and develop strategies to reduce or prevent it.

The paper contributes toward understanding the relatively neglected topic of knowledge rejection in the knowledge management field and offers a new way of conceptualizing the phenomenon. It proposes that there are two types of knowledge rejection – undesirable and desirable – and advances a more precise and up-to-date definition of undesirable knowledge rejection. Responding to calls for more research on CKBs, the study examines a hitherto unresearched behavior of knowledge rejection and provides a foundation for further study in this area.

From the perspective of local government tax administration, the impact of geographic dispersion on the corporate tax burden is investigated in this paper.

Using unbalanced panel data with a sample of listed companies from 2003 to 2020 in China, this paper focuses on the effect of geographic dispersion on corporate tax burden and the mechanisms.

It is found that corporate tax burden is positively related to geographic dispersion. It is also found that geographic dispersion affects the corporate tax burden by increasing the effort of local government tax administration. In addition, the relation between geographic dispersion and corporate tax burden is more pronounced for local SOEs prior to the implementation of Golden Tax Project III and in cases where local governments face stronger financial pressure to obtain revenue.

This study has important implications for the promotion of the coordinated development of the regional economy, as well as the legalization, modernization and informatization of tax administration.

The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.

The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.

The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.

The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

This study provides new insights into antecedents and outcomes of reverse logistics practices by examining green customer salience as the driver of reverse logistics practices and examining environmental performance and green firm reputation as the outcomes of reverse logistics practices.

A research model examining the proposed relationships was developed and tested using data from beverage manufacturers in Ghana. The model was analysed using partial least squares structural equation modelling.

This study confirmed that green customer salience drives reverse logistics practices. It was also revealed that reverse logistics directly enhances environmental performance, but not green firm reputation. Additionally, the effect of reverse logistics on green firm reputation was fully mediated through environmental performance.

To the best of the authors’ knowledge, no previous studies have empirically examined the relationship between green customer salience, reverse logistics, environmental performance and green firm reputation.

A novel method has been proposed to reduce the false alarm rate of arrhythmia patients regarding life-threatening conditions in the intensive care unit. In this purpose, the atrial blood pressure, photoplethysmogram (PLETH), electrocardiogram (ECG) and respiratory (RESP) signals are considered as input signals.

Three machine learning approaches feed-forward artificial neural network (ANN), ensemble learning method and k-nearest neighbors searching methods are used to detect the false alarm. The proposed method has been implemented using Arduino and MATLAB/SIMULINK for real-time ICU-arrhythmia patients' monitoring data.

The proposed method detects the false alarm with an accuracy of 99.4 per cent during asystole, 100 per cent during ventricular flutter, 98.5 per cent during ventricular tachycardia, 99.6 per cent during bradycardia and 100 per cent during tachycardia. The proposed framework is adaptive in many scenarios, easy to implement, computationally friendly and highly accurate and robust with overfitting issue.

As ECG signals consisting with PQRST wave, any deviation from the normal pattern may signify some alarming conditions. These deviations can be utilized as input to classifiers for the detection of false alarms; hence, there is no need for other feature extraction techniques. Feed-forward ANN with the Lavenberg–Marquardt algorithm has shown higher rate of convergence than other neural network algorithms which helps provide better accuracy with no overfitting.

The purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).

(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.

Results indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.

The findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

The purpose of this study is to reveal the effect of nano-Al₂O₃ particle addition on the nucleation/growth kinetics, microhardness, wear resistance and corrosion resistance of Co–P–xAl₂O₃ nanocomposite plating.

The kinetics and properties of Co–P–xAl₂O₃ nanocomposite plating prepared by electroplating were investigated by electrochemical measurements, scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Vickers microhardness measurement, SRV5 friction and wear tester and atomic force microscopy.

A 12 g/L nano-Al₂O₃ addition in the plating solution can transform the nucleation/growth kinetics of the plating from the 3D progressive model to the 3D instantaneous model. The microhardness of the plating increased with the increase of nano-Al₂O₃ content in plating. The wear resistance of the plating did not adhere strictly to Archard’s law. An even and denser corrosion product film was generated due to the finer grains, with a high corrosion resistance.

The effect of different nano-Al₂O₃ addition on the nucleation/growth kinetics and properties of Co–P–xAl₂O₃ nanocomposite plating was investigated, and an anticorrosion mechanism of Co–P–xAl₂O₃ nanocomposite plating was proposed.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.

The purpose of this paper is to present current state of understanding on jet electrodeposition manufacturing; to compare various experimental parameters and their implication on as deposited features; and to understand the characteristics of jet electrodeposition deposition defects and its preventive procedures through available research articles.

A systematic review has been done based on available research articles focused on jet electrodeposition and its characteristics. The review begins with a brief introduction to micro-electrodeposition and high-speed selective jet electrodeposition (HSSJED). The research and developments on how jet electrochemical manufacturing are clustered with conventional micro-electrodeposition and their developments. Furthermore, this study converges on comparative analysis on HSSJED and recent research trends in high-speed jet electrodeposition of metals, their alloys and composites and presents potential perspectives for the future research direction in the final section.

Edge defect, optimum nozzle height and controlled deposition remain major challenges in electrochemical manufacturing. On-situ deposition can be used as initial structural material for micro and nanoelectronic devices. Integration of ultrasonic, laser and acoustic source to jet electrochemical manufacturing are current trends that are promising enhanced homogeneity, controlled density and porosity with high precision manufacturing.

This paper discusses the key issue associated to high-speed jet electrodeposition process. Emphasis has been given to various electrochemical parameters and their effect on deposition. Pros and cons of variations in electrochemical parameters have been studied by comparing the available reports on experimental investigations. Defects and their preventive measures have also been discussed. This review presented a summary of past achievements and recent advancements in the field of jet electrochemical manufacturing.