Search results

This study is a pilot study exploring the usefulness and ease of use of a prototype VR PetCPR system and discusses the possibility of using it to facilitate pet healthcare skills acquisition. The designed VR PetCPR training system aims to provide pet healthcare professionals with an inexpensive, accessible and reliable CPR training tool and refine their skills in a controlled and simulated environment.

The study was conducted in a one-day workshop. The workshop consisted of the morning section (Section A) and the afternoon section (Section B). Section A was the knowledge acquisition stage. Section B is the VR PetCPR stage. Trainees were then given 30 min to experience the VR PetCPR set. When trainees were ready, they were required to complete two trials of dog CPR practice. After the practice, trainees completed the questionnaire and reported their attitudes toward VR PetCPR practice.

Overall, trainees held positive attitudes toward the effectiveness and usefulness of the VR PetCPR. After practicing skills via VR CPR, over half of the trainees responded that the system is effective in helping them understand the essential knowledge (e.g. operation status, operation positions, etc.) of performing CPR skills on a 30-pound dog. A significantly positive attitude was reported on trainees’ perceptions toward the ease of use of practicing their chest compression skills with the PetCPR. The positive attitudes significantly outnumbered the negative attitudes on explicit instruction and guidance, accessibility, convenience in practice and straightforward interface.

From data collected from 16 animal hospitals in the United States, Europe and Australia with 709 cases, 147 dogs (28%) and 58 cats (30%) temporarily attained ROSC during CPR, and 14 dogs (3%) and four cats (2%) survived to hospital discharge. Training veterinary CPR techniques and implementing RECOVER guidelines still have a long way to go. However, recent virtual reality simulations for CPR training were mainly designed for human patients CPR (Issleib et al., 2021; Liu et al., 2022; Almousa et al., 2019; Wong et al., 2018). The VR PetCPR remains a missing puzzle in the current VR training designs.

The main objectives of this paper are to develop a novel perturbation method (PM) to solve the complex-orthogonal eigenvalue problem and further propose an exact complex mode superposition method (CMSM) for the non-proportionally rate-independent damped systems.

A novel PM is developed to solve the eigenvalue problem. The PM reduced the N-order generalized complex eigenvalue problem into a set of n algebraic equations by the perturbation theory. The convergence and accuracy of the PM are demonstrated by several numerical examples. Further, an exact CMSM is presented. The influences of the imaginary part response of the modal coordinate and the off-diagonal elements of the damping matrix as well as the modal truncation on the solution by CMSM are discussed to illustrate the effectiveness of the developed CMSM.

The eigenvalues obtained by PM would converge to the exact ones with the increase of the modal numbers. For seismic response, the influence of the imaginary part solutions of the modal coordinate would increase with the increase of the coupling factor. The contribution of higher modes to acceleration response is greater than that to the displacement. The cumulative mode contribution coefficient of acceleration is developed to estimate the numbers of the complex modes for the acceleration seismic response by the CMSM.

1. An eigenvalue perturbation method for a rate-independent damped system is proposed. 2. PM is carried out by the real mode and accomplishes the reduction of the matrix. 3. CMSM is established for rate-independent damped systems. 4. CMSM considers the effect of imaginary part solutions of the modal coordinate. 5. Modal truncation index is developed to estimate the complex mode number for CMSM.

Despite the growing attention being paid to the role of uncertainty in the competitive business environment, few studies have considered uncertainty as an antecedent factor and explored its direct impact on accelerating a firm’s innovation speed. This study develops a conceptual framework that examines the impacts of technological uncertainty and market uncertainty on innovation speed, building on complex adaptive theory. Furthermore, it is important to note that the internal resources of a firm and its external environment are not separate entities. In this study, we investigate the moderating role of a firm's internal and external resource ability (financial constraints level and organizational slack level) in the relationship between environmental uncertainty and innovation speed.

Our data sample is the panel data of China's A-share listed companies. The data year span is from 2000 to 2018. We use a hierarchical regression analysis model.

Our results reveal that both technology uncertainty and market uncertainty can promote innovation speed. Still, a firm’s organizational slack positively moderates the relationship between technology uncertainty and innovation speed, and financial constraints negatively moderate the relationship between demand uncertainty and innovation speed.

Our research contributes to the existing literature on uncertainty and extends its research perspective by no longer taking uncertainty as an environmental factor but exploring its direct impact. Still, our research focuses on innovation speed and discusses the impact of environmental uncertainty (including technology uncertainty and demand uncertainty) on firms’ innovation speed, expanding the limitations of previous research, which usually holds a relatively general perspective on innovation problems.

This research uses the evolutionary game model theory to explore how to make decisions to maximize their own interests in the process of project claims from the perspective of small and medium-sized contractors in the construction industry.

This study defines the discount factor in the claim process based on the characteristics of construction claims and provides a specific calculation method. The paper analyzes the matching degree between the evolutionary game model and the process of construction claims. Further, the discount factor is introduced to construct an evolutionary game model of engineering claims with the goal of maximizing the contractor’s benefits.

The results of this study show that in the situation (C*d1-nC1*d1>0, v2-v1-g>0) and (C*d1-nC1*d1>0, v2-v1-g<0), the contractor claim decision-making strategy is a truthful claim, while in the situation (C*d1-nC1*d1<0, v2-v1-g>0) and (C*d1-nC1*d1<0, v2-v1-g<0), the contractor claim decision-making strategy is a high-price claim. The discount factor will affect the decision-making rate. It is noted that the fines and the explicit costs received during the contractor’s high-priced claim process exhibit a positive correlation with the rate of truthful claim decision-making by contractors. Meanwhile, the final revenue of high-priced claims by contractors shows a positive correlation with the rate of high-priced claim decision-making by the sensitivity analysis.

The author simulates the process of solving the actual claim problem through the evolutionary game model in engineering claims. It is hoped that researchers will collect empirical cases and compare the actual case solutions with the model solutions to further revise the model in future studies, an evolutionary game model of engineering claim decision-making with interference factors can be constructed to analyze the evolutionary stability. Secondly, the single factor sensitivity analysis of individual parameters is carried out in this paper, and the influence of multiple factors on claim decisions can be further analyzed in the later research.

The analysis of the claim process based on the evolutionary game model is conducive to the contractor’s rapid claim decision-making. The introduction of the discount factor to analyze the claim process is more conducive to the accuracy of the contractor’s claim decision.

The proposed model provides a supplement to the existing studies on dynamic construction claim decision-making. The claim decision is conducive to controling cost for the contractor, improving the contractor’s management level and developing a healthy construction market.

This paper investigates the spillover effect of firms’ social media engagement with investors on consumption market performance and examines the impact of balanced/imbalanced social media stakeholder engagement strategies on firms’ consumption market performance.

The study employs multi-source secondary data covering 3,856 quarterly observations of 188 firms in the Chinese retail industry over six years (2015–2020). Polynomial regression analysis and response surface methodology are used to test the hypotheses.

The study reveals that firms’ social media engagement with investors has a positive spillover effect on consumption market performance. Additionally, the authors find that a balanced social media engagement strategy, which allocates resources evenly between consumers and investors, is more likely to optimize firm performance than an imbalanced strategy.

The research reveals cross-stakeholder spillover effects of social media engagement, introduces balanced/imbalanced engagement strategy concepts and extends the balanced marketing perspective to the social media context, providing guidance for firms to optimize their social media strategies.

Ball grid array (BGA) package is prone to failure issues in a thermal vibration-coupled environment, such as deformation and fracture of solder joints. To predict the minimum equivalent stress of solder joints more accurately and optimize the solder joint structure, this paper aims to compare the machine learning method with response surface methodology (RSM).

This paper introduced a machine learning algorithm using Grey Wolf Optimization (GWO) Support Vector Regression (SVR) to optimize solder joint parameters. The solder joint height, spacing, solder pad diameter and thickness were the design variables, and minimizing the equivalent stress of solder joint was the optimization objective. The three dimensional finite element model of the printed circuit board assembly was verified by a modal experiment, and simulations were conducted for 25 groups of models with different parameter combinations. The simulation results were employed to train GWO-SVR to build a mathematical model and were analyzed using RSM to obtain a regression equation. Finally, GWO optimized these two methods.

The results show that the optimization results of GWO-SVR are closer to the simulation results than those of RSM. The minimum equivalent stress is decreased by 8.528% that of the original solution.

This study demonstrates that GWO-SVR is more precise and effective than RSM in optimizing the design of solder joints.

This study illustrates the conceptual framework that expands the knowledge of the fundamental components that describe how AI-driven servant leadership (SEL) influences the job resources (JR), work engagement (WE) and job performance (JP) of tourism and hospitality employees.

The empirical study was conducted on a sample of 953 international tourism and hospitality employees who were selected via a purposive and snowball sampling approach in a cross-sectional survey. The analysis was performed using a partial least square-structural equation modeling.

The results of this study confirmed the positive impact of AI-driven SEL on employee JR with the boundary conditions of AI-driven SEL.

This study finding assists tourism and hospitality practitioners in understanding that in the near future, AI will have a major effect on the nature of work, including the impact on leadership styles. Hence, AI-driven SEL holds both positive (through direct impact on JR) and negative (via boundary conditions) impacts on employees’ JP and ultimately organizational success. Accordingly, managers should employ AI-driven SEL to increase employees’ JR, and once employees achieve high WE, they should constrict AI-driven SEL boundary conditions and their influence between JR and WE and WE and JP.

This study offers a novel and original conceptual model that advances AI-driven social theory, SEL theory and job demands-resources (JD-R) theory by synthesizing, applying and generalizing gained knowledge in a methodical way.

This study aims to investigate the relationship between chief executive officer (CEO) power and the level of tax avoidance of Tunisian listed companies. It also examines the moderating role of institutional ownership in this association.

The sample comprises 306 firm-year observations of companies listed on the Tunis Stock Exchange during the 2013–2020 period.

The results indicate that CEO power reduces tax avoidance levels. Moreover, the relationship between CEO power and tax avoidance is more pronounced in the presence of institutional ownership, suggesting that CEOs act less opportunistically when monitored by institutional investors, which results in a reduction in tax avoidance.

This study suggests that CEO power and institutional shareholders’ influence are important factors in determining firms’ avoidance behavior. This study has significant implications for shareholders and regulatory bodies. Indeed, shareholders apprehend the impact of appointing a powerful CEO on tax avoidance practices. This study may also provide regulators with new insights into the influence of CEO power dimensions and institutional ownership on tax aggressiveness.

This study fills the gap in the accounting literature by investigating how CEO power may impact tax avoidance behavior and provides empirical evidence on the moderating impact of institutional ownership on this relationship in an emerging economy context characterized by a weakly protected investor setting.

This review study aims to explore the prevalent paradoxes in digital transformation (DTN) of business and provide insights on how businesses can effectively navigate them.

The study conducts a systematic literature review, utilizing findings from a bibliometric analysis. A sample of 229 articles published in top-tier journals, retrieved from the Scopus database, is reviewed to identify nine clusters representing different sectors and paradoxes in DTN.

The review identifies and summarizes studies addressing the paradoxes that arise during DTN in various sectors. Scholars have analyzed the growing need for digital innovations and the benefits they bring, but this study aggregates high-quality research to address the gap in understanding prevalent paradoxes.

This study provides valuable insights into the paradoxes of DTN and offers guidance to businesses on effectively managing these challenges. It contributes to the existing literature by consolidating and presenting key research findings in this domain.

This study examines the role of corporate governance on corporate tax avoidance from the developing country perspective of Malaysia.

A sample of 318 firm-year observations from 2016 to 2020 from the 100 largest listed companies in Malaysia was analysed using a fixed effects panel least squares regression model.

CEOs play a significant role in corporate tax avoidance in Malaysia. Specifically, they are motivated by money and power to engage in risky tax avoidance activity. It was also found that corporate governance mechanisms related to the board of directors have a limited effect on companies’ tax compliance issues.

This study’s findings can help regulators and policymakers understand the circumstances leading to increased tax aggressiveness as well as the limitations of certain governance mechanisms in curbing tax avoidance activity within companies. The findings can also assist shareholders and investors in formulating internal policies to create better alignment of their interests with those of management. The unique emerging economy evidence and insights from this study advance knowledge and can inspire fellow researchers in their future studies.

This study differs from most prior studies by examining the governance and tax issue from a developing country perspective, that of Malaysia. Developments in the country’s corporate governance framework and tax landscape in recent years make it relevant and interesting to investigate the issue in this emerging economy. Offering unique empirical evidence and insights from an emerging economy viewpoint, and with findings that may be generalised to other emerging economies sharing similar market traits (particularly ASEAN nations), this study enriches and extends the existing literature.