Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach.

The COVID-19 pandemic had brought changes to individuals, especially in consumer behavior. As the government of different countries has been implementing safety protocols to mitigate the spread of the virus, people became apprehensive about traveling and going out. This paved way for the emergence of third-party logistics (3PL). Statistics have proven the rapid escalation regarding the use of 3PL in various countries. This study utilized Artificial Neural Network and Random Forest Classifier to validate and justify the factors that affect consumer intention in selecting a 3PL service provider during the COVID-19 pandemic integrating the Service Quality Dimensions and Pro-Environmental Theory of Planned Behavior. The findings of this study revealed that attitude is the most significant factor that affects the consumers' behavioral intention. Other factors such as customer satisfaction, customer perceived value, perceived environmental concern, assurance, responsiveness, empathy, reliability, tangibility, perceived behavioral control, subjective norm, and perceived authority support, are all contributing factors that affect behavioral intention. Machine learning algorithms, specifically ANN and RFC, resulted to be reliable in predicting factors as they obtained accuracy rates of 98.56% and 93%. Results presented that consumers' attitude, satisfaction, perceived value, assurance by the 3PL, and perceived environmental concerns were highly influential in choosing a 3PL package carrier. It was seen that people would be encouraged to use 3PL service providers if they demonstrate availability and environmental concerns in catering to the customers' needs. Subsequently, 3PL providers must assure safety and convenience before, during, and after providing the service to ensure continuous patronage of consumers. This is considered to be the first study that utilized a machine learning ensemble to measure behavioral intention for the logistic sector. The framework, analysis tools, and findings of this study could be extended and applied among other behavioral intentions regarding transportation worldwide. Managerial insights among service providers are discussed.

Factors influencing job satisfaction among dentists during the new normal of the COVID-19 pandemic in Indonesia: A structural equation modeling approach.

BACKGROUND: Dentistry is one of the highest risk occupations that face COVID-19, especially in countries that are severely affected by the pandemic, such as Indonesia. OBJECTIVE: The purpose of the study was to determine factors influencing job satisfaction among dentists during the new normal of COVID-19 pandemic in Indonesia by utilizing the Structural Equation Modeling (SEM) approach. METHODS: A total of 310 Indonesian dentists voluntary completed an online questionnaire, which contained 58 questions. Several latent variables such as perceived severity of COVID-19, staff cooperation and management commitment, personal protective equipment, job stress, working hours, income, and overall job satisfaction were analyzed simultaneously. RESULTS: SEM revealed perceived severity of COVID-19 had significant effects on job stress (ß:0.394, p = 0.025) and the utilization of personal protective equipment (ß:0.757, p = 0.001). Subsequently, job stress (ß:-0.286, p = 0.001), working hours (ß:0.278, p = 0.018), income (ß:0.273, p = 0.003), personal protective equipment (ß:0.145, p = 0.038), and staff cooperation & management commitment (ß:0.091, p = 0.002) were found to have significant effects on overall job satisfaction. In addition, management & staff cooperation was found to have a significant association with job stress reduction (ß:-0.319, p = 0.003) which subsequently led to higher satisfaction. CONCLUSIONS: The current study is one of the first that analyzed job satisfaction among dentists in Indonesia during the global COVID-19 pandemic. The integrated latent variables can be applied and extended to evaluate job satisfaction among dentists during the COVID-19 pandemic in other countries. Finally, this study contributed as a theoretical foundation for policymakers to enhance the job satisfaction of dentists during the COVID-19 pandemic.

The Evaluation of Preference and Perceived Quality of Health Communication Icons Associated with COVID-19 Prevention Measures.

Icons have been widely utilized to describe and promote COVID-19 prevention measures. The purpose of this study was to analyze the preference and subjective design features of 133 existing icons associated with COVID-19 prevention measures published by the health and medical organizations of different countries. The 133 icons represent nineteen different function names, such as "Wash Hands" and "Wear Face Mask". A total of 57 participants were recruited to perform two different tests: ranking test and subjective rating test. The ranking test was conducted to elicit the preference ranking of seven icon designs representing each function name. It was followed by a subjective rating test using 13 semantic scales on the two most preferred icons to analyze their perceived quality. Spearmen correlation was applied to derive the possible correlations between users' rankings and the semantic scales, and Friedman's test was also performed to determine the true difference between ranking in terms of each semantic scale to provide a fully meaningful interpretation of the data. Generally, findings from the current study showed that the image presented in the icon is the key point that affects the icons' perceived quality. Interestingly, Spearman's correlation analysis between preference ranking and semantic scales showed that vague-clear, weak-strong, incompatible-compatible, and ineffective-effective were the four strongest semantic scales that highly correlated with the preference ranking. Considering the significant relationships between the semantic distances and the functions, images depicted in an icon should be realistic and as close as possible to its respected function to cater to users' preferences. In addition, the results of Spearman's correlation and Friedman's test also inferred that compatibility and clarity of icon elements are the main factors determining a particular icon's preferability. This study is the first comprehensive study to evaluate the icons associated with the COVID-19 prevention measures. The findings of this study can be utilized as the basis for redesigning icons, particularly for icons related to COVID-19 prevention measures. Furthermore, the approach can also be applied and extended for evaluating other medical icons.

Determining Factors Affecting the Acceptance of Medical Education eLearning Platforms during the COVID-19 Pandemic in the Philippines: UTAUT2 Approach.

eLearning has been the medium of delivery of medical educational institutions to address the scarcity of medical professionals during the COVID-19 pandemic. In this study, the Unified Theory of Acceptance and Use of Technology (UTAUT2) was extended to determine the factors affecting the acceptance of eLearning platforms to medical education in the Philippines during the COVID-19 pandemic. A total of 360 medical students voluntary participated and answered an online questionnaire that consisted of 40 questions. Structural Equation Modeling (SEM) indicated that performance expectancy was found to have the highest effect on behavioral intention, which was followed by learning value and instructor characteristics. A high behavioral intention was found to affect the actual use of eLearning platforms. Interestingly, social influence and habit were found not to be significant to behavioral intentions. This study is the first study that has explored the acceptance of eLearning platforms among medical students in the Philippines during the COVID-19 pandemic. The findings can be a theoretical guideline of the Commission on Higher Education of the Philippines for eLearning platforms. Finally, the framework would be very valuable for enhancing the open innovation in eLearning platforms in medical fields worldwide.