Indonesian martial artists' preferences in martial arts schools: Sustaining business competitiveness through conjoint analysis

The popularity of martial arts in the present times has become apparent, therefore, it is necessary to explore martial artists' preferences and the schools' competitiveness. The purpose of this study was to assess martial artists' preferences concerning the services offered by martial arts schools. Conjoint analysis was utilized to analyze the responses of fifty-five (55) martial artists based on the seven (7) martial arts schools' attributes. The results showed that the type of martial arts was found to be the most important attribute (30.449%) followed by distance (27.970%), price range (22.706%), social environment (11.097%), class preference (5.080%), goal (1.562%), and schedule (1.135%). Furthermore, Muay Thai or Kickboxing was the most preferred martial art, Mixed Martial Arts (MMA) was the second priority, next was Taekwondo, then Karate, and finally Boxing. In addition, the martial artists' preferred distance was less than 8 km, and a monthly training cost of 150,000 to 450,000 IDR (10 to 20 USD). Martial artists liked attending open classes, treated martial arts as a hobby, and favored attending classes once or twice weekly. With the lack of conjoint-related studies in the martial arts industry, the findings contributed to academicians and addressed issues of inadequate studies. Most importantly, the researchers presented managerial implications to leverage marketing techniques and develop the business operations of martial arts schools.

Determination of loyalty among high school students to retain in the same university for higher education: An integration of Self-Determination Theory and Extended Theory of Planned Behavior

Student loyalty generally refers to the formed bond between the student and a university. This relationship between a university and its students proves essential in a university's success in the competitive field of higher education institutions. The aim of this study was to determine the factors affecting students' loyalty among high school students to pursue their college or higher education in their current universities by utilizing Self-Determination Theory and Extended Theory of Planned Behavior. A total of 1224 high school students voluntarily participated and answered an online questionnaire that consist of 80 questions. Structural Equation Modeling (SEM) showed that competency had the highest direct significant effect on perceived behavioral control which subsequently led to student satisfaction, followed by relatedness and empathy. In addition, student satisfaction had the highest direct effect significant effect on student loyalty, followed by university image and effectiveness. Interestingly, university ranking, programs offered, and kinship patronage also had significant indirect effects on student loyalty. This new framework may be a theoretical foundation for universities to enhance student loyalty and student recruitment. Considering students as customers, the satisfaction of students would result in an increase in the application which would present an increase in population, sales, marketability, and profitability of the university.

Determinants of continuous visiting behavior to Palawan, Philippines: Integrating Uncertainty Reduction Theory and Expectation Confirmation Theory

Palawan is a globally known island located in the Philippines. It has received several recognitions from a variety of international tourism organizations. The study aims to identify the factors affecting continuous visiting behavior to Palawan's travel accommodations. The study incorporated covariance-based structural equation modeling (CB-SEM) to apply ideologies of Uncertainty Reduction Theory (URT) and Expectation Confirmation Theory (ECT). 712 valid respondents answered an online questionnaire that was distributed to several social media platforms. Structural Equation Modeling (SEM) identified that interactive uncertainty significantly influenced perceived performance compared to passive uncertainty. Both the physical environment and attitude of employees significantly produced an impact on service experience and price acceptance. However, the physical environment negatively influenced price acceptance. Meanwhile, the attitude of employees was the sole exogenous variable that influenced price acceptance. Food and beverage didn't contribute a significant influence on service experience and price acceptance. Additionally, perceived performance and service experience contributed to positive confirmation. It was also revealed that confirmation was significant towards price acceptance, but was insignificant towards tourist satisfaction. Moreover, price acceptance significantly influenced tourist satisfaction. This study is the first comprehensive study that analyzed the visiting behavior in Palawan. Finally, integrating URT and ECT can be applied and extended, especially for analyzing the visiting behavior of different tourist destinations worldwide.

A machine learning ensemble approach to predicting factors affecting the intention and usage behavior towards online groceries applications in the Philippines

The emergence of e-commerce platforms, especially online grocery shopping, is heightened by the COVID-19 pandemic. Filipino consumers started to adapt online due to the strict quarantine implementations in the country. This study intended to predict and evaluate factors influencing the intention and usage behavior towards online groceries incorporating the integrated Protection Motivation Theory and an extended Unified Theory of Acceptance and Use of Technology applying machine learning ensemble. A total of 373 Filipino consumers of online groceries responded to the survey and evaluated factors under the integrated framework. Artificial Neural Network that is 96.63 % accurate with aligned with the result of the Random Forest Classifier (96 % accuracy with 0.00 standard deviation) having Perceived Benefits as the most significant factor followed by Perceived Vulnerability, Behavioral Intention, Performance Expectancy, and Perceived. These factors will lead to very high usage of online grocery applications. It was established that machine learning algorithms can be used in predicting consumer behavior. These findings may be applied and extended to serve as a framework for government agencies and grocers to market convenient and safe grocery shopping globally.

Factors Influencing Non-Fungible Tokens (NFT) Game Engagement during the COVID-19 pandemic: The Theory of Planned Behavior (TPB) and Hedonic Motivation System Adoption Model (HMSAM) Approach

The prominent form of Non-Fungible Token (NFT) is found in the gaming industry. NFT games received immense attention during the COVID-19 pandemic because of their play-to-earn model. NFT gamers can enjoy and increase their finances in their spare time. Hence, the researchers utilized Structural Equation Modeling (SEM) to investigate the intention and immersive behaviors of 1082 respondents. The modified framework from the Theory of Planned Behavior (TPB) and Hedonic Motivation System Adoption Model (HMSAM) underwent SEM tests. These theories and methods were used to analyze relationships among hypotheses and assess factors influencing NFT game engagement. The results showed that hedonic motivation produced positive and significant influences on perceived usefulness, curiosity, joy, attitude, subjective norms, and perceived behavioral control. Subjective norms significantly influenced perceived ease of use. In due course, perceived ease of use yielded positive and significant effects on perceived usefulness, joy, attitude, and perceived behavioral control. Moreover, perceived usefulness, curiosity, joy, attitude, and perceived behavioral control had significant positive effects on behavioral intention. In addition, perceived usefulness, curiosity, joy, and attitude significantly and positively affected immersion. Meanwhile, only four hypotheses were not supported by the study. These findings were translated into theoretical and managerial implications to contribute to the academe given the strong the change of behavior of users towards NFT games during the pandemic; gaming industry since they will be able to develop, improve and create a new ecosystem in the gaming space, and NFT stakeholders since they will benefit from the development that will influence this study.

Determination of factors affecting customer satisfaction towards "maynilad" water utility company: A structural equation modeling-deep learning neural network hybrid approach

The Maynilad Water Services Inc. (MWSI) is responsible for supplying water to the west zone of Metro Manila. The utility provides service to 17 cities and municipalities which frequently experience water interruptions and price hikes. This study aimed to identify the key factors affecting customer satisfaction toward MWSI by integrating the SERVQUAL dimensions and Expectation Confirmation Theory (ECT). An online questionnaire was disseminated to 725 MWSI customers using the snowball sampling method to obtain accurate data. Ten latent were analyzed using Structural Equation Modeling and Deep Learning Neural Network hybrid. It was found that Assurance, Tangibles, Empathy, Expectations, Confirmation, Performance, and Water consumption were all factors affecting MWSI customers' satisfaction. Results showed that having an affordable water service, providing accurate water bills, on-time completion of repairs and installations, intermittent water interruptions and professional employees contribute to the general satisfaction. MWSI officials may utilize this study's findings to assess further the quality of their services and design effective policies to improve. The employment of DLNN and SEM hybrid showed promising results when employed in human behavior. Thus, the results of this study would be beneficial when examining satisfaction to utilities and policies among service providers in different countries. Moreover, this study could be extended and applied among other customer and service-focused industries worldwide.

Consumer preference analysis on the attributes of samgyeopsal Korean cuisine and its market segmentation: Integrating conjoint analysis and K-means clustering

Samgyeopsal is a popular Korean grilled dish with increasing recognition in the Philippines as a result of the Hallyu. The aim of this study was to analyze the preferability of Samgyeopsal attributes which includes the main entree, cheese inclusion, cooking style, price, brand, and drinks using Conjoint Analysis and market segmentation using k-means clustering. A total of 1018 responses were collected online through social media platforms by utilizing a convenience sampling approach. The results showed that the main entrée (46.314%) was found to be the most important attribute, followed by cheese (33.087%), price (9.361%), drinks (6.603%), and style (3.349%). In addition, k-means clustering identified 3 different market segments: high-value, core, and low-value consumers. Furthermore, this study formulated a marketing strategy that focused on enhancing the choice of meat, cheese, and price based on these 3 market segments. This study has significant implications for enhancing Samgyeopsal chain businesses and helping entrepreneurs with consumer preference on Samgyeopsal attributes. Finally, conjoint analysis with k-means clustering can be utilized and extended for evaluating food preferences worldwide.

Determining factors affecting customer satisfaction of the national electric power company (MERALCO) during the COVID-19 pandemic in the Phillippines

This study aimed to determine factors affecting customer satisfaction of national electric power companies during the COVID-19 pandemic by integrating SERVQUAL and Expectation-Confirmation Theory approaches. A total of 529 participants voluntarily participated and answered an online questionnaire of 49 questions. Structural equation modeling indicated that Tangibility, Empathy, and Responsiveness were positively related to Service Quality which subsequently led to Customer Expectation, Energy Consumption, and Perceived Performance (PE). In addition, a higher PE was positively related to Confirmation, which eventually led to Customer Satisfaction. It was evident that integrating SERVQUAL and ECT could holistically measure customer satisfaction among electricity service providers.

The effects of communication, empathy, encouragement, growth, and rewards on employee performance: A structural equation modeling approach

BACKGROUND

Improving employee performance has been crucial in different organizations for it reflects the company's product and service quality.

OBJECTIVE

The purpose of this study was to determine the factors affecting employee performance in the engineering and technology department in the Philippines during the COVID-19 pandemic.

METHODS

The effects of these factors such as communication, empathy, encouragement, growth and rewards to employee performance were analyzed.

RESULTS

Structural equation modeling (SEM) revealed that among the five factors, the encouragement, growth, and rewards were found to have a significant effect on employee performance in the engineering and technology department. Surprisingly, communication and empathy were found to have no significant effect to employee performance.

CONCLUSIONS

This was the first study that investigated the factors affecting employee performance in the engineering and technology department in the Philippines during the COVID-19 pandemic. The results could serve as a guideline for the management under this type of department. The framework could also be helpful for sustaining the elevated performance of the employees in the engineering and technology department.

Evaluating factors influencing customers' intention to eat Korean cuisine "Samgyeopsal" in the Philippines: A structural equation model forest classifier approach

Samgyeopsal has become a widely popular cuisine in the Philippines since 2014. The rise of Samgyeopsal is evident worldwide as it is available in countries such as the United States, Northern, and Southern Asia. This study aimed to explore the intention to eat Samgyeopsal during the COVID-19 pandemic utilizing structural equation modeling and random forest classifier. With a total of 1014 responses collected online, the result showed that utilitarian and hedonic motivation, Korean influence, and attitude led to very high actual behavior in east Samgyeopsal in the Philippines. Moreover, subjective norm, perceived behavioral control, and intention led to significant results influencing intention to actual behavior. Lastly, the COVID-19 safety protocol showed the least significant result. This study is the first study that evaluated the intention of consumers to eat Samgyeopsal in the Philippines during the COVID-19 pandemic. The results of this study would be beneficial to Korean BBQ restaurateurs and the further development of their marketing strategies even in other countries. Finally, the model construct of this study can be extended and applied in evaluating the consumers' eating intention toward other varieties of food or cuisines worldwide.

The effects of biomechanical risk factors on musculoskeletal disorders among baggers in the supermarket industry

BACKGROUND

Baggers play a significant role in the customer service of supermarket stores.

OBJECTIVE

The purpose of this study was to determine the effects of biomechanical risk factors on musculoskeletal disorders (MSD) experienced by baggers in the supermarket industry.

METHODS

Forty baggers employed among five supermarket stores in the National Capital Region in the Philippines participated in the study. To examine the biomechanical risk factors of the baggers, this study used an observational approach as well as standard ergonomic tools like REBA and NIOSH. In addition, musculoskeletal discomfort was subjectively rated using the standardized Cornell Musculoskeletal Disorder Questionnaire at the end of the work shift. Furthermore, correlation and stepwise regression analysis were utilized to determine the association between biomechanical risk factors and MSD.

RESULTS

Approximately 76% of study participants reported work-related MSD. The highest prevalence was in the foot area, followed by upper back, shoulder, lower leg, lower back, neck, and upper arm. Pearson correlation analysis had found a significant association between MSD and biomechanical risk factors. The highest correlation was observed between MSD and postural risk index (R2 = 0.863, p < 0.001), followed by weight lifted (R2 = 0.836, p < 0.001), task duration (R2 = 0.816, p < 0.001), task frequency (R2 = 0.756, p < 0.001), and lifting index (R2 = 0.661, p < 0.001). Furthermore, stepwise regression analysis revealed that the postural risk index (REBA) had the highest coefficient value (β=16.99), indicating the strongest positive effect to MSD.

CONCLUSION

This present study revealed that grocery baggers are frequently exposed to risk factors such as awkward posture, lifting heavy loads, extended task durations, and prolonged postures during repetitive tasks increased their risk of developing MSDs. Hence, preventive measures are suggested to minimize the risk of MSD, such as the implementation of intervention through ergonomic solutions like awareness and training on safe lifting practices, adjustment of workstations to fit the stature of workers, introducing rest breaks in between work shifts, use of floor mats, and use of compression stockings in conjunction with safety shoes.

Determining factors affecting the perceived usability of air pollution detection mobile application "AirVisual" in Thailand: A structural equation model forest classifier approach

Air pollution has been evident worldwide. It presented numerous pieces of evidence that affect health-related adverse effects causing diseases and even death and the development of technology has helped monitor the exposure of people to air pollution. This research analyzed factors affecting the perceived usability of air pollution detection on the 'AirVisual' mobile application based on the integrated model of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2). A total of 416 participants voluntarily answered a self-administered survey consisting of adapted constructs covering factors such as Performance expectancy (PE), Effort expectancy (EE), Social influence (SI), Facilitating conditions (FC), Habit (HB), Perceived risk (PR), Perceived trust (PT), Intention to use (IU), and Perceived usability (PU). Structural Equation Modeling and Random Forest Classifier were utilized to determine factors affecting perceived usability of the 'AirVisual' mobile application. The results showed that PE, EE, SI, and FC were key factors leading to very high PU among users. Moreover, IU was seen to be the most significant factor affecting PU, followed by PT, PR, and HB. This study is one of the first studies that considered the evaluation of usability among health-related mobile applications covering air pollution. The results and the framework utilized in this model may be applied to evaluate other factors and applications related to health among people. Lastly, this study can also be extended to evaluate other mobile applications worldwide.

Understanding the perceived behavior of public utility bus passengers during the era of COVID-19 pandemic in the Philippines: Application of social exchange theory and theory of planned behavior

Over the years, passengers in the Philippines have relied on public utility bus (PUB) to reach a destination. However, PUB has been greatly affected by the adverse effects of the coronavirus disease (COVID-19) outbreak. Therefore, the study analyzed passengers' behavior using PUB during the COVID-19 pandemic by integrating social exchange theory (SET) and the theory of planned behavior (TPB). A total of 505 PUB users completed the online questionnaire containing sixty-seven (67) measures. Through confirmatory factor analysis - structural equation modeling (CFA-SEM), all the twelve (12) hypotheses were found significant. Accessibility, safety, economic benefit, and crisis management had a significant and positive influence on passengers' trust. Moreover, passengers' trust produced a significant positive influence on attitude, subjective norm, and perceived behavioral control. Additionally, attitude, subjective norm, and perceived behavioral control generated a significant positive influence on the intention to use PUB. Furthermore, perceived behavioral control had a significant positive influence on perceived passenger behavior. Lastly, the intention to use PUB developed a substantial and positive influence on perceived passenger behavior. PUB companies and policymakers can utilize these findings to develop additional PUB reforms for the benefit of passengers, drivers, operators, companies, and the government during the COVID-19 pandemic.

Socio-Economic Factors Affecting Member's Satisfaction towards National Health Insurance: An Evidence from the Philippines

The National Health Insurance, "PhilHealth", is the healthcare provider for Filipino citizens in the Philippines. The study focused on determining the effects of members' satisfaction with PhilHealth among Filipino members. The study utilized 10 latent variables from the integrated Service Quality (SERVQUAL) and Expectation-Confirmation Theory (ECT). There are 500 respondents that are used and analyzed through Structural Equation Modeling (SEM) and a Deep Learning Neural Network (DLNN). Utilizing SEM, it was revealed that Reliability, Responsiveness, Socio-Economic Factors, Expectation, Perceived Performance, Confirmation of Beliefs, and Members' Satisfaction are significant factors in the satisfaction of PhilHealth members. Utilizing DLNN, it was found that Expectation (EX) is the most significant factor, and it is consistent with the results of the SEM. The government can use the findings of this study for the improvement of PhilHealth. The framework that is used for the analysis can be extended and can apply to future research with regard to its provided services. The overall results, framework, and concept utilized may be applied by other service industries worldwide.

Young adult preference analysis on the attributes of COVID-19 vaccine in the Philippines: A conjoint analysis approach

Objective

Vaccines are utilized to prevent the severity of illnesses like the COVID-19 virus. Currently, there are a lot of COVID-19 vaccines available in the market like Pfizer, Moderna, AstraZeneca, Johnson and Johnson, and Sinovac. This research aimed to analyze the preference on the existing vaccine attributes of COVID-19.

Study design

Specifically, this study considered 7 attributes such as cost, brand, recommendations, efficacy, side effects, vaccine type, and dose.

Methods

A conjoint analysis with orthogonal design was utilized and 865 respondents were participated.

Results

The result showed that consumers considered brand as the highest attribute, specifically Pfizer and Moderna among other brands. Moreover, the efficacy of 90% and higher were the preferred vaccine with 1 in 100 patient side effects reported. It was seen that safety and effectiveness is the priority in choosing a COVID-19 vaccine. Interestingly, the knowledge and understanding of the COVID-19 vaccine was found to drive consumer's preference for the vaccines available.

Conclusions

The findings of this study could be utilized by the government to increase the willingness to be vaccinated. Lastly, the result of this study would pave a way to promote herd immunity to help fight the COVID-19 pandemic worldwide.

Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand

With the constant mutation of COVID-19 variants, the need to reduce the spread should be explored. MorChana is a mobile application utilized in Thailand to help mitigate the spread of the virus. This study aimed to explore factors affecting the actual use (AU) of the application through the use of machine learning algorithms (MLA) such as Random Forest Classifier (RFC) and Artificial Neural Network (ANN). An integrated Protection Motivation Theory (PMT) and the Unified Theory of Acceptance and Use of Technology (UTAUT) were considered. Using convenience sampling, a total of 907 valid responses from those who answered the online survey were voluntarily gathered. With 93.00% and 98.12% accuracy from RFC and ANN, it was seen that hedonic motivation and facilitating conditions were seen to be factors affecting very high AU; while habit and understanding led to high AU. It was seen that when people understand the impact and causes of the COVID-19 pandemic’s aftermath, its severity, and also see a way to reduce it, it would lead to the actual usage of a system. The findings of this study could be used by developers, the government, and stakeholders to capitalize on using the health-related applications with the intention of increasing actual usage. The framework and methodology used presented a way to evaluate health-related technologies. Moreover, the developing trends of using MLA for evaluating human behavior-related studies were further justified in this study. It is suggested that MLA could be utilized to assess factors affecting human behavior and technology used worldwide.

The Effect of Positive Reinforcement of Behavioral-Based Safety on Safety Participation in Philippine Coal-Fired Power Plant Workers: A Partial Least Square Structural Equation Modeling (PLS-SEM) Approach

The power plant accident is considered one of the man-made disasters in many developing countries, including the Philippines. The purpose of the study was to identify the factors influencing behavioral-based safety of coal-fired power plant workers which subsequently led to their active safety participation. 201 coal-fired power plant workers in the Philippines answered the questionnaire which consist of 60 items using a purposive sampling approach. PLS-SEM revealed that PM had significant effects on SI, SMS, and SP. In addition, SP was found to have a significant effect on BBS which subsequently led to SPT. Finally, SMS was found to have a significant effect on SC which subsequently led to SCM, BBS, and SPT. This study is the first study that explored the BBS in the Philippine coal-fired power plant. This study can be used to positively reinforce the safety participation of workers in the coal-fired power plant industry.

Utilizing Structural Equation Modeling-Artificial Neural Network Hybrid Approach in Determining Factors Affecting Perceived Usability of Mobile Mental Health Application in the Philippines

Mental health problems have emerged as one of the biggest problems in the world and one of the countries that has been seen to be highly impacted is the Philippines. Despite the increasing number of mentally ill Filipinos, it is one of the most neglected problems in the country. The purpose of this study was to determine the factors affecting the perceived usability of mobile mental health applications. A total of 251 respondents voluntarily participated in the online survey we conducted. A structural equation modeling and artificial neural network hybrid was applied to determine the perceived usability (PRU) such as the social influence (SI), service awareness (SA), technology self-efficacy (SE), perceived usefulness (PU), perceived ease of use (PEOU), convenience (CO), voluntariness (VO), user resistance (UR), intention to use (IU), and actual use (AU). Results indicate that VO had the highest score of importance, followed by CO, PEOU, SA, SE, SI, IU, PU, and ASU. Having the mobile application available and accessible made the users perceive it as highly beneficial and advantageous. This would lead to the continuous usage and patronage of the application. This result highlights the insignificance of UR. This study was the first study that considered the evaluation of mobile mental health applications. This study can be beneficial to people who have mental health disorders and symptoms, even to health government agencies. Finally, the results of this study could be applied and extended among other health-related mobile applications worldwide.

Choosing a package carrier during COVID-19 pandemic: An integration of pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL)

Sustainability and safety have become the two most important considerations of consumers of the current century. The limited movement of consumers and significant shift to online business as effects of the current health pandemic led to an increased demand for package delivery services worldwide. This study investigated the factors that influence the intention of consumers in the Philippines to choose a package delivery or carrying service during the COVID-19 pandemic using the integrated pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL). An online questionnaire was distributed as the instrument data collection, and 400 respondents who have utilized the package delivery service during the pandemic participated in the study. The theoretical model was examined using the partial least square structural equation modeling (PLS-SEM) with higher-order constructs. Testing the different parameters of structural model, measurement model, and the model fit presented values within the threshold. Moreover, the HTMT and Fornell & Larcker discriminant validity analysis was performed to determine the overall fit of the constructs of the model. These tests demonstrated the acceptability of the model. The findings revealed that perceived environmental concern, perceived authority support, subjective norm, attitude, service quality, customer perceived value, and customer satisfaction significantly influence the consumer's intention to choose a package delivery service during the pandemic. The consumers' perception of pro-environmental activities was also an essential contributor since perceived environmental concern and perceived authority support indirectly affect behavior intention. The findings contribute to developing and validating an integrated model on sustainability and service quality in package delivery services. The study also provides suggestions to service providers to ensure quality and safety on package delivery during the pandemic.

Factors Affecting the Perceived Usability of the COVID-19 Contact-Tracing Application "Thai Chana" during the Early COVID-19 Omicron Period

Thai Chana is one of the mobile applications for COVID-19 disease-control tracking, especially among the Thais. The purpose of this study was to determine factors affecting the perceived usability of Thai Chana by integrating protection motivation theory, the extended technology acceptance model, and the system usability scale. In all, 800 Thais participated and filled an online questionnaire with 56 questions during the early COVID-19 omicron period (15 December 2021 to 14 January 2022). Structural equation modeling (SEM) showed that the understanding of COVID-19 has significant effects on perceived severity and perceived vulnerability, which subsequently leads to perceived usefulness. In addition, perceived usefulness and perceived ease of use have significant direct effects on attitude, which subsequently leads to the intention to use, actual use, and perceived usability. This study is one of the first studies that have analyzed the mobile application for COVID-19 disease-control tracking. The significant and substantial findings can be used for a theoretical foundation, particularly in designing a new mobile application for disease-control tracking worldwide. Finally, protection motivation theory, the extended technology acceptance model, and the system usability scale can be used for evaluating other disease-control tracking mobile applications worldwide.

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 (β:0.394, p = 0.025) and the utilization of personal protective equipment (β:0.757, p = 0.001). Subsequently, job stress (β:-0.286, p = 0.001), working hours (β:0.278, p = 0.018), income (β:0.273, p = 0.003), personal protective equipment (β:0.145, p = 0.038), and staff cooperation & management commitment (β: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 (β:-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.

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.