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.

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.

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.

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.

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 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.

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.

Determination of factors influencing young adults' intention to have COVID-19 vaccine in the Philippines: An integration of Health Belief Model and the Theory of Planned Behavior.

Objectives: The COVID-19 pandemic continues to increase around the world and businesses and markets across the world significantly decreased. The purpose of this study was to determine the factors that affect the intention to be vaccinated for the COVID-19 vaccine among young Filipino adults by integrating the Health Belief Model and Extended Theory of Planned Behavior. Study design: A cross-sectional study design was utilized. Methods: Factors such as understanding of the COVID-19 vaccine, self-efficacy, cues to action, perceived barriers, perceived benefits, perceived side effects, perceived behavioral control, attitude, subjective norm, and intention to be vaccinated were analyzed by utilizing Structural Equation Modeling (SEM). Results: With 865 young Filipino adults who answered a self-administered survey, it was seen that Understanding of the COVID-19 vaccine has the highest direct significant effect on cues to action, followed by perceived barriers, and perceived benefits. Interestingly, the primary factor was Understanding COVID-19 vaccines which had an indirect significant effect on the intention to get vaccinated. This is because knowing what the vaccine is for, its effects, and the application would lead to the acceptance of the COVID-19 vaccine. Moreover, the impact of being known to have the COVID-19 vaccine would lead to the intention to get vaccinated. Conclusions: The findings of this study can be utilized especially by the government in developing strategies for encouraging people to take the COVID-19 vaccine. Finally, the model construct of the study can be applied to explore more factors that can affect the intention to be vaccinated with the COVID-19 vaccine and other vaccines people 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 (ß=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.

The effect of positive reinforcement of behavioral-based safety on safety participation in Philippine coal-fired power plant workers: a partial least squares structural equation modeling approach.

The power plant accident is considered one of the man-made disasters in many developing countries, including the Philippines. This study aimed to identify the factors influencing behavioral-based safety (BBS) of coal-fired power plant workers which subsequently led to their active safety participation (SPT). In total, 201 coal-fired power plant workers in the Philippines answered the questionnaire consisting of 60 items using a purposive sampling approach. Partial least squares structural equation modeling (PLS-SEM) revealed that personal measures (PM) had significant effects on safety incentives (SI), safety management system (SMS) and safety perception (SP). SP also had significant effect on BBS which subsequently led to SPT. Finally, SMS had significant effect on safety culture (SC) which subsequently led to safety communication (SCM), BBS and SPT. This study is the first to explore BBS in the Philippine coal-fired power plant, and can positively reinforce SPT of workers in the coal-fired power plant industry.

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.

Evaluating the influence of service quality, hedonic, and utilitarian value on shopper's behavioral intentions in urban shopping malls during the COVID-19 pandemic.

Shopping malls are subjected to a lot of changes during the COVID-19 pandemic, especially in the Philippines. The objective of the study was to evaluate the influence of service quality, hedonic, and utilitarian value of malls on shopping mall goers' behavioral intentions during the COVID-19 pandemic. SERVQUAL five dimensions were utilized to represent the service quality aspect, while utilitarian and hedonic values are used to embody the shopping mall values among Filipino citizens. Additionally, we included convenience and social experience as part of our model, to which relationships were assessed toward the utilitarian and hedonic shopping mall values, respectively. An online survey was distributed and collected 519 valid responses among Filipino shopping mall goers. Using Structural Equation Modeling (SEM), results showed that for service quality aspect, tangibles, empathy, and assurance had significant effects on shopper's shopping mall satisfaction during the COVID-19 pandemic. On the other hand, both shopping mall values present positive effects on shopper's satisfaction on which utilitarian value gave the strongest influence in the overall model, followed by the hedonic value. Convenience and social experience also showed positive effects on utilitarian and hedonic values, respectively. The utilized extended framework from SERVQUAL dimensions and hedonic and utilitarian values to measure satisfaction and behavioral intentions was seen to be applicable to measure human behavior and lifestyle studies. Overall, the satisfaction from both service quality and shopping mall values aspect strongly influences shoppers' behavioral intention in going to the mall.

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.

How important is the tuition fee during the COVID-19 pandemic in a developing country? Evaluation of filipinos' preferences on public university attributes using conjoint analysis.

In a developing country like the Philippines, it is critical to understand the important factors which lead college students to their current colleges and universities, especially during the COVID-19 pandemic. This study utilized the conjoint analysis approach with an orthogonal design for evaluating understudy's inclination in choosing a college with the various attributes such as the tuition fee, distance or location, employability, academic reputation, recommended by friends and peers, recommended by family or relatives, and the availability to transfer was assessed. A total of 518 Filipino students studying at public and state universities participated in answering the 16 combined attributions about university preference using purposive sampling approach. Based on the utilities estimate, the most important attribute was the tuition fee of the preferred university with an importance value of about 32.839%, followed by the employability rate of the university with about 6% gap difference. The mid-concerned attributes were the distance/location with an estimated of 11.139%, recommendation of friends or peers with approximately 11.689% tying together, and the academic reputation with an estimated of 10.638%. The two least important attributes were identified to be the availability to transfer, having with only about 2.713%, and the recommendation of parents with only 2% difference at approximately 4.453%. The outcomes of this study can aid college chairmen and enrolment specialists tweak their advertising procedures by giving significant data to the chief gatherings engaged with settling college decision choices.

Factors Affecting Perceived Effectiveness of Government Response towards COVID-19 Vaccination in Occidental Mindoro, Philippines.

The COVID-19 pandemic has caused several developing countries to fall behind on vaccination at the onset of the pandemic, thus affecting the mobility of easing restrictions and lowering virus transmission. The current study integrated the Protection Motivation Theory (PMT) and extended the Theory of Planned Behavior (TPB) to evaluate factors affecting the perceived effectiveness of government response towards COVID-19 vaccination in Occidental Mindoro. A total of 400 respondents from the municipalities of Occidental Mindoro answered the online questionnaires, which contained 61 questions. This study outlined the relationship between the dependent and independent variables using structural equation modeling (SEM). The results indicated that knowledge of COVID-19 vaccination had significant direct effects on its perceived severity. Subjective standards had significant adverse effects on willingness to follow. In addition, perceived behavioral control was discovered to impact willingness to follow positively. It also showed that perceived government response was significantly affected by adaptive behavior and actual behavior regarding the perceived government response. Meanwhile, it was found that the perceived government response had significant effects on perceived effectiveness. The current study is one of the first to study the factors that affect the perceived effectiveness of government response toward COVID- 19 vaccination.

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.

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.