Analysis of Actual Fitness Supplement Consumption among Health and Fitness Enthusiasts.

With the rising popularity of fitness supplements, understanding the factors driving their consumption behaviors is crucial. This study investigated the actual consumption of fitness supplements utilizing the Theory of Planned Behavior (TPB), Health Belief Model (HBM), and the Theory of Effort Minimization in Physical Activity (TEMPA) frameworks. The TPB provided insights into how attitudes, subjective norms, and perceived behavioral control influence individuals' intentions to consume fitness supplements. Additionally, the HBM sheds light on perceived effectiveness, benefits, barriers, and health motivation related to supplement consumption. Integrating the TEMPA framework further investigated the role of effort minimization in physical activity contexts. Through an online questionnaire, data were collected from a sample of 250 fitness supplement-consuming respondents. SEM analysis revealed significant associations between behavioral intentions and attitudes, perceived behavioral control, health motivation, and controlled precursors. However, it was seen that subjective norms, perceived effectiveness, perceived benefits, and automatic precursors were deemed insignificant. The findings contribute to a comprehensive understanding of the factors shaping actual consumption behaviors, offering valuable implications for marketers, health professionals, and policymakers seeking to promote informed and responsible supplement use among health and fitness enthusiasts.

Determining Factors Influencing Collegiate Players' Intention to Pursue a Professional Career.

The rise of professional careers in playing sports has been seen in the recent generation. Ranging from traditional sports to recent e-games, it can be seen that student athletes are not only considering these as motivational factors for education, but also as future career paths. This study aims to fill the knowledge gap about the factors influencing college athletes' aspirations to play professionally. The study examines the complex web of athlete decision-making by utilizing the extended Theory of Planned Behavior (TPB) and analyzing the roles of motivational factors, self-efficacy, affective behavior, and behavioral domains. With the use of structural equation modeling, the study deciphers the intricate links, emphasizing the critical role that attitude plays in affective behavior. It emphasizes how much optimism and self-efficacy shape an athlete's behavior and subsequent pursuit of professional careers. The current research provides a benchmark for future studies exploring student athletes' career goals. This research adds understanding to the knowledge gap regarding the complex decision-making procedures of aspiring professional athletes. Both theoretical and practical implications are provided based on the results of the study, which stakeholders and institutions may consider for student athletes wanting to pursue a professional sports career.

Determining factors affecting Filipino consumers' behavioral intention to use cloud storage services: An extended technology acceptance model integrating valence framework.

Cloud Storage (CS) is a service that digitally stores, remotely manages, backs up, and renders internet-accessible data. However, despite its known benefits compared to traditional storage devices, this service is not widely used in developing nations such as the Philippines. This study integrated the Valence Theoretical Framework into the Extended Technology Acceptance Model (ETAM) to evaluate the influence of twelve variables on Filipino consumers' behavioral intention (BI) toward adopting CS services. The data is gathered through an online survey. Structural Equation Modeling was employed to examine the responses of 431 cloud users, mainly students and working professionals. Results showed that Perceived Benefit and Perceived Usefulness were the strongest determinants of BI. The Job Relevance was also found to be a significant factor. Therefore, CS providers should find additional ways to make their offerings more beneficial for the daily tasks of students and working individuals. Furthermore, considering the substantial influence of Perceived Risk and Subjective Norms on BI, CS providers must strengthen their security measures to boost users' trust in their services. Consumers who receive excellent service are likely to give positive reviews, which can be helpful to individuals who might also be considering purchasing CS for their data. Although the focus of this study is CS services, this can also serve as a reference when analyzing the BI of consumers concerning the adoption of other novel technologies applied in various sectors, including education, e-commerce, healthcare, and more.

Analyzing Preceding factors affecting behavioral intention on communicational artificial intelligence as an educational tool.

During the pandemic, artificial intelligence was employed and utilized by students around the globe. Students' conduct changed in a variety of ways when schooling returned to regular instruction. This study aimed to analyze the student's behavioral intention and actual academic use of communicational AI (CAI) as an educational tool. This study identified the variables by utilizing an integrated framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) and self-determination theory. Through the use of an online survey and Structural Equation Modeling, data from 533 respondents were analyzed. The results showed that perceived relatedness has the most significant effect on the behavioral intention of students in using CAI as an educational tool, followed by perceived autonomy. It showed that students use CAI based on the objective and the possibility of increasing their productivity, rather than any other purpose in the education setting. Among the UTAUT2 domains, only facilitating conditions, habit, and performance expectancy provided a significant direct effect on behavioral intention and an indirect effect on actual academic use. Further implications were presented. Moreover, the methodology and framework of this study could be extended and applied to educational technology-related studies. Lastly, the outcome of this study may be considered in analyzing the behavioral intention of the students as the teaching-learning environment is still continuously expanding and developing.

Determinants of satisfaction and continuance intention towards online food delivery service users in Indonesia post the COVID-19 pandemic.

The COVID-19 pandemic has resulted in behavioural changes in the way people consume food in Indonesia, because people tend to use online food delivery (OFD) services to order food after the pandemic. In line with this, application-based OFD service providers in Indonesia such as GoFood, GrabFood, ShopeeFood, and others are growing year after year, creating competition among OFD service providers. On the other hand, now that the COVID-19 pandemic condition has begun to improve, people may return to ordering food in the traditional manner, namely by visiting restaurants directly without using the OFD service application. As a result, it may jeopardize the stability of the OFD service business. As a result, the purpose of this study is to investigate the factors that influence the satisfaction and intent of OFD service users in Indonesia to continue using OFD services in the future. The Unified Theory of Acceptance and Use of Technology (UTAUT2), Expectancy Confirmation Model (ECM), online review, online rating, and online tracking were all combined to do structural equation modeling (SEM) using the PLS-SEM approach. Data were gathered using an online poll of 325 respondents who have used OFD services. According to the findings of the structural model analysis, effort expectancy, hedonic motivation, price-saving orientation, and confirmation all have a direct impact on the level of satisfaction of OFD service users. Meanwhile, performance expectancy, habit, online review, and satisfaction all influence the intention to continue using OFD services. The findings of this study can be used as a reference for OFD service providers as a service improvement strategy, as well as to expand the literature on consumer behaviour regarding OFD services and provide a foundation for future research.

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.

The impact of green innovation initiatives on competitiveness and financial performance of the land transport industry.

The transportation sector is one of the primary contributors to greenhouse gas emissions that have deteriorating effects on the state of the environment. The implementation of sustainable practices has become one of the most challenging tasks of organizations at present. This study examined the effect of implementing green innovation initiatives on a firm's competitiveness and financial performance of motor vehicle companies in the Philippines. Data were gathered through an online survey questionnaire with a total of 206 respondents composed of employees of various ranks working in companies engaged in the manufacture, distribution, retail, and service of motor vehicles. The theoretical framework presented a hierarchical latent variable model which was validated using the partial least square structural equation modelling (PLS-SEM). The model fit, measurement, general construct fit, discriminant validity, and structural model parameters were examined and found to have acceptable values. The findings indicated that environmental regulations, market demand, government pressure, competitor pressure, corporate social responsibility, and employee conduct were the significant drivers of green innovation initiatives. The study also revealed that the implementation of green innovation initiatives positively affects the firm's competitiveness and financial performance. Motor vehicle companies and other types of organizations are encouraged to demonstrate not only their concern for society or community but also their concern for the environment to acquire better market leverage and financial position.

Antecedents of behavioral intentions for purchasing safety tools among women.

The rise of crimes and violence against women are evident worldwide. The self-protection and behavioral aspects however are underexplored. The need for assessment for safety such as the purchasing intentions of safety tools should be considered to promote the mitigation and reduction of violence and crimes against women, may it be in households or outdoors. This study aimed to holistically analyze the determinants of behavioral intentions to purchase self-defense tools among women. Focusing on the Philippines, the structural equation modeling considering the extended theory of planned behavior (TPB) and protection motivation theory (PMT) integrated model was completely analyzed. A total of 553 valid respondents were purposively gathered to completely assess the behavioral domains and protective behaviors of women. From the results, self-efficacy showed the most significant factor affecting purchasing intentions, followed by behavioral intentions, and the behavioral domains under TPB. Moreover, indirect effects of PMT variables to purchasing intentions were seen; highest from understanding of safety, perceived risk, and then perceived severity. The extended latent variable such as perceived safety showed an indirect effect while buying impulse showed a direct significant effect on purchasing intentions. This is considered as the first study that assessed the different variables affecting purchasing intentions of self-defense tools. The findings of this study would provide a gateway as benchmark for how women feel, behave, and seeks protection. Implementing the suggestion with other aspects would end up promoting the overall safety of a country, not just for women, but for all victims against crime and violence.

Employees' preference analysis on lean six sigma program coaching attributes using a conjoint analysis approach.

The purpose of this study was to determine the preference of employees for Lean Six Sigma project coaching attributes. Conjoint analysis with an orthogonal design was utilized and six attributes were considered: coaching style, frequency of coaching sessions, duration of coaching sessions, the turn-around time of feedback, documentation review, and mock defense. In addition, 4 different projects were also evaluated: Quick Win project, Yellow Belt project, Green Belt project, and Black Belt project. The results showed that for Quick Win projects, employees consider conducting a mock defense as the highest preference, followed by having a documentation review, and a democratic coaching style. For Yellow Belt projects, employees considered conducting a mock defense as the highest preference, followed by having a documentation review, and a weekly coaching session. For Green Belt projects, employees consider having a documentation review as the highest preference, followed by a transactional coaching style, and conducting a mock defense. Lastly, for Black Belt projects, employees consider having a documentation review as the highest preference, followed by conducting a mock defense, and a 1-week turn-around time for feedback. The results of this study will help companies to implement and to sustain better employee-oriented LSS programs.

Predicting factors influencing perceived online learning experience among primary students utilizing structural equation modeling Forest Classifier approach.

Introduction: Amid the COVID-19 pandemic, the temporary closure of educational institutions led to the adoption of remote or online learning delivery. Challenges, especially for grade schools were evident. Objective: This study aimed to identify factors affecting the perceived online discussion experience of Filipino primary students through distance learning in the National Capital Region, Philippines. Method: Variables such as cognitive presence, teaching presence, social presence, and online discussion experience were investigated simultaneously by utilizing the structural equation modeling (SEM) and random forest classifier (RFC) approach. A total of 385 currently enrolled Filipino grade school student participants were surveyed. Results: Results show that cognitive presence has the most significant impact on the perceived online discussion experience, followed by teaching presence, and social presence. This study is the first study that analyzed the online discussion experience among grade school students in online education in the Philippines considering SEM and RFC. It was seen that highly significant factors such as teaching presence, cognitive presence, social presence, triggering events, and exploration will lead to high and very high learning experience with grade school students. Conclusion: The findings of this study would be significant for teachers, educational institutions, and government agencies to improve the online delivery of primary education in the country. In addition, this study presents a reliable model and results which can be extended and applied for academicians, educational institutions, and the education sector to develop ways in enhancing the online delivery of primary education worldwide.

Introduction: Au milieu de la pandémie de COVID-19, la fermeture temporaire des établissements d'enseignement a conduit à l'adoption de la prestation d'apprentissage à distance ou en ligne. Les défis, en particulier pour les écoles primaires, étaient évidents. Objectif: Cette étude visait à identifier les facteurs affectant l'expérience de discussion en ligne perçue des élèves philippins du primaire par le biais de l'apprentissage à distance dans la région de la capitale nationale, aux Philippines. Méthode: Des variables telles que la présence cognitive, la présence dans l'enseignement, la présence sociale et l'expérience de discussion en ligne ont été étudiées simultanément en utilisant l'approche de structural equation modeling (SEM) et de Random Forest classifier (RFC). Un total de 385 élèves philippins actuellement inscrits à l'école primaire ont été interrogés. Résultats: Les résultats montrent que la présence cognitive a l'impact le plus significatif sur l'expérience de discussion en ligne perçue, suivie de la présence pédagogique et de la présence sociale. Cette étude est la première étude qui a analysé l'expérience de discussion en ligne parmi les élèves du primaire dans l'éducation en ligne aux Philippines en tenant compte du SEM et du RFC. Il a été constaté que des facteurs très importants tels que la présence d'enseignement, la présence cognitive, la présence sociale, les événements déclencheurs et l'exploration conduiront à une expérience d'apprentissage élevée et très élevée avec les élèves du primaire. Conclusion: En outre, cette étude présente un modèle et des résultats fiables qui peuvent être étendus et appliqués aux universitaires, aux établissements d'enseignement et au secteur de l'éducation afin de développer des moyens d'améliorer la prestation en ligne de l'enseignement primaire dans le monde entier.

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.

Application of Conjoint Analysis and 5Ps Marketing Mix in Identifying Customer Preference of Alcohol Consumption among Youths in the Philippines.

Alcoholic beverages have long been one of the most popular commodities. They have been mass-produced worldwide because of their popularity and demand. On a survey by Statista in 2021, alcohol consumption is projected to increase in the Philippines. Thus, the popularity of numerous alcoholic beverages piqued the curiosity of consumers and researchers alike. This study used conjoint analysis that aims to have a better understanding of consumer preferences for alcohol consumption among youths. Additionally, the study considered the following attributes: (1) type of alcoholic beverage, (2) oral sensation, (3) flavor, (4) origin, (5) color, and (6) price. Results revealed that the product's price is the most crucial attribute influencing consumer preferences by 26.311%, followed by the type of alcoholic beverage with an importance score of 26.237%. The least considered attribute is the product's color, having an importance score of 7.790%. These were supported by two statistical tests, the Pearson's Correlation Test and Kendall's Tau Test, which both obtained a value higher than 0.8. Managerial implications were presented in the study to help provide strategies and development for alcoholic beverage distribution in the Philippines based on the findings of this study, which relate to young consumers.

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.

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.

Classification modeling of intention to donate for victims of Typhoon Odette using deep learning neural network.

The need for stability in the economy for world development has been a challenge due to the COVID-19 pandemic. In addition, the increase of natural disasters and their aftermath have been increasing causing damages to infrastructure, the economy, livelihood, and lives in general. This study aimed to determine factors affecting the intention to donate for victims of Typhoon Odette, a recent super typhoon that hit the Philippines leading to affect 38 out of 81 provinces of the most natural disaster-prone countries. Determining the most significant factor affecting the intention to donate may help in increasing the engagement of donations among other people to help establish a more stable economy to heighten world development. With the use of deep learning neural network, a 97.12% accuracy was obtained for the classification model. It could be deduced that when donors understand and perceive both severity and vulnerability to be massive and highly damaging, then a more positive intention to donate to victims of typhoons will be observed. In addition, the influence of other people, the holiday season when the typhoon happened, and the media as a platform have greatly contributed to heightening the intention to donate and control over the donor's behavior. The findings of this study could be applied and utilized by government agencies and donation platforms to help engage and promote communication among donors. Moreover, the framework and methodology considered in this study may be extended to evaluate intention, natural disasters, and behavioral studies 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.

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.