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German JD, Ong AKS, Redi AANP, Prasetyo YT, Robas KPE, Nadlifatin R, Chuenyindee T. Classification modeling of intention to donate for victims of Typhoon Odette using deep learning neural network. Environ Dev 2023; 45:100823. [PMID: 36844910 PMCID: PMC9939386 DOI: 10.1016/j.envdev.2023.100823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
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.
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Affiliation(s)
- Josephine D German
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Ardvin Kester S Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | | | - Yogi Tri Prasetyo
- Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, 32003, Taiwan
- International Bachelor Program in Engineering, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, 32003, Taiwan
| | - Kirstien Paola E Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya, 60111, Indonesia
| | - Thanatorn Chuenyindee
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok, 10220, Thailand
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Ong AKS, Prasetyo YT, Sacro MCC, Artes AL, Canonoy MPM, Onda GKD, Persada SF, Nadlifatin R, Robas KPE. Determination of factors affecting customer satisfaction towards "maynilad" water utility company: A structural equation modeling-deep learning neural network hybrid approach. Heliyon 2023; 9:e13798. [PMID: 36873542 PMCID: PMC9981920 DOI: 10.1016/j.heliyon.2023.e13798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/10/2023] [Accepted: 02/13/2023] [Indexed: 02/19/2023] Open
Abstract
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.
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Affiliation(s)
- Ardvin Kester S Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Muralla St., Intramuros, Manila, 1002, Philippines
| | - Yogi Tri Prasetyo
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Muralla St., Intramuros, Manila, 1002, Philippines.,International Bachelor Program in Engineering, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, 32003, Taiwan.,Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, 32003, Taiwan
| | - Mariela Celine C Sacro
- Young Innovators Research Center, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Alycia L Artes
- Young Innovators Research Center, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Mariella Phoemela M Canonoy
- Young Innovators Research Center, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Guia Karyl D Onda
- Young Innovators Research Center, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Satria Fadil Persada
- Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta, 11480, Indonesia
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya, 60111, Indonesia
| | - Kirstien Paola E Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Muralla St., Intramuros, Manila, 1002, Philippines
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Ong AKS, Prasetyo YT, Kishimoto RT, Mariñas KA, Robas KPE, Nadlifatin R, Persada SF, Kusonwattana P, Yuduang N. Determining factors affecting customer satisfaction of the national electric power company (MERALCO) during the COVID-19 pandemic in the Phillippines. Util Policy 2023; 80:101454. [PMID: 36506908 PMCID: PMC9728044 DOI: 10.1016/j.jup.2022.101454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 11/05/2022] [Accepted: 11/05/2022] [Indexed: 06/17/2023]
Abstract
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.
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Affiliation(s)
- Ardvin Kester S Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Yogi Tri Prasetyo
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
- International Program in Engineering for Bachelor, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, 32003, Taiwan
- Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, 32003, Taiwan
| | - Ryuichi T Kishimoto
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
- School of Graduate Studies, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
- College of Engineering and Information Technology, Pamantasan Ng Lungsod Ng Valenzuela. MXV9+GJF, Maysan Rd, Valenzuela, Metro Manila, Philippines
| | - Klint Allen Mariñas
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
- Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan, 320, Taiwan
| | - Kirstien Paola E Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya, 60111, Indonesia
| | - Satria Fadil Persada
- Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta, 11480, Indonesia
| | - Poonyawat Kusonwattana
- Department of Industrial Engineering, Faculty of Engineering, North-Chiang Mai University, Chiang Mai, 50230, Thailand
| | - Nattakit Yuduang
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
- School of Graduate Studies, Mapúa University, Manila, Philippines. 658 Muralla St., Intramuros, Manila, 1002, Philippines
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Ong AKS, Prasetyo YT, Kusonwattana P, Mariñas KA, Yuduang N, Chuenyindee T, Robas KPE, Persada SF, Nadlifatin R. Determining factors affecting the perceived usability of air pollution detection mobile application "AirVisual" in Thailand: A structural equation model forest classifier approach. Heliyon 2022; 8:e12538. [PMID: 36619460 PMCID: PMC9813733 DOI: 10.1016/j.heliyon.2022.e12538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 11/07/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
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.
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Affiliation(s)
- Ardvin Kester S. Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Yogi Tri Prasetyo
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines,International Program in Engineering for Bachelor, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 32003, Taiwan,Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 32003, Taiwan,Corresponding author.
| | - Poonyawat Kusonwattana
- Department of Industrial Engineering, Faculty of Engineering, North-Chiang Mai University, Chiang Mai 50230, Thailand
| | - Klint Allen Mariñas
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines,Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan 320, Taiwan
| | - Nattakit Yuduang
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Thanatorn Chuenyindee
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok, 10220, Thailand
| | - Kirstien Paola E. Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Satria Fadil Persada
- Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta 11480, Indonesia
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia
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German JD, Ong AKS, Perwira Redi AAN, Robas KPE. Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach. Heliyon 2022; 8:e11382. [PMID: 36349283 PMCID: PMC9633627 DOI: 10.1016/j.heliyon.2022.e11382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/04/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
The COVID-19 pandemic had brought changes to individuals, especially in consumer behavior. As the government of different countries has been implementing safety protocols to mitigate the spread of the virus, people became apprehensive about traveling and going out. This paved way for the emergence of third-party logistics (3PL). Statistics have proven the rapid escalation regarding the use of 3PL in various countries. This study utilized Artificial Neural Network and Random Forest Classifier to validate and justify the factors that affect consumer intention in selecting a 3PL service provider during the COVID-19 pandemic integrating the Service Quality Dimensions and Pro-Environmental Theory of Planned Behavior. The findings of this study revealed that attitude is the most significant factor that affects the consumers' behavioral intention. Other factors such as customer satisfaction, customer perceived value, perceived environmental concern, assurance, responsiveness, empathy, reliability, tangibility, perceived behavioral control, subjective norm, and perceived authority support, are all contributing factors that affect behavioral intention. Machine learning algorithms, specifically ANN and RFC, resulted to be reliable in predicting factors as they obtained accuracy rates of 98.56% and 93%. Results presented that consumers’ attitude, satisfaction, perceived value, assurance by the 3PL, and perceived environmental concerns were highly influential in choosing a 3PL package carrier. It was seen that people would be encouraged to use 3PL service providers if they demonstrate availability and environmental concerns in catering to the customers' needs. Subsequently, 3PL providers must assure safety and convenience before, during, and after providing the service to ensure continuous patronage of consumers. This is considered to be the first study that utilized a machine learning ensemble to measure behavioral intention for the logistic sector. The framework, analysis tools, and findings of this study could be extended and applied among other behavioral intentions regarding transportation worldwide. Managerial insights among service providers are discussed.
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Affiliation(s)
- Josephine D. German
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines
| | - Ardvin Kester S. Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines
- Corresponding author.
| | | | - Kirstien Paola E. Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines
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Ong AKS, Dejucos MJR, Rivera MAF, Muñoz JVD, Obed MS, Robas KPE. Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic. Heliyon 2022; 8:e11293. [DOI: 10.1016/j.heliyon.2022.e11293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/22/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022] Open
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Chuenyindee T, Montenegro LD, Ong AKS, Prasetyo YT, Nadlifatin R, Ayuwati ID, Sittiwatethanasiri T, Robas KPE. The perceived usability of the learning management system during the COVID-19 pandemic: Integrating system usability scale, technology acceptance model, and task-technology fit. Work 2022; 73:41-58. [PMID: 35871387 DOI: 10.3233/wor-220015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND The education system has shifted from traditional to online during the COVID-19 pandemic. Thus, the Learning Management System (LMS) is one of the most important and comprehensive learning platforms that support and facilitate online learning during this pandemic. OBJECTIVE This study explored the perceived system usability of LMS during the COVID-19 pandemic by utilizing Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and System Usability Scale (SUS). METHODS An online survey was utilized to collect data from 502 Filipino students from different academic institutions and different areas of study. RESULTS Structural Equation Modeling (SEM) indicated that students' perceived ease of use of LMS had a significant effect on perceived usefulness which subsequently and positively led to students' perceived satisfaction of LMS. In addition, LMS technology characteristics was found to have a significant effect on LMS task-technology fit which subsequently led to perceived usefulness and perceived satisfaction. Interestingly, perceived satisfaction was found to have a significant effect on students' perceived system usability of LMS which was calculated using a System Usability Scale (SUS). CONCLUSION The findings have implications within the education system globally, particularly in recognizing the relevance of LMS moving forward. Furthermore, since this is the first study that integrated SUS, TAM, and TTF, the conceptual framework can be utilized to evaluate the perceived usability of LMS worldwide.
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Affiliation(s)
- Thanatorn Chuenyindee
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok, Thailand
| | - Lorenzo Dones Montenegro
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines.,School of Graduate Studies, Mapúa University, Manila, Philippines.,Department of Arts & Letters, Mapúa University, Manila, Philippines
| | - Ardvin Kester S Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines
| | - Yogi Tri Prasetyo
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines.,Department of Industrial Engineering and Management, Yuan Ze University, Taoyuan, Taiwan
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya, Indonesia
| | - Irene Dyah Ayuwati
- Faculty of Business and Information Technology, Institut Teknologi Telkom Surabaya, Surabaya, Indonesia
| | - Thaninrat Sittiwatethanasiri
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok, Thailand
| | - Kirstien Paola E Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines
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Ong AKS, Prasetyo YT, Yuduang N, Nadlifatin R, Persada SF, Robas KPE, Chuenyindee T, Buaphiban T. Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand. IJERPH 2022; 19:ijerph19137979. [PMID: 35805634 PMCID: PMC9265314 DOI: 10.3390/ijerph19137979] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 06/25/2022] [Accepted: 06/27/2022] [Indexed: 02/08/2023]
Abstract
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.
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Affiliation(s)
- Ardvin Kester S. Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (A.K.S.O.); (N.Y.); (K.P.E.R.)
| | - Yogi Tri Prasetyo
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (A.K.S.O.); (N.Y.); (K.P.E.R.)
- Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 32003, Taiwan
- Correspondence: ; Tel.: +63(2)-8247-5000 (ext. 6202)
| | - Nattakit Yuduang
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (A.K.S.O.); (N.Y.); (K.P.E.R.)
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia;
| | - Satria Fadil Persada
- Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta 11480, Indonesia;
| | - Kirstien Paola E. Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (A.K.S.O.); (N.Y.); (K.P.E.R.)
| | - Thanatorn Chuenyindee
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand; (T.C.); (T.B.)
| | - Thapanat Buaphiban
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand; (T.C.); (T.B.)
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Yuduang N, Ong AKS, Vista NB, Prasetyo YT, Nadlifatin R, Persada SF, Gumasing MJJ, German JD, Robas KPE, Chuenyindee T, Buaphiban T. Utilizing Structural Equation Modeling-Artificial Neural Network Hybrid Approach in Determining Factors Affecting Perceived Usability of Mobile Mental Health Application in the Philippines. Int J Environ Res Public Health 2022; 19:ijerph19116732. [PMID: 35682313 PMCID: PMC9180905 DOI: 10.3390/ijerph19116732] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 05/26/2022] [Accepted: 05/27/2022] [Indexed: 12/18/2022]
Abstract
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.
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Affiliation(s)
- Nattakit Yuduang
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Ardvin Kester S. Ong
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
| | - Nicole B. Vista
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Yogi Tri Prasetyo
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
- Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Taoyuan 32003, Taiwan
- Correspondence: ; Tel.: +63-(2)-8247-5000 (ext. 6202)
| | - Reny Nadlifatin
- Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia;
| | - Satria Fadil Persada
- Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta 11480, Indonesia;
| | - Ma. Janice J. Gumasing
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Josephine D. German
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
| | - Kirstien Paola E. Robas
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
| | - Thanatorn Chuenyindee
- School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines; (N.Y.); (A.K.S.O.); (N.B.V.); (M.J.J.G.); (J.D.G.); (K.P.E.R.); (T.C.)
- School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand;
| | - Thapanat Buaphiban
- Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand;
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