The large consumption of fast fashion brings many negative environmental impacts. Filipino consumers love and buy fast fashion because it is relatively cheap but trendy, and there are lots of fashionable designs to choose from. Despite the shortage in water supply and disposal issues of fast fashion, people still continue to purchase. The lack of awareness of consumers on sustainable fashion consumption led the researchers to conduct a study that aims to identify factors affecting Filipino consumers’ buying decisions on fast fashion using the combined theory of planned behavior, elaboration likelihood model, and hedonic motivation. A total of 407 participants were gathered through a convenience sampling approach, and the data collected were analyzed using structural equation modeling (SEM). The result shows that attitude towards fast fashion is the highest contributing factor to purchase intention. While social media positively affects purchase intention, sustainability advocacy negatively impacts the consumers’ intention to buy fast fashion. The awareness of sustainability leads to consumption reduction of fast fashion garments. Surprisingly, perceived product price and quality do not show a significant influence on purchase intention. Incorporating sustainability advocacy on social media may be a great strategy to encourage the sustainable consumption of fashion garments. The findings of this study could be a great tool to influence fashion companies and government institutions to promote sustainability awareness and transition marketing strategies to the sustainable consumption of fashion.

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.

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

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.

This present research examines the behavioral intentions of Filipinos to use online grocery applications during the novel COVID-19 pandemic. The study proposes an integration of the health belief model (HBM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) to identify the factors affecting the acceptance and usage of Filipinos of online grocery applications in terms of the impact of health risk for COVID-19. To accurately measure the factors and their relationship to behavioral intentions and usage behavior, a questionnaire was developed and distributed to 373 residents in the Philippines. Partial least squares structural equation modeling (PLS-SEM) was applied as an analytical method for this study. The results revealed that performance expectancy, perceived benefits, perceived severity, and cues to action significantly influenced the behavioral intentions and usage of online grocery apps during the COVID-19 pandemic. The study’s findings can be utilized as a theoretical framework for future researchers of consumer behavior; e-commerce developers; and grocery industry retailers, to enhance the innovation and services of online grocery applications. The results of this study may also be used and capitalized on by investors and managers to apply in strategizing when developing and marketing online grocery applications among consumers. Moreover, the framework of this study may be adopted and utilized by other online markets, even in different counties. Further theoretical and practical aspects are discussed in this paper.

The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thailand. This study aimed to predict factors affecting the perceived usability of Thai Chana by integrating the Protection Motivation Theory and Technology Acceptance Theory considering the System Usability Scale, utilizing deep learning neural network and random forest classifier. A total of 800 respondents were collected through convenience sampling to measure different factors such as understanding COVID-19, perceived severity, perceived vulnerability, perceived ease of use, perceived usefulness, attitude towards using, intention to use, actual system use, and perceived usability. In total, 97.32% of the deep learning neural network showed that understanding COVID-19 presented the most significant factor affecting perceived usability. In addition, random forest classifier produced a 92% accuracy with a 0.00 standard deviation indicating that understanding COVID-19 and perceived vulnerability led to a very high perceived usability while perceived severity and perceived ease of use also led to a high perceived usability. The findings of this study could be considered by the government to promote the usage of contact tracing applications even in other countries. Finally, deep learning neural network and random forest classifier as machine learning algorithms may be utilized for predicting factors affecting human behavior in technology or system acceptance worldwide.