Sawmong, Sudaporn

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Preferred name
Sawmong, Sudaporn
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Email
sudaporn.sa@kmitl.ac.th

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    Item type:Publication,
    Factors influencing e-loyalty among Thai consumers in mobile food delivery applications
    (2023-01-01)
    Sawmong, Sudaporn
    ;
    Ahadi, Navidreza
    ;
    Dansomboon, Suwaj
    The study investigates the key factors influencing customer e-loyalty toward mobile food delivery applications (MFDAs) in Thailand. Employing a quantitative research approach, the study collected 360 responses from MFDA users through a simple random sampling technique. The data was analysed using structural equation modelling (SEM), which revealed that factors such as trustworthiness, consumer awareness, innovative design, technology acceptance, and consumer satisfaction positively impact consumer e-loyalty. The findings confirmed significant correlations between these variables, highlighting their importance in shaping consumer e-loyalty in MFDA. The study's findings indicated that the MFDA service provider may utilise them to acquire a better understanding of the food delivery application's (FDA) customer loyalty in the future, refining their services, improving customer engagement, as well as developing marketing strategies, uncovering opportunities, and gaining a competitive edge. By leveraging these findings, companies can uncover new opportunities and gain a competitive advantage in the rapidly evolving food delivery market.
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    Item type:Publication,
    Factors affecting Thai consumers' online purchase intention toward organic foods for health benefits and convenience
    (2023-01-01)
    Sawmong, Sudaporn
    ;
    Ahadi, Navidreza
    This study aims to explore several factors influencing Thai consumers’ online purchase intentions through different purchasing phases. An expanded research model based on the theory of reasoned action was employed. The research used survey questionnaires to collect data from a sample of 400 online consumers to test the hypotheses and analyse the data. During data processing, the researchers used descriptive statistics to ascertain the sample size’s attributes. Additionally, a structural equation model was employed in this study to identify relationships between variables influencing consumer online purchase intention. The results confirm the relationship between variables and alignment with the hypothesis and theoretical framework.