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Factors influencing e-loyalty among Thai consumers in mobile food delivery applications
(2023-01-01)
Sawmong, Sudaporn
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Ahadi, Navidreza
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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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The Development of Community Enterprise Entrepreneurs in the Crop Production Sector for Entry into e-Commerce
(2023-01-01)
Chienwattanasook, Krisada
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Jarinto, Krit
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Sulong, Madaoh
The spread of coronavirus disease in 2019 (COVID-19) in Thailand has led to a lack of liquidity and income for entrepreneurs, increasing the variety of distribution channels compared to store sales. This will be a solution for businesses that are struggling. The objectives of this research are to provide training and guidance to community enterprise groups, build a platform and collect product data from community enterprises in the research area, i.e. community enterprises in Chachoengsao Province. This research is participatory action-based with a group of entrepreneurs and 25 groups of community enterprises with three main processes: first, selection and training on e-commerce, second, development of electronic databases and marketing consultation to collect data from the website and consult experts. Finally, advertising and publicity in the online media to make consumers and the general public aware of the project in order to increase the sales and revenues of the community enterprise entrepreneurs. The results of the study indicate political and practical recommendations. To begin with, the government should provide financial support such as low-interest funds or loans as well as have clear, concrete, and continuity policies to support and promote community enterprises. In addition,community enterprises should raise awareness about the importance of real participation, manage big data, and form online trading will facilitate which can ensure sustainability.
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Barriers and Factors Affecting the E-Commerce Sustainability of Thai Micro-, Small- and Medium-Sized Enterprises (MSMEs)
(2022-07-01)
Amornkitvikai, Yot
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Tham, Siew Yean
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Harvie, Charles
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Buachoom, Wonlop Writthym
It is anticipated that e-commerce will contribute to achieving the 17th Sustainable Development Goal, which seeks to improve implementation mechanisms and revitalize global partnerships for sustainable development. However, MSMEs still face a digital gap compared to large enterprises, which affects their e-commerce sustainability. The study’s objective is to examine the factors and barriers affecting the e-commerce sustainability of Thai micro-, small- and medium-sized enterprises (MSMEs) based on a survey of retail and food and beverage (F&B) service MSMEs in metropolitan Bangkok. Estimations confirm the significance of the TOE framework for Thai MSMEs. Internal e-commerce tools (i.e., smartphones and websites) and external e-commerce platforms (i.e., social media, e-marketplaces, and food delivery platforms) can enhance e-commerce sustainability. However, the age of firms and owners (CEOs) affects e-commerce sustainability negatively. Exports, B2B e-commerce, and e-commerce experience can promote the e-commerce sustainability of Thai MSMEs. However, they perceive that many consumers are still not literate in using e-commerce. In addition, Thailand still has insufficient security to prevent hacking and malware. Therefore, Thai entrepreneurs’ e-commerce literacy is insufficient to enhance their e-commerce sustainability. On the other hand, sustainable e-commerce can increase customer satisfaction, loyalty, and trust through customer support, leading to more long-term online shopping. Hence, this study focuses on e-commerce sustainability-based economic dimensions, as measured by the percentage of e-commerce sales to total sales (e-commerce utilization/intensity).
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E-commerce web page classification based on automatic content extraction
(2015-08-24)
Petprasit, Warid
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Jaiyen, Saichon
Currently, There are many E-commerce websites around the internet world. These E-commerce websites can be categorized into many types which one of them is C2C (Customer to Customer) websites such as eBay and Amazon. The main objective of C2C websites is an online market place that everyone can buy or sell anything at any time. Since, there are a lot of products in the E-commerce websites and each product are classified into its category by human. It is very hard to define their categories in automatic manner when the data is very large. In this paper, we propose the method for classifying E-commerce web pages based on their product types. Firstly, we apply the proposed automatic content extraction to extract the contents of E-commerce web pages. Then, we apply the automatic key word extraction to select words from these extracted contents for generating the feature vectors that represent the E-commerce web pages. Finally, we apply the machine learning technique for classifying the E-commerce web pages based on their product types. The experimental results signify that our proposed method can classify the E-commerce web pages in automatic fashion.
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Web content extraction based on subject detection and node density
(2015-02-27)
Petprasit, Warid
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Jaiyen, Saichon
Currently, very large data have been transferred from everywhere through World Wide Web. Consequently, the information extraction systems have been arising and many researches have been focusing on those data for utilizing them. These systems are very useful for data pre-processing and cleaning for real-time applications. Moreover, these systems can make other analyzing systems to analyze the data in real time such as social network mining, web mining, data mining, or even special tasks such as false advertisement detection, demand forecasting, and comment extraction on product and service reviews. In this paper, we focus on extracting the content data of web pages in e-commerce web sites based on subject detection and node density. In the experimental results, it can signify that our proposed method is appropriated to extract the data rich region in data-intensive pages in an automatic fashion.
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Combining Group Compromised Price with bundle search strategies
(2005-12-01)
Boongasame, Labor
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Boonjing, Veera
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Thipakorn, Bundit
This paper proposes combining the buyer coalition strategy, called Group Compromised Price, with bundle search strategy to obtain the greater discounts from forming a coalition that gives the number of buyers as large as possible. Copyright 2005 ACM.

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