Marketing Mix Factors Affecting Consumer Online Shopping Decisions In Narathiwat Province After the COVID-19 Situation
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Creator Sumalee Grodgangunt
Title Marketing Mix Factors Affecting Consumer Online Shopping Decisions In Narathiwat Province After the COVID-19 Situation
Contributor Chonlakan Satabodee, Mathurose Tongintharach, Rungsiri Padungrat
Publisher Faculty of Management Science Nakhon Pathom Rajabhat University.
Publication Year 2566
Journal Title Journal of Management Science Nakhon Pathom Rajabhat University
Journal Vol. 10
Journal No. 2
Page no. 212-222
Keyword Marketing mix, Consumers, Online products, COVID-19 situation
URL Website https://so03.tci-thaijo.org/index.php/JMSNPRU/issue/view/17616
Website title https://so03.tci-thaijo.org/index.php/JMSNPRU/index
ISSN 2392-5817
Abstract The objectives of this research are 1) to study and compare consumers' online purchasing decisions. in Narathiwat province After the COVID-19 situation classified by personal factors 2) To study marketing mix factors that affect consumers' online purchasing decisions. in Narathiwat province after the COVID-19 situation, quantitative research methods the sample group is consumers who purchase products online in Narathiwat Province. there were 400 people. Data were collected using questionnaires. Statistics used in the research include frequency, percentage, mean, standard deviation, t-test, F-test, and multiple regression analysis using a stepwise method.The results of the research found that 1) Comparative analysis of consumers' online purchasing decisions. in Narathiwat province After the COVID-19 situation, it was found that consumers with different genders, ages, and educational levels and monthly income are different. Consumers decide to buy products online. in Narathiwat province After the COVID-19 situation Not different 2) Marketing mix factors have a positive effect on consumers' online purchasing decisions. in Narathiwat province After the COVID-19 situation Statistically significant at the .05 level, the marketing mix factor has a predictive power of 75.30 percent.
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