พฤติกรรมของผู้บริโภคเจเนอเรชันวายในอำเภอเมืองเชียงใหม่ต่อการใช้บริการสั่งอาหารแบบจัดส่งผ่านโมไบล์แอปพลิเคชัน

Abstract

The purpose of this independent study is to investigate consumer behavior of Generation Y in Mueang Chiang Mai district regarding using food delivery services via mobile applications. Questionnaires were used as a tool to gather data from 385 samples who are in generation Y, are living in Mueang Chiang Mai district, and have used the food delivery services in the past 3 months. The data were analyzed using descriptive statistics in the form of frequency, percentage, and mean and using inferential statistics in the form of Independent-Sample T-test and One-Way ANOVA. The majority of the samples were females, holding a bachelor's degree or lower, working at private companies, with an average monthly income of lower than 20,000 baht. The online marketing mix factors that had the greatest average impact on the use of food delivery services via mobile applications in each factors are as follows: for the product factors, stable application system; for the price factors, reasonable price for service; for the place factors, convenient and prompt payment channels; for the promotion factors, collaboration between applications and restaurant partners on food promotions; for the personalization factors, system's capability of suggesting preferred restaurants; and for privacy factors, not disclosing users' personal information, such as address, telephone number or credit card number, to people who are not related to the service. The results demonstrated that the influence of online marketing mix on the use of food delivery services via mobile applications varied according to different demographic characteristics. The product factors had a different effect on consumers' usage of food delivery services according to gender, education level, occupation, and average monthly income. The influence of price and place factors differed according to gender and occupation. The impact of promotion factors differed according to gender, occupation, and average monthly income. Personalization factors had a different effect according to education level and average monthly income. Finally, the impact of privacy factors differed according to occupation and average monthly income.