Marketing Mix Factors Affecting Consumers' Decision-Making in Purchasing Football Boots in Mueang Khon Kaen District, Khon Kaen Province

Abstract

The objectives of this research were 1) to study of the marketing mix level of consumers in Khon Kaen Municipality 2) to study on the Purchasing decision football Boots of consumers in Khon Kaen Municipality 3) to study marketing mix factors affecting for purchasing decision football boots in khon kaen municipality khon kaen province. The sample group consisted of 400 consumers who wanted to buy football boots in Khon Kaen Municipality. The research instruments were a questionnaire five rating scale questions with a confidence value of 0.90. The statistics used for data analysis were percentage, mean, standard deviation, and Stepwise Multiple Regression Analysis. The research findings were as follows: 1) Marketing mix level of consumers in Khon Kaen Municipality Khon Kaen Province Overall, it is at a high level (x=4.14) when considering each aspect. with the highest average of the 3 ranks, it was found that the marketing promotion aspect (x= 4.22) had the highest average product side (x=4.18), price side (x= 4.09) and distribution channel side (x = 4.08) 2) The level of decision making for purchasing football shoes by consumers in Khon Kaen Municipality. Khon Kaen Province It is at a high level (x=4.16). When considering the 3 highest average aspects, it was found that the purchasing decision aspect It has the highest mean (x= 4.28), followed by awareness of needs (x= 4.19) and post-purchase behavior (x=4.15). 3) The multiple regression analysis found that the four independent variables jointly explained the factors affecting the decision to buy football boots of consumers in Khon Kaen Municipality, Khon Kaen Province, explaining the factors affecting the decision by 72.80 percent. When considering the independent variables that had the best influence on the decision to buy football shoes of consumers in Khon Kaen Municipality, the product factor (X1) (=0.343) was followed by price factors (X2) (=0.219), marketing promotion factors (X4) (=0.152), and distribution channels (X3) (=0.127). The prediction equation can be written in the form of raw scores and standard scores as follows: Raw Score Predictive Equation: Y ̂ = . 409+.343(X1) +.219(X2) +.152(X4) +.127(X3)