FACTORS INFLUENCING THE DECISION TO BUY A SAMSUNG MOBILE PHONE BRAND OF CONSUMERS IN PATHUM THANI PROVINCE

  • รัฐพล วงษ์ทน วงษ์ทน
  • พัชร์หทัย จารุทวีผลนุกูล จารุทวีผลนุกูล
Keywords: Decision Making to Buy, Consumer Behavior, Marketing Mix

Abstract

                The objectives of the independent study "The factors influencing the decision to buy a Samsung mobile phone brands of consumer in Pathum Thani province" were (1) to study the factors influencing the decision to buy mobile phones, Samsung brand of consumers in Pathum Thani province, (2) to study the buying behavior affecting the decision to buy Samsung mobile phone brands of consumer in Pathum Thani Province, and (3) to study the marketing mix factors influencing the decision to buy Samsung mobile phone of consumers in Pathum Thani province. The population of this research is consumers living in Pathum Thani Province, the 1,116,964 people. Data by using the formula Yamane of 400 people were sampled by purposive sampling. Data were analyzed by statistics using percentage, frequency, mean, standard deviation, and compared the difference with t-test, one way ANOVA, and multiple regression analysis.  

The results showed that most of the respondents were male (217 people), age 20 - 25 years (174 people), with bachelor degree (216 people.), having professional employees(149 people) and earn 10,001 - 20,000 baht (165 people.) For results of hypothesis testing, it was found that (1) personal factors; sex, age, occupation, and average income per month have varying effects on the decision to purchase mobile phones, Samsung brand of consumers in Pathum Thani province, at significant level of 0.05, (2) the buying behaviors, including memory of the phone and places have varying effects on the decision to purchase mobile phones, Samsung brand of consumers in Pathum Thani province, at significant level of 0.05, and (3) marketing mix factors including the price (β = 0.516) followed by the product (β = 0.396) and the smallest is the promotion. (β = 0.123), have the predictive power 62.4 (Adjusted R2 = 0.624).

Published
2018-09-19
Section
Business Administration and Management Articles

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