Factors Influencing the Adoption of Loan Payment Services, Through Digital Service Channels of the Government Housing Bank Case Study Loan Repayment Machine in Bangkok

  • สุชีวา คงมั่ง
  • รวิดา วิริยกิจจา
  • ณัฐพันธ์ บัววราภรณ์
  • พนิตา สุรชัยกุลวัฒนา
Keywords: The Loan repayment machine, Influencing the acceptance

Abstract

The objectives of this research are 1) to study the factors influencing the acceptance of the use of Loan repayment machine (LRM) 2) to suggest ways to develop the service system of Loan repayment machine (LRM) To reduce service usage Payment of the loan at the counter Bank branch Which collected data from Design Thinking and collecting data from 200 questionnaires distributed to those who use the Loan repayment machine (LRM) at the branch offices of the Government Housing Bank In Bangkok A total of Set 20 branches each, 10 branches analyzers using t-test and analysis of variance (One-way ANOVA) to determine the relationship between demographic factors And technology acceptance factors Influencing the acceptance of the Loan repayment machine (LRM) service of the Government Housing Bank In Bangkok from average (Mean) standard deviation (Standard Deviation) This study found that Most of the samples were female, aged 36 years and over. Is a private company employee With an average personal income of 20,000 - 30,000 baht per month, collecting data from people who use the Loan repayment machine (LRM) when considering each factor Both perception of ease of use, awareness of the benefits of use, current usage and future use Can summarize the study results of each factor from the average thinking It was found that the perception of the ease of use of the Loan repayment machine (LRM) is an average of 4.68, followed by the Loan repayment machine (LRM) which is easy to find the location. The average value of 4.64, respectively, was statistically significant at the level of 0.05. The technology acceptance factor had an effect on the acceptance of the use of the Loan repayment machine (LRM) services in Bangkok. At the statistical significance level of 0.05.

Published
2020-01-30

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