Data for Survey of Digital Banking Adoption in Mae Hong Son Thailand
Description
This dataset, collected in March 2024 from 426 rural farm households in Mae Hong Son province, Thailand, was designed to examine the key factors influencing digital banking adoption among small-scale farmers. Guided by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study tests the hypothesis that the 5S framework—Subsidy, Security, Signal, Satisfaction, and Socio-demographic factors—significantly affects both the likelihood of adoption (analyzed using probit models) and the intra-household adopter ratio (analyzed using tobit models).
Files
Steps to reproduce
The questionnaire was first developed in English, validated, and translated into Thai before administration through Microsoft 365 forms, with offline collection when necessary. It comprised mandatory listed-choice and Likert-scale questions across five sections: screening, demographics, farming experience, banking experience, and scaled items. Branching logic skipped irrelevant questions, and help texts enhanced clarity. A pilot with 30 households outside the sample refined overlapping and income items. Final data were collected face-to-face in March 2024, during the harvest season, by six enumerators across seven districts, with household coordination supported by village leaders. Key variables were selected, with certain Likert-scale items recoded into binary form to meet the requirements of probit and tobit regression models. Data analysis was conducted using Stata 17.0. Three files are provided: (1) an Excel file containing two worksheets—one describing the variables and the other presenting the raw data, (2) the Stata dataset, and (3) the Stata do-file.
Institutions
- Asian Institute of Technology