Effect of Payment Anxiety and Trust in shaping Behavioral Intention toward Digital Payment

Dataset Description This dataset contains primary mixed-methods data measuring the adoption level and user acceptance of two main digital payment methods: QRIS (Quick Response Code Indonesian Standard) Barcode and NFC (Near Field Communication) / QRIS Tap. The data was collected to analyze the factors influencing users' Behavioral Intention in adopting contactless payment technologies based on technology acceptance models, with a specific focus on performance expectancy, ease of use, trust, and payment anxiety. Methodology and Data Collection Quantitative Method (Survey): Online questionnaire survey (Google Forms) respondents between April 20, 2026, and May 5, 2026. Qualitative Method (Interviews): Semi-structured interviews with 5 selected respondents to gain deeper insights into the quantitative findings. Questionnaire Translation & Adaptation: The questionnaire items were adapted from established theoretical models (e.g., UTAUT/TAM) and translated into Indonesian for the respondents. (Note: If you used back-translation or a specific expert validator, you can add that detail here). File Formats: Excel (.xlsx) for survey responses (56 columns) and Word document (.docx) for interview transcripts. Quantitative Data Structure and Variables (Constructs) Each technology (QRIS Barcode and NFC) is measured using 5 main variables, each with 5 indicators using a Likert scale: PE (Performance Expectancy): The extent to which users believe the technology helps attain gains in transaction speed and efficiency. PEOU (Perceived Ease of Use): The degree to which users believe using the technology will be free of effort. TR (Trust): Users' level of trust in system security, third-party reliability, and personal data protection. PA (Perceived Anxiety / Risk): The level of anxiety or concern regarding security risks, system errors, financial loss, and fraud. BI (Behavioral Intention): Users' intention or plan to continue using, preferring, and recommending the technology. Qualitative Data Analysis Findings The qualitative transcripts explore three main thematic issues: Performance Expectancy & Ease of Use (Similarity Issue): Respondents generally feel that the physical difference between scanning (QRIS Barcode) and tapping (NFC) does not significantly impact their perceived usefulness. Both methods are considered equally practical because the core benefit is being "cashless"—speeding up transactions and eliminating the need for exact change. However, it was noted that NFC availability at merchants is not yet as widespread as QRIS Barcode. User Anxiety (Payment Anxiety) & Familiarity: Most respondents experienced anxiety when they first started using digital payments, fearing double deductions, system errors, or hacks. However, this anxiety significantly decreased as they became familiar with the technology. This reduction in anxiety is heavily supported by the transparency of banking/e-wallet systems, such as real-time notifications, clear transaction histories, and account mutation features, which serve as proof of transaction if errors occur. User Trust & NFC System Design: Regarding the rapid nature of NFC transactions, respondents emphasized the need for strong confirmation indicators to build trust. Visual notifications stating "Transaction Successful" with nominal details on the app screen, as well as audio confirmations (e.g., AI voice or machine beep at the cashier), are highly expected. Furthermore, some respondents expressed specific security concerns about NFC, noting it feels more vulnerable than QRIS Barcode which requires a PIN/password. To mitigate this, users suggested adding extra security layers for NFC, such as dual confirmation (biometrics or PIN) and time-out settings to prevent unauthorized balance deductions during network lags or fraudulent tapping. Reuse Potential This dataset is highly suitable for statistical testing (using SEM-PLS, AMOS, or linear regression via SPSS/Python/R) to validate digital payment adoption models, as well as for thematic qualitative analysis regarding consumer trust and risk perception in financial technology.