DATASET ON ENHANCING STOCK MARKET INVESTMENT DECISIONS THROUGH BLOCKCHAIN TRANSACTION SECURITY: A STUDY ON INVESTOR INTENTIONS
Description
This dataset was collected as part of a study investigating the impact of blockchain-based transaction security on investor intentions in the stock market. It comprises responses from 460 participants, including both experienced and potential investors, who provided insights into their perceptions of blockchain technology, investment behavior, and financial attitudes. The dataset includes demographic variables such as age, location, and monthly income, as well as key psychological and behavioral indicators based on the Theory of Planned Behavior (TPB). The dataset captures multiple dimensions of investor decision-making, including money attitude (classified into avoidance, worship, status, and vigilance), subjective norms (normative beliefs and motivation to comply), perceived behavioral control, transaction security perceptions using blockchain, and investment intention. Each variable was measured using a structured questionnaire with Likert-scale responses, allowing for a quantitative analysis of investor preferences. The dataset was processed and analyzed using Smart PLS (Partial Least Squares Structural Equation Modeling), ensuring robust validation of the proposed research model. Descriptive statistics, reliability tests, and hypothesis testing were conducted to examine the relationships between blockchain security, investor confidence, and decision-making processes. Additionally, the dataset offers insights into how financial literacy, social influence, and risk perception shape investment behavior in the presence of blockchain security mechanisms. This dataset is valuable for researchers, financial analysts, and policymakers interested in understanding how emerging financial technologies impact investor behavior and trust in stock market transactions. It provides a foundation for further studies on financial technology adoption, fraud prevention, and regulatory frameworks aimed at enhancing investment security.
Files
Steps to reproduce
This study employs a quantitative research approach using the Theory of Planned Behavior (TPB) to analyze factors influencing investors' intention to invest. The structured methodology systematically measures variables such as money attitude, subjective norms, and perceived behavioral control, while also assessing the role of blockchain-based transaction security in shaping investor confidence. A survey-based data collection method was used, targeting 460 respondents from diverse backgrounds, including both experienced and novice investors. The data was analyzed using Smart PLS, a structural equation modeling (SEM) technique that ensures statistical robustness. The study also considers control variables such as demographics, prior investment experience, and risk tolerance, providing a more nuanced understanding of investment decisions. The research follows a cross-sectional time horizon (May 18, 2024 - December 31, 2024) and uses a purposive sampling technique to select participants with relevant investment experience. The unit of analysis focuses on individuals, allowing for an in-depth assessment of investor behavior. The dataset consists of demographic data and self-assessment responses, while questionnaires and rating scales serve as the primary research tools. Data analysis follows structured steps, including data verification, coding, descriptive statistics, visualization, and hypothesis testing using Smart PLS. This method enables comprehensive evaluation of blockchain’s role in investment security while identifying key factors influencing investor decisions.