Scale Development and Measurement Model of Behavioural Biases, Financial Capabilities, and Investment Decisions - A Study of IT Sector Employees in Bengaluru City
- Vineetha Vijayan Department of Commerce, Bishop Heber College (Autonomous) (Affiliated to Bharathidasan University, Tiruchirappalli - 620 024), Tamil Nadu, India, India
- Nidhish Padmanabhan Department of Commerce, Bishop Heber College (Autonomous) (Affiliated to Bharathidasan University, Tiruchirappalli - 620 024), Tamil Nadu, India, India
-
C. Precilla
*
Department of Commerce, Bishop Heber College (Autonomous) (Affiliated to Bharathidasan University, Tiruchirappalli - 620 024), Tamil Nadu, India,
India
Abstract
This study examines the behavior and financial ability bias structures and their impact on the investment decision-making of the Information Technology (IT) sector employees residing in the Bengaluru Urban region of India. Drawing upon behavioural finance theory, the research conceptualizes a framework in which the Narcissism Bias (NRB), Cognitive Dissonance Bias (CDB) and Heuristics Bias (HB) are the antecedent constructs operating through Financial Risk Tolerance (FRT) and Financial Literacy (FL), having the capabilities to influence the Investment Decision (ID). A structured questionnaire was developed, validated by the domain experts, and administered to 85 IT professionals in a pilot study. Furthermore, the measurement instrument was refined through Exploratory Factor Analysis (EFA) using Principal Component Analysis with Varimax Rotation in SPSS, and subsequently validated through Confirmatory Factor Analysis (CFA) using AMOS. The EFA yielded a six-factor solution explaining 67.69% of the total variance, supported by a KMO of 0.801 and a significant Barlett’s Test (χ² = 2171.429, df = 595, p < .001). The CFA final model produced an acceptable fit (χ² = 479.252, df = 451, p = .173; CMIN/DF = 1.063; RMSEA = .027; CFI = .790; IFI = .843; AIC = 633.252), which is acceptable given the pilot study sample size of 85 respondents. All the indicator loadings were statistically significant (p< 0.05), with most standardised loadings exceeding 0.70. Three items were eliminated during EFA (HB3, HB5, CDB1), and the FL construct was excluded from CFA due to its mixed objective and subjective design, which led to a separate analytical treatment. The findings validated a five-construct measurement model and offered theoretical and practical implications for understanding financially distorted decision-making amongst IT professionals.
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