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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67762
Volume:
10 |
10 |
Oct 2026
Pages:
1-14
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Bachelor of Business Administration
Koneru lakshmaiah University
Bachelor of Business Administration
Koneru lakshmaiah University
While mobile trading apps and digital payment platforms have facilitated easier access to the markets than ever, there are still many members of the ‘Generation Z’ group that would not like to invest their first time. Mobile trading app and digital payment systems have helped anyone to enter the market quickly and easily, but there are those in Generation Z who still aren't convinced. This study investigates the relationship between financial, behavior and digital barriers and the investment initiation intent among the Gen z in Vijayawada, India. This approach was derived from the Theory of Planned Behavior; this theory argues that the attitude, subjective norms and perceived behavior control influence a person's intention to engage in a target behavior. Financial barriers, behavioral and digital barriers are considered as factors that decrease perceived control over investing. Primary data were collected with the help of a semi-structured questionnaire containing the five-point Likert items and 92 responses were received. The data were subsequently analyzed using Multiple Linear Regression (MLR) in MS Office Excel and the internal consistency was good to high for the constructs. The results indicate that having a digital barrier has the most significant impact on intention to invest followed by financial barrier with nothing distinguished as a behavioral barrier after accounting for the impact of digital barrier and financial barrier.
KEYWORDS
This paper discussed relationship between financial, behavioral and digital barriers concerning the initiation of investment among Gen-Z of Vijayawada has been analyzed, and it was shown that remains statistical relationship among the given variables and such a relationship can be discussed of the results from 92 survey responses with the help of Chi-square tests, ANOVA and multiple regression analysis. The two-barrier measured 43.3% of the variance for investment intent together. The strongest predictor was digital barriers while financial barriers were a smaller but still significant predictor; behavioral barriers were related to intent but did not have an independent effect when accounting for the other two types of barriers. The level of each barrier type was confirmed by chi-square tests and ANOVA showed differences by intent group (but not by gender, age, education or employment status), and income. Correlates showed that stronger barriers were related to stronger intent, suggesting that barriers are salient to those who are contemplating investing, namely to the youngest cohort. Much prior work was conducted on different facets of these investment barriers (financial, behavioral, and digital) separately, and the study adds a study conducted in a Tier-2 Indian city.
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Publication Date
10/9/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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