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This research explores how men and women differ in their approach to investing and making financial decisions, focusing on salaried personnel in Chennai urban area. Today, people have many choices when it comes to investing their money, such as bank deposit, gold, insurance, mutual funds, and shares. However, the way individuals select these options is not the same for everyone, as it is influenced by factors like income, financial knowledge, willingness to take risks, and gender.
The study is based on information collected directly from 112 respondents through a questionnaire, with an equal number of men and women participants. A descriptive method was used to study the data, and tools like percentage analysis and the chi-square test helped in understanding patterns and relationship between gender and funding choices.
The results clearly show a difference in preferences. Men individuals are more likely to choose investment options that involve higher risk but offer better returns, together with stocks and mutual funds. On the other hand, women participants tend to select safer options like bank deposit and insurance, showing a more cautious approach. Differences were also noticed in how both groups view risk and make financial decisions.
In conclusion, the study highlights that gender has a noticeable impact on investment behaviour. Recognizing the ones versions can be useful in improving financial awareness and in designing better investment strategies for salaried individuals
"A GENDER-BASED CLASSIFICATION OF INVESTMENT BEHAVIOUR AND FINANCIAL DECISION-MAKING AMONG SALARIED EMPLOYEES IN CHENNAI CITY", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.a725-a729, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604103.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator