Among the employees of the textile sector in the state of Haryana, the current paper analyzes the rates of psychological capital on Innovative Performance among employees in the textile industry of Haryana. Psychological capital entails different components like optimism, hope, resilience, and self-efficacy, whereas Innovation entails components like idea generation, idea promotion and idea implementation, which is also a major source of competitiveness within the textile industry in Haryana. Due to the fast use of automation and digital technologies, textile producers have been able to grow more in productive and minimise costs. These innovations are not only able to enable businesses cut down the cost of doing business, but also make them leaders in satisfying the global demand of fast fashion. Innovative Performance among the employees is an important study because the textile industry of Haryana is also facing issues like experiencing contest, technological problems, and innovation requirements, and the employees’ capabilities become very crucial in such an instance. The sample size was 100 employees, and the statistical evaluation revealed that the employees have relatively high scores of Psychological Capital (Mean = 4.21, SD = 0.41). It was evident because male employees showed higher levels of Psychological Capital in comparison of female employees. The statistical evaluation score of innovative performance (Mean = 4.15, SD = 0.38) revealed that the employees have high innovative performance. To improve things like motivation, teamwork, idea generation, idea promotion and idea implementation and job performance in the textile industry, the results exhibit the value of positive psychological resources, high innovative performance and close social relations. The research is focused on how psychological capital can contribute to positive Innovative Performance towards the development of performance and organisation.

Today, companies and brands advertise their goods and services using various media platforms and provide consumers with offers that stand out from the competition and encourage them to make a purchase. New media are produced by technological advancements, providing customers with a diverse range of information. Prior to purchasing goods and services, customers can examine product reviews, compare prices and features across products using an internet platform, and make an informed decision. Due to the numerous and varied offers made by advertisements, digital advertising is now one of the most effective, quick, and amazing ways to generate desire to purchase.  The present study, which is descriptive and analytical in nature, attempts to examine the impact of digital advertising on consumer buying behaviour in Sivakasi Taluk with a sample of 120 respondents selected by using a convenience sampling technique. To analyse the data, a set of statistical techniques such as percentage analysis, Correlation, and Regression was used.  It is found that there is a strong relationship exists between digital advertising and consumer buying behavior, such that consumers buy more products to which they are exposed to the benefits through digital information. Therefore, it is suggested that providing close information to target customers and prospects may enhance sales volume and increase profit.

The rapid expansion of FinTech trading platforms has transformed the investment landscape in India by providing easy and quick access to financial markets. In cities like Surat, a growing number of retail investors actively use digital platforms for trading and investment purposes. However, despite technological advancement, investors often make decisions influenced by psychological and emotional factors rather than rational analysis. This study aims to examine the behavioural biases affecting investment decisions on FinTech trading platforms in Surat District. The study is descriptive in nature and is based on primary data collected from 700 FinTech investors using a structured questionnaire. Secondary data was collected from journals, reports, and previous studies. Various statistical tools such as frequency analysis, descriptive statistics, normality tests, reliability analysis, correlation, t-test, ANOVA, and chi-square tests were applied for data analysis. The findings reveal that behavioural biases like overconfidence, herd behaviour, and loss aversion significantly influence investment decisions. Results also indicate that factors such as age, experience, and platform usage patterns play an important role in shaping investor behaviour. The study concludes that while FinTech platforms encourage greater participation in financial markets, they also increase the risk of biased decision-making. Understanding these biases can help investors make better choices, assist platforms in designing responsible systems, and support policymakers in improving investor protection. The study contributes valuable insights into behavioural finance in the context of digital trading.