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This study aims to understand how brand personality affects purchase intention through brand love and perceived quality in e-commerce.

Three hundred forty-eight users of e-commerce sites in New Delhi, India, were surveyed for the study. The data set was examined using confirmatory factor analysis, and the research hypotheses were assessed using structural equation modeling.

Two important conclusions emerged from the study. First, brand love and perceived quality have been considerably and favorably influenced by all six dimensions of brand personality of e-commerce brands. Second, the purchase intention toward the e-commerce sites is significantly and positively impacted by brand love and perceived quality.

This study by exploring various dimensions of brand personality, will assist e-commerce executives in increasing purchase intention toward the e-retailing sites.

This research is supposed to be the foremost to look at how brand personality, through brand love and perceived quality affects purchase intention toward e-commerce websites. The attachment theory is used in this study as a theoretical foundation for linking e-commerce brand personality to customers’ purchase intentions via brand love and perceived quality.

Introduction: Data play a very significant role in solving the problem faced at micro and macro levels. Financial inclusion and insurance penetration have been a major problem of developing economies. These two economic indicators can be strengthened with the emergence of data alchemy.

Purpose: The present research study is conducted with the objective of measuring the impact of technological infrastructure, data alchemist techniques, and regulatory environment on insurance penetration and financial inclusion.

Methodology: To meet the research objectives, data were collected through a random sampling technique from the insurance agents in Mumbai, which can be considered the heart of insurance in India. On the data collected, the partial least squares (PLS) algorithm was applied using smart PLS software. PLS is a statistical method used for predictive modeling and analysis of complex data with multiple variables.

Findings: The final results revealed a significant relationship between data alchemy techniques and financial inclusion. Also, a significant impact on the financial inclusion level of the regulatory environment is also recorded. However, in a developing country like India, currently data alchemy techniques are not significantly impacting insurance penetration.