Female entrepreneurship in the handicraft sector is gaining global interest, particularly in developing nations like India. This study aims to identify the key constructs influencing women's entrepreneurial intentions and behavior in the Indian handicraft industry. Female entrepreneurship is crucial for economic progress, offering opportunities for innovation, job creation, poverty reduction, and socio-economic growth. However, despite its significance, research in this area, especially concerning the Indian context, remains limited. This study addresses this gap by exploring various factors influencing women's entrepreneurial journey, from their student years to post-graduation. The research employs a survey research design with convenience sampling, utilizing AMOS 25 software for data analysis. The study acknowledges the traditional cultural constraints that often impact Indian women's participation in entrepreneurship while highlighting the success of many Indian women entrepreneurs across diverse sectors.

The literature review examines existing research on female entrepreneurship, focusing on intention and the factors influencing it. A search of the Scopus database yielded 47 articles after refining the search criteria to focus on empirical papers exploring factors influencing female entrepreneurs' inclination to start a new venture. The review encompasses studies examining gender differences in entrepreneurial goals (Shabsough et al., 2021), risk-taking behavior (Fallatah, 2012), the impact of gender disparities and challenges faced by women entrepreneurs (Bhatti et al., 2021), the role of education and support (Abebe & Kegne, 2023), and the influence of social networks and resources (Alonso-Galicia et al., 2015). The review highlights existing research gaps concerning the crucial components originating from underlying theoretical models and proposes a model to evaluate women's entrepreneurial aspirations, incorporating innovativeness and expected social support as critical factors.

The study uses a survey research design with convenience sampling, collecting data from female students enrolled in various business and entrepreneurial courses at Indian universities. A questionnaire was employed with 36 items measured on a 7-point Likert scale, including open-ended and closed-ended questions. The questionnaire also incorporated nine demographic questions. 631 questionnaires were distributed, yielding 482 responses after excluding those with uniform responses. The constructs were operationalized using scales adapted from previous studies and included: entrepreneurial intention, subjective norm, attitude, anticipated social support, anticipated inclination, anticipated behavioral control, innovativeness and digitalization, and entrepreneurial behavior. Data analysis was conducted using AMOS 25.0. The researchers first assessed common method bias and normality, then performed confirmatory factor analysis (CFA) to evaluate the measurement model and structural equation modeling to assess the structural model. Harman's single-factor test was used to check for common method bias. The CFA assessed convergent and discriminant validity using measures such as factor loading, Cronbach's alpha, average variance extracted (AVE), and the Heterotrait-Monotrait (HTMT) ratio. Fit indices such as RMSEA, GFI, CFI, and AGFI were used to assess the model fit.

The data analysis revealed that the constructs exhibited acceptable levels of reliability and validity. The structural model fit the data well, with significant relationships identified between various constructs and entrepreneurial intention and behavior. Specifically, anticipated feasibility, anticipated inclination, entrepreneurial attitude, and subjective norm were found to directly influence entrepreneurial intention. Innovativeness and digitalization, anticipated social support, and anticipated behavioral control were found to significantly influence entrepreneurial behavior. Furthermore, entrepreneurial intention strongly predicted entrepreneurial behavior. The model explained 74% of the variance in entrepreneurial intention and 46% of the variance in entrepreneurial behavior. The indirect effects of anticipated feasibility, anticipated inclination, entrepreneurial attitude, and subjective norm on entrepreneurial behavior through entrepreneurial intention were also significant.

The findings support the proposed integrated model combining elements of the Theory of Planned Behavior (TPB) and the Entrepreneurial Event Model (EEM), extended with constructs such as innovativeness, digitalization, and anticipated social support. The strong positive relationship between entrepreneurial intention and behavior suggests that a clear intention to start a business translates into action. The significant influence of social support, attitude, and perceived behavioral control highlights the importance of these factors in shaping entrepreneurial endeavors. The study contributes to the existing literature by offering a more comprehensive model tailored to the Indian context and specifically focusing on women in the handicraft industry. While some findings align with previous research, others differ, potentially reflecting the specific cultural context and the focus on students already engaged in entrepreneurial activities.

This study provides valuable insights into the factors driving female entrepreneurship in the Indian handicraft industry. The validated model offers a robust framework for understanding entrepreneurial intentions and behavior. The findings emphasize the importance of educational programs, social support, and a positive attitude in fostering entrepreneurship among women. Future research could explore the role of moderating variables and conduct longitudinal studies to track changes in entrepreneurial intentions over time.

The study's limitations include the use of convenience sampling, potentially limiting the generalizability of the findings. The cross-sectional design prevents the establishment of causal relationships. Future research could employ a larger, more representative sample and a longitudinal design to address these limitations. Additionally, incorporating moderating variables could enrich the understanding of the relationships identified in the study.