Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 2s (2025) 324 https://internationalpubls.com Building a Sustainable Future: Understanding Generation Z's Purchasing Intention Toward Green Insurance Sharon Elsen Abraham1, Mahadev Ota*2 1,2Department of Mathematics and Actuarial Science, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, 600048, Tamil Nadu, India. 1Email: sharonelsen173@gmail.com, 2Email: mahadev.ota@gmail.com *Corresponding author M- +91 8144618689 Article History: Received: 15-09-2024 Revised: 22-10-2024 Accepted: 03-11-2024 Abstract: Introduction: Green insurance involves offering insurance products and services that foster environmental sustainability. These policies aim to incentivize eco-conscious practices by providing coverage for environmentally responsible initiatives, such as renewable energy projects, energy-efficient technologies, and sustainable behaviors. As concerns over environmental conservation grow, particularly among younger generations, interest in green insurance is steadily increasing. Objective: The purpose of this study is to identify the variables influencing Generation Z's intention to purchase green insurance in South India. towards green insurance in South India. Methods: A survey questionnaire was given to a sample of Generation Z customers in the area in order to gather data for the study. The study focused on four key variables green attitude, perceived effectiveness, subjective norms, and willingness to pay. To create and validate a purchasing intention model, the study uses exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). Results: Results revealed that green attitude, perceived effectiveness, subjective norms, and willingness to pay are having positive impact on green purchase intention of Gen Z. Our findings not only provide new insights into the green purchase intention of Generation Z but also offer practical implications for marketing and policy-making. Conclusion: These insights are vital for insurance companies looking to tailor their products and marketing strategies to better appeal to Generation Z, thereby fostering the growth of the green insurance market in India. Keywords: Green insurance, green purchase intention, Generation Z 1. Introduction Green insurance refers to insurance policies and services designed to support and promote environmentally friendly practices. These policies typically encourage sustainability by covering eco- friendly projects or offering incentives for using renewable energy, energy-efficient technology, or adopting environmentally responsible intention. The rising concern for environmental sustainability has led to increased interest in green insurance, particularly among younger consumers. Studying Generation Z's purchase intentions helps businesses understand and tap into a critical consumer group that values sustainability, innovation, and digital convenience, ultimately leading to better marketing strategies and product development. Many studies have been done on both green purchase intention Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 2s (2025) 325 https://internationalpubls.com and green insurance. But no studies have particularly examined the factors affecting the purchasing intention of Generation Z towards green insurance in South India. So, we intended to fill this gap. In recent years, green insurance, insurance policies aimed at promoting sustainability through environmentally responsible practices, has gained traction as part of this green shift. Despite its growing relevance, understanding the specific factors influencing Generation Z's purchase intention towards green insurance remains an underexplored area. Jitender Kumar et al. (2024) conducted a comparative analysis of Gen X and Gen Y, revealing that attitudes and green trust are significant predictors of green purchase intention (GPI), crucial for fostering trust across age groups. Panda, D. et al. (2024) assessed Indian consumers' GPI, highlighting the rising interest in green consumer behavior in emerging markets. Mishra and Farooqi (2024) examined Indian millennials' green purchasing behavior towards fast-moving consumer goods. Madad Ali et al. (2023) investigated how millennials' green purchasing habits and buying intentions were influenced, highlighting the critical role social media had in influencing their views on sustainability. 2. Objectives Our objective is to identify and measure the factors affecting Gen Z's intention to purchase green insurance. It specifically seeks to evaluate how green attitude (GA), Perceived effectiveness (PE), subjective norms (SN) and willingness to pay (WOP) influence the purchase intentions of Indian consumers within this generation. 3. Hypothesis development The term "green attitude" describes a person's optimistic or upbeat thoughts, convictions, and emotions regarding ecologically friendly actions, goods, and procedures. In terms of consumer behavior, those who have a strong green attitude are more likely to give ecological benefits top priority when making purchases, which might raise demand for sustainable goods and services. Several studies have confirmed a positive relationship between consumers' attitudes toward green products and their purchase intentions or behaviors. Higueras-Castillo et al. (2020) emphasized attitude as a key predictor of green purchase intentions. Kumar et al. (2017) and Wang et al. (2018) supported this link, while Lai and Cheng (2016) and Yadav and Pathak (2016) found that a favorable attitude increases involvement in green purchasing decisions. So, we hypothesized the following: Hypothesis 1 (H1): Green attitude has a positive impact on the green purchase intention of Gen Z. A person's belief or perception about how likely a specific action, product, or behavior is to produce the intended or desired result is known as perceived efficacy. In various contexts, such as marketing, health, or environmental behavior, perceived effectiveness can play a crucial role in shaping attitudes, intentions, and actions. Jaiswal and Kant (2018) identified PE as a key precursor to green purchase intentions and actions. Posri (2014) and Handique (2014) found a direct positive link between PCE and eco-friendly purchasing, demonstrating that higher PCE predicts green consumer behavior. Previous studies also support this significance, such as those by Dagher & Itani (2014), Kim (2011), and Tan (2011). So we framed the following hypothesis: Hypothesis 2 (H2): Young consumers' purchase intentions are positively impacted by perceived consumer effectiveness. The apparent social pressure someone feels to participate in or abstain from a particular behavior is known as subjective norms. It illustrates how a person's decision-making process is impacted by the Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 2s (2025) 326 https://internationalpubls.com views, convictions, and expectations of important people (such family, friends, or society). Paul et al. (2016) and Liu et al. (2020) highlight the important causal link between intention and subjective norms (SN). Wang et al. (2019) identify SN as a strong motivator of environmentally responsible behavior, reflecting consumers' sense of moral obligation. Based on this, the following hypothesis was put forth: Hypothesis 3 (H3); Subjective norm is having a positive impact on GPI. A person's willingness to pay (WOP) is the maximum amount of money they are prepared to spend on a good or service. Prakash and Pathak (2017) and Yadav and Pathak (2017) claim that buyers are growing increasingly inclined to pay more for ecologically friendly products. The idea of price sensitivity is also examined by Hsu et al. (2017), who highlight consumers' willingness to pay more for goods that have a smaller environmental impact. In 2014, a global Nielsen poll found that over 55% of consumers are willing to pay more for goods and services from companies that are committed to sustainability. Thus, we formulated this theory: Hypothesis 4 (H4): The GPI is benefiting from willingness to pay. 4. Methodology A descriptive research method using a survey approach was adopted for the study. 401 Responses were collected. A self-designed questionnaire, with items adapted from various sources, was used. First, we did a multi-collinearity test to check whether any multi-collinearity problems exist and found out that there are none. The validity test was then conducted using confirmatory factor analyses (CFAs), and the fit indices revealed that the measurement model suited the data reasonably well. We used Cronbach's alpha to evaluate the scale's internal consistency. Cronbach's alpha reliability and average variance recovered are used to evaluate the model's validity and reliability. Next, a statistical program is used to evaluate discriminant validity. Finally, we used structural model assessment to test the significance of hypothesized paths. The statistical technique of structural equation modelling studies the relationships between many variables. SEM can test more dependent variables than comparable methods like regression, which can only do so at a time. After running the analysis, we found our model to be fit and our hypotheses to be significant. Exploratory factor analysis was done using the statistical package for social sciences (IBM SPSS 20), and CFA and SEM were completed by analysis of moment structures (AMOS) software 5. Results and Discussion 5.1 Multi collinearity test Since the tolerance level is greater than 0.2 and the VIF values are fewer than 10, we did not find any multicollinearity issues (Table 1). Helms and Mansfield (1982). Table. 1 Multi collinearity test Model Collinearity statistics Tolerance VIF GA 0.838 1.194 PE 0.866 1.154 SN 0.997 1.003 WOP 0.894 1.119 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 2s (2025) 327 https://internationalpubls.com 5.2 Reliability and validity of the model Cronbach's Alpha was used to measure construct dependability. The findings showed that every item is dependable because the alpha (α) value is higher than .07 (Hair et al., 2013). (Table 2.2). Table. 2 Reliability data Construct Cronbach alpha reliability GPI 0.849 GA 0.818 PE 0.698 SN 0.853 WOP 0.796 Completed using SPSS and AMOS The average variance-extracted values exceeded the 0.05 criterion for all the constructs except for perceived effectiveness, but one can accept 0.4 also, according to Fornel & Larcker (1981). Therefore, it is clear that the scales utilised for this investigation have the necessary convergent validity 5.3 Discriminant validity The square root of the AVE was compared to all inter-construct correlations in order to assess discriminant validity. Additionally, upon assessment, every ratio fell below the necessary threshold of.85 (Henseler et al., 2015). Discriminant validity was thus established. (Table 3.3). Table 3. Discriminant validity (assessed using Prof. Gaskingston statistical package) GA SN WOP PE GA 0.733 SN 0.048 0.770 WOP 0.345 -0.020 0.708 PE 0.432 -0.037 0.296 0.671 5.4 Structural Model Assessment The relationships were examined using an AMOS-generated structural equation model which is represented in Figure 1. To be deemed a well-fitting model, the values of the Tucker and Lewis (1973) index (TLI), the confirmatory fit index (CFI) (Bentler, 1990), the CMIN/df, and the goodness-of-fit (GFI) indices must all be greater than 0.90 (Hair et al., 2010). Furthermore, Hair et al. (2010) state that a model is considered appropriate If the standardized root mean square residual (RMR) and the root mean square error approximation (RMSEA) are both smaller than 0.08, which is determined by AMOS, is less than 0.05.The model's fit indices were within the permissible range. With a squared multiple correlation (R2) of 0.42 for GPI, green attitude, perceived efficacy, subjective norms, and willingness to pay explain for 42% of the variance in GPI. Also, we got the Standardized RMR = .0364. The study assessed the impact of green attitude, perceived effectiveness, subjective norms, and Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 2s (2025) 328 https://internationalpubls.com willingness to pay on GPI. All the results were positive and significant, supporting their respective hypotheses. Table: 4 present hypotheses results. Table. 4: Hypothesis results Hypothesized Relationship Standardized Estimates t-value p-value Decision GPI→ GA .132 2.094 0.036 Accept GPI→ PE .481 6.484 0.000 Accept GPI → SN .127 2.499 0.012 Accept GPI → WOP .182 3.140 0.002 Accept Figure.1: Structural equation model 6. Conclusion In conclusion, this study addresses the key factors influencing Generation Z’s green insurance purchasing intentions in South India. 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