Women’s empowerment is a process that results in the movement of position from powerless to powerful. This means making women stronger and more financially, socially, and politically skilled. Women’s empowerment is a multidimensional concept in which women achieve greater control over material, financial, and intellectual resources ( Mohapatra & Sahoo, 2016). Perceived social support refers to an individual’s perception of material, psychological, and overall support from friends, family members, and other members of society whenever required ( Ioannou, Kassianos, & Symeou, 2019). Existing literature clarifies that perceived social support advances the sense of social empowerment in women ( Moradi & Funderburk, 2006). Perceived social support is critical predictor of social empowerment in women. Women’s perceived ability to draw attention to needed help contributes to their empowerment ( Cakir & Guneri, 2011). This study indicates that various types of perceived social support impact women’s empowerment differently ( Barringer, Hunter, Salina, & Jason, 2016). Consequently, positive perceived social support helps women empower resources to cope with multiple stressors and belonging support enhances perceived empowerment among women, creating an environment in which they engage in positive activities ( Barringer, Hunter, Salina, & Jason, 2016). However, there are relatively few empirical findings on the relationship between these two variables among self-help group members.

Life satisfaction has become an important issue in recent years for most organizations and governments. Countries such as the UK, Germany, Australia, and the USA spend considerable amounts of money and continuously track life satisfaction over time. The level of empowerment is significantly related to life satisfaction, regardless of income, gender, religion, geographical location, and so on ( Hossain et al., 2019). The perception of empowerment substantiates the sense of control over one’s life, improves self-esteem, and increases life satisfaction ( Cheung et al., 2005). Thus, life satisfaction, self-esteem, and a sense of mastery are the outcomes of social empowerment. The study found that women get more life satisfaction from being a self-help group member than from having a say in production decisions ( Hossain et al., 2019).

Self-help group members experience several life challenges that require support from others. The others referred to here were family, friends, and colleagues. It is evident from research that support from family and friends is the strongest determinant of life satisfaction ( Akanni & Oduaran, 2018; Kasprzak, 2010). Social support plays a significant role in managing stress, leading to higher life satisfaction ( Mahanta & Agarwal, 2013). Females reported higher levels of perceived social support from friends than males, but there was no significant difference between males and females in terms of social support from family.

Furthermore, females were found to have higher life satisfaction than males ( Mahanta & Agarwal, 2013). An increase in the extent of attachment leads to an increase in life satisfaction and a decrease in attachment among people, leading to a reduction in life satisfaction ( Shahyad, Besharat, Asadi, Shiralipour, & MirnaderMiri, 2011). Thus, perceived social support is a significant factor that influences life satisfaction ( Lu et al., 2015).

Hypothesis development

The study’s hypothesis was developed after the conceptual framework was finalized. The first hypothesis explored the relationship between Perceived Social Support (PSS) and Social Empowerment (SE). H1:

Perceived Social Support (PSS) significantly influences Social Empowerment (SE).

The second hypothesis investigates the relationship between perceived social support and life satisfaction. H2:

Perceived Social Support (PSS) positively associated with Life Satisfaction (LS).

hypothesis is developed to understand the nature of the relationship between social empowerment and life satisfaction. H3:

Social Empowerment (SE) is positively related to Life Satisfaction (LS).

The mediating role of SE

The latent construct PSS is hypothesized to influence SE and Effects. The potential mediating effect of social empowerment is interesting to fill this research gap. Therefore, the fourth and fifth hypotheses were developed as follows: H4:

Social Empowerment (SE) significantly mediates the relationship between PSS and LS.

Moderating role of Decision Making (DM) and External Communication (EC)

This study is also interested in understanding and confirming the moderating role of DM and EC in the relationship between the constructs. Hence, this study develops the following hypothesis to test this moderating effect: H5a:

Decision making (DM) significantly moderates the relationship between PSS and LS.

In order to assess the hypothesis of the study, a comprehensive empirical investigation was carried out involving the members of three notable self-help groups: the Navodaya Self-Help Group, the Sthri Shakthi Self-Help Group, and the Shri Kshetra Dharmasthala Rural Development (SKDRD) self-help group, all located in the vibrant region of Southern Karnataka, India. The research utilized a judgmental sampling method, a strategic approach that allowed us to select participants based on our informed knowledge and insights. This method was deliberately chosen to ensure that we could target a specific demographic with anticipated characteristics that aligned with the objectives of our study. The final sample comprised a total of 333 individuals.

Among the respondents, the largest segment, accounting for 43%, belonged to the middle age group of 40 to 50 years, indicating a robust representation of middle-aged individuals. In addition, 22% of the participants were in the 50 to 60 age range, while 18% were younger than 30. The study also captured insights from 17% of respondents who were aged 60 and over, highlighting a diverse age spectrum within the groups. More than 63% of the respondents were married, demonstrating a strong commitment to personal relationships, contrasting with approximately 37% who identified as single, divorced, or widowed.

When examining employment status, a significant portion of the respondents, 46%, identified themselves as homemakers, reflecting the traditional roles often observed in the community. Meanwhile, 30% of the population were daily wage earners, who typically engage in various manual labor jobs to support their families. Around 24% were employed in the private or public sector, contributing to the local economy in different professional capacities.

Remarkably, the participants in this study exhibited a deep-rooted connection to their self-help groups, with over 80% having engaged in their activities for more than a year. This statistic underscores not only their commitment but also the meaningful experiences and support that self-help groups provide to their members, fostering personal growth and community resilience.

Data were gathered through a carefully designed survey questionnaire administered during the regular weekly meetings of the Self-Help Group (SHG) located in the southern Karnataka. The investigator actively facilitated the survey process, ensuring that all participants understood the questions and had the necessary support to complete the questionnaire. The researcher secured both verbal and written permission from all participants. The informed written consent form was included with the questionnaire. Verbal consent was obtained to affirm understanding of the research and participation in the study. Furthermore, data collection was voluntary, and all responses were anonymized. Participants were informed of their right to withdraw from the survey at any time, with the assurance that their personal information would be kept confidential. To ensure a comfortable setting, each member was allocated 15 minutes to complete the survey at their own pace thoughtfully. Once the members finished, the investigator collected the completed questionnaires.

The model formulated in this study comprises five distinct variables that interact to explore the relationship between perceived social support and life satisfaction. The independent variable, perceived social support (PSS), is at the forefront, quantified using a comprehensive 12-item scale developed by Zimet, Dahlem, Zimet, and Farley (1988). This scale assesses the extent to which individuals feel supported by their social networks. The dependent variable under investigation is life satisfaction, evaluated through a 5-item scale created by Diener, Emmons, Larsen, and Griffin (1985). This scale captures individuals’ overall contentment with their lives, providing insights into their subjective well-being.

In addition to these primary variables, the model incorporates one intervening variable, Women’s Social Empowerment, which reflects how women feel empowered to make decisions and take action. Furthermore, the model features two moderators: decision-making and external communication. These moderators examine how the ability to make choices and communicate with others can influence the relationship between perceived social support and life satisfaction. The measures for Women’s Social Empowerment, decision-making, and external communication are derived from a scale developed by Chatterjee, Gupta, and Upadhyay in their 2018 research titled “Empowering Women and Stimulating Development at the Bottom of the Pyramid through Micro-entrepreneurship.”

To gauge responses for all these constructs, participants completed a 5-point Likert scale survey, where a score of 5 indicates “Strongly Agree,” a score of 4 represents “Agree,” a score of 3 signifies “Neutral,” a score of 2 denotes “Disagree,” and a score of 1 means “Strongly Disagree.” This structured approach to measuring the variables enhances the depth and clarity of the study’s findings. Common Method Bias: To mitigate the risk of common method bias, the questionnaire was designed with the constructs arranged in a random order. This strategy was implemented to discourage respondents from making assumptions about causal relationships between the constructs based on their positioning in the survey. Furthermore, the analysis included a collinearity test, which reported a Variance Inflation Factor (VIF) value of less than 5. This result indicates that concerns regarding common method bias are unlikely to affect the findings of this study, thereby enhancing the validity of the results.

In Figure 1, the numbers on the arrows are path coefficients that indicate the direct effect of one variable (cause) on another variable (effect). The weights of the different path coefficients enabled us to rank their relative statistical importance. The path coefficient values between the two constructs of the structural model should be more than 0.20 to demonstrate its significance ( Wong, 2013). The path coefficient value in Figure 1 (inner model) explains that Perceived Social Support (PSS) has the most substantial effect on Social Empowerment (0.725) and Life Satisfaction (0.580). Social empowerment was a good predictor of life satisfaction (0.407).

The R ² values or numbers in the circle show the extent to which the other latent variables explain the latent variable’s variance. In management research, the R ² of 0.75 was substantial, 0.50 is moderate, and 0.25 is weak ( Wong, 2013). Figure 1 above shows that the coefficient of determination R ² is 0.845 for the life satisfaction endogenous latent variable, implying that exogenous latent variables, i.e., perceived social support and social empowerment) explain 84.5% of the variance in life satisfaction of women’s self-help group members. Also, Figure 1 illustrates that the coefficient of determination R ² is 0.526 for the women’s social empowerment, implying that perceived social support explains 52.6% variance in the social empowerment (SE).

Table 2 presents the path, t-value, and statistical significance values for all the variables considered for the study. The positive path coefficient value in the relationship between different constructs considered for the study indicates a direct relationship between the two constructs. Using the bootstrapping procedure in the PLS-SEM, T-statistics were checked to see if the inner model’s path coefficient was significant. The path coefficient will be substantial if the T-statistics is higher than 1.96 using a two-tailed T-test with a significance level of 5% ( Wong, 2013). Table 2 explains that PSS (β=0.725, t=30.548, p=0.000) strongly influences the SE, supporting H1. Further, the exogenous variable PSS (β=0.580, t=13.781, p=0.000) and SE (β=0.407, t=9.446, p=0.000) strongly predict the endogenous variable life satisfaction, supporting H2 & H3.

A mediation analysis was performed to assess the mediating role of social empowerment in the relationship between PSS and LS. The results (see Table 3) reveal a significant indirect effect of PSS on life satisfaction (β=0.295, t=9.084, p=0.000). PSS’s total effect of PSS ( Table 3) on LS was significant (β=0.875, t=64.127, p=0.000). However, as shown in Table 3, the effect of PSS on LS was significantly reduced with inclusion of the mediator (SE) (β=0.295, t=9.084, p=0.000). The difference in the values can be easily seen in the results. This shows the mediating role of SE in the relationship between PSS and LS, thus supporting H4.

This study assessed the moderating role of DM on the relationship between PSS→ LS and SE→ LS. Without including the moderating effect (DM*PSS), the R-squared value for LS is 0.845. This shows that PSS accounts for an 84.5% change in LS. Including the interactive term, the R-square increased to 87.4%. This indicates an increase of 2.9% in variance explained by the dependent variable (LS).

Furthermore, the significance of this moderating effect was analyzed. The results indicate a negative and insignificant moderating impact of DM on the relationship between PSS and LS (β=-0.001, t=0.025, p=0.980), not supporting H5a. This shows that, with an increase in DM, the relationship between PSS and LS is not weakened. Table 4 presents a summary of the moderation analyses. A similar observation was made in the moderating effect of DM on the relationship between SE and LS, not supporting H5b.

Further, a slope analysis is presented to better understand the nature of the moderating effects ( Figure 3).

As shown in Figure 2, the line is flatter for low DM. This indicates that, at a low level of DM, the impact of PSS on LS is like that of higher DM. At higher DM, the line tends to flatter; this shows that at higher DM, the increase in PSS does not lead to a similar change in LS. In conclusion, a higher DM does not weaken the impact of PSS on LS.

F ² Effect size

Regarding the interactive effect, the f ² effect size indicates the extent to which moderation explains the endogenous construct. The f-square effect size was 0.00, which was insignificant. According to Cohen ( Cohen, 1988), f ² effect size values of 0.02, 0.15, and 0.35 are considered as small, medium, and large effect sizes of moderation, respectively. In this study, there was a negligible or insignificant moderating effect. This indicates that the moderating effect does not contribute significantly to explaining the endogenous construct (LS).

This study assessed the moderating role of EC on the relationship between constructs. Without including the moderating effect (EC*PSS), the R-squared value for LS is 0.845. This shows that PSS accounts for an 84.5% change in LS. Including the interactive term, the R-square increased to 89.9%. This indicates an increase of 5.4% in variance explained by the dependent variable (LS).

Furthermore, the significance of this moderating effect was analyzed as shown in Figure 4. The results indicate a positive and significant moderating impact of EC on the relationship between PSS and LS (β=-0.167, t=5.370, p=0.000), supporting H6a. This indicates that increased EC strengthens the relationship between PSS and LS. Table 5 presents a summary of the moderation analyses.

Further, slope analysis is presented to better understand the nature of the moderating effects ( Figure 5).

As shown in Figure 5, the line is much steeper for low EC, indicating that at a low EC level, the impact of PSS on LS is much more robust compared to higher EC. However, at higher EC, the line tends to straighten, indicating that the increase in PSS leads to a similar change in LS at higher EC. In conclusion, higher EC strengthens the impact of PSS on LS.

F ² Effect size

Concerning the interactive effect, the f ² effect size indicates the extent to which moderation explains the endogenous construct. The F-squared effect size was 0.136, which was significant. According to Cohen ( Cohen, 1988), the f ² effect size values of 0.02, 0.15, and 0.35 are considered small, medium, and large effect sizes of moderation, respectively. In this study, there was a moderately significant moderating effect. This shows that the moderating effect significantly explains the endogenous construct (LS).

Furthermore, this study assessed the moderating role of EC on the relationship between SE and LS. The results indicate a negative and significant moderating impact of EC on the relationship between SE and LS (β=-0.290, t=8.589, p=0.000), supporting H6b. This shows that an increase in EC weakened the relationship between SE and LS. The F-squared effect size was 0.488, which was significant. This reveals that the EC has a large, significant moderating effect. This shows that the moderating effect of EC significantly contributes to explaining the endogenous construct (LS). However, the moderating effect of EC on the relationship between PSS and SE was insignificant (β=-0.006, t=0.118, p=0.906), which does not support H6c.