The contemporary workforce landscape, especially within the Information Technology (IT) sector has witnessed a notable surge in the phenomenon of moonlighting. The concept of moonlighting is defined as “the simultaneous holding of two or more jobs at a single time by an individual” (Nunoo et al., 2018). In other words, moonlighting employment is held by an individual as secondary employment with his or her primary employment or main job at a single time (Boyd et al., 2015).

A prevalence of moonlighting in India has been observed particularly in the wake of the COVID-19 pandemic, the socio-economic factors are the driving force for the employees to take on secondary jobs (often at night) to supplement their primary income moreover. While moonlighting can enhance skills, provide job satisfaction, and help manage financial needs, it also poses risks such as burnout, reduced productivity, and potential conflicts of interest (Biswabhushan Behera, Anshul Kapoor, Pramod Kumar Nayak, Asjad Usmani and Vikas Rao Vadi, 2023). Issues such as boredom, the need for additional finances, and personal interests, were also a key driver for employees showcasing moonlighting behavior as such withdrawal behaviors, disengagement from the workplace and a focus on individual self-identity was interrupted as consequences of moonlighting (Mahankal et al., 2023). There arises deficiencies in Indian legislative policies and executive guidelines regarding the   regulations on moonlighting within the workforce, and it is suggested that companies should include clauses in employment contracts to address conflicts of interest while fostering trust and engagement and calls the government to develop a clear policy on moonlighting to provide legal clarity and balance the needs of both employers and employees (Biswabhushan Behera, Anshul Kapoor, Pramod Kumar Nayak, Asjad Usmani and Vikas Rao Vadi, 2023), whereby preventing recent layoffs by Wipro. Since Job satisfaction considerably and negatively influenced people’s intentions to work extra hours (Dr. Luxmi Malodia and Priya Kumari Butail, 2024) organizations should create a favourable working environment and create a comprehensive policy on moonlighting. As the authors embark on this research project few questions were generated, like the predominant motives driving moonlighting among Young Adults professionals in the Indian IT industry, impact of moonlighting on job satisfaction and organizational commitment within the context of the IT sector, the role of remote work as an enabler that provokes moonlighting, pattern of moonlighting on demographic factors like age, gender, and experience, through a comprehensive exploration of these questions, this research aims to contribute valuable insights into the motivations, consequences, and future implications of moonlighting within the dynamic landscape of the Indian IT workforce.

This literature review systematically examines a range of previously published studies to investigate the concept of moonlighting, defined as “the simultaneous holding of two or more jobs at a single time by an individual” (Nunoo et al., 2018). Moonlighting, also referred to as secondary employment, side jobs, dual jobs holding, multiple jobs holding, plural employment, extra income, and double work (Betts, 2006; Hausken & Ncube, 2018a, 2018b; Timothy & Nkwama, 2017; Urwick & Kisa, 2014), has been a growing trend in the workforce.

Studies have found that job satisfaction has a high positive impact on organizational commitment, with an inverse relationship between organizational commitment and moonlighting intentions (Seema et al., 2020). However, little correlation has been found between an individual's human capital (skills, education, experience) and their moonlighting wage, with underreporting of income through moonlighting also observed (Averett, 2001). Disparities in organizational commitment and moonlighting practices between genders have been noted in the Small Medium Enterprise sector in the Delhi NCR region (Khatri & Khushboo, 2014), while key drivers contributing to an increase in multiple-job holding have been identified among middle-level employees in selected IT companies (Ashwini et al., 2017).

The IT sector has seen a growing prevalence of moonlighting among workers, propelled by economic shifts and the surge in remote work (George & Hovan, 2022). Job satisfaction has been found to have a negatively significant impact on the inclination towards moonlighting among IT professionals (Malodia & Butail, 2024). The COVID-19 pandemic has further highlighted the socio-economic factors driving employees to take on secondary jobs to supplement their primary income, with moonlighting becoming a common practice in India (Biswabhushan Behera, Anshul Kapoor, Pramod Kumar Nayak, Asjad Usmani and Vikas Rao Vadi, 2023).

While moonlighting can enhance skills, provide job satisfaction, and help manage financial needs, it also poses risks such as burnout, reduced productivity, and potential conflicts of interest (Biswabhushan Behera, Anshul Kapoor, Pramod Kumar Nayak, Asjad Usmani and Vikas Rao Vadi, 2023). Issues such as boredom, the need for additional finances, and personal interests, have also been identified as key drivers for employees showcasing moonlighting behaviour, withdrawal behaviors, disengagement from the workplace, and a focus on individual self-identity as consequences of moonlighting (Mahankal et al., 2023). The introduction of Work from Home (WFH) during the COVID- 19 pandemic has created opportunities for individuals to explore alternative income sources (Majumdar, 2022).

Statistically, a study revealed 78.4% of respondents believe moonlighting improves knowledge horizon, 91.9% believe it helps to earn more, 83.8% acknowledge finding insufficient time to nurture family due to moonlighting, and 45.9% state that moonlighting diminishes involvement and real-time contribution to organizational development (Lahori & More, 2023). The major drivers/ motives behind moonlighting were financial needs, with secondary reasons including career development, skill acquisition, and personal development, a strong positive correlation between identified factors (pecuniary motivation, opportunity, personal reasons, and primary job-related motivation) and moonlighting intention were observed (Sabu, 2022).

Moonlighting has emerged as a coping mechanism for those facing financial insecurity due to permanent employment erosion, wage cuts, and freezing of increments (Majumdar, 2022), with financial concerns expressed as the major motive for the moonlighting intentions by various authors (Irfan et al., 2023). The rise of the gig economy has increased the incidences of moonlighting, with some arguing it may hinder job performance, while others believe it equips workers with new skills and better living standards (M. Shobana and S.Uma Mageswari 2024).

Internationally, the National Longitudinal Survey of Youth 1979, released by the U.S. Bureau of Labor Statistics, found that gender-specific patterns influence moonlighting behavior, with female moonlighting rates increasing in the United States and overall moonlighting rates similar to those in the 1970s (Catalina & Kimmel, 2009). 5% to 35% of the working population in the United States engages in multiple job holding (MJH), with work arrangements including part-time jobs or a combination of full- and part-time positions (Campion et al., 2019). University teachers in Pakistan demonstrated that moonlighting intentions are directly related with their job satisfaction (Ara & Akbar, 2016).

Moonlighting poses risks such as trade secret exposure, conflict of interest, absenteeism, and misuse of employer resources, with approximately one in five employees engaging in side gigs while holding a primary job, and over 40% of employees involved in moonlighting (Gehlot & Bhati, 2023). Deficiencies in Indian legislative policies and executive guidelines regarding the regulations on moonlighting within the workforce have been noted, with calls for companies to include clauses in employment contracts to address conflicts of interest while fostering trust and engagement, and for the government to develop a clear policy on moonlighting to provide legal clarity and balance the needs of both employers and employees (Biswabhushan Behera, Anshul Kapoor, Pramod Kumar Nayak, Asjad Usmani and Vikas Rao Vadi, 2023).

While moonlighting can provide financial benefits and new experiences, it may also lead to reduced productivity, employee burnout, and health risks, highlighting the need for balanced moonlighting policies to ensure both employer confidentiality and employee freedom (Nikita, Menal and Akash, 2023). Organizations need to develop targeted strategies and supportive HR practices to manage the impacts of moonlighting, ensuring that employees can effectively balance multiple roles without compromising their primary job performance or well-being and prevent reduced productivity, work-life balance issues, and potential conflicts with primary job responsibilities (Dr. A. Shaji George1, A.S. Hovan George 2022).

Despite the growing body of research on moonlighting, recent anecdotal studies highlighting the need for data-driven investigations into the motives behind moonlighting among young adults, a demographic with relatively little research focus. Geographical variation in moonlighting patterns has also been underemphasized, with moonlighting in relation to cultural dimensions and gender warranting further exploration. The IT industry in the Delhi NCR region, in particular, presents an opportunity for study, given the sector's growth and the potential for moonlighting in this field. Addressing these research gaps can provide valuable insights into the complex phenomenon of moonlighting and inform strategies for managing its impacts in the modern workforce.

Research Objectives

1. To study the influence of job security and moonlighting behavior among young adult professionals in the Indian IT industry.
2. To study the influence of monetary benefits and moonlighting behavior among young adult professionals in the Indian IT industry.
3. To study the influence of skill enhancement and moonlighting behavior among young adult professionals in the Indian IT industry.
4. To study the influence of boredom and moonlighting behavior among young adult professionals in the Indian IT industry.

Hypotheses:

1. H1: Job security has negative impact on the intentions for moonlighting behavior among Young Adults professionals in the Indian IT industry.
2. H2: Monetary benefits have a positive impact on the intentions for moonlighting behavior among Young Adults professionals in the Indian IT industry.
3. H3: Skill enhancement has a positive impact on the intentions for moonlighting behavior among Young Adults professionals in the Indian IT industry.
4. H4: Boredom at work has a positive impact on the intentions for moonlighting behavior among Young Adults professionals in the Indian IT industry.

The research methodology for this study involves treating employees of the IT industry as the primary subjects. The sample size comprises at least 200 individuals, with the final sample consisting of 234 participants. The sample frame includes key characteristic features such as employment in the IT industry, an age group of 18 to 35 years old, and geographical locations targeting specific regions where the IT industry is prominent, such as Delhi NCR. This study employs causal research methods, relying on primary data collected directly from the respondents and cross-series data to draw conclusions. The study underscores the importance of addressing these factors in organizational policies and practices to effectively manage moonlighting activities among employees in the evolving workforce landscape.

Limitations and Constraints

The study faces several limitations and constraints, including limited access to comprehensive data on moonlighting behaviors and challenges in obtaining a diverse and representative sample size. Reliance on self-reported data raises concerns about reliability and accuracy, while ethical considerations regarding participant consent and data confidentiality must be carefully managed. Time, budget, and resource constraints further limit the scope of the research. Additionally, regional and cultural variations in moonlighting behaviors may be overlooked, and defining and measuring moonlighting, as well as controlling for confounding variables, present significant challenges. These factors may impact the study's overall validity and generalizability.

Conceptual Framework

Moonlighting is a function of the above-mentioned variables

f(x)= fy1 + fy2+ fy3 + fy4 + S.E (Standard error)

Job security, monetary benefits, skill enhancement, and boredom significantly influence moonlighting intentions. Individuals with lower perceived job security are more likely to engage in moonlighting activities as a form of income diversification and risk reduction (Ng and Feldman, 2012). Similarly, precarious employment situations can drive individuals to seek supplementary sources of income through moonlighting (Boushey and Glynn,2012). Monetary benefits also play a crucial role, as individuals are more likely to moonlight when they perceive substantial financial rewards, especially if their primary job does not meet their financial needs (Kalleberg and Leicht 1991 and Piccolo and Colquitt 2006). Skill enhancement further motivates moonlighting, as Parker and Onsman (2016) highlighted that individuals may seek additional work to acquire new skills or enhance existing ones, particularly when their primary job offers limited opportunities for skill development. Moonlighting can provide diverse experiences and transferable skills, enhancing employability and career prospects (Greenhaus and Powell 2006). Moonlighting can counteract feelings of monotony and dissatisfaction in one's main job, providing variety and interest in professional life (Wrzesniewski et al.1997 and Fisher and To 2012).

Data Analysis

Table 1: - Table representing the demographics of the respondents.

The data reveals that the majority of respondents are young adults between the ages of 20 and 30, comprising 87.2% of the total population, while only 12.8% fall in the 30-40 age range. In terms of gender, males slightly outnumber females, making up 56.4% of the sample, with females representing 43.6%. When it comes to educational qualifications, a significant portion, 48.7%, are graduates, while 35.9% have completed postgraduate studies, and a smaller group, 15.4%, are undergraduates. This indicates a highly educated population. Additionally, the marital status data shows that 79.5% of respondents are unmarried, with only 20.5% being married, reflecting a predominantly young and single demographic. Overall, the data suggests a sample of primarily young, educated individuals, with a slight male majority, who are mostly unmarried.

Crosstab table

Table 2: - Table representing respondents with their intentions willing to engage in moonlighting while considering monetary benefits.

The crosstabulation between intentions and monetary benefits reveals a clear positive relationship between the two variables. Respondents who strongly disagree with the intentions largely perceive monetary benefits as either very low or neutral, with no one associating high benefits with their intentions. Those who disagree show a more spread-out perception, but still lean towards lower or neutral benefits. As respondents become neutral in their intentions, more start associating very high monetary benefits. The strongest correlation appears among those who agree or strongly agree, where a significant portion links their intentions with high or very high benefits. Overall, the data suggests that as perceptions of monetary benefits increase, so does agreement with intentions.

Table 3: - Table representing respondents with their intentions willing to engage in moonlighting while considering Skill enhancement.

The crosstabulation between intentions and skill enhancement shows a varying relationship based on the level of agreement with intentions. Respondents who strongly disagree primarily perceive skill enhancement as low or very low (18 and 12 respondents, respectively), with a small portion recognizing very high enhancement. Those who disagree have a more balanced view, with many perceiving neutral or high skill enhancement (18 respondents each), but none associating it with very high. Respondents who are neutral toward intentions overwhelmingly associate their intentions with high skill enhancement (30 respondents). Among those who agree, a significant number also associate high or very high skill enhancement, while those who strongly agree show a more mixed perception, associating both low and high skill enhancement in small numbers. Overall, as respondents move from disagreement to agreement, there is a noticeable shift toward perceiving higher levels of skill enhancement.

Table 4: - Table representing respondents with their intentions willing to engage in moonlighting while considering Job security.

The crosstabulation between intentions and job security shows a diverse relationship. Respondents who strongly disagree with intentions largely perceive job security as either very low (18 respondents) or neutral (12 respondents), with a small portion linking it to very high security. Those who disagree have a mixed view, with many associating job security as low or neutral (18 and 12 respondents, respectively), but also recognizing some high job security. Among respondents who are neutral, a significant portion perceives neutral or very high job security, while others see it as either low or high. In the agree group, the majority associate their intentions with neutral job security (36 respondents), but a smaller number perceive it as low or high. Lastly, those who strongly agree are split between low, neutral, and very high job security perceptions. Overall, as respondents' agreement with intentions increases, there is a tendency to perceive job security as neutral, with a smaller portion linking it to very high security.

Table 5: - Table representing respondents with their intentions willing to engage in moonlighting while considering Boredom.

The crosstabulation between intentions and boredom reveals distinct patterns across different levels of agreement. Among those who strongly disagree with intentions, boredom is perceived mostly as neutral (18 respondents) or low (12 respondents), with no one reporting high levels of boredom. Respondents who disagree show a wider spread, with many perceiving low boredom (24 respondents), while others experience neutral or even very high boredom. Those who are neutral in their intentions tend to experience high or neutral boredom, with fewer reporting low or very high levels. In the agree group, a mix of responses is seen, with most associating their intentions with neutral or low boredom, while a smaller number experience high or very high boredom. Lastly, respondents who strongly agree report more high or very high boredom, but also some low boredom. Overall, as agreement with intentions increases, boredom appears to become more varied, with a noticeable portion experiencing higher levels of boredom among those who agree or strongly agree.

Correlation

Table 6: - Table representing Correlation amongst various factors.

Correlations:

The correlation coefficients between variables indicate that "Intentions for moonlighting" exhibit weak to moderate positive correlations with boredom (0.339), monetary benefit (0.377), and skill enhancement (0.308). This implies that individuals with higher intentions tend to report experiencing more boredom, aiming for greater monetary benefits, and seeking more skill enhancement. The positive correlation suggests that as intentions increase, there is a tendency for these factors to increase as well, indicating a potential alignment between individuals' intentions and their perceptions or experiences regarding boredom, monetary benefits, and skill enhancement.

Test for Linearity

1. Intentions of moonlighting and monetary benefits.

The ANOVA table indicates a significant relationship between your intentions and monetary benefits, with an F-value of 15.526 and a p-value of .000, showing that different levels of intentions significantly affect perceptions of monetary benefits. The linearity component also reflects a strong relationship (F = 38.008, p = .000), while the deviation from linearity suggests notable variations among groups (F = 8.032, p = .000).

The measures of association reveal a moderate relationship between your intentions and monetary benefits. The correlation coefficient (R) of 0.361 indicates a moderate positive correlation, while the R Squared (0.131) shows that about 13.1% of the variance in monetary benefits is explained by intentions. The Eta value (0.462) and Eta Squared (0.213) suggest that approximately 21.3% of the variation in monetary benefits can be attributed to different levels of intentions. Overall, these results indicate a significant influence of intentions on perceptions of monetary benefits.

2. Intentions of moonlighting and skill enhancement.

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The ANOVA table demonstrates a significant relationship between your intentions and skill enhancement. The F-value of 7.792 and a p-value (Sig.) of .000 indicate statistically significant differences in skill enhancement based on varying levels of intentions. The linearity component shows a strong relationship (F = 24.582, p = .000), suggesting a clear linear trend. However, the deviation from linearity is not significant (F = 2.195, p = .089), indicating that while there is a linear relationship, variations among groups are not statistically significant. Overall, these results imply that intentions significantly influence perceptions of skill enhancement, primarily through a linear relationship.

The measures of association indicate a moderate relationship between your intentions and skill enhancement. The correlation coefficient (R) of 0.307 suggests a moderate positive correlation, while the R Squared (0.094) indicates that approximately 9.4% of the variance in skill enhancement can be explained by intentions. The Eta value (0.346) reflects a moderate association, with Eta Squared (0.120) showing that about 12% of the variation in skill enhancement is attributable to different levels of intentions. Overall, these metrics suggest that intentions have a meaningful impact on perceptions of skill enhancement.

3. Intentions of moonlighting and job security.

The ANOVA table indicates a significant relationship between your intentions and job security. The F-value of 15.067 and a p-value (Sig.) of .000 show that there are statistically significant differences in job security based on varying levels of intentions. The linearity component demonstrates a strong linear relationship (F = 13.491, p = .000), confirming that intentions strongly influence perceptions of job security. Additionally, the deviation from linearity is also significant (F = 15.593, p = .000), suggesting that there are meaningful variations among groups that deviate from the linear trend. Overall, these results imply that intentions have a substantial and statistically significant impact on perceptions of job security.

The measures of association reveal a weak to moderate relationship between your intentions and job security. The correlation coefficient (R) of 0.216 indicates a weak positive correlation, while the R Squared (0.047) suggests that approximately 4.7% of the variance in job security can be explained by intentions. The Eta value (0.456) reflects a moderate association, with Eta Squared (0.208) indicating that about 20.8% of the variation in job security is attributable to different levels of intentions. Overall, these results suggest that while intentions have some influence on perceptions of job security, the relationship is not particularly strong.

4. Intentions of moonlighting and sleep hour

The ANOVA table indicates a significant relationship between your intentions and boredom. The F-value of 11.023 and a p-value (Sig.) of .000 suggest that there are statistically significant differences in boredom levels based on varying intentions. The linearity component shows a strong linear relationship (F = 33.491, p = .000), confirming that intentions significantly influence perceptions of boredom. Additionally, the deviation from linearity is also significant (F = 3.533, p = .016), indicating meaningful variations among groups that deviate from the linear trend. Overall, these results imply that intentions have a substantial and statistically significant impact on perceptions of boredom.

The measures of association indicate a moderate relationship between your intentions and boredom. The correlation coefficient (R) of 0.350 suggests a moderate positive correlation, while the R Squared (0.123) indicates that approximately 12.3% of the variance in boredom can be explained by intentions. The Eta value (0.402) reflects a moderate association, with Eta Squared (0.161) suggesting that about 16.1% of the variation in boredom is attributable to different levels of intentions. Overall, these results imply that intentions have a meaningful impact on perceptions of boredom, indicating a noteworthy relationship between the two variables.

Test for autocorrelation (Durbin- Watson)

Interpretation for autocorrelation

Reference

• Durbin -Watson value = 2, NO autocorrelation

• Durbin -Watson value <2, Positive/ significant autocorrelation
  • Durbin -Watson > 2, Negative/ insignificant autocorrelation
• With a Durbin-Watson value of 1.624, the test suggests that there is significant autocorrelation in the residuals of the regression model.

Reliability:

Cronbach's Alpha (0.708) suggests an acceptable level of internal consistency (reliability) for the set of all five variables used in the analysis.

Test of Normality

• Null H0- Residual are normally distributed.
• Alternate H0 - Residual are not normally distributed.

As the p- value of both the tests (Kolmogorov- Smirnov and Shapiro- Wilk) is 0.00 which is less than 5% level of significance, thus we reject the null hypothesis which means that residuals are not normally distributed.

ANOVA

Interpretation of the ANOVA

As the p- value of the ANOVA is 0.000 which is less than 5%of the level of significance, so we say that model exist or in other words all the independent variable jointly affects the dependent variable.

Multi collinearity/T test

Interpretation of Multi collinearity

As we observe the p value, we find that, some of the vales of independent variables are 0.000, which is less than 5% significance level. Thus, we conclude all the independent variables (monetary benefit and boredom) jointly and positively contributes to the dependant variable (intentions of moonlighting).

If the value of VIF goes above 5 or the tolerance goes below 0.2, it indicates the strong presence of collinearity among the variables. If multicollinearity is detected it is important to identify which to factors are strongly corelated with each other.

In this scenario no multicollinearity is detected.

Goodness of Fit (Model summary)

Interpretation of Goodness of Fit (Model summary)

Here, the R square is 0.226 which means that model formed is able to explain 22% variance of the dependent variable.

Regression Model

The equation formed considering the unstandardized coefficient is Intentions of moonlighting= 0.995 + 0.230 (Monetary benefit) + 0.079 (Skill enhancement) + 0.008 (Job security) + 0.300 (Boredom).

Key findings

Findings indicate that job security (Ng and Feldman, 2012) is negatively correlated with moonlighting behaviour, while monetary benefits (Kalleberg and Leicht 1991 and Piccolo and Colquitt 2006), pursuit of skill enhancement (Parker and Onsman, 2016), and boredom (Wrzesniewski et al.1997 and Fisher and To 2012) at work positively influence moonlighting behaviour. Utilizing regression analysis, the study explores the relationships between job security, monetary benefits, pursuit of skill enhancement, boredom at work, and moonlighting behaviour. These results highlight the significance of financial incentives, career advancement opportunities, and workplace engagement in shaping individuals' decisions to engage in secondary employment. The study provides a comprehensive view of the surveyed population, which is predominantly young, well-educated, and unmarried, with a slight male predominance. This demographic includes individuals who are early in their careers, highly adaptable, and open to new employment trends such as moonlighting and gig work. The findings reveal a broad range of perceptions regarding various factors. Monetary benefits (Kalleberg and Leicht 1991 and Piccolo and Colquitt 2006) are perceived differently by the respondents indicating considerable diversity in views. Skill enhancement (Parker and Onsman, 2016), job security (Ng and Feldman, 2012) and boredom (Wrzesniewski et al.1997 and Fisher and To 2012) also shows varied opinions. Correlation analysis shows weak to moderate positive relationships between intentions to moonlight and boredom, monetary benefits, and skill enhancement, suggesting that higher intentions align with increased boredom, desire for monetary gain, and skill improvement. The regression model, with an R-squared value of 0.226, indicates that while boredom and monetary benefits significantly influence intentions, skill enhancement and job security do not have a statistically significant impact in this context.

The findings of the study provide valuable insights into the motives driving moonlighting behavior among Young Adults professionals in the Indian IT industry. It is evident that factors such as job security, monetary benefits, pursuit of skill enhancement, and boredom at work significantly influence individuals' propensity to engage in moonlighting activities. Specifically, individuals with lower job security, higher perceived monetary benefits, a desire for skill enhancement, and greater boredom at work are more likely to engage in moonlighting. These findings underscore the complex interplay between individual motivations, organizational dynamics, and external factors shaping moonlighting behavior in the contemporary workforce. Additionally, the study highlights the importance of addressing these factors in organizational policies and practices to better understand and manage moonlighting activities among employees.

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