Workplace antecedents of quiet quitting behavior: Insights from graduate workers in India

: Drawing on a theoretical framework of Job Demands-Resources (JD-R), our study aims to consider how workplace antecedents of perceived quiet firing (also known as involuntary attrition), perceived co-worker support, and experience (tenure at an organization) may influence quiet quitting behavior. Data were collected via questionnaire responses from 209 workers in India who had graduated from university within the last 7 years. The findings show that (1) perceived quiet firing is positively associated with quiet quitting; (2) perceived co-worker support is negatively associated with quiet quitting; (3) experience moderates the positive association between perceived quiet firing and quiet quitting in such a way that the relationship is weaker as one’s tenure at an organization increases; and (4) experience does not moderate the negative association between perceived co-worker support and quiet quitting. The study’s contributions come from understanding how the interplay of demands (i.e., perceived quiet firing) and resources (i.e., perceived co-worker support and experience) determine quiet quitting behaviors in the workplace. Additionally, the temporal dimension of experience facilitates the acquisition of organizational-specific knowledge and resources. In contrast, perceptions of co-worker support appear specific to a given point in time. Policy implications come from providing guidance to organizations on how to reduce quiet quitting behaviors by ensuring that the resources available to employees exceed the demands placed on them.


Introduction
The COVID-19 pandemic represented a global chance event that caused significant disruption to our daily lives and careers (Onyeaka et al., 2021;Donald, 2020).Social distancing restrictions gave individuals a significant period of time to reflect upon their relationship between non-work and work demands, as well as what constitutes a meaningful life (Baños et al., 2022;Da et al., 2022).The restrictions also exacerbated pre-existing mental health and wellbeing challenges, particularly in university students and graduates (Dodd et al., 2021;Donald and Jackson, 2022).As restrictions began to be lifted, two dominant trends were observed.The first was the 'great resignation' whereby individuals either pivoted to a new career or decided to retire from the workforce (Sull et al., 2022).The second was 'quiet quitting', which forms the focus of the study reported in this manuscript.
The term 'quiet quitting' (hereafter QQ) emerged in 2022 across mainstream media and social media, defined as "a phenomenon resulting from employees in many industries realizing that the goals they are regularly asked to exceed are not sustainable or worth it, and that additional productivity or efficiency efforts are not rewarding to them" (Atalay and Dağistan, 2023, p. 2).The same authors observe how, since the start of 2022, QQ behavior has increased worldwide, including in developing countries such as India (the focus of our study).Therefore, understanding the antecedents to QQ is of significant interest to employees and their employers.
Drawing on a theoretical framework of Job Demands-Resources (JD-R), our study aims to consider how workplace antecedents of perceived quiet firing (also known as involuntary attrition; hereafter QF), perceived co-worker support (hereafter CS), and experience (tenure at an organization) may influence QQ behavior.
QF is when an employee believes that an employer is making their working conditions untenable with the aim of getting them to resign (Wigert, 2022).A survey of more than 20,000 employees found that 48% had witnessed QF while 35% had experienced it during their careers (Lockie, 2022).Such an approach usually takes the form of unreasonable job demands.The JD-R model proposes that the interplay of job demands and job resources impacts employee wellbeing and performance (Demerouti et al., 2001).Consequently, QQ can reflect a behavior taken by an employee to cope with high levels of stress in the workplace (Hamouche et al., 2023).As QF likely leads to job demands exceeding one's available resources, employees may seek to offset these increased demands via QQ.The positive association between QF and QQ has also been proposed during scale development and validation of these constructs (Anand et al., 2023).Therefore, we propose: H1: Perceived quiet firing (QF) is positively associated with quiet quitting (QQ).An employee's subjective assessment of the availability of support and encouragement from their co-workers is termed CS (Cohen and Wills, 1985).CS is critical since it develops a sense of community, alleviates loneliness, and boosts overall job satisfaction (Eisenberger et al., 2020).It has also been shown to reduce stress, increase psychological wellbeing, and help safeguard against undesirable outcomes, making it particularly valuable during trying times such as increased workloads (Halbesleben et al., 2014;Cavanaugh et al., 2000).JD-R theory acknowledges how social support from colleagues can act as a resource (Demerouti et al., 2001).The acquisition of additional resources can enable an individual to cope with high job demands (Bakker and Demerouti, 2017), for example, those imposed via QF.Therefore, we propose: H2: Perceived co-worker support (CS) is negatively associated with quiet quitting (QQ).
We are also interested in exploring the role of experience (i.e.tenure at an organization) as a moderator on H1 and H2.The longer an individual spends at an organization, the more familiar they are likely to be with its operations.In other words, they have had a greater opportunity to develop tacit knowledge (Polanyi, 1958), referring to skills, knowledge, and abilities gained through experience.Therefore, experience at an organization may represent an additional resource to manage the increased demands associated with QF and reduce the impacts of QF on QQ.Additionally, given the positioning of experience as a resource (Demerouti et al., 2001), tenure at an organization may complement the proposed benefit of CS in reducing QQ.Therefore, we propose: H3: Experience at the organization moderates the positive association between perceived quiet (QF) and quiet quitting (QQ) in such a way that the association is weaker as one's tenure at the organization increases.
H4: Experience at the organization moderates the negative association between perceived co-worker support (CS) and quiet quitting (QQ) in such a way that the association is stronger as one's tenure at the organization increases.
The theoretical contribution of our study comes from advancing the JD-R theory through empirical validation to understand how the interplay of demands (i.e., QF) and resources (i.e., CS and experience) determine QQ behaviors in the workplace.The practical contribution comes from providing insights into the phenomena of QQ for employees and employers.

Sampling and data collection
The research was conducted as a cross-sectional study whereby sampling criteria was purposive as participants had to be employees in India who had graduated from university within the last 7 years.The data were collected using an online questionnaire between August and November 2023.Ethics approval was obtained from the Institutional Review Board, and all participants provided informed consent before participating in the study.We invited 300 workers to participate and received 209 completed questionnaires representing a response rate of 69.67%.Of the participants, 120 identified as female and 89 as male, offering a gender split of (57.4%/42.6%)representative of the population under study.The average experience of participants in terms of tenure at their current organization was 4.56 years, and the average age of participants was 30.3 years.

Instrument
Perceived quiet quitting (QQ) was assessed using a 7-item scale (Anand et al., 2023).A sample item is "I am doing the bare minimum work to avoid getting fired".The scale employs a five-point Likert Scale (1 = never/completely disagree, 5 = very often/completely agree).Cronbach's α was 0.84.
Perceived quit firing (QF) was assessed using a 7-item scale (Anand et al., 2023).A sample item is "My manager/supervisor has shown less interest in my career trajectory/development".The scale employs a five-point Likert Scale (1 = never/completely disagree, 5 = very often/completely agree).Cronbach's α was 0.85.
Perceived co-worker support (CS) was assessed using a 4-item scale developed by Haynes et al. (1999) and also used by Norling and Chopik (2020).A sample item is "My co-workers listen to me when I need to talk about work-related problems".The scale employs a four-point Likert Scale (1 = strongly disagree, 4 = strongly agree).Cronbach's α was 0.91.
Experience was measured in years as the length of tenure an individual had with their current employer.
Demographic information on age and gender was also collected.

Data analysis procedure
IBM SPSS 23.0 and Warp Partial Least Square (WarpPLS) were used for data analysis.Structural Equation Modelling (SEM) was conducted to explore path coefficients of direct hypotheses (H1 and H2) using WarpPLS 8.0.The PLS-SEM approach is suitable for exploratory, confirmatory, and predictive analyses [22] .Moderation tests (H3 and H4) were carried out with the PROCESS macro developed by Preacher et al., (2007).

Descriptive statistics
Table 1 shows the means, standard deviations, and correlations, indicating a significant correlation between the variables.Before evaluating the reliability and validity of the measurement items, the indicators were tested via Variance Impact Factors (VIFs) for the assumption of constant variance, outliers, and normality.All VIFs were less than 2.17 and, therefore, considerably lower than the recommended threshold of 10.0, suggesting that multicollinearity was not a problem (Hair et al., 2017).
The study data were generated from a single source of self-reported survey data.Thus, we needed to check for common method bias (Podsakoff et al., 2003).We used Harman's single-factor test as an exploratory assessment.The factor extraction results revealed an extracted total variance of 34%, showing the absence of common method bias.
The fit of the data with the proposed conceptual model was tested using variancebased SEM-PLS with WarpPLS 8.0 (Kock, 2012).Here, the CR values ranged from 0.88 to 0.93 and met or exceeded the recommended level of 0.70 (Gefen et al., 2000).The Average Variance Extracted (AVE) ranged from 0.53 to 0.79, within the recommended level of above 0.50 (Hair et al., 2017).The Variance Inflation Factor (VIF) results ranged from 1.25 to 2.16, below the recommended cut-off level of 5.00 (Hair et al., 2017).The tests supported the reliability and validity of the study variables (per Table 2).
We also checked the normalized factor loadings (per Table 3), which also validated the three scales.

Assessment of measurement model
Table 4 shows the checks conducted that showed a strong goodness of fit for the model.

Moderation analysis
H3 proposed that experience at the organization moderates the positive association between QF and QQ in such a way that the association is weaker as one's tenure at the organization increases.The interaction effect was significant (β = −0.24,p < 0.001).Therefore, H3 was supported.
H4 proposed that experience at the organization moderates the negative association between CS and QQ in such a way that the association is stronger as one's tenure at the organization increases.The interaction effect was non-significant (β = 0.21, ns).Therefore, H4 was rejected.
Table 6 shows the moderation analysis for H3 and H4.
Table 6.Moderation analysis.Additionally, Figure 1 provides a visual representation of the moderation effect for H3, whereby experience at the organization moderates the positive association between QF and QQ in such a way that the association is weaker as one's tenure at the organization increases.

Validation of the model
Figure 2 shows the empirically validated model with the three supported hypotheses (H1, H2, and H3).

Discussion
The positive relationship between QF and QQ supports previous findings from the initial validation of these two scales in India (Anand et al., 2023).The factor loadings of seven items to each scale also replicate the findings during the scale development and validation of QF and QQ (Anand et al., 2023).This seems logical since the JD-R model proposes that the interplay of job demands and job resources impacts wellbeing and performance (Demerouti et al., 2001), whereby QQ can reflect actions by an employee to cope with increased stress levels due to QF (Hamouche et al., 2023).
The negative relationship between CS and QQ responds to calls to consider antecedents that decrease QQ behavior (Anand et al., 2023).Again, our findings align with the JD-R theory since CS represents a resource (Demerouti et al., 2001) that can help reduce stress, increase job satisfaction, and increase performance (Eisenberger et al., 2020;Halbesleben et al., 2014;Cavanaugh et al., 2000).These aspects would suggest a reduced likelihood of QQ behavior (Anand et al., 2023).
The moderating role of experience (representing tenure at the organization) reduces the strength of the QF-QQ relationship.Perhaps this suggests an accumulation of resources over time as employees have greater opportunities to develop tacit knowledge (Polanyi, 1958).JD-R theory is again supported here since adding resources helps the employee manage job demands (Demerouti et al., 2001), leading to reduced QQ behaviors.
An unexpected finding in the context of JD-R theory was that, contrary to our expectations, experience has no moderation role on the negative relationship between CS and QQ.A possible reason is that two distinct temporal factors are at play.Unlike tenure at an organization that facilitates the accumulation of resources over time, CS is perhaps more indicative of a resource at a specific snapshot in time.That is to say, while CS can reduce QQ behavior, the resources at that point in time lead to this outcome.In contrast, resources acquired over time from experience do not significantly impact the CS-QQ relationship.

Theoretical contribution
The theoretical contribution comes from three distinct albeit interrelated aspects.First, we offer one of the earliest studies using the newly developed QF and QQ scales (Anand et al., 2023).Our support for the strong positive association between QF and QQ and the validity of the two distinct 7-item scales contributes to the robustness of these scales for use in India.Second, we respond to calls to consider antecedents that can reduce QQ behaviors (Anand et al., 2023).Third, we observe an interesting interaction between two temporal dimensions of (a) the accumulation of resources over time versus (b) the resources an individual perceives to have at a given time.The perspective acknowledges the interplay of person, context, and time in determining career sustainability (De Vos et al., 2020;Van der Heijden and De Vos, 2015).From the JD-R theory perspective, it is interesting that tenure at an organization (representing the opportunity to accumulate resources over time within one's resource caravan) (Nimmi et al., 2021;Hobfoll et al., 2018;Hobfoll, 2012) does not moderate how CS (as a resource at a specific point in time) can reduce QQ intentions.Put differently, accumulating resources over time lessens the impact of the increased job demands from QF on QQ behavior but does not enhance the CS resource's impact on QQ behavior.

Practical and policy contribution
The practical and policy contributions of the study focus on the employee and employer perspectives, recognizing their interconnected and interdependent nature and the new psychological contract between such actors operating within a career ecosystem (Donald, 2023a;Baruch and Rousseau, 2019;Baruch, 2013).However, the implications for employees and employers transcend national and global economies since the global cost of disengaged workers accounted for $8.8 trillion in lost productivity according to the latest figures as of September 2023 (Pendell, 2023).
The adaptive work behavior of QQ has negative implications for the employee and the employer (Mahand and Caldwell, 2023).These include a decline in productivity, morale, and quality of work, coupled with increased absenteeism (Yildiz, 2023).Our findings provide empirical support for the view that QF likely does more harm than good for an organization since it erodes trust and commitment (Mahand and Caldwell, 2023).Instead, showing respect to employees and encouraging them to respect their co-workers appears to be a better strategy.This supports the view that employees who feel respected in the workplace have higher levels of morale, motivation, and productivity (Jamal Ali and Anwar, 2021).Therefore, we recommend that employers foster an environment of trust and inclusivity, set clear expectations, provide frequent feedback, and encourage social interaction between employers in the workplace to build interpersonal connections.Additionally, policies that provide support could be beneficial, such as mentorship and peer support schemes, as well as opportunities for training and development.Managers and supervisors may also benefit from being informed of the potential harm of QF behaviors, suggesting policies around mandatory training should be considered.Finally, wellbeing support and career counseling opportunities can help employees to balance job demands and resources.Career counseling can also help individuals to identify growth opportunities within their current role or recognize the need to change employers.This aligns with empirical findings in the UK that turnover is not always a bad thing for either the employee or the employer (Donald, 2023b).

Limitations and future research directions
Our study shares several limitations with published studies: (i) data were collected via a single method of questionnaires (Donald et al., 2023), the self-reported nature of the participant perceptions may introduce social desirability or recall error bias (Nimmi et al., 2021), and participants only came from a single country of India (Nimmi et al., 2022).
Future research could consider exploring different antecedents of QQ or conducting a study using the same variables but in other geographical regions.It may also be interesting to compare participants' views from different sectors or consider the intersectionality of various demographic aspects.Comparing employees' perspectives with those of other actors may also offer greater insights, as could adopting a qualitative approach.Research could also look more closely at the role that time plays, acknowledging that career sustainability has three dimensions: person, context, and time (De Vos et al., 2020;Van der Heijden and De Vos, 2015).For example, longitudinal studies that adopt a career span approach (Baruch and Sullivan, 2022) or bridge educational and workplace contexts responding to calls to consider the integration of graduate employability and worker employability literature (Akkermans et al., 2024).

Conclusion
Our study aimed to consider how workplace antecedents of QF, CS, and experience may influence QQ behavior.The findings show that (1) QF is positively associated with QQ; (2) CS is negatively associated with QQ; (3) experience moderates the positive association between QF and QQ in such a way that the relationship is weaker as one's tenure at an organization increases; and (4) experience does not moderate the negative association between CS and QQ.The study's contributions come from understanding how the interplay of demands (i.e., QF) and resources (i.e., CS and experience) determine QQ behaviors in the workplace.Additionally, the temporal dimension of experience facilitates the acquisition of organizational-specific knowledge and resources.In contrast, perceptions of CS appear specific to a given point in time.

Figure 1 .
Figure 1.Moderation impact of organizational tenure on the relationship between Perceived Quiet Firing (QF) and Quiet Quitting (QQ).

Table 1 .
Descriptive statistics and correlations.

Table 2 .
Reliability and validity.

Table 5 .
Direct effect hypothesis testing.