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Article

Motivation, Urban Pressures, and the Limits of Satisfaction: Insights into Employee Retention in a Changing Workforce

by
Rob Kim Marjerison
1,
Jin Young Jun
2,
Jong Min Kim
2,* and
George Kuan
3
1
Institute for Sustainability Studies, Wenzhou-Kean University, Wenzhou 325060, China
2
Department of International Trade, College of Social Sciences, Konkuk University, Seoul 05029, Republic of Korea
3
International Business, International School of Management, 75007 Paris, France
*
Author to whom correspondence should be addressed.
Systems 2025, 13(8), 661; https://doi.org/10.3390/systems13080661
Submission received: 10 July 2025 / Revised: 1 August 2025 / Accepted: 4 August 2025 / Published: 5 August 2025
(This article belongs to the Section Systems Practice in Social Science)
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Abstract

This study aims to clarify how different types of motivation influence employee retention by identifying the distinct roles of intrinsic and extrinsic factors in shaping job satisfaction, particularly under varying levels of urban stress and generational identity. Drawing on Herzberg’s Two-Factor Theory and Self-Determination Theory, we distinguish between intrinsic drivers (e.g., autonomy, achievement) and extrinsic hygiene factors (e.g., pay, stability). Using survey data from 356 Chinese employees and applying PLS-SEM with a moderated mediation design, we investigate how urbanization and Generation Z moderate these relationships. Results show that intrinsic motivation enhances satisfaction, especially in urban settings, while extrinsic factors negatively affect satisfaction when perceived as insufficient or unfair. Job satisfaction mediates the relationship between motivation and retention, although this effect is weaker among Generation Z employees. These findings refine motivational theories by demonstrating how environmental pressure and generational values jointly shape employee attitudes. The study contributes a context-sensitive framework for understanding retention by integrating individual motivation with macro-level moderators, offering practical implications for managing diverse and urbanizing labor markets.

1. Introduction

Although cities such as Beijing, Shanghai, Shenzhen, and Guangzhou offer competitive salaries, advanced industries, and clear career trajectories, they still report lower job satisfaction and higher turnover intentions compared to less urbanized regions [1]. These cities have emerged as powerful economic centers that attract both domestic and international talent. However, the persistently high turnover rates suggest a paradox beneath their apparent success [2,3]. Structural pressures associated with urban environments may diminish the effectiveness of material rewards and instead increase workers’ dependence on psychological resources such as autonomy, recognition, and perceptions of fairness [4,5].
Given this context, it becomes important to examine how urban life affects employees’ job-related attitudes. Urban living often involves high costs of living, long commutes, intense competition, and weakened social connections [6,7,8]. These conditions can lead to emotional fatigue, burnout, and disengagement. Under such circumstances, extrinsic rewards like salary and job security tend to lose their motivational strength, whereas intrinsic needs—such as autonomy, competence, and relatedness—are more likely to shape satisfaction. This is because intrinsic motivation often functions as a compensatory response to psychological needs that are not fulfilled through material means. Moreover, in complex and uncertain settings, the need for control and a sense of meaning becomes increasingly relevant [9,10,11].
Such developments also raise critical questions regarding employee retention. Recent studies have found that retention decisions are influenced more by personal purpose, identity, and job fit than by monetary compensation [12,13,14]. This trend is particularly salient among younger generations such as Gen Z, who tend to prioritize autonomy and meaningful work over long-term job security or loyalty to an organization [15]. Consequently, the traditional link between job satisfaction and retention has become weaker, calling into question the continued relevance of compensation-centered retention strategies [16,17].
Despite the growing interest in this area, most existing studies have tended to focus on either urbanization or generational differences, without exploring how these two contextual forces interact. For example, some research highlights that urban employees report lower job satisfaction and higher turnover intentions compared to rural workers [18,19], while other studies suggest that motivational drivers and satisfaction determinants differ across generations [20,21]. However, empirical evidence that investigates their combined and interactive effects remains limited.
To address this gap, the present study proposes a theoretical model that examines how intrinsic and extrinsic motivation influence job satisfaction and retention intention, while also considering urbanization and generational identity as contextual moderators. The model draws on multiple theoretical perspectives, including Herzberg’s Two-Factor Theory [11] and Self-Determination Theory, he Theory of Planned Behavior, and Social Exchange Theory. It seeks to explain how different types of motivation contribute to satisfaction, how satisfaction relates to retention, and how these relationships may vary depending on urban and generational contexts.
Guided by this framework, the study aims to answer the following research questions:
(1) How do intrinsic and extrinsic motivations affect job satisfaction and retention?
(2) Does job satisfaction mediate the relationship between motivation and retention?
(3) How do urban and generational contexts influence these relationships?
By answering these questions, this study aims to contextualize the motivation–satisfaction–retention framework within today’s rapidly changing urban and generational environments, offering both theoretical and practical insights into the design of more effective retention strategies.
The remainder of this paper is structured as follows: Section 2 presents the theoretical framework and hypotheses. Section 3 outlines the research design and analytical methods. Section 4 reports the empirical results, and Section 5 discusses key implications and future research directions.

2. Literature Review

2.1. Firm Performance as an Outcome of Digital Transformation

2.1.1. Motivational Factors (Intrinsic Factors)

Motivational factors (MF) are a core concept in organizational behavior and human resource management. Based on Herzberg’s Two-Factor Theory [11], MF include achievement, recognition, the nature of the work, responsibility, opportunities for growth, and personal development. These elements are part of the job content and contribute to meaningful engagement, employee well-being, and sustained psychological satisfaction [22,23].
Empirical studies have measured intrinsic motivation—conceptually aligned with MF—using multi-item scales that capture autonomy, mastery, purpose, and recognition [24,25]. These indicators consistently show high reliability and validity, supporting their use as a single latent construct in structural models [26]. Factor analysis typically groups them into one dimension, confirming conceptual coherence [27].
Recent research in organizational psychology and employee engagement further confirms that intrinsic motivation (i.e., MF) predicts job satisfaction, commitment, and performance [22,23,24]. Given both its theoretical grounding and empirical validation, MF is a key component of our model.

2.1.2. Hygiene Factors (Extrinsic Factors)

Hygiene factors (HF) form the second part of the dual-factor framework [11]. Unlike Motivational factors (MF), HF relates to the work environment rather than the task itself. Examples include salary, supervision, company rules, coworker relations, job security, and physical conditions. These elements help prevent dissatisfaction but do not generate positive satisfaction, thus maintaining a neutral emotional state.
Organizational studies commonly use multi-item scales to assess hygiene factors, including fairness in compensation, procedural clarity, managerial support, and work environment [9,28]. These constructs have shown solid reliability and validity, especially in studies of job satisfaction, turnover, and commitment [29,30]. Structural and regression models often treat hygiene factors as a distinct latent variable that complements motivational factors [11,31].
More recent work has expanded the definition to include perceptions of fairness and workplace infrastructure [32,33]. This broader view underscores the ongoing relevance of hygiene factors in modern organizations. Their inclusion in the present model is conceptually appropriate and methodologically supported. Their conceptual and methodological justification supports their inclusion in this study.

2.1.3. Job Satisfaction

Job satisfaction is one of the most widely studied topics in organizational behavior and industrial psychology. It reflects not only how employees evaluate their work experience, including emotional responses to their roles, relationships, and conditions, but also how work contributes to their overall sense of well-being [28,34].
Multiple theories explain its origins and function. The two-factor theory posits that intrinsic motivators like recognition, achievement, and growth drive satisfaction, while hygiene factors reduce dissatisfaction without promoting satisfaction [11]. Social Exchange Theory [35] adds that satisfaction stems from perceived fairness and reciprocity. Employees who feel valued are more likely to be satisfied.
Satisfaction also serves as a mediator. It transmits the effects of core antecedents such as motivation, leadership, and organizational climate to outcomes like turnover intention and commitment. Prior studies show that both intrinsic and extrinsic job characteristics affect retention primarily through satisfaction [30,36,37]. Structural models and mediation studies consistently confirm its role as a psychological bridge between job attributes and behavioral outcomes [12,31].
For these reasons, we conceptualize job satisfaction both as a motivational outcome and as a mediating pathway to employee retention.

2.1.4. Intention to Remain at the Current Workplace

Intention to remain refers to the deliberate choice to stay with one’s current organization. It is a key indicator of employee retention. Unlike actual turnover, which can only be observed after it happens, this construct captures forward-looking attitudes and serves as a strong predictor of future behavior [30,38]. It reflects not only current satisfaction but also expectations for growth, value, and organizational fit.
This construct is grounded in several theories. The Theory of Planned Behavior [39] identifies intention as the immediate driver of behavior. Social Exchange Theory [35] emphasizes that fair and mutual relationships—through recognition, support, or development—reinforce the intention to stay [28,30]. Organizational Commitment Theory highlights the role of emotional attachment and satisfaction in long-term retention [14,40].
Empirical studies across industries confirm that intention to remain is influenced by leadership [41], work-life balance [42], and the motivational climate [43]. For younger workers and knowledge-based sectors, psychological factors are especially relevant given weaker institutional loyalty [44].
Accordingly, this study conceptualizes intention to remain as the primary outcome variable, influenced by motivation and mediated by job satisfaction.

2.1.5. Urbanization as a Contextual Moderator

Urbanization refers to the degree to which people live and work in densely populated, industrialized, and infrastructure-intensive environments. It is increasingly recognized in organizational research as a contextual factor that shapes employee experience and outcomes. Urban environments are typically fast-paced, competitive, and high-cost, leading to diverse and often fragmented social interactions [8,45]. These conditions influence how employees view their work, engage with organizations, and make career decisions [5,46].
Urbanization has been linked to employee stress, work life balance, job mobility, and labor market fluidity [2,47,48,49,50]. Urban employees typically face more job options and greater external pressure, which can shape their responses to rewards and satisfaction. Compared to workers in less urbanized areas, they may hold different expectations and behavioral norms.
Recent studies have treated urbanization as a moderator in the relationship between job characteristics and employee outcomes. For example, the impact of leadership, organizational support, and job resources on satisfaction and engagement varies across urban and rural contexts [51,52]. These findings are consistent with Contingency Theory, which views urbanization as a boundary condition that modifies how organizational variables operate [53].
In this study, urbanization is examined as a moderator in the relationship between intrinsic motivation and job satisfaction. Employees in highly urbanized environments may rely more on intrinsic motivators to stay engaged, or they may become less sensitive to them due to external stress and job alternatives.

2.1.6. Generational Differences and the Role of Generation Z

Generational cohort theory explains differences in values, attitudes, and behaviors across age-based groups shaped by shared social and historical experiences [54,55]. Generational identity encompasses not only age but also how individuals relate to work, authority, and organizational commitment. It has become a useful lens for understanding workforce diversity and differences in work attitudes [44,56].
Empirical studies report clear generational differences in job expectations, motivation, communication, and career flexibility [56]. For instance, Baby Boomers tend to show stronger loyalty, Generation X values autonomy, and Millennials prioritize meaningful work and real-time feedback. These differences shape how each group responds to leadership, rewards, and satisfaction [37].
Generation Z, usually defined as those born after the mid-1990s, is the most recent to enter the workforce and has attracted growing research attention. Studies show that Gen Z employees, as digital natives, prioritize flexibility, autonomy, and personal growth over job security and long-term employment [44]. Their approach emphasizes short-term, self-directed career paths and often includes an entrepreneurial mindset, making them less responsive to traditional retention strategies.
As a result, many studies now treat generational cohort as a moderator in organizational models. Generational differences are known to influence how employees respond to leadership, organizational support, and motivational factors [44,51]. These findings suggest that generational membership acts as a contextual factor that affects how employees interpret and react to work conditions.
In this study, Generation Z is modeled as a moderator between job satisfaction and intention to remain. Even when Gen Z employees report high satisfaction, their unique career outlook may weaken the connection between satisfaction and long-term retention.

2.2. Hypothesis Development

One of the most widely used frameworks for explaining job satisfaction is Herzberg’s Two-Factor Theory. It argues that employee attitudes toward work are shaped by two distinct types of factors: motivators and hygiene factors [11]. Motivators such as achievement, recognition, job content, and growth opportunities are built into the work itself and are considered the primary drivers of true satisfaction. In today’s work environment, workplace well-being has emerged as a particularly salient intrinsic motivator. Elements of well-being, including psychological safety, emotional resilience, and a sense of purpose, are increasingly recognized as essential components of a satisfying job experience. This perspective is consistent with Self-Determination Theory [9], which emphasizes that intrinsic motivation promotes personal wellbeing and effective functioning at work. When employees feel that their job offers autonomy, mastery, and purpose, they are more likely to report satisfaction. Previous empirical research supports this link, showing that intrinsic motivators are positively related to engagement, performance, and satisfaction [27,31,57]. Based on these foundations, we propose the following hypothesis:
H1. 
Intrinsic reward motivators (MF) have a significantly positive effect on job satisfaction (JS).
According to the theory, hygiene factors such as salary, job security, company policies, and physical conditions are needed to prevent dissatisfaction, but they do not create satisfaction by themselves [11]. These external factors relate to the work setting, not the job itself. When they are absent, dissatisfaction can increase, but when they are present, they only help maintain a neutral attitude without significantly raising satisfaction levels [58].
Some recent studies suggest that extrinsic rewards can influence satisfaction in contexts where material needs dominate [59,60]. However, others point out that such rewards may backfire, especially in high-pressure or high-expectation environments, where they may seem inadequate or unfair [61]. When employees perceive these rewards as falling short, it can lead to frustration or disengagement and lower their overall satisfaction. Consistent with this framework and our empirical findings, we suggest the following:
H2. 
Extrinsic hygiene factors (HF) have no significant positive effect on job satisfaction (JS) and may even influence it negatively under certain conditions.
Job satisfaction is widely recognized as one of the strongest predictors of an employee’s intention to stay. Social Exchange Theory [35] suggests that the employment relationship is based on reciprocal exchanges. When employees receive favorable treatment—such as meaningful work or supportive conditions—they feel obligated to return loyalty, trust, and long-term commitment [28,30,62]. In this view, job satisfaction reflects how fairly employees believe the exchange relationship is maintained.
This logic is supported by Organizational Commitment Theory [63], which argues that satisfied employees are more likely to form emotional bonds with the organization [14]. When they feel content with their roles and work environment, they are more likely to identify with organizational goals and want to remain. Affective commitment driven by satisfaction is consistently linked to lower turnover and stronger retention [29,64].
Empirical evidence confirms that satisfaction is a strong and consistent predictor of retention across industries and demographics [51,52,65]. Based on this, we propose the following:
H3. 
Job satisfaction (JS) has a significantly positive effect on intention to remain (IR).
Urbanization is often linked to both structural and psychological stress, including high living costs, long commutes, weak social networks, and intense job competition [45]. These pressures can lower job satisfaction, even in environments that offer material rewards or career development opportunities [5,46]. However, recent work in occupational psychology suggests that stressful conditions may increase the value of motivational resources [25,31].
The Job Demands and Resources (JD-R) model and the stress buffering hypothesis both propose that personal and work-related resources—such as intrinsic motivators like purpose and autonomy, or extrinsic rewards like fair pay and job security—help reduce the negative effects of high-stress environments. In urban workplaces, which are often impersonal and demanding, employees may depend more on these motivational factors to sustain wellbeing and satisfaction [66]. This resource compensation effect suggests that motivation may become even more influential in urbanized settings.
Following this logic and consistent with our empirical results, we propose that urbanization strengthens the effect of both intrinsic and extrinsic motivation on job satisfaction. In highly urban contexts, motivation may play a larger role by offsetting environmental stress.
H4. 
Urbanization positively moderates the relationship between motivational factors (MF), Hygiene Factors (HF) and job satisfaction (JS), strengthening their effects.
Although job satisfaction is generally a strong predictor of retention, this relationship may vary across generations [15]. Generational Theory [55,67] argues that each cohort forms distinct work values and behaviors shaped by their social and cultural context. Generation Z, usually defined as those born after the mid-1990s, entered the workforce with expectations that differ significantly from earlier generations.
Unlike older cohorts, Gen Z tends to prioritize autonomy, learning opportunities, work life balance, and rapid career advancement over long-term loyalty to an organization. Research shows that younger employees, including Gen Z, often see work as a short-term, transactional arrangement rather than a long-term commitment [44]. Even if they are satisfied with their current job, they may still seek outside opportunities or gig work that better fits their personal goals. This suggests that job satisfaction alone may be a weaker predictor of retention for this generation.
This generational shift indicates that the positive relationship between job satisfaction and intention to remain may be less pronounced for Generation Z, whose career decisions are driven more by individual goals than organizational ties.
H5. 
Generation Z negatively moderates the relationship between job satisfaction (JS) and employees’ intention to remain (IR), weakening the effect of satisfaction on retention.

2.3. Research Framework

Figure 1 visually summarizes the conceptual framework. Job Satisfaction (JS) is influenced by two distinct constructs—Motivational Factors (MF; intrinsic) and Hygiene Factors (HF; extrinsic)—which in turn shape Intention to Remain (IR). This structure reflects an indirect pathway from motivation to retention, tested through H1 to H3.
The model also includes two moderating variables that account for contextual differences. Urbanization is assumed to alter how strongly motivational factors affect job satisfaction, based on the idea that urban settings may amplify or suppress these effects (H4). Meanwhile, Generation Z is expected to influence how satisfaction translates into retention, with the possibility that younger employees are less likely to stay despite being satisfied (H5).
Together, the diagram integrates motivational, environmental, and generational elements into a conditional process model for understanding employee retention.

3. Empirical Approach

3.1. Methodology

This study applied partial least squares structural equation modeling (PLS-SEM) to examine how intrinsic motivational factors (MF) and extrinsic hygiene factors (HF) affect job satisfaction (JS), and how JS, in turn, influences the intention to remain (IR). It also tested whether these relationships differ by urbanization and generation (Generation Z). PLS-SEM is well suited for models with mediating and moderating variables, especially with small or non-normal distributed samples [68]. After confirmatory factor analysis and reliability testing, bootstrapping and interaction terms were used to assess both direct and moderated effects. Multi-group analysis was conducted to compare structural paths by subgroup, including urban versus non urban settings and generational cohorts.

3.2. Survey Instrument

The survey used validated scales to measure motivation, job satisfaction, and employee retention. All items followed a 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree), consistent with organizational behavior research practices [69]. Motivational factors (MF) and hygiene factors (HF) were based on Herzberg’s Two-Factor Theory and included autonomy, recognition, salary, and job stability [11,70]. Items for job satisfaction (JS) were adapted from Belias, Rossidis, Papademetriou and Mantas [51], and items for intention to remain (IR) were drawn from Mahfouz, Halim, Bahkia and Alias [30].
Demographic and contextual variables included gender, education, job tenure, and generation. Education was coded as 1 for university or higher, 0 for below. Job tenure was coded as 1 for three years or more, and 0 for less than three years. Generation Z was identified by year of birth (1 = Gen Z; 0 = non-Gen Z). The English survey was translated into Mandarin using Brislin’s [71] back translation method and reviewed by bilingual PhD researchers.

3.3. Data Collection

Data were collected using an online survey distributed through Wen Juan Xing, a widely used Chinese survey platform. The link was circulated via WeChat to reach currently employed individuals across various industries and regions. Although this approach involved non-probabilistic sampling, it enabled access to working professionals through peer-to-peer networks. This type of network-based referral sampling is common in exploratory research using social media platforms [72]. While not random, the method allowed for diversity in geography, sector, and demographics.
After excluding incomplete or invalid responses, 356 valid cases were retained. Only respondents who were currently employed were included to ensure relevance to job satisfaction and retention constructs. A combination of convenience and referral-based sampling was used, appropriate for studies targeting working populations.
To improve clarity and consistency, a pretest was conducted with native Mandarin speakers. Based on their feedback, minor revisions were made to enhance readability and ensure conceptual alignment between the English and Chinese versions. The survey avoided forced responses and ensured anonymity. Duplicate IP addresses were filtered to reduce repeat entries.

4. Empirical Results

4.1. Sample Characteristics and Descriptive Statistics

The final sample (n = 356) included a diverse group of currently employed individuals, allowing for subgroup comparisons across motivation types, generational cohorts, and urbanization levels. As shown in Table 1, gender distribution was nearly equal (49.7% male, 50.3% female), and participants had varied educational backgrounds, ranging from high school (21.9%) and vocational training (21.9%) to undergraduate (38.8%), master’s (11.8%), and doctoral degrees (5.6%).
In terms of generational cohort, 26.1% were Generation X (born 1965–1980), 36.8% Generation Y (1981–1995), and 35.4% Generation Z (1996–2006). Only 1.7% fell outside these defined ranges. Most participants (66.3%) had less than three years of job tenure, reflecting a largely early-career sample.
Urbanization was categorized using a two-tier classification based on population density and infrastructure [5,46]. Respondents lived in second-tier cities (43.8%), third- or fourth-tier cities (29.5%), or rural areas (26.7%). No respondents were from first-tier cities, which aligns with the study’s focus on non-core urban labor markets.
Employment sectors were evenly distributed across government (19.9%), manufacturing (19.4%), services (20.5%), agriculture (21.3%), and technology (18.8%). Job roles included managerial, administrative, technical, and customer-facing positions. The majority (67.1%) worked in small or medium-sized enterprises (SMEs), while about one-third were employed by firms with multi-city or international operations.
Although the sample does not represent the national labor force in a probabilistic sense, it reflects a broad spectrum of industries, job roles, and regional settings. The focus on early-career employees and non-core urban labor markets was intentional and aligns with the study’s aim to examine motivational mechanisms under modern urban constraints.

4.2. Reliability Testing

As summarized in Table 2, all constructs showed high internal consistency. Cronbach’s alpha values ranged from 0.90 (MF) to 0.99 (IR), exceeding the recommended threshold of 0.70 [68]. Composite reliability (CR) values were also above 0.90 across all constructs, confirming measurement reliability.
Standardized factor loadings ranged from 0.96 to 1.06 and were all statistically significant [73]. Although some loadings slightly exceeded 1.0, this can occur in PLS-SEM due to multicollinearity or normalization during bootstrapping. No problematic cross-loadings were observed. The average variance extracted (AVE) for all constructs exceeded 0.70, supporting convergent validity.
Together, these results confirm the psychometric adequacy of the measurement model and justify the use of four latent variables (MF, HF, JS, IR) in the subsequent structural model.
Confirmatory factor analysis (CFA) supported the validity of the measurement model (see Table 3). The model demonstrated excellent fit: the Comparative Fit Index (CFI = 0.999) and Tucker-Lewis Index (TLI = 0.999) both exceeded the 0.95 benchmark, indicating strong incremental fit. The Root Mean Square Error of Approximation (RMSEA = 0.011) was well below the 0.05 threshold, supporting close model fit. In addition, the chi-square statistic was non-significant (p = 0.235), suggesting minimal discrepancy between the observed and model-implied covariances.
Taken together, these indices confirm that the measurement model is structurally valid and appropriate for further structural equation modeling.

4.3. Hypothesis Testing

Partial least squares structural equation modeling (PLS-SEM) was employed to evaluate the hypothesized relationships among intrinsic motivational factors (MF), extrinsic hygiene factors (HF), job satisfaction (JS), and intention to remain (IR). PLS-SEM is appropriate for complex models with small samples and non-normal data distributions [68]. and emphasizes prediction over model fit.
As shown in Table 4, MF strongly predicts JS (β = 1.52), while HF show a significant negative effect (β = −0.36). JS positively affects IR (β = 0.50), confirming its mediating role.
Model fit indices indicate excellent fit: CFI and TLI both equal 1.00, RMSEA = 0.000, and the chi-square test was non-significant (p = 0.59). These results support the robustness of the structural model.
To empirically test the hypothesized relationships among intrinsic motivational factors (MF), extrinsic hygiene factors (HF), job satisfaction (JS), and employees’ intention to remain (IR), this study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) with a moderated mediation design. This approach enabled simultaneous testing of direct and indirect effects, as well as the moderating roles of urbanization (as a situational amplifier of motivational effects on satisfaction) and Generation Z (as a boundary condition influencing the satisfaction–retention link).
PLS-SEM is suitable for exploratory models involving complex structural relationships, interaction terms, and latent constructs, particularly in studies with moderate sample sizes and potential non-normality [68]. Unlike covariance-based SEM, PLS-SEM emphasizes prediction and explained variance, making it well-suited for examining behavioral responses to motivational factors across urban and generational contexts.
The full model included four latent constructs—Motivational Factors (MF), Hygiene Factors (HF), Job Satisfaction (JS), and Intention to Remain (IR)—along with two interaction terms (MF × Urbanization and JS × Generation Z), capturing the moderating influences of urban stress and generational orientation.
As shown in Table 5, the results support multiple hypothesized relationships. MF had a strong positive effect on JS (β = 1.11, p < 0.001), confirming H1. In contrast, HF showed a significant negative effect on JS (β = −0.60, p < 0.001), supporting H2. This aligns with the idea that hygiene factors may prevent dissatisfaction but do not necessarily promote satisfaction, and may even reduce it when perceived as insufficient or misaligned with expectations. In highly urbanized or competitive environments, extrinsic incentives may fall short of fairness standards and thereby reduce satisfaction.
JS positively influenced IR (β = 0.28, p < 0.001), supporting H3. Generation Z significantly weakened this relationship (β = −0.52, p < 0.001), as shown by the interaction term JS × Gen Z, supporting H5. This suggests that younger workers are less likely to base retention decisions solely on satisfaction, consistent with prior research on Gen Z’s career fluidity.
Urbanization played a dual moderating role. It significantly intensified the effects of both MF × Urbanization (β = 0.58, p = 0.04) and HF × Urbanization (β = 0.56, p < 0.001) on JS, supporting H4a and H4b. MF had a stronger positive effect in more urbanized settings, suggesting that autonomy, purpose, and personal growth help buffer urban stress. Conversely, the negative relationship between HF and JS was amplified in highly urbanized contexts. When such rewards are seen as inadequate or unfair, their adverse effects are magnified in competitive or high-cost urban environments.
Urbanization itself also had a significant negative direct effect on JS (β = −5.53, p = 0.005), reinforcing the idea that urban stress lowers baseline satisfaction levels while simultaneously intensifying the relevance of MF.
Together, these findings demonstrate how motivational structures function under conditions of urban pressure and generational transition. The results validate the use of a PLS-SEM moderated mediation framework and support integrating psychological and contextual perspectives to understand employee retention dynamics.

4.4. Robustness Check

4.4.1. Robustness Check by Gender

To assess the robustness of the baseline structural model, a multigroup SEM analysis was conducted using gender as the grouping variable. Although previous studies suggest gender-based differences in work values, motivation, and job satisfaction [74,75], the bootstrap-based comparison revealed no statistically significant differences across gender groups in the key structural relationships. Specifically, the effects of MF and HF on JS, as well as the effect of JS on IR, did not vary significantly between male and female respondents. These results, summarized in Table 6, confirm that the core pathways identified in the baseline model are stable and generalizable across gender, thereby reinforcing the robustness of the hypothesized relationships.

4.4.2. Robustness Check by Tenure

To further assess the robustness of the structural relationships identified in the baseline model, a multigroup analysis was conducted based on employee tenure. Specifically, we examined whether the core path coefficients—MF → JS, HF → JS, and JS → IR—differed significantly between employees with longer and shorter tenures within their current organizations.
Tenure was dichotomized at the three-year mark, a commonly used threshold in retention research to distinguish early-stage employees from more embedded or committed workers [76]. Prior studies suggest that after approximately three years, employees are more likely to develop organizational attachment, clearer role expectations, and stable satisfaction baselines, all of which may influence how they respond to motivational inputs [77]. Thus, examining tenure-based subgroups offers a theoretically grounded test of the model’s consistency across different stages of work experience.
A bootstrap-based multigroup SEM procedure with 500 resamples per group was used to estimate path differences. As shown in Table 7, none of the differences reached statistical significance at the 5% level. This includes the negative effect of HF on JS, which remained stable across both tenure groups despite diverging from conventional expectations. These findings suggest that the structural relationships in the full model—including the counterintuitive negative link between HF and JS—are robust across varying levels of tenure.
Overall, this analysis reinforces the model’s generalizability and stability across early-career and longer-tenured employees, supporting the validity of the hypothesized pathways across diverse experience contexts.

5. Conclusions

This study investigated how intrinsic motivational factors and extrinsic hygiene factors influence job satisfaction, and how satisfaction shapes employees’ intention to remain. By incorporating urbanization and generational identity as contextual moderators, this research extends existing motivational frameworks to account for contemporary workforce dynamics. Using PLS-SEM on data from 356 employees in China, the findings provide both theoretical refinement and practical relevance.
Intrinsic motivation significantly improved job satisfaction, reaffirming Herzberg’s and Self-Determination Theory [11,25]. In contrast, extrinsic rewards had a significant negative effect on job satisfaction. This outcome highlights that in high-pressure contexts such as competitive urban settings, the perceived adequacy and fairness of external compensation becomes more influential than their mere presence [8,30]. Under such conditions, financial or material rewards may become sources of dissatisfaction rather than neutral stabilizers.
While job satisfaction was positively linked to retention, this relationship was notably weaker among Generation Z. This generational nuance suggests that traditional retention strategies may have limited effectiveness for younger cohorts who value autonomy and meaningful work over organizational attachment [13,17].
Urbanization negatively affected satisfaction directly but enhanced the impact of both intrinsic and extrinsic motivators, indicating that environmental stress may activate compensatory psychological mechanisms [45,46]. These context-specific patterns were robust across subgroups (e.g., gender, tenure), demonstrating the model’s applicability across diverse employee profiles.
Overall, this research proposes a context-sensitive model that reconceptualizes motivation and retention as adaptive processes shaped by environmental and generational dynamics. By bridging classical motivation theories with urban labor dynamics and generational shifts, it offers both conceptual advancement and practical guidance for managing contemporary workforces.

5.1. Theoretical Implications

This study offers several contributions to theories of motivation and employee retention.
First, by identifying a negative relationship between extrinsic rewards and job satisfaction, the findings challenge the long-standing assumption in Herzberg’s original theory that hygiene factors are merely neutral [11]. In today’s high-pressure work environments, satisfaction is shaped not by whether rewards are offered, but by whether they are perceived as sufficient and fair relative to personal expectations [8,30]. When these conditions are not met, such rewards may actively reduce satisfaction rather than stabilize it. This perspective refines Herzberg’s framework and offers updated empirical support for how employees cognitively appraise compensation and support in context.
Second, the study reaffirms Self-Determination Theory by confirming the strong positive influence of motivational factors on job satisfaction [25,31], and extends the theory by showing that this effect is amplified in urban settings [45,46]. This finding aligns with the Job Demands–Resources (JDR) model, which suggests that autonomy and a sense of purpose function as critical psychological resources for maintaining well-being under stress [66]. In such conditions, intrinsic motivation supports not only engagement but also resilience.
Third, by integrating urbanization as both a direct predictor and a contextual moderator, the study expands the theoretical treatment of environmental context. While many motivational frameworks treat setting as a passive backdrop, these results show that urban pressures can heighten the psychological value of meaningful work and alter how employees assess reward adequacy [8].
Finally, The moderating effect of generational identity contributes to Generational Theory by demonstrating that psychological contracts differ by age group. The weakened link between satisfaction and retention intention among Gen Z suggests that motivation and organizational commitment are shaped by cohort-specific values and expectations [13,78]. These findings emphasize the need to incorporate generational perspectives into retention models, particularly in labor markets characterized by younger and more mobile workforces.
Taken together, these implications reframe motivation not as a fixed mechanism, but as a context-dependent process influenced by environmental pressures and generational worldviews. The study contributes a more nuanced and temporally grounded understanding of how employees evaluate their work and decide whether to stay or leave.

5.2. Practical Implications

This study provides actionable insights for human resource professionals and organizational leaders seeking to enhance employee satisfaction and retention in increasingly urban and generationally diverse workplaces.
First, the consistent and robust effect of intrinsic motivation underscores the importance of job designs that promote autonomy, purpose, and personal growth [25,31]. In high-pressure urban environments, organizations should move beyond task stability and instead create roles that foster meaning and self-direction.
Second, the negative relationship between hygiene-related extrinsic rewards and satisfaction implies that material rewards, when perceived as inadequate or unfair, may lead to disengagement. In competitive urban labor markets, employers should prioritize perceived equity over mere financial benchmarks. This includes transparent communication, regular feedback loops, and adaptive compensation systems [8,30].
Third, the weakened satisfaction–retention link among Gen Z suggests that younger employees view employment as modular and purpose-driven. HR strategies should offer flexible career paths, project-based roles, and fast-track development aligned with personal goals [13,17].
Finally, the model’s robustness across subgroups (e.g., gender, tenure) shows that motivation-based strategies can be broadly applied while allowing tailored interventions based on specific workforce segments.

5.3. Limitations and Future Research

While this study provides a contextually grounded view of how motivational factors and satisfaction affect retention across urban and generational lines, several limitations merit attention and open directions for future inquiry.
First, the cross-sectional design limits causal interpretation. Although structural equation modeling provides a strong basis for theoretical testing, longitudinal studies are needed to capture how motivational pathways evolve over time, particularly during career transitions or organizational changes.
Second, the sample is drawn exclusively from China, where urbanization and generational change are pronounced. While this enhances internal validity, it restricts generalizability. Comparative studies in diverse cultural and institutional contexts could determine whether the observed patterns hold across different labor markets [52].
Third, urbanization was measured through a binary tiered-city classification, which may oversimplify the lived experience of urban workers. Future research should consider multidimensional indicators of environmental demands in urban settings, such as commuting time, housing affordability, population density, or access to infrastructure, in order to better capture the psychosocial pressures that influence motivation and satisfaction [46,79,80].
Fourth, the definition of Generation Z was based on year of birth alone, which may neglect underlying psychological characteristics that vary within the same cohort. Future research could adopt validated psychometric scales, such as the Digital Nativeness Scale [81] to assess digital fluency, and Career Orientation Inventories [82,83] to capture values commonly associated with Gen Z work preferences, including autonomy, growth, and flexibility.
Finally, this study focused on individual-level motivational processes without incorporating organizational-level variables such as leadership, job design, or cultural norms. Future research could employ multilevel models to explore how institutional structures interact with personal motivation in shaping satisfaction and retention [51].
By addressing these limitations, future studies can further develop a comprehensive understanding of how individual, organizational, and contextual factors converge to influence workforce commitment in dynamic labor environments.

Author Contributions

Conceptualization, R.K.M. and J.M.K.; methodology, J.M.K. and G.K.; software, R.K.M.; validation, R.K.M., J.M.K. and J.Y.J.; formal analysis, R.K.M.; investigation, R.K.M.; resources, R.K.M.; data curation, R.K.M. and G.K.; writing—original draft preparation, R.K.M. and J.M.K.; writing—review and editing, G.K. and J.Y.J.; visualization, R.K.M.; supervision, J.M.K.; project administration, J.M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was reviewed and approved by the Institutional Review Board of Wenzhou-Kean University (Approval Number: WKUIRB2025-001).

Data Availability Statement

The data gathered and used in this study is available upon reasonable request to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Systems 13 00661 g001
Figure 1. Research Framework Methodology.
Figure 1. Research Framework Methodology.
Systems 13 00661 g001
Table 1. Demographic Characteristics of the Respondents (n = 356).
Table 1. Demographic Characteristics of the Respondents (n = 356).
VariableSubcategoryFrequencyPercent
GenderMale 17749.7
Female17950.3
Other00
Education LevelHigh school7821.9
Technical and Vocational School7821.9
Undergraduate13838.8
Master4211.8
Terminal Degree, MD, JD, PHD205.6
Generation 1965~1980 Gen X9326.1
1981~1995 Gen Y13136.8
1996~2006 Gen Z12635.4
Other 61.7
Years in current job Below 6 months5716
7 months–1 year7922.2
1 year–3 years10028.1
3 years–5 years8724.4
5 years and above339.3
Monthly SalaryBelow 30006518.3
3001–5000359.8
5001–10,00010028.1
10,001–15,0008523.9
15,001 or above7119.9
What size city do you live inFirst-tier city00
Second-tier city15643.8
Third and fourth tier city10529.5
Township, rural area9526.7
Industry SectorGovernment 7119.9
Manufacturing6919.4
Services7320.5
Agriculture 7621.3
Technology related6718.8
Current Position DutiesManagement/Supervision6819.1
Administrative4412.4
Customer Service5314.9
Manufacturing6618.5
Agriculture359.8
Technology related9025.3
Employer Firm SizeLess than 50 employees12434.8
50–200 Employees11532.3
201+ Employees11732.9
Employer Firm Facilities One facility11833.1
Facilities in 2+ cities12334.6
Facilities in 2+ countries11532.3
Table 2. Factor Loadings and Reliability of Latent Constructs.
Table 2. Factor Loadings and Reliability of Latent Constructs.
ConstructNo. of ItemsFactor Loading (Range)Mean
Loading		Cronbach’s α
Motivational Factors (MF)60.98–1.061.020.90
Hygiene Factors (HF)80.98–1.051.000.97
Job Satisfaction (JS)60.96–0.990.970.99
Intention to Remain (IR)70.99–1.031.010.99
Table 3. Confirmatory Factor Analysis Model Fit Statistics.
Table 3. Confirmatory Factor Analysis Model Fit Statistics.
Fit IndexValueThresholdInterpretation
CFI (Comparative Fit Index)1.00≥0.95Excellent fit
TLI (Tucker–Lewis Index)1.00≥0.95Excellent fit
RMSEA (Root Mean Square Error of Approximation)0.01≤0.05Excellent fit
χ2 p-value0.24>0.05Not significant
(good fit)
Table 4. Summary of Hypothesis Testing Results (Baseline Model).
Table 4. Summary of Hypothesis Testing Results (Baseline Model).
SectionRelationship/IndexEstimateSignificance
Structural PathsJS ← MF (H1)1.52p < 0.01
JS ← HF (H2)−0.36p < 0.01
IR ← JS (H3)0.50p < 0.01
Model Fit IndicesCFI 1.00≥0.95 (Excellent)
TLI 1.00≥0.95 (Excellent)
RMSEA0.00≤0.05 (Good fit)
χ2 (p)0.59>0.05 (not significant)
Table 5. Summary of Hypothesis Testing Results (Moderated Mediation Model).
Table 5. Summary of Hypothesis Testing Results (Moderated Mediation Model).
HypothesisPathEstimate (β)p-ValueSupported
H1JS ← MF (Motivational Factors → Satisfaction)1.11<0.001Yes
H2JS ← HF (Hygiene Factors→ Satisfaction)−0.60<0.001No
H3IR ← JS (Satisfaction → Intention to Remain)0.28<0.001Yes
H4aJS ← MF × Urbanization0.580.04Partial
H4bJS ← HF × Urbanization0.56<0.001Yes
—JS ← Urbanization (Direct Effect)−5.530.01—
H5IR ← JS × Generation Z−0.52<0.001Yes
Table 6. Gender-Based Multigroup SEM Results: Comparison of Structural Paths.
Table 6. Gender-Based Multigroup SEM Results: Comparison of Structural Paths.
PathMean Difference (βm − βf)95% CIp-ValueModeration by Gender
JS ← MF−0.31[−0.82, 0.21]0.18No
JS ← HF−0.07[−0.25, 0.11]0.15No
IR ← JS+0.05[−0.17, 0.27]0.68No
Table 7. Tenure-Based Multigroup SEM Results (3 + Years vs. <3 Years).
Table 7. Tenure-Based Multigroup SEM Results (3 + Years vs. <3 Years).
PathMean Difference95% CIp-Value
JS←MF−0.34[−0.85, 0.21]0.82
JS←HF−0.12[−0.31, 0.09]0.74
IR←JS0.075[−0.16, 0.30]0.52
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Marjerison, R.K.; Jun, J.Y.; Kim, J.M.; Kuan, G. Motivation, Urban Pressures, and the Limits of Satisfaction: Insights into Employee Retention in a Changing Workforce. Systems 2025, 13, 661. https://doi.org/10.3390/systems13080661

AMA Style

Marjerison RK, Jun JY, Kim JM, Kuan G. Motivation, Urban Pressures, and the Limits of Satisfaction: Insights into Employee Retention in a Changing Workforce. Systems. 2025; 13(8):661. https://doi.org/10.3390/systems13080661

Chicago/Turabian Style

Marjerison, Rob Kim, Jin Young Jun, Jong Min Kim, and George Kuan. 2025. "Motivation, Urban Pressures, and the Limits of Satisfaction: Insights into Employee Retention in a Changing Workforce" Systems 13, no. 8: 661. https://doi.org/10.3390/systems13080661

APA Style

Marjerison, R. K., Jun, J. Y., Kim, J. M., & Kuan, G. (2025). Motivation, Urban Pressures, and the Limits of Satisfaction: Insights into Employee Retention in a Changing Workforce. Systems, 13(8), 661. https://doi.org/10.3390/systems13080661

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