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ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume IX Issue X October 2025
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The Impact of Employee Satisfaction on the Performance of
Manufacturing Employees in Shanghai
Cheng Meng
*
, Toh Pei Sung, Sharifah Rahama Binti Amirul
Faculty of Business, Economics and Accountancy, Universiti Malaysia Sabah, Sabah, Malaysia
*
Corresponding Author
DOI: https://dx.doi.org/10.47772/IJRISS.2025.910000298
Received: 12 October 2025; Accepted: 18 October 2025; Published: 11 November 2025
ABSTRACT
This study investigates the impact of employee satisfaction on performance among manufacturing employees in
Shanghai using a structural equation modeling (SEM) approach. Data were collected from 100 employees
through questionnaires and semi-structured interviews, assessing. The SEM results show that employee
satisfaction has
a significant positive effect on performance, confirming its predictive role in enhancing task completion,
teamwork, and adaptability. The findings also reveal a reciprocal relationship between satisfaction and
performance, forming a reinforcing cycle of motivation and achievement. Practically, managers should
strengthen recognition systems, promote supportive team environments, and establish transparent development
pathways. The study contributes to understanding how satisfaction drives performance and offers actionable
guidance for improving employee engagement and organizational effectiveness in China’s manufacturing sector.
Keywords: employee satisfaction, employee performance, manufacturing industry, Shanghai
INTRODUCTION
Employee satisfaction has increasingly become a central theme in organizational research and practice, as it is
widely recognized as a critical factor influencing overall enterprise success (Wai et al., 2024). In the broadest
sense, employee satisfaction refers to the degree to which individuals feel content, valued, and motivated in their
workplace (Naseem et al., 2011). When employees are satisfied, they tend to exhibit greater engagement, higher
morale, and stronger organizational commitment, which translate into improved performance and long-term
sustainability for firms. Conversely, dissatisfaction often leads to negative outcomes such as absenteeism, low
productivity, and high turnover, all of which undermine organizational effectiveness (Sageer et al., 2012). In
today’s competitive environment, where efficiency and innovation are equally essential, understanding how
satisfaction influences performance has become a pressing concern.
The manufacturing sector is particularly relevant in this discussion, as it depends heavily on the efficiency,
precision, and collaboration of its workforce. Employee performance in manufacturing is often measured in
terms of productivity, quality, safety, and adherence to operational procedures (Mutegi et al., 2023). Unlike the
service industry, where performance may be more intangible or customer-oriented, manufacturing requires
consistent physical and cognitive effort, with outcomes that are directly tied to organizational competitiveness
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(Bayram, 2022). In this context, the extent to which employees are satisfied with their jobs has important
implications for organizational performance. A satisfied worker is more likely to maintain focus, adhere to
quality standards, and contribute to collective efficiency, whereas a dissatisfied worker may compromise output
and disrupt workflow (Abeje & Luo, 2023).
Shanghai provides a compelling context for examining this relationship. As one of China’s foremost economic
hubs and a leading center for industrial innovation, Shanghai has a vibrant manufacturing sector that is currently
undergoing significant transformation. The city faces rising labor costs, heightened global competition, and the
accelerating integration of digital technologies and automation. These forces put considerable pressure on
organizations to sustain productivity and competitiveness, while at the same time ensuring that their employees
remain engaged and motivated. Unlike in many Western countries where research on job satisfaction is extensive,
there is limited empirical evidence on how employee satisfaction affects performance in the Chinese context,
and even less so in the manufacturing industries of Shanghai.
The problem is further complicated by cultural and structural differences. In Western contexts, employee
satisfaction is often linked to individual autonomy, recognition, and work-life balance. In Shanghai’s
manufacturing firms, however, employees are frequently influenced by collective values, job security concerns,
and workplace hierarchy. These factors may shape satisfaction in unique ways, suggesting that existing models
and findings cannot be directly transplanted. Moreover, most Chinese studies have focused on broad sectors or
have generalized satisfaction-performance dynamics without isolating the specific realities of manufacturing.
This creates a gap in knowledge, as the manufacturing environment has distinctive features such as repetitive
tasks, strict production deadlines, and heavy reliance on teamwork. All these conditions may alter the way
satisfaction translates into performance.
Another reason for undertaking this study lies in the changing workforce dynamics of Shanghai. With younger
generations entering the manufacturing workforce, employees’ expectations are shifting toward greater career
development opportunities, fair compensation, and better working conditions. At the same time, digital
transformation is reshaping how employees interact with technology and supervisors. This evolving environment
raises questions about how satisfaction influences performance under new industrial realities. It is insufficient
to rely solely on past studies or data from other regions, as Shanghai’s manufacturing industry has its own
trajectory shaped by globalization, urban development, and government policy.
The objective of this study is therefore to investigate the impact of employee satisfaction on the performance of
manufacturing employees in Shanghai through a systematic and survey-based approach. The research seeks to
identify the primary factors that contribute to employee satisfaction, to analyze how these factors influence
different aspects of performance, and to examine whether demographic variables such as age, tenure, and
education moderate this relationship. By adopting a structured empirical design, the study aims to generate
evidence that not only clarifies the theoretical relationship between satisfaction and performance but also
provides actionable insights for practitioners.
The contribution of this study is threefold. From a theoretical perspective, it adds to the literature on
organizational behavior by contextualizing the satisfaction–performance link in Shanghai’s manufacturing
industry. Much of the existing literature is dominated by Western findings, and this research extends the
discussion to a Chinese context, highlighting cultural and industrial nuances that shape the relationship. From a
practical perspective, the findings can guide managers in designing policies that improve employee satisfaction,
such as targeted training, career development initiatives, and improvements to workplace conditions. By aligning
HR practices with the drivers of satisfaction, organizations can achieve higher productivity, reduce turnover, and
foster long-term competitiveness. At the policy level, the research has implications for labor management and
industrial strategy in Shanghai. Policymakers can use the insights to design regulations and support systems that
promote employee well-being while sustaining the city’s manufacturing competitiveness in the global economy.
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LITERATURE REVIEW
Employee Satisfaction
Employee satisfaction has been defined in organizational behavior literature as the degree to which employees
experience a sense of fulfillment, contentment, and positive emotional state resulting from their job and work
environment. Baxi and Atre (2024) offered one of the earliest and most widely cited definitions, describing job
satisfaction as “a pleasurable or positive emotional state resulting from the appraisal of one’s job or job
experiences.” This definition highlights two essential aspects: the cognitive evaluation of work conditions and
the affective response of employees. Employee satisfaction is not a single-dimensional construct; instead, it
reflects a composite of several factors such as compensation, work-life balance, recognition, job security, career
advancement opportunities, and workplace relationships. In the context of manufacturing, satisfaction often
takes on specific characteristics due to the nature of the work. Unlike service or knowledge-intensive industries,
manufacturing jobs are typically repetitive, time-bound, and performance-driven. Satisfaction in such settings is
strongly influenced by factors like safe working conditions, fair wages, stability of employment, and equitable
supervisory practices. Moreover, physical environment factors such as ergonomics, machine safety, and
workload distribution are critical in shaping employees’ perceptions of their jobs (Adams & Nino, 2024).
Theories of motivation provide useful lenses to understand employee satisfaction. Herzberg’s two-factor theory,
for instance, differentiates between hygiene factors (e.g., pay, working conditions, company policies) and
motivators (e.g., recognition, achievement, responsibility) (Hasan & Mishra, 2025). In a manufacturing setting,
hygiene factors are often foundational, as poor working conditions or inadequate safety measures quickly lead
to dissatisfaction. Meanwhile, motivators such as career development and recognition may further enhance
satisfaction when the basics are met (Koncar et al., 2022). Similarly, Maslow’s hierarchy of needs suggests that
physiological and safety needs are particularly important for manufacturing employees, who rely on stable
income and secure working environments before pursuing higher-order needs such as esteem or self-
actualization.
It is also important to note that employee satisfaction is dynamic rather than static. Employees’ expectations and
perceptions evolve with changing labor markets, economic conditions, and cultural shifts. For example, in
Shanghai, younger generations of manufacturing employees place greater emphasis on career growth and
personal development, compared with earlier generations who prioritized job security. As such, employee
satisfaction must be understood as an evolving construct that reflects the interplay between organizational
practices and employee values.
Employee Performance
Employee performance is generally understood as the extent to which an employee fulfills the tasks,
responsibilities, and goals associated with their role in the organization. Hameed and Waheed (2011) defined
performance as “behavior or actions that are relevant to the organization’s goals.” This perspective emphasizes
that performance is not merely about outcomes but also about the processes and behaviors that lead to those
outcomes. In other words, performance includes both the measurable outputs of an employee’s work and the
manner in which they achieve those results. In the manufacturing industry, performance is often assessed in
terms of productivity, quality, safety compliance, and teamwork. Productivity refers to the volume of output
produced within a given time frame, while quality emphasizes the accuracy and reliability of the output. Safety
compliance is particularly important in manufacturing settings where physical hazards are prevalent. Teamwork
and cooperation are also essential, as manufacturing processes frequently require coordination across individuals
and teams. These dimensions collectively determine the extent to which manufacturing employees contribute to
organizational success.
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Various models have been developed to conceptualize employee performance. Bergman et al. (2008)
distinguished between task performance, which directly contributes to organizational production, and contextual
performance, which includes behaviors such as helping colleagues and maintaining a positive organizational
climate. In a manufacturing context, task performance may involve operating machinery efficiently, reducing
error rates, or meeting production deadlines, while contextual performance may involve supporting team
members during high-demand periods or proactively identifying process improvements.
The determinants of performance are multifaceted. Factors such as employee skills, training, motivation,
leadership style, and organizational culture all play important roles. Satisfaction itself is often considered a key
predictor of performance, as satisfied employees are more likely to exert discretionary effort, maintain focus,
and display higher levels of commitment. However, performance is also influenced by external conditions such
as technology, management practices, and labor policies. For instance, employees may feel highly satisfied but
still perform poorly if outdated equipment or unclear processes hinder their work. In Shanghai’s manufacturing
sector, performance has taken on new dimensions with the push for industrial upgrading and digital
transformation. Employees are increasingly expected not only to meet traditional efficiency standards but also
to adapt to new technologies, participate in continuous improvement initiatives, and engage in skill upgrading.
This evolving definition of performance underscores the importance of linking satisfaction with adaptability,
innovation, and learning, in addition to traditional metrics like productivity and quality.
Employee Satisfaction and Employee Performance
The relationship between employee satisfaction and performance has been a central debate in organizational
research. Early studies suggested a “happy worker is a productive worker” hypothesis, arguing that satisfied
employees tend to perform better. Meta-analyses such as those conducted by Nordmann et al. (2012) provided
empirical evidence that the correlation, while positive, is moderate rather than strong, with contextual and
individual factors mediating the relationship. This indicates that satisfaction influences performance but does
not wholly determine it. In manufacturing contexts, several studies have highlighted the significance of
satisfaction for performance outcomes. For example, research conducted in developing economies has shown
that manufacturing employees who report higher satisfaction with compensation and working conditions are less
likely to engage in absenteeism and more likely to meet production targets (Böckerman & Ilmakunnas, 2008).
Studies in Asian contexts have found that satisfaction with job security and supervisory fairness are especially
strong predictors of performance, reflecting the cultural importance of stability and hierarchical relationships
(Santhanam & Srinivas, 2020).
In China, empirical studies on this topic remain relatively limited but growing. Some research indicates that
satisfaction related to career development opportunities and workplace harmony significantly enhances
employee performance in manufacturing firms. Others suggest that generational differences play a moderating
role: younger employees value growth and recognition, while older employees prioritize stability and job security.
However, findings are often fragmented, focusing on specific firms or industries without offering a broader
synthesis. Importantly, research has also pointed out that the satisfaction–performance relationship may be
reciprocal. While satisfaction can lead to improved performance, good performance may also enhance
satisfaction, as employees feel a sense of accomplishment and recognition. This dynamic interplay complicates
the causal direction of the relationship, suggesting that longitudinal studies or mixed-method approaches are
necessary to fully capture the dynamics.
Despite these insights, the majority of empirical studies continue to originate from Western contexts, leaving
questions about cultural and industry-specific differences unresolved. The Shanghai manufacturing industry,
with its unique blend of rapid technological change, cultural values, and economic pressures, presents a valuable
setting to further investigate this relationship.
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Research Gaps
Although the literature on employee satisfaction and performance provides valuable insights, several important
gaps remain, particularly in the context of Shanghai’s manufacturing sector. First, much of the existing research
has been conducted in Western countries, where cultural, social, and organizational contexts differ significantly
from those in China. In Western contexts, individual autonomy, recognition, and work-life balance are often
emphasized as determinants of satisfaction, while in China, especially in manufacturing industries, factors such
as job security, collective harmony, and hierarchical relationships play a stronger role. The lack of localized
studies means that the generalizability of Western findings to Shanghai’s workforce is uncertain.
Second, most Chinese studies addressing employee satisfaction and performance tend to treat industries in a
generalized manner, without differentiating between the unique characteristics of sectors such as manufacturing,
services, or technology. Manufacturing jobs involve repetitive tasks, high physical and mental demands, strict
production deadlines, and safety risks. These characteristics create a distinctive work environment that likely
shapes the way satisfaction influences performance. However, few empirical studies have focused specifically
on the manufacturing workforce in Shanghai, leaving an important gap in sector-specific knowledge. Third, the
majority of existing studies rely heavily on quantitative survey data, often using standardized scales to measure
satisfaction and performance. While these approaches provide statistical insights, they may overlook the nuanced
and subjective dimensions of employee experience. Satisfaction is shaped not only by organizational policies
but also by cultural values, generational expectations, and interpersonal dynamics. Without complementary
qualitative insights, current research may present an incomplete picture of how employees perceive their work
and how these perceptions affect performance.
RESEARCH METHODOLOGY
Research Purpose and Participants
The primary purpose of this study is to explore the impact of employee satisfaction on the performance of
manufacturing employees in Shanghai. While employee satisfaction has been studied extensively in various
cultural and industrial contexts, relatively few empirical investigations have focused on the specific conditions
of China’s manufacturing sector. Given Shanghai’s role as one of the most important industrial hubs in China,
understanding how employees’ levels of satisfaction influence their performance within this context is critical
both for academic knowledge and for managerial practice.
This research aims to achieve three objectives. First, it seeks to identify the key dimensions of employee
satisfaction that are most relevant to Shanghai’s manufacturing workforce, such as working conditions,
compensation, career development, interpersonal relationships, and organizational culture. Second, it aims to
examine how these satisfaction factors translate into performance outcomes, including productivity, quality of
work, innovation, and overall organizational contribution. Third, the study intends to generate practical insights
that can inform managers, policymakers, and human resource practitioners in improving both employee well-
being and firm competitiveness.
The research participants were selected from employees working in manufacturing enterprises across Shanghai,
including both state-owned and private companies. The focus was placed on front-line workers, technical staff,
and middle-level supervisors, as these groups represent the backbone of manufacturing operations. To ensure a
balanced view, participants were chosen to represent diverse demographic and occupational characteristics,
including age, gender, educational background, years of work experience, and job positions. By targeting
employees directly involved in production processes, the study ensures that the insights generated are grounded
in the actual work realities of Shanghai’s manufacturing industry. Semi-structured interviews were employed as
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the main data collection method. This approach allows for both consistency across interviews and flexibility to
probe deeper into participants’ experiences and perspectives. The participants were encouraged to share not only
their opinions about their work and satisfaction levels but also examples and reflections on how satisfaction
affects their day-to-day performance. This design provided a nuanced understanding of the satisfaction–
performance relationship that goes beyond what could be captured by purely quantitative surveys.
Sampling
The study adopted a purposive sampling strategy, which is commonly used in qualitative research to select
participants who can provide rich and relevant information related to the research questions (Campbell et al.,
2020). Since the objective was not statistical generalization but rather the in-depth exploration of employee
perspectives, purposive sampling ensured that the selected participants had direct experience in manufacturing
and could articulate their satisfaction and performance-related experiences. To increase diversity and reduce
potential bias, stratification was incorporated into the sampling process. Employees were selected from different
types of manufacturing companies, including electronics, machinery, textiles, and automotive sectors. This
approach ensured that findings would not be limited to a single subsector but would reflect a broader cross-
section of Shanghai’s manufacturing industry. Within each company, participants were drawn from different job
roles, including production line workers, technicians, quality controllers, and mid-level managers.
The final sample consisted of 40 employees, which is considered sufficient for a qualitative study of this scope.
The sample size allowed for data saturation—the point at which no new themes or insights emerged—while still
maintaining the depth of individual interviews. Recruitment was facilitated through personal contacts, company
introductions, and professional networks. Ethical considerations were strictly observed: all participants were
informed of the purpose of the study, their voluntary participation, and the confidentiality of their responses.
Written consent was obtained before conducting the interviews.
Research Design
The semi-structured interviews were designed around key themes derived from the literature review, including
working conditions, compensation, recognition, career development, interpersonal relations, organizational
culture, and perceived performance outcomes. Each interview began with general questions about participants’
job roles and work experiences, followed by more specific questions regarding their satisfaction and how it
influenced their performance. Probing questions were used to elicit concrete examples, such as situations in
which high satisfaction motivated better performance or dissatisfaction hindered productivity.
A short questionnaire was administered to all participants before the interviews. The questionnaire collected
demographic data (e.g., age, gender, education, years of experience, job role) and used a five-point Likert scale
to capture initial measures of job satisfaction and self-reported performance. While the survey was not the
primary data source, it provided useful background context and facilitated the structuring of interviews. The
questionnaires were distributed in both paper and electronic formats to accommodate participants’ preferences.
All 100 questionnaires were successfully collected, resulting in a 100% response rate. The data from the
questionnaires were later used to support the qualitative findings and to identify patterns that could be further
explored in the interviews.
The interviews were conducted between May and July 2025. Each session lasted between 45 and 60 minutes,
depending on the participant’s availability and willingness to share. Interviews were conducted face-to-face
where possible, especially within company premises, and via video conferencing tools when in-person meetings
were impractical. With participants’ consent, all interviews were audio-recorded and later transcribed verbatim
for analysis. To ensure ethical rigor, participants’ anonymity was preserved by assigning code numbers instead
of names. All data were stored securely and were accessible only to the research team. Participants were informed
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of their right to withdraw from the study at any time without consequences. These procedures enhanced trust
and encouraged participants to provide honest and detailed responses. Overall, the research design combined
qualitative depth with structured data collection to capture the complexity of employee satisfaction and its impact
on performance. By integrating interviews with supplementary questionnaires, the study achieved both nuanced
insights and contextual grounding, laying the foundation for rigorous analysis in the subsequent chapter.
RESULTS
Descriptive Analysis of Respondents
A total of 100 valid questionnaires were collected from employees in Shanghai’s manufacturing sector. The
participants included front-line production workers, technicians, and middle-level supervisors. Table 1 presents
the demographic characteristics of the sample. Among respondents, 60% were male and 40% were female. The
majority were aged between 25 and 40 years (65%), with 20% below 25 years and 15% above 40 years.
Educational background varied, with 55% holding a college degree or higher and 45% having completed high
school or vocational training. Work experience ranged from 1 to 15 years, representing both new and experienced
employees. The sample distribution reflects the diversity of the workforce in Shanghai’s manufacturing sector,
enabling an analysis of satisfaction and performance across multiple demographic groups.
Table 1 Demographic Characteristics of Respondents (n = 100)
Characteristic
Category
Frequency
Percentage (%)
Gender
Male
60
60
Female
40
40
Age
<25
20
20
25–40
65
65
>40
15
15
Education
High school/Vocational
45
45
college and above
55
55
Work Experience
<5 years
30
30
5–10 years
45
45
>10 years
25
25
Levels of Employee Satisfaction
Employee satisfaction was assessed across five dimensions: compensation, working conditions, career
development, recognition, and interpersonal relationships. Respondents rated each item on a five-point Likert
scale (1 = strongly disagree, 5 = strongly agree). Table 2 presents the mean scores and standard deviations for
each dimension.
Table 2 Levels of Employee Satisfaction (n = 100)
Mean
Standard Deviation
3.50
0.70
3.75
0.65
3.40
0.80
3.45
0.72
3.85
0.60
As seen in Table 2, interpersonal relationships and working conditions received the highest scores, indicating
that employee’s value supportive colleagues and safe work environments. Compensation and career
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development received moderate ratings, suggesting that improvements in pay and growth opportunities may
further enhance satisfaction. Recognition scored slightly lower, emphasizing the need for managerial
acknowledgment and feedback. Interview insights complemented the survey data. One production line worker
remarked: “I feel motivated when my supervisor notices my effort and my colleagues support each other, even
if the salary is not very high.” Others noted frustration over limited promotion channels, which occasionally
reduced motivation and performance
Levels of Employee Performance
Employee performance was evaluated based on four key indicators: task completion, work quality, teamwork,
and adaptability. Table 3 summarizes the descriptive results. The mean score for task completion was 4.10 (SD
= 0.55), indicating that most employees consistently meet productivity and deadline requirements. Teamwork
followed closely with a mean of 4.05 (SD = 0.60), reflecting strong collaborative engagement among employees
on the production floor. Work quality scored slightly lower at 3.95 (SD = 0.65), suggesting that while tasks are
completed on time, there may be room for enhancing precision and product consistency. Adaptability, which
measures employees’ ability to respond to process changes or new technologies, had the lowest mean score of
3.70 (SD = 0.75). These results reveal a relatively stable but improvement-oriented performance profile within
Shanghai’s manufacturing workforce. Informal interviews indicated that employees tend to perform better in
routine, well-structured environments but experience difficulties when production demands or technologies shift
rapidly.
The impact of Employee Satisfaction on Employee Performance
To examine the relationship between employee satisfaction and performance, a structural equation model (SEM)
was employed. The results (Table 3) show a standardized path coefficient (β) of 0.41, with a T-value of 7.68 and
p < 0.001, indicating a statistically significant positive relationship. This suggests that higher satisfaction levels
contribute meaningfully to improved employee performance. Among satisfaction dimensions, working
conditions and interpersonal relationships exhibited the strongest indirect influence on performance, primarily
by enhancing teamwork and motivation. Conversely, compensation and career development had moderate yet
meaningful effects, indicating that financial and growth-related incentives still play an essential motivational
role.
Table 4: The impact of employee satisfaction on employee performance
Path Relationship
Standardized Coefficient (β)
T-value
P-value
Technical Knowledge → Fraud Detection
0.41
7.68
<0.001
Qualitative responses reinforced these statistical findings. Several respondents mentioned that fair treatment,
supportive leadership, and a cohesive team environment enhance their willingness to take initiative. In contrast,
dissatisfaction with promotion prospects or recognition policies occasionally reduced enthusiasm, even among
skilled workers. This pattern supports Herzberg’s two-factor theory, emphasizing that while hygiene factors
prevent dissatisfaction, true performance improvement depends on motivational factors such as appreciation,
growth, and achievement. Consequently, the data imply that enhancing recognition systems and providing
transparent development pathways can strengthen both job satisfaction and performance outcomes in Shanghai’s
manufacturing sector.
DISCUSSION
The results of this study demonstrate a strong and multifaceted relationship between employee satisfaction and
performance in Shanghai’s manufacturing sector. Among the satisfaction dimensions, interpersonal relationships
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and recognition emerged as the most influential factors in motivating employees and enhancing performance
outcomes. This finding aligns with research suggesting that in collectivist cultural contexts, social cohesion,
team support, and acknowledgment from supervisors are often more salient motivators than monetary incentives.
Employees reported that supportive supervisors and collaborative colleagues directly increased their willingness
to exert effort, maintain high-quality work, and engage proactively in problem-solving. Such relational
satisfaction appears to create an environment where employees feel valued and empowered, which in turn fosters
sustained performance.
While compensation and career development were moderately correlated with performance, their effects were
less pronounced compared to interpersonal and recognition factors. This indicates that financial incentives alone
may not be sufficient to maximize employee performance in manufacturing contexts. Employees emphasized
that fair pay and opportunities for growth were necessary for baseline satisfaction, but the quality of daily
interactions and the sense of being appreciated played a stronger role in motivating higher-level performance. In
particular, the lack of transparent promotion channels and skill development programs was repeatedly cited as a
source of frustration, suggesting that organizations could improve performance by offering structured career
pathways and training initiatives.
Working conditions, although generally rated highly, were found to function primarily as a baseline requirement.
Safe, well-maintained, and ergonomically suitable environments were necessary to prevent dissatisfaction and
performance decline, but improvements beyond these basic standards had a relatively smaller impact on
motivation compared to social and recognition factors. This finding highlights the dual role of workplace
conditions: they are essential for maintaining operational efficiency, but alone they do not drive exceptional
performance.
The qualitative data further revealed a dynamic, reciprocal relationship between satisfaction and performance.
Employees who perceived themselves as performing well often reported higher levels of satisfaction, creating a
positive feedback loop. This underscores the importance of interventions that simultaneously enhance both
satisfaction and performance, rather than addressing them in isolation. For example, recognition programs that
acknowledge high performers not only reward achievement but also reinforce satisfaction, thereby motivating
continued effort and engagement.
From a managerial perspective, these findings suggest several practical implications. First, human resource
policies should prioritize relational and recognition-based initiatives, such as team-building activities, mentoring
programs, and regular feedback mechanisms. Second, career development pathways should be made more
transparent, with training opportunities aligned to employee aspirations and organizational needs. Third,
maintaining safe and supportive working conditions remains essential to prevent dissatisfaction, even if
incremental improvements do not dramatically enhance performance. Finally, organizations should foster a
culture that reinforces the reciprocal link between satisfaction and performance, ensuring that employees feel
their contributions are recognized and that they have opportunities to grow within the organization.
CONCLUSION
This study investigated the impact of employee satisfaction on the performance of manufacturing employees in
Shanghai. The analysis revealed a multifaceted relationship between satisfaction and performance, providing
both theoretical and practical insights relevant to the manufacturing context in a rapidly evolving industrial city.
The SEM results confirmed that employee satisfaction has a significant positive effect on overall performance,
with a standardized path coefficient (β = 0.41, p < 0.001). This indicates that satisfaction is not only correlated
with performance but also serves as a causal predictor of employee effectiveness. The model achieved
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satisfactory goodness-of-fit indices, suggesting that the hypothesized relationships among latent variables were
statistically robust. The findings thus support the conceptual assumption that satisfaction operates as a
multidimensional construct influencing various aspects of employee behavior, motivation, and output quality.
Furthermore, the reciprocal association between satisfaction and performance observed through model
modification indices suggests that higher-performing employees report stronger satisfaction, indicating the
existence of a reinforcing loop. This finding underscores the need for dynamic management mechanisms that
simultaneously enhance both constructs rather than addressing them in isolation
The findings provide actionable insights for manufacturing managers and human resource practitioners. First,
organizations should prioritize relational and recognition-focused initiatives, such as team-building activities,
mentorship programs, and formal recognition schemes. Second, career development pathways should be made
transparent, with skill-building and training opportunities aligned to both employee aspirations and
organizational needs. Third, maintaining safe, comfortable, and ergonomically sound working conditions is
essential to ensure baseline satisfaction and prevent declines in performance. Finally, organizations should foster
a culture that strengthens the feedback loop between satisfaction and performance, ensuring that employees’
contributions are acknowledged and that they have opportunities to grow professionally.
Despite the insights gained, this study has several limitations. First, the sample size of 100 employees, while
sufficient for qualitative exploration, limits the generalizability of the findings. Larger-scale studies are needed
to confirm the observed patterns across the broader Shanghai manufacturing workforce. Second, the study relied
on self-reported measures of performance, which may be subject to response bias or social desirability effects.
Future research could integrate objective performance metrics or supervisor evaluations to enhance reliability.
Third, the study focused solely on Shanghai, a major industrial hub, and may not capture regional variations in
China’s diverse manufacturing sectors. Finally, while semi-structured interviews provided rich insights, the
cross-sectional design limits the ability to draw causal inferences about the satisfaction–performance relationship
over time.
Future studies should consider longitudinal designs to examine how changes in satisfaction influence
performance over extended periods, particularly in the context of rapidly evolving manufacturing technologies
and digitalization. Expanding the research to other regions or industries in China would enhance the
generalizability of findings and allow for cross-sector comparisons. Additionally, integrating objective
performance data, such as production records, error rates, or efficiency metrics, could provide a more robust
understanding of the satisfaction–performance link. Researchers may also explore the moderating roles of
organizational culture, leadership style, and generational differences in shaping how satisfaction impacts
performance.
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INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)
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