Advances in Human Resource Management Research Volume 4.
Issue 1 .
e-ISSN: 2985-7570 DOI: https://doi.
org/10.
60079/ahrmr.
The Role of Job Satisfaction in Mediating the Effects of the Digital Work Environment.
Organizational Culture, and Work Commitment on Banking Employee Performance Rezky Ratnasari Taufan A 1* Taupan 2 Sian Linda Lerebulan 3 Moh Zulkifli Murfat 4 1 Universitas Muslim Indonesia.
Makassar.
Indonesia.
Email: rezkyratnasari@umi.
2 Universitas Muslim Indonesia.
Makassar.
Indonesia.
Email: taupan.
taupan@umi.
3 Sekolah Tinggi Ilmu Ekonomi Port Numbay Jayapura.
Jayapura.
Indonesia.
Email: sianl.
lerebulan@gmail.
4 Universitas Muslim Indonesia.
Makassar.
Indonesia.
Email: mohzulkifli.
murfat@umi.
ARTICLE HISTORY
Submitted Reviewed Revised Accepted Published November 29, 2025 December 30, 2025 January 07, 2026 January 12, 2026 January 29, 2026 January 31, 2026 Conflict of Interest Statement:
The author.
declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
ABSTRACT
Purpose: This study aims to examine the effects of the digital work environment, organizational culture, and work commitment on employee performance, with job satisfaction serving as a mediating variable in the banking sector in Makassar.
Research Method: This study employed a quantitative approach with an explanatory research design.
Data were collected from 184 banking employees using purposive sampling techniques.
The data were analyzed using covariance-based Structural Equation Modeling (SEM) with the assistance of AMOS to test both direct and indirect relationships among the Results and Discussion: The findings indicate that the digital work environment, organizational culture, and work commitment have positive and significant effects on job satisfaction.
Job satisfaction also has a positive and significant effect on employee performance.
Furthermore, the digital work environment and work commitment have both direct and indirect effects on employee performance, indicating partial mediation through job satisfaction.
In contrast, organizational culture does not directly affect employee performance, but it has a significant indirect effect through job satisfaction, indicating full mediation.
Implications: The study highlights the importance of integrating digital transformation initiatives with effective human resource management Banking organizations should focus on creating supportive digital work environments, strengthening organizational culture, and fostering employee commitment in order to enhance job satisfaction and improve overall performance.
Keywords: digital work environment.
organizational culture.
work commitment.
employee performance.
Introduction The rapid advancement of information technology in the era of the Fourth Industrial Revolution has driven significant transformation in the banking sector.
Digitalization is no longer an option, but rather a strategic necessity to enhance efficiency and competitiveness.
A report by the World Bank .
indicates that most global financial institutions have adopted digital systems as the backbone of their operations, while McKinsey & Company .
projects that digital-based banking interactions will dominate the industry in the coming years.
In Indonesia, this transformation has been reinforced The Author.
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through policies issued by Otoritas Jasa Keuangan .
, alongside the increase in digital banking transactions, which reached IDR 52,545 trillion in 2022 according to Bank Indonesia .
Makassar, as the economic hub of Eastern Indonesia, demonstrates rapidly growing banking The growth of banking assets and service expansion has made this region a relevant context for examining the implementation of digital transformation in the banking sector (OJK, 2.
In line with these developments, various banking institutions have adopted digital-based systems such as mobile banking, core banking, and hybrid work arrangements, all of which have directly reshaped employeesAo work environments.
However, such digital transformation has not always been accompanied by optimal improvements in employee performance.
Preliminary observations indicate the presence of adaptation pressure, role ambiguity, and increased workloads resulting from changes in digital-based work systems.
In addition, organizational cultures that are not yet fully adaptive, along with declining work commitment, have contributed to lower employee job satisfaction, which ultimately affects performance (Handayani et al.
, 2020.
Jorgensen et al.
, 2019.
Judge et al.
, 2.
Previous studies have shown that the work environment, organizational culture, and work commitment influence job satisfaction and employee performance (Prasetyo & Wahyudin, 2021.
Rahmawati & Sudiro, 2022.
Trang et al.
, 2.
Nevertheless, most prior research has viewed the work environment from a conventional perspective and has not comprehensively integrated the digital dimension.
Furthermore, the mediating role of job satisfaction has rarely been tested simultaneously within an integrated model, particularly in the banking sector of Eastern Indonesia.
Based on these considerations, this study aims to analyze the effects of the digital work environment, organizational culture, and work commitment on job satisfaction and employee performance, as well as to examine the mediating role of job satisfaction in the banking sector in Makassar.
This study is expected to provide theoretical contributions to the development of mediation models in human resource management research within the digital context, particularly in Eastern Indonesia.
Practically, the findings may serve as a basis for recommendations to banking management and regulators in improving employee performance in the digital era.
This study offers a significant theoretical contribution to the field of human resource management by extending existing models of employee performance into the context of digital transformation in the banking industry.
While previous studies have primarily examined conventional workplace factors, this research integrates the concept of the digital work environment with organizational culture and work commitment in a single analytical framework (Bentley et al.
, 2016.
Robbins & Judge, 2019.
Meyer & Allen, 1.
Furthermore, the study enriches the literature by confirming the mediating role of job satisfaction in explaining how organizational and technological factors influence employee performance (Brahmasari & Suprayetno, 2008.
Rina et al.
, 2.
These findings contribute to a broader understanding of employee behavior in technology-driven organizations, particularly in emerging economies such as Indonesia.
From a practical perspective, this research provides useful insights for banking managers and organizational leaders in designing effective workforce strategies during digital transformation.
The results indicate that investments in technology alone are insufficient to improve employee performance unless they are accompanied by efforts to enhance job satisfaction, strengthen commitment, and cultivate a supportive organizational culture (Judge et al.
, 2001.
Yousef, 2.
Therefore, managers should focus on creating user-friendly digital systems, providing continuous training, clarifying job roles, and maintaining employee well-being to ensure that digitalization initiatives generate positive performance outcomes.
This study also carries important managerial implications for the banking sector in Makassar and other regions experiencing similar transitions.
Banks operating in competitive environments need The Author.
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to recognize that employee adaptation to digital systems is a strategic issue rather than merely an operational challenge.
Human resource policies should prioritize employee engagement, motivation, and satisfaction as key drivers of service quality and productivity.
By doing so, organizations can reduce resistance to change and improve overall organizational resilience (Denison et al.
, 2012.
Griffin et al.
In terms of policy contribution, the findings may serve as evidence-based input for regulators such as Otoritas Jasa Keuangan and Bank Indonesia in formulating policies that support sustainable digital transformation in the financial sector.
Regulatory frameworks should not only encourage technological adoption, but also promote workforce readiness, employee capability development, and fair labor practices in the digital workplace.
Such policies are essential to ensure that technological progress is aligned with human capital development and long-term sectoral performance.
The remainder of this paper is organized as follows.
Section 2 provides literature review and hypothesis development.
Section 3 presents research method and design.
Section 4 provides empirical result and discussion.
Section 5 is conclusion.
Literature Review and Hypothesis Development 1 Employee Performance Employee performance is a primary indicator of organizational success, reflecting the extent to which employees achieve work outcomes in terms of quality and quantity in accordance with assigned responsibilities (Mangkunegara, 2.
In the human resource management perspective, performance is influenced not only by individual competence, but also by motivation and organizational support (Mathis & Jackson, 2.
In modern organizations, employee performance is no longer viewed as a unidimensional construct.
Campbell et al.
argued that performance consists of multiple components, including task proficiency and work effort.
Likewise.
Borman and Motowidlo .
distinguished between task performance and contextual performance, where contextual dimensions such as adaptability, cooperation, and initiative have become increasingly important in dynamic work Griffin et al.
further emphasized that in periods of organizational change, such as digital transformation, employee performance largely depends on the ability to adapt to new work Therefore, in the context of digital banking, employee performance should be assessed not only through work outputs, but also through employeesAo capacity to adapt to digital systems and changing workplace conditions.
2 Digital Work Environment and Job Satisfaction The digital work environment refers to working conditions supported by information technology, including digital systems, collaborative platforms, and network infrastructure that enable efficiency and flexibility at work.
Digital transformation has reshaped work processes, making them more integrated, faster, and system-oriented.
According to the Technology Acceptance Model (TAM).
Davis .
explained that technology acceptance is determined by perceived usefulness and perceived ease of use.
This framework was later extended by the Unified Theory of Acceptance and Use of Technology (UTAUT), which added social influence and facilitating conditions as determinants of technology usage in organizations (Venkatesh et al.
, 2.
Empirical studies indicate that an effective digital work environment can enhance job satisfaction through easier access to information, improved work efficiency, and reduced administrative burden.
However, if not accompanied by organizational The Author.
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readiness, digitalization may also create work pressure and reduce employee satisfaction.
Accordingly, employees who perceive digital systems as useful and supportive are more likely to experience higher job satisfaction.
H1: The digital work environment has a positive and significant effect on job satisfaction.
3 Organizational Culture and Job Satisfaction Organizational culture represents a system of values, norms, and beliefs that shape the behavior of organizational members (Schein, 2.
It serves as a guide for how individuals interact, make decisions, and respond to change.
In the context of digital transformation, an adaptive and innovative culture becomes essential to support successful technology implementation.
Denison et al.
found that cultures emphasizing involvement and adaptability contribute positively to job satisfaction and organizational effectiveness.
Robbins and Judge .
also noted that a positive organizational culture strengthens employeesAo emotional attachment to the organization.
Previous studies have shown that organizational cultures supporting collaboration, innovation, and trust are positively associated with employee job satisfaction.
In contrast, rigid and change-resistant cultures may lower employee satisfaction, especially in organizations undergoing technological Therefore, a supportive organizational culture is expected to foster greater job satisfaction among employees.
H2: Organizational culture has a positive and significant effect on job satisfaction.
4 Work Commitment and Job Satisfaction Work commitment refers to employeesAo psychological attachment to the organization, reflecting loyalty and willingness to remain part of the organization (Meyer & Allen, 1.
Work commitment consists of three dimensions: affective commitment, continuance commitment, and normative commitment.
Employees with strong commitment tend to be more involved in their work and maintain positive perceptions of the organization.
In addition, work commitment acts as a stabilizing factor during organizational changes, including digital transformation.
Prior studies found that committed employees are more satisfied with their jobs and demonstrate stronger performance outcomes.
Employees who identify with organizational goals are more likely to feel fulfilled and motivated in their roles.
H3: Work commitment has a positive and significant effect on job satisfaction.
5 Job Satisfaction and Employee Performance Job satisfaction is an individualAos affective evaluation of their job (Locke, 1.
It reflects the extent to which employees are satisfied with various job aspects, such as the work environment, compensation, supervision, and workplace relationships.
Herzberg et al.
distinguished between motivator factors, which create satisfaction, and hygiene factors, which prevent dissatisfaction.
Empirical evidence suggests that satisfied employees tend to demonstrate higher motivation, stronger commitment, lower absenteeism, and better work performance.
Judge et al.
found a positive relationship between job satisfaction and employee performance, although the relationship may vary across contexts.
digital banking environments, satisfied employees are more likely to adapt effectively to technological changes and maintain high service quality.
H4: Job satisfaction has a positive and significant effect on employee performance.
The Author.
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6 Direct Effects of Organizational Factors on Employee Performance A supportive digital work environment can directly improve performance by increasing efficiency, communication speed, and decision-making accuracy.
Likewise, a strong organizational culture can align employee behavior with organizational objectives, while committed employees are more likely to exert extra effort in achieving organizational goals.
Therefore, these variables are expected to directly influence employee performance.
H5: The digital work environment has a positive and significant effect on employee performance.
H6: Organizational culture has a positive and significant effect on employee performance.
H7: Work commitment has a positive and significant effect on employee performance.
7 The Mediating Role of Job Satisfaction Job satisfaction functions as a psychological mechanism through which organizational factors influence employee performance (Baron & Kenny, 1.
Employees who experience supportive digital systems, positive organizational culture, and strong commitment are more likely to feel satisfied, which subsequently enhances their performance.
Previous studies also confirmed that job satisfaction mediates the relationship between organizational variables and employee outcomes, although the strength of mediation may vary depending on context.
H8: Job satisfaction mediates the relationship between the digital work environment and employee H9: Job satisfaction mediates the relationship between organizational culture and employee performance.
H10: Job satisfaction mediates the relationship between work commitment and employee performance.
Research Method This study employed a quantitative approach with an explanatory research design to examine the effects of the digital work environment, organizational culture, and work commitment on employee performance, with job satisfaction serving as a mediating variable.
The research was conducted in the banking sector in Makassar, which represents the Eastern Indonesia region experiencing accelerated digital transformation.
The target population consisted of banking employees.
however, the exact population size could not be determined due to limited access to comprehensive data on the total number of banking Therefore, this study applied a non-probability sampling method using purposive sampling.
The respondents were selected based on the following criteria: .
being employed in the banking sector, .
being involved in a digital-based work system, and .
having at least one year of work A total of 184 respondents participated in the study.
This sample size followed the recommendation for covariance-based Structural Equation Modeling (CB-SEM), which suggests a minimum of 5Ae10 times the number of indicators (Hair et al.
, 2.
, indicating that the sample was adequate for SEM analysis.
Data were collected through a survey using a structured questionnaire measured on a five-point Likert scale.
The research instrument was developed based on indicators adapted from previous studies.
The questionnaire consisted of items measuring the digital work environment, organizational culture, work commitment, job satisfaction, and employee performance.
Prior to the main analysis, the instrument was assessed to ensure clarity, validity, and reliability.
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The data analysis was conducted in two stages.
First, descriptive analysis was used to describe the demographic characteristics of respondents and provide an overview of the study variables.
Second, inferential analysis was performed using covariance-based Structural Equation Modeling (SEM) with IBM SPSS AMOS.
The SEM procedure included testing the measurement model through Confirmatory Factor Analysis (CFA) to assess construct validity and reliability, followed by structural model testing to examine the hypothesized relationships among variables.
Model fit was evaluated using several goodness-of-fit indices, including Chi-square.
Comparative Fit Index (CFI).
Tucker-Lewis Index (TLI).
Goodness-of-Fit Index (GFI).
Adjusted Goodness-of-Fit Index (AGFI), and Root Mean Square Error of Approximation (RMSEA).
Hypothesis testing was based on path coefficients and significance levels .
-value.
, while mediation effects were examined through indirect effect analysis using the bootstrapping approach.
Results and Discussion 1 Analysis Results 1 Characteristics of Respondents The characteristics of respondents in this study are presented to provide a general overview of the profiles of individuals involved, as well as to serve as a basis for understanding the context of the research findings.
The demographic variables analyzed include gender, age, and educational level, which are considered relevant in explaining variations in respondentsAo perceptions of the digital work environment, organizational culture, work commitment, and their implications for job satisfaction and employee performance.
The selection of these characteristics was based on the assumption that demographic factors play an important role in shaping individual adaptation patterns to changes in work systems, particularly in the context of digital transformation within the banking sector.
Differences in age, educational background, and gender may influence employeesAo readiness to adopt digital technology, respond to organizational change, and maintain commitment in a dynamic work Therefore, examining respondent characteristics provides important preliminary insights into the social and organizational context of the study.
Accordingly, the analysis of respondent characteristics is not merely descriptive in nature, but also serves to establish an initial context for understanding the dynamics of the relationships among the variables under investigation.
The distribution of respondent characteristics in this study is presented in Table 1.
Tabel 1.
Respondent Characteristics Characteristics Gender Age Education Category Male Female 20 Ae 30 years 31 Ae 40 years 41 Ae 50 years Source: Data Processed .
Based on Table 1, the distribution of respondents demonstrates a relatively balanced gender composition between male employees .
%) and female employees .
%), indicating that the banking The Author.
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sector in Makassar does not exhibit the dominance of any particular gender within its workforce This balanced representation suggests that employment opportunities and organizational participation in the banking industry are relatively inclusive, allowing both male and female employees to contribute equally to organizational performance and adaptation to digital transformation.
Table 2.
Construct Validity Test Construct/Indicator X1.
X1.
X1.
X1.
X2.
X2.
X2.
X2.
X2.
X2.
X3.
X3.
X3.
X3.
Y1.
Y1.
Y1.
Y1.
Y2.
Y2.
Y2.
Y2.
Loading Factor () Digital-Based Work Environment (X.
Organizational culture (X.
Work Commitment (X.
Job satisfaction (Y.
Employee Performance (Y.
p-value Notes Valid Valid Valid References Valid Valid Valid Valid Valid References Valid Valid Valid References References Valid Valid Valid References Valid Valid Valid Source: Processed data .
In terms of age, the majority of respondents were within the 31Ae40 years age group .
%), followed by those aged 41Ae50 years .
%) and 20Ae30 years .
%).
This distribution indicates that the banking workforce is largely dominated by employees in their productive age with relatively mature professional experience, which plays an important role in adapting to digital-based work environments.
The limited proportion of very young employees implies that digital transformation in the banking sector does not rely solely on digital-native generations, but also on experienced employees who have developed substantial organizational knowledge and professional competencies.
Regarding educational background, most respondents held a BachelorAos degree .
%), while 34% possessed a MasterAos degree.
This finding suggests that human resources in the banking sector tend to have a relatively high level of education.
Such conditions reflect cognitive readiness and analytical capacity that support the implementation of digital-based work systems.
The relative homogeneity of educational attainment also indicates that differences in perceptions regarding the research variables are more likely The Author.
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to be influenced by organizational factors rather than disparities in educational background.
Construct validity was assessed through Confirmatory Factor Analysis (CFA) to evaluate the ability of each indicator to reflect its respective latent construct.
The results revealed that all indicators achieved loading factor values above the required minimum threshold, indicating that all measurement items were convergently valid and suitable for further analysis within the structural model.
The results of the measurement model testing through Confirmatory Factor Analysis (CFA) indicate that all indicators for each construct achieved loading factor values above 0.
50 and were statistically significant at the 95% confidence level .
< 0.
This finding suggests that all indicators were able to adequately reflect the latent constructs being measured.
Therefore, each measurement item demonstrated satisfactory representativeness and contributed meaningfully to its respective More specifically, the Digital Work Environment construct (X.
showed loading factor values ranging from 0.
609 to 0.
920, indicating strong indicator contributions in forming the construct.
For the Organizational Culture construct (X.
, all indicators also demonstrated acceptable validity, although one indicator recorded a relatively lower loading value .
Nevertheless, this value remains within the acceptable tolerance level commonly applied in social science research.
Tabel 3.
Validity and Reliability Construct Testing Construct Work Environment (X.
Organizational Culture (X.
Work Commitment (X.
Job Satisfaction (Y.
Indicator Loading () A 1AeA
AVE
Note X1.
X1.
X1.
X1.
X2.
X2.
X2.
X2.
X2.
X2.
X3.
X3.
X3.
X3.
Y1.
Y1.
Y1.
Y1.
Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Reliable Source: Processed data .
The constructs of Work Commitment (X.
Job Satisfaction (Y.
, and Employee Performance (Y.
also produced consistent results, with all indicators obtaining loading factor values above 0.
60 and significant at the required level.
These findings confirm that the measurement model in this study satisfies the criteria of convergent validity, indicating that the indicators within each construct share a high proportion of common variance.
Accordingly, it can be concluded that all constructs in this study The Author.
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are valid and appropriate for further testing in the structural model stage.
To strengthen the assessment of measurement quality, the model was further evaluated through convergent validity and construct reliability testing to ensure that each indicator accurately and consistently reflected its latent variable.
Convergent validity was assessed using loading factor values and Average Variance Extracted (AVE), while construct reliability was evaluated using Construct Reliability (CR).
Referring to the criteria proposed by Hair et al.
, indicators are considered valid when loading factor values are Ou 0.
50 and AVE values are Ou 0.
50, while constructs are considered reliable when CR values are Ou 0.
The results of the measurement model evaluation indicate that all indicators across each construct achieved loading factor values above the minimum threshold of 0.
50, thereby satisfying the criteria for convergent validity.
The highest loading factor values were identified for indicators X1.
and X3.
, suggesting that these indicators made a particularly strong contribution in reflecting their respective latent constructs.
These findings demonstrate that the selected indicators were highly representative of the variables being measured.
Nevertheless, several indicators showed relatively moderate loading factor values, such as X1.
and X2.
Although comparatively lower, these values remain within the acceptable tolerance range for covariance-based Structural Equation Modeling (SEM) analysis (Hair et al.
, 2.
Therefore, these indicators were retained because they still provided meaningful explanatory power for their associated constructs.
Furthermore, the Average Variance Extracted (AVE) values for all constructs exceeded the recommended threshold of 50, namely 0.
563 for the Digital Work Environment, 0.
578 for Organizational Culture, 0.
582 for Work Commitment, and 0.
541 for Job Satisfaction.
These results indicate that each construct was able to explain more than 50% of the variance of its indicators, confirming that convergent validity was successfully achieved.
From the reliability perspective, all constructs demonstrated Construct Reliability (CR) values above the minimum criterion of 0.
70, specifically 0.
834 for the Digital Work Environment, 0.
872 for Organizational Culture, 0.
845 for Work Commitment, and 0.
824 for Job Satisfaction.
These findings indicate that the constructs used in this study possessed strong internal consistency and were reliable measures of the latent variables.
Based on these results, it can be concluded that the measurement model fulfilled the required standards of convergent validity and construct reliability, and was therefore appropriate for further testing in the structural model stage.
Source: Processed data .
Figure 1.
Initial Structural Model The Author.
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The results of structural model testing using covariance-based Structural Equation Modeling (SEM) indicate that the proposed model achieved an overall level of fit classified as marginal fit.
This is reflected in the Chi-Square value of 463.
731 with a probability value of 0.
000, suggesting that the model did not fully satisfy the criteria of absolute fit.
However, considering that the Chi-Square statistic is highly sensitive to sample size, model evaluation should not rely solely on this indicator.
Therefore, additional goodness-of-fit indices were examined to provide a more comprehensive assessment of model The CMIN/DF value of 2.
591 indicates that the model remained within the acceptable threshold (< 3.
, suggesting a reasonably good fit between the proposed model and the observed data.
Furthermore, the Goodness-of-Fit Index (GFI) of 0.
823 and Adjusted Goodness-of-Fit Index (AGFI) of 771 place the model within the marginal fit category, as both values did not yet reach the ideal cutoff level of Ou 0.
Similarly, the Tucker-Lewis Index (TLI) of 0.
818 and Comparative Fit Index (CFI) of 845 indicate that the model did not fully satisfy the expected incremental fit criteria.
Meanwhile, the Root Mean Square Error of Approximation (RMSEA) value of 0.
093 suggests a mediocre fit, as it exceeds the preferred threshold of O 0.
08, although it remains within a tolerable range for models with relatively high complexity.
Taken together, although several goodness-of-fit indicators did not reach their ideal levels, the model can still be considered acceptable at a marginal level and suitable for further analysis, particularly for examining causal relationships among the latent variables in the structural model.
Based on the structural model estimation results, the Digital Work Environment (X.
Organizational Culture (X.
, and Work Commitment (X.
demonstrated effects on Job Satisfaction (Y.
and Employee Performance (Y.
The relationships among variables showed varying directions and strengths, where several paths exhibited positive coefficients while others indicated relatively weaker Job Satisfaction (Y.
was found to have a direct influence on Employee Performance (Y.
, indicating that higher levels of job satisfaction contribute to improved individual performance in the context of digitally transformed banking organizations.
In addition, the presence of job satisfaction as an intervening variable highlights its important role as a psychological mechanism that bridges the influence of organizational factors on employee performance.
Source: Processed data .
Figure 2.
Final Structural Model The Author.
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The results of the structural model testing after model modification indicate a significant improvement in the overall level of model fit.
This is reflected in the Chi-Square value of 178.
151 with a probability value of 0.
130, suggesting that the model has satisfied the good fit criterion, as the probability value exceeds the threshold of 0.
This finding demonstrates that the discrepancy between the observed covariance matrix and the estimated covariance matrix is statistically insignificant, indicating that the modified model adequately represents the empirical data.
The CMIN/DF value of 1.
128 further confirms that the model possesses an excellent level of fit (O 2.
, indicating that the proposed structural model is highly consistent with the observed data.
addition, the Goodness-of-Fit Index (GFI) of 0.
920 and Adjusted Goodness-of-Fit Index (AGFI) of 0.
suggest that the model has generally met the goodness-of-fit criteria, although AGFI remains in the marginal category while approaching the recommended ideal threshold.
These results imply that the model demonstrates satisfactory explanatory power in capturing the relationships among latent The incremental fit indices also show highly satisfactory results, with a Tucker-Lewis Index (TLI) of 0.
986 and a Comparative Fit Index (CFI) of 0.
989, both of which exceed the minimum acceptable value of 0.
This indicates that the modified model has a very strong ability to explain the relationships among the variables under investigation when compared with the null model.
Furthermore, the Root Mean Square Error of Approximation (RMSEA) value of 0.
026 reflects a very low approximation error (O .
, suggesting an excellent fit between the structural model and the empirical data.
Based on all goodness-of-fit indicators, the structural model in this study can be concluded to have achieved the criteria of good fit and is therefore appropriate for subsequent hypothesis testing.
The structural model demonstrates that the Digital Work Environment.
Organizational Culture, and Work Commitment have effects on Job Satisfaction and Employee Performance.
Moreover.
Job Satisfaction is confirmed to function as an intervening variable that mediates the relationship between the independent variables and employee performance.
The positive effect of job satisfaction on employee performance indicates that higher levels of employee satisfaction are associated with improved performance outcomes.
This finding reinforces the role of job satisfaction as an important psychological mechanism in explaining the relationship between organizational factors and performance outcomes within the context of digitally transformed banking institutions.
Table 4.
Evaluation of the goodness of fit indices criteria for overall models Index Goodness of Fit
Cut-off Value Chi-Square (NA) Probability CMIN/DF GFI
AGFI
TLI
CFI
RMSEA
Expected Small Ou 0.
O 2.
Ou 0.
Ou 0.
Ou 0.
Ou 0.
O 0.
Initial Model Notes Marginal Not Fit Marginal Marginal Marginal Marginal Marginal Marginal Final Model Notes Good Good Good Good Marginal Good Good Good The results of the goodness-of-fit evaluation indicate that the initial model did not satisfy the required criteria for an acceptable model fit.
This is reflected in the Chi-Square value of 463.
730 with a probability value of 0.
000, indicating that the model was not fit to the observed data.
In addition, several other fit indices, including CMIN/DF .
GFI .
AGFI .
TLI .
, and CFI .
, were below the recommended cut-off values.
Therefore, the initial model was categorized as marginal fit and The Author.
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was not yet appropriate for hypothesis testing.
After model modification was conducted by considering modification indices while maintaining theoretical justification, a substantial improvement in model fit was achieved.
The Chi-Square value decreased to 178.
151 with a probability value of 0.
090, indicating that the revised model had met the fit criterion.
Furthermore, the CMIN/DF value of 1.
128 demonstrates a good level of model fit, as it falls below the maximum recommended threshold of 2.
These results suggest that the modified model better represents the empirical covariance structure.
However, several goodness-of-fit indices, namely GFI .
AGFI .
TLI .
, and CFI .
, remained below the recommended cut-off value of Ou 0.
90, indicating that the model still falls within the marginal fit Meanwhile, the RMSEA value of 0.
026 reflects a low approximation error and satisfies the criterion for good fit.
This suggests that although some comparative fit measures remain limited, the overall residual discrepancy between the model and the observed data is relatively small.
Overall, although not all fit indices reached the ideal thresholds, the structural model in this study can be considered acceptable under the marginal fit category and sufficiently appropriate for proceeding to the hypothesis testing stage.
Nevertheless, the findings should be interpreted with caution, taking into account the limitations of the model in optimally explaining the relationships among the investigated Tabel 5.
Hyphotesis Hyphotesis Relationship between variables Estimate () p-value Notes Significant Significant Significant Significant Significant Insignificant Work Environment Ie Job Satisfaction Organizational Culture Ie Job Satisfaction Work Commitment Ie Job Satisfaction Job Satisfaction Ie Employee Performance Work Environment Ie Employee Performance Organizational Culture Ie Employee Performance Work Commitment Ie Employee Performance Significant Based on the hypothesis testing results, most of the relationships among variables in the research model were found to be statistically significant.
The Digital Work Environment.
Organizational Culture, and Work Commitment each demonstrated positive and significant effects on Job Satisfaction.
These findings indicate that both environmental and psychological organizational factors play an important role in shaping employeesAo affective evaluations of their jobs.
In other words, employees are more likely to experience higher satisfaction when they perceive supportive digital systems, constructive organizational values, and strong attachment to the organization.
Furthermore.
Job Satisfaction was found to have a significant positive effect on Employee Performance, suggesting that the level of employee satisfaction serves as a key determinant in enhancing individual work outcomes.
Employees who are satisfied with their jobs tend to show higher motivation, stronger engagement, and better adaptability, which ultimately contribute to improved performance.
This finding is consistent with the argument that positive work attitudes are closely linked to productive employee behavior.
In addition, the Digital Work Environment and Work Commitment also exerted significant direct effects on Employee Performance, indicating that these two variables influence performance not only indirectly through job satisfaction, but also directly.
A well-functioning digital work environment may improve The Author.
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efficiency, speed, and work quality, while strong employee commitment may encourage greater effort, responsibility, and persistence in achieving organizational goals.
These direct relationships highlight the strategic importance of technological readiness and employee attachment in digitally transformed However.
Organizational Culture did not show a significant direct effect on Employee Performance.
This finding suggests that, within the context of this study, organizational culture has not been sufficiently strong to directly stimulate higher employee performance.
Instead, its influence appears to operate through indirect mechanisms, particularly through increasing job satisfaction.
Overall, these results confirm that employee performance in the digital banking context is influenced not only by structural organizational factors, but also by how employees perceive and evaluate their working conditions.
Table 6.
Indirect Effect Result Hypothesis H10 Path Mediating Work Environment Ie Job Satisfaction Ie Employee Performance Organizational Culture Ie Job Satisfaction Ie Performance Work Environment Ie Job Satisfaction Ie Employee Performance Direct Effect Indirect Effect Total Effect Notes Significant Significant Significant The results of the indirect effect testing indicate that Job Satisfaction plays a significant mediating role in the relationships between the Digital Work Environment.
Organizational Culture, and Work Commitment on Employee Performance.
All mediation paths were found to be statistically significant with p-values below 0.
05, indicating that the influence of the exogenous variables on employee performance occurs not only directly, but also indirectly through the mechanism of job These findings emphasize the importance of psychological factors in translating organizational conditions into improved employee outcomes.
More specifically, the Digital Work Environment demonstrated an indirect effect of 0.
147 on employee performance through job This suggests that supportive digital systems, accessible technology, and efficient work processes enhance employee satisfaction, which subsequently improves performance.
Thus, the benefits of workplace digitalization are not limited to operational efficiency, but also extend to employeesAo emotional and motivational responses.
Meanwhile.
Organizational Culture and Work Commitment showed indirect effects of 0.
163 and 0.
128, respectively.
The indirect effect of organizational culture indicates that shared values, collaboration, and adaptability may not immediately improve performance, but they contribute significantly by increasing employeesAo sense of satisfaction.
Likewise, stronger work commitment fosters positive attitudes toward the organization, which in turn enhances employee performance through higher satisfaction levels.
Accordingly, it can be concluded that Job Satisfaction functions as an important mediator that strengthens the relationship between organizational variables and employee performance.
The mediation effect may take the form of partial mediation when direct effects remain significant, or full mediation when the direct effect becomes insignificant.
These results confirm that improving employee performance in digital banking organizations requires not only The Author.
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structural and managerial interventions, but also strategies aimed at increasing employee job 2 Discussion The findings of this study indicate that the Digital Work Environment.
Organizational Culture, and Work Commitment exert different influences in shaping Employee Performance.
More specifically, the results confirm that employee performance is determined not only by structural organizational factors, but also by psychological mechanisms mediated through Job Satisfaction.
Therefore, the relationships among variables in this study are not purely linear in nature, but involve employeesAo affective evaluations of their working conditions as an important explanatory process.
These findings are consistent with prior literature that positions job satisfaction as a key variable in explaining the relationship between organizational factors and individual performance.
However, this study provides an additional contribution by demonstrating that not all organizational variables have a direct effect on employee performance.
Organizational Culture, for instance, did not show a significant direct effect, but influenced performance indirectly through job satisfaction as a case of full mediation.
This suggests that organizational culture functions more as a contextual factor that shapes employeesAo perceptions, attitudes, and emotional attachment to their work rather than as an immediate driver of performance outcomes.
In contrast, the Digital Work Environment and Work Commitment were found to have both direct and indirect effects on employee performance.
These results indicate a pattern of partial mediation, in which both variables not only influence job satisfaction but also directly contribute to performance improvement.
In this context, the digital work environment serves as an operational factor that enhances efficiency, communication, and work effectiveness, while work commitment functions as a psychological factor that sustains employeesAo consistency, dedication, and willingness to achieve organizational goals.
The implications of these findings suggest that the success of digital transformation in the banking sector is not determined solely by technological implementation, but also by the organizationAos ability to manage human factors effectively.
Without adaptive organizational culture and adequate job satisfaction, digitalization may fail to generate optimal performance Nevertheless, this study has several limitations, particularly the use of a cross-sectional design, which does not fully capture changes in employee behavior over time.
In addition, limitations in the sampling technique may restrict the generalizability of the Therefore, future studies are recommended to employ longitudinal approaches and broader sample coverage in order to obtain more comprehensive insights.
Overall, this study contributes to the human resource management literature by emphasizing that employee performance in the digital era is the result of a complex interaction among technological factors, organizational culture, and individual psychological conditions.
Concluding Remarks and Recommendation This study demonstrates that employee performance in the digitally transformed banking sector is not shaped solely by organizational factors in a direct manner, but rather through psychological mechanisms mediated by Job Satisfaction.
The Digital Work Environment.
Organizational Culture, and Work Commitment were all found to have significant effects on job satisfaction, which subsequently The Author.
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contributes to improved employee performance.
These findings highlight the importance of employeesAo affective evaluations of their work conditions in translating organizational resources into higher performance outcomes.
More specifically, the Digital Work Environment and Work Commitment exert both direct and indirect effects on employee performance, indicating a pattern of partial mediation.
Organizational Culture does not have a direct effect on performance, but significantly influences performance through job satisfaction, reflecting a full mediation pattern.
This suggests that organizational culture does not automatically improve employee performance, but first shapes employeesAo perceptions, attitudes, and satisfaction as essential preconditions for higher performance.
The practical implication of this study is that the success of digital transformation in the banking sector cannot rely solely on technological investment.
It must be accompanied by efforts to strengthen organizational culture and enhance employee commitment in ways that foster greater job satisfaction.
Without effective management of human factors, digitalization may fail to generate optimal performance improvements.
From a theoretical perspective, this study contributes to the human resource management literature by reinforcing the mediating role of job satisfaction in the relationship between organizational factors and employee performance.
It also integrates technological, cultural, and psychological perspectives into a comprehensive analytical However, this study is limited by its cross-sectional design and sampling technique, which may restrict the generalizability of the findings.
Therefore, future research is recommended to employ longitudinal approaches and expand sample coverage in order to gain deeper and more comprehensive Statement of Use of Generative AI During the preparation of this work, the author used ChatGPT to assist in improving clarity and readability of the text.
The author reviewed and edited the output and takes full responsibility for the content of the publication.
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