International Journal of Social Science (IJSS) Vol.
5 Issue.
3 Oktober 2025, pp: 343-354 ISSN: 2798-3463 (Printe.
| 2798-4079 (Onlin.
DOI: https://doi.
org/10.
53625/ijss.
EXPLORING THE RELATIONSHIP BETWEEN
ORGANIZATIONAL CULTURE.
HUMAN RESOURCE
PRACTICES.
AND BUSINESS PERFORMANCE: THE
MEDIATING ROLE OF EMPLOYEE ENGAGEMENT IN THE
CONSTRUCTION INDUSTRY
Tommy Yudistira1*.
Roy Sembel2.
Melinda Malau3 IPMI Institute Universitas Kristen Indonesia Email: 1tommy.
yudhistira@ipmi.
id, 2roy.
sembel@ipmi.
id, 3melinda.
malau@uki.
Article Info Article history:
Received Aug 07, 2025 Revised Aug 28, 2025 Accepted Sept 10, 2025 Keywords:
Organizational Culture.
Human Resource.
Employee Engagement.
Business Performance.
Construction Industry ABSTRACT Over the past two decades.
IndonesiaAos construction industry has expanded rapidly due to infrastructure investment, urbanization, and economic growth.
This study examines the influence of organizational culture and Human Resource Management (HRM) practices on employee engagement and business performance, as well as the mediating role of employee engagement.
Using a quantitative approach, data were collected from 249 respondents out of 710 employees in office and project divisions, selected with Krejcie and MorganAos sampling method.
Structural Equation Modeling with Partial Least Squares (SEM-PLS) using SMART-PLS was applied for analysis.
The results indicate that both organizational culture and HRM practices significantly affect employee engagement and business performance.
Moreover, employee engagement mediates these relationships, reinforcing their impact on business The studyAos novelty lies in integrating the Resource-Based View (RBV) and the job demands-resources model, providing empirical evidence that intangible resources can be transformed into sustainable competitive advantage through employee engagement This is an open access article under the CC BY-SA license.
Corresponding Author:
Tommy Yudistira IPMI Institute Email: tommy.
yudhistira@ipmi.
INTRODUCTION
In the last two decades.
IndonesiaAos construction industry has undergone significant expansion, primarily influenced by infrastructure development, rapid urbanization, and sustained economic growth.
This progress has captured the interest of domestic and global stakeholders, with the sector being largely dominated by state-owned enterprises such as PT Wijaya Karya and PT Pembangunan Perumahan, as well as leading private corporations like PT Agung Podomoro Land and PT Lippo Karawaci.
For instance.
Wika has demonstrated robust financial performance, evidenced by its Q3 2023 revenue of Rp 27.
03 trillion (USD 1.
85 billio.
and net profit of Rp 1.
38 trillion (USD 95 millio.
Similarly.
PP reported revenue of Rp 17.
59 trillion (USD 1.
2 billio.
and a net profit of Rp 555.
billion (USD 38.
1 millio.
during the same period, underscoring the financial prowess of these industry leaders.
The Indonesian government's ambitious infrastructure initiatives, notably the Trans-Java Toll Road and the Nusantara new capital city project, have significantly propelled the industry forward, attracting substantial investments and fostering opportunities for both domestic and foreign participants.
For instance.
Wika's involvement in constructing the TransJava Toll Road has notably contributed to its financial growth (Indonesian Ministry of Public Works and Housing, a.
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IndonesiaAos sustained economic growth continues to create momentum for the expansion of its construction sector, particularly through government support, technological adoption, and an increasing emphasis on sustainability.
However, structural challenges, including shortages of skilled labor and bureaucratic inefficiencies, remain critical barriers to achieving sustainable and inclusive development (Maricourt, 2.
Within this context.
PT Wijaya Karya (Perser.
Tbk (WIKA), established in 1961, has emerged as one of the most prominent state-owned enterprises, specializing in Engineering.
Procurement, and Construction (EPC) services.
With a broad portfolio spanning infrastructure, energy, industrial facilities, and real estate.
WIKA plays a pivotal role in advancing national infrastructure development.
Nevertheless, its financial performance from 2020 to 2024 indicates relatively unsatisfactory outcomes, highlighting the need for stronger financial strategies and organizational resilience.
In 2024.
PT Wijaya Karya (Perser.
Tbk (WIKA) experienced a notable decline in financial performance, with net revenue and total assets dropping by 15% and 4%, respectively, compared to the prior year.
This downturn was largely driven by unprecedented challenges that heavily impacted the construction industry.
WIKAAos core business Pandemic-related disruptions, such as supply chain interruptions, labor shortages, and project delays, severely constrained the companyAos revenue generation and overall profitability.
Additionally, ongoing economic uncertainty and weakened market demand further intensified these financial difficulties.
Consequently.
WIKA faced significant obstacles in maintaining financial stability while navigating unfavorable market conditions.
The recovery of PT Wijaya Karya (WIKA)Aos financial performance is closely tied to strategic initiatives that include proactive cost management, operational efficiency, and adaptive responses to evolving market conditions.
Government-led stimulus packages and infrastructure development programs have also played a crucial role in reinforcing WIKAAos revenue base during challenging economic conditions (Rangkuti et al.
, 2023.
Chiang et al.
, 2.
While financial indicators highlight positive growth, fluctuations in revenue and profit continue to pose significant challenges due to macroeconomic volatility, regulatory complexities, and industry-level competition.
These conditions underscore the necessity of comprehensive strategic responses such as operational streamlining, diversification of revenue streams, and investments in technology and human capital development (Kaur, 2.
Over the last three years.
WIKA has demonstrated steady financial growth, with revenues reaching Rp.
trillion (US$2.
2 billio.
in 2024, marking a 12.
7% year-on-year increase.
Profit after tax rose by 43.
2% to Rp.
trillion (US$110 millio.
, highlighting the firmAos resilience and diversification capacity in a volatile market.
However, human capital management indicators showed fluctuations, particularly in employee training participation and engagement levels.
The Employee Engagement Index (IKK) declined by 2% in 2024 compared to the previous year, suggesting the need for more consistent engagement strategies.
The literature emphasizes that human resource practices are strongly correlated with employee engagement and organizational outcomes in the construction sector.
Effective HR strategies, including competitive rewards, structured career development, continuous training, and inclusive policies, contribute positively to workforce motivation and performance (Mansoor, 2021.
Kavyashree & Kulenur, 2.
Engaged employees are typically more productive, demonstrate stronger organizational commitment, and deliver superior service quality, ultimately enhancing organizational competitiveness (Jaiswal, 2.
Equally important is the role of organizational culture in driving performance outcomes.
A strong organizational culture aligns employees with company values, fosters trust in leadership, and ensures alignment with organizational goals (Naido, 2024.
BravoWell, 2.
Studies show that positive cultural attributes are associated with higher levels of employee engagement, while negative or toxic cultures can significantly erode workforce motivation (Hofstede Insights, 2.
LSA Global .
further identified that cultural components such as alignment with goals, trust in senior leadership, and recognition of employee value are critical predictors of engagement levels.
Employee engagement also acts as a mediating variable in the relationship between HR practices, organizational culture, and business performance.
Research by Dorrian et al.
and Lopez .
highlights that engagement translates HRM practices and cultural values into improved firm outcomes by enhancing productivity, innovation, and organizational sustainability.
In the construction industry, this mediating role is particularly significant due to the sectorAos reliance on human capital as a driver of project performance and long-term competitiveness.
Further evidence shows that effective HRM practices, when aligned with business strategies, can improve employee satisfaction, organizational commitment, and overall productivity (Wang et al.
, 2019.
Zhang et al.
, 2.
Li et al.
emphasize that employee involvement and fair reward systems foster greater effort and accountability, reinforcing the connection between HR strategies and business outcomes.
This body of research underscores the importance of integrating HRM, organizational culture, and employee engagement into a coherent framework to achieve sustained performance in the construction sector.
In summary, prior studies converge on the view that human resource management, organizational culture, and employee engagement are mutually reinforcing elements that critically shape business performance in construction.
HR practices create the structural and developmental foundation, organizational culture provides the values and a.
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5 Issue.
3 Oktober 2025, pp: 343-354 ISSN: 2798-3463 (Printe.
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53625/ijss.
alignment, and employee engagement translates these inputs into productivity and innovation.
This triadic relationship not only strengthens organizational resilience but also positions firms such as WIKA to sustain competitiveness amid external challenges.
LITERATURE REVIEW
Human Resources Human Resource Management as a body of knowledge is replete with apparent contradictions and unexplored Yet, if practical application is any kind of indicator, the theoretical incongruity of Human Resource Management has not hampered its uptake.
Academic calls for the development of a theory of Human Resource Management have .
or various reason.
failed to deliver frameworks with practical capacity (Bam and Nkado, 2.
Human Resource Management is often described as a Aoseries of seemingly disjointed activitiesAo (Aktar and Pangil.
The practices that are carried out under the ambit of Human Resource Management often have a theoretical Most of these lower-level theories are adopted from disciplines like industrial psychology and organisational Business Performance The examination of business performance has been a focal point in studies spanning diverse industries Given the dual facets of opportunities and challenges presented by globalization, organizations find themselves compelled not only to compete and thrive but essentially to endure (Abdullah et al.
, 2.
The definition of business performance can take various forms, aligning with the perspective and context of a particular study.
Bourne et al.
contend that performance should encompass both financial and non-financial dimensions.
They identify financial performance indicators such as market share, new customers, return on capital employed, return on investment, number of new customers, and sales.
Non-financial measures encompass customer characteristics, the societal impact of business, employee attributes, product performance, and process performance.
endorse the adoption of both financial and non-financial dimensions in gauging organizational performance, categorizing them into innovative performance, production performance, market performance, and financial performance (Cheah et al.
, 2.
Employee Engagement Employee engagement remains one of the extensively studied phenomena in the field of Human Resources.
However, there exists a notable disagreement among practitioners and scholars regarding the precise definition of this Nonetheless, academic researchers widely characterize employee engagement as a positive, satisfying, workconnected state of mind characterized by vigor, absorption, and dedication (Koe et al.
, 2.
In more specific terms, scholars describe engagement as the workforce's active involvement in their work, wherein they fully utilize their physical, mental, and emotional resources to accomplish organizational tasks.
This active involvement is manifested as participation, liveliness, and determined focus directed toward achieving organizational goals (Chahal and Bakshi.
Organizational Culture The construction industry aspires to achieve greater efficiency (Okwir et al.
, 2.
Recognized impediments include confrontational contracting behavior, a lack of innovation, and general indifference to research and development (Pinto, 2.
Some successful construction organizations have strategically deviated from the traditional 'construction only' business model, demonstrating a departure from established practices.
While such a shift entails cultural change and associated risks, it has revitalized these organizations by expanding their scope of operations and Organizational culture (OC) emerges as a critical factor influencing a firm's efficiency and productivity (Purwanto et al.
, 2.
Advocates propose that fostering and sustaining a culture conducive to performance improvement can enhance the efficiency of firms and, consequently, the construction industry (Ramdan et al.
, 2.
Huma Resources Practices Human Resource (HR) management is conceptualized as a managerial perspective with theoretical and prescriptive dimensions, emphasizing the establishment of an integrated series of personnel policies aligned with organizational strategy.
This alignment is intended to ensure the quality of working life, high employee commitment and performance, as well as organizational effectiveness and competitive advantage (Ramdan et al.
, 2.
Rehman & Anwar .
initially explore potential connections between HR management and organizational performance, considering aspects such as organizational social capital climate and knowledge exchange.
However, the mechanisms through which HR management influences organizational performance are subject to debate (Saulina, 2.
management encompasses two primary streams: best fit or hard HR management, which strategically aligns individuals with organizational goals, and best practice or soft HR management, which aims to enhance employee commitment and capability for improved business performance (Sheng et al.
, 2.
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RESEARCH METHODS
This study employed a quantitative research design to examine the relationships between organizational culture, human resource management (HRM) practices, employee engagement, and business performance within the Indonesian construction industry.
The population consisted of 710 employees from office and project divisions, with a sample of 249 respondents determined using Krejcie and MorganAos sampling table.
Data were collected through structured questionnaires and analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS) via the SMART-PLS software.
This method was chosen for its ability to assess complex relationships between latent variables and test mediation effects.
RESULT AND DISCISSION
Outer Model (Measurement Mode.
The evaluation of the measurement model is conducted to assess the validity and reliability of the model.
In PLSSEM, the measurement model is the outer model, which comprises a set of relationships between indicators and latent variables (Hair et al.
, 2.
According to Hair et al.
, to assess convergent validity, the outer loading values should be greater than 0.
However.
Henseler et al.
suggest that reflective indicator loadings can be considered a good measure for latent variables if they are above 0.
oading factor ranging between 0.
50 and 1.
Reflective Indicators Loading Factor The results of the reflective indicators' loading factors in the first measurement model.
In the case of indicators OC3.
HR6.
HR7.
HR8, and BP6, the loading values are found to be less than 0.
7, as recommended by Hair et al.
Therefore.
OC3.
HR6.
HR7.
HR8, and BP6 are excluded from the indicators of organization culture.
HR practices, and business performance.
Figure 1.
Reflective Result In The First Stage After dropping the indicators OC3.
HR6.
HR7.
HR8, and BP6, the results of the final measurement model are presented in Figure 2 below.
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Figure 2.
Measurement Model Final In Figure above, it is evident that all loading values meet the criteria of being less than 0.
7, as recommended by Hair et al.
Convergent Validity One method to assess convergent validity is by examining the average variance extracted (AVE), which should ideally be greater than 0.
AVE is only applicable to reflective measurement models.
Table below presents the Average Variance Extracted values:
Table 1.
Average Variance Extracted (AVE) Values Variable Code AVE Value Business Perfromance Employee Engagement HR Practices Organization Culture Source: Results of data processing with Smart PLS .
Based on Table above, it can be concluded that all variables meet the criteria of having AVE values greater This indicates strong convergent validity for each variable, as more than 50% of the variance in the reflective indicators is explained by their corresponding latent variables.
Discriminant Validity The results of the previous testing indicate that all values meet the requirements for testing the loading factor and average variance extracted (AVE), exceeding the threshold of 0.
Therefore, it can be considered valid and suitable for measuring each latent variable.
Since there are no issues with convergent validity, the next step to be examined is related to the problem of discriminant validity for each construct, considering the correlation values between constructs in the model (Hair et al.
, 2.
This method is often referred to as the Fornell-Larcker Criterion and HTMT.
Table 2.
Fornell-Larcker Criterion
Business Employee Organization Variable Performance Engagement
Practices Culture Business Performance 0,877 Employee Engagement
0,546
0,944
HR Practices 0,557 0,701 0,896 Organization Culture 0,535 0,787 0,739 0,858 Source: Results of data processing with Smart PLS .
From the above results, it can be observed that the square root of AVE correlation values for each latent variable has the highest value compared to the square root of AVE correlations with other latent variables.
This implies that each latent variable exhibits good discriminant validity, although some latent variables still have high correlations with other constructs.
However, according to Henseler et al.
, the Fornell-Larcker Criterion approach may fail to a.
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identify discriminant validity issues in certain large cases.
Therefore.
Henseler et al.
recommend assessing discriminant validity using the heterotrait-monotrait ratio of correlations (HTMT).
Bootstrapping procedures with 5000 resamples are conducted to obtain confidence interval (CI) values less than or equal to 1.
00 to identify no issues with discriminant validity (Henseler et al.
, 2.
Table 3.
HTMT
Business Employee Variable Performance Engagement
Practices Business Performance Employee Engagement
0,600
HR Practices 0,592 0,772 Organization Culture 0,574 0,877 0,806 Source: Results of data processing with Smart PLS .
The information you've provided indicates that, based on Table 3, there is still one value greater than 0.
However, it's worth noting that this might be acceptable, especially if the Fornell-Larcker Criterion values .
rom the previous testin.
have already met the specified criteria.
The Fornell-Larcker Criterion and HTMT are complementary methods for assessing discriminant validity.
While the Fornell-Larcker Criterion focuses on the square root of AVE.
HTMT considers the ratios of correlations.
Internal Consistency Reliability After assessing the validity of the indicators, the next step is to evaluate the reliability of each latent construct using Cronbach's alpha and composite reliability values.
The Cronbach's alpha and composite reliability values can be considered to ensure the reliability of PLS construction scores, as suggested by Hair et al.
, with values ranging 7 to 0.
Table below presents the results of the internal consistency reliability test:
Table 4.
Internal Consistency Reliability Test Results (Cronbach's Alpha and Composite Reliabilit.
Cronbach
Composite Alpha (CA) Reliability (CR) Business Performance 0,943 Employee Engangement
0,942
HR Practices 0,953 Organization Culture 0,882 0,918 Source: Results of data processing with Smart PLS .
Variable Code The results of the internal consistency reliability test in Table 4.
indicate that both Cronbach's alpha and composite reliability values surpass the specified criteria, falling within the range of 0.
7 to 0.
9, as recommended by Hair et al.
This suggests that the measurement model exhibits satisfactory internal consistency reliability, ensuring the reliability of the latent construct scores.
Inner Model (Structural Mode.
The testing of the inner model involves the development of a concept and theory-based model to analyze the relationships between exogenous and endogenous variables, as outlined in the conceptual framework.
The analysis of the inner model is carried out with the objective of ensuring that the constructed structural model is robust and accurate.
R-Square The coefficient of determination.
R-Square (RA), indicates the extent to which independent variables explain the dependent variable.
The R-Square value ranges from zero to one.
As the R-Square value approaches one, it signifies that the independent variables provide all the information needed to predict the variation in the dependent variable.
Conversely, a smaller R-Square value indicates a limited ability of the independent variables to explain the variation in the dependent variable.
R-Square has a limitation, as the value tends to increase with the addition of each independent variable, even if the added variable does not significantly impact the dependent variable.
Based on the data processing conducted, the obtained R-Square values are as follows:
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Table 5.
Variable Business Performance (BP) Employee Engagement (EE) Source: Results of data processing with Smart PLS .
Based on Table 5, it can be concluded that all independent variables in the study collectively explain 1% of the variation in the dependent variable.
Employee Engagement.
Additionally, the model is able to account for about 36.
3% of the variance in the Business Performance variable.
This suggests that the chosen independent variables have a substantial explanatory power regarding Employee Engagement, while their explanatory capability for Business Performance is somewhat lower.
The specific values and coefficients in Table 4.
6 would provide a more detailed understanding of the relationships between variables.
Effect size .
2 ) Effect size .
A) is a measure used to assess the relative impact of an influencing variable .
on the influenced variable .
The F-Square model value is employed to determine the magnitude of the effect size of endogenous latent variables on exogenous latent variables.
If the fA value equals 0.
35, it can be interpreted that the predictor latent variable has a strong influence.
If it is equal to 0.
15, it indicates a moderate influence, and if it is equal to 0.
02, it implies a weak influence (Hair et al.
, 2.
Table 6.
Effect size .
Business Employee Variable Result
Performance Engagement
Business Performance Employee Engagement
0,030
Moderate HR Practices 0,057 Moderate HR Practices Organization Culture 0,090 0,009 Organization Culture 0,456 Source: Results of data processing with Smart PLS .
Moderate Weak Strong Based on Table 6, it appears that the variables Employee Engagement and HR Practices have a moderate effect on Business Performance.
Similarly, among HR Practices, there is a moderate effect on Employee Engagement.
the other hand.
Organization Culture has a weak effect on Business Performance.
Lastly.
Organizational Culture has a strong effect on Employee Engagement.
Predictive Relevance (Q.
Q2 predictive relevance is utilized to present a synthesis of validation and fitting functions with predictions from manifest variables and parameter estimates of constructs.
A Q2 value greater than 0 indicates that the model possesses predictive relevance, while Q2 values less than 0 suggest that the model lacks predictive relevance (Hair et , 2.
The Q2 values can be observed in Table 4.
8, which represents Predictive Relevance (Q.
for the structural model, measuring how well the observed values are generated by the model and its parameter estimates.
This criterion is applicable only to reflective endogenous factor models.
A Q2 value greater than 0 demonstrates that the model has predictive relevance, whereas a Q2 value less than 0 indicates that the model lacks predictive relevance.
Table 7.
Predictive Relevance (Q.
Variable SSO
SSE
QA (=1-SSE/SSO)
Business Performance 1285,000 940,824 0,268 Employee Engagement
514,000
218,754
0,574
HR Practices 1285,000 1285,000 Source: Results of data processing with Smart PLS .
Based on Table 7, it is observed that for the variables Employee Engagement and Business Performance, they meet the criteria for predictive relevance with Q2 values greater than 0.
Therefore, it can be concluded that both Employee Engagement and Business Performance variables fulfill the criteria for predictive relevance.
This suggests that the model has demonstrated the ability to generate values that align well with the observed data for these variables and has relevance in making predictions.
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Hypotheses Testing Analysis This research analyzes the influence of organizational culture and HR practices on employee engagement and business performance.
The variable of employee engagement serves as a mediator in this study.
Figure 4.
3 presents the results of the final structural model testing of the hypotheses.
Figure 3.
Structural Model Final The results of the hypothesis testing are presented in the following Table 8 below:
Table 8.
Hypotheses Testing Direct Hypotheses yvalue Organization culture -> Employee Engagement
000***
Decision Support
HR Practices -> Employee engagement 000*** Support
Employee engagement-> Business performance 005*** Support
Organization culture -> Business Performance Support
003***
Support HR Practices -> Business performance Mediating Test Organization culture -> employee engagement -> Business 007*** Support Performance HR Practices ->Employee Engagement-> Business Support Performance Note: *) Significant if P-Value < 0,05.
If < 0,01 = *** .
If <0,05 = ** .
If < 0,1 = * Source: Results of data processing with Smart PLS .
Based on Table 8, all hypotheses are accepted because the p-values for all related variables are below the provision criteria, for the first, second, third, fifth, and sixth hypotheses are the hypotheses with the highest support because they are below 0.
01 (<0.
, while the seventh hypothesis gets 2 stars or the second level of support because it is below 0.
05 and the fourth hypothesis is at the third level of support because it is below 0.
However, all hypotheses show significance and a positive influence.
Furthermore, the t-values are all above the standard, which is 1.
indicating a significant influence (Hair et al.
, 2.
Importance Performanced PLS-SEM studies that draw on IPMA results offer important insights into the role of antecedent constructs and their relevance for managerial actions.
The IPMA also becomes particularly useful when contrasting PLSSEM results from a multigroup analysis (Hair et al.
, 2.
as several studies illustrate.
However, to date, no comprehensive tutorial highlights the requirements for using the method, or offering a step-by-step introduction to its use.
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Table 9.
IPMA Construct Results per Indicator Indicator MV performance Total Effect - BP
EE2
87,81
0,09
EE3
83,33
0,09
HR1
71,08
0,09
HR2
72,18
0,09
HR3
71,01
0,09
HR4
62,13
0,10
HR5
68,22
0,09
OC1
79,64
0,11
OC2
77,50
0,12
OC4
78,99
0,10
OC5
78,27
0,11
Average 75,47 0,098 Source: Results of data processing with Smart PLS .
The table shows the importance and performance of each indicator.
What needs to be highlighted are indicators with high importance and low performance.
Those that fill the requirements are OC1.
OC2.
OC4 and OC 5.
ItAos evident that PT.
WIKA is performing well, but there are specific areas that need improvement.
Figure 4.
IPMA Construct Processing Results Per Quadrant Source: Results of data processing with Smart PLS .
Based on the image above, the indicators in Quadrant I .
igh performance & high importanc.
show performance values above 75.
4, indicating that the company is performing well and that these aspects are important to The indicators in this quadrant are EE2 and EE3.
Indicators in Quadrant II .
ow performance & high importanc.
require greater attention to improve performance, namely OC1.
OC2.
OC4, and OC5.
Meanwhile, indicators in Quadrant i .
igh performance & low importanc.
suggest the need for reallocation of human resources a.
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and adjustments in organizational culture so that management efforts can be directed toward more critical business performance areas, specifically HR1.
HR2.
HR3.
HR4, and HR5.
CONCLUSION
This study investigated the influence of organizational culture and human resource management (HRM) practices on employee engagement and business performance within the Indonesian construction industry.
Using a quantitative approach with SEM-PLS analysis, the findings demonstrate several key insights.
First, organizational culture and HRM practices are shown to have a significant and positive impact on both employee engagement and business performance.
This highlights that well-structured HRM strategies and a strong organizational culture are critical drivers of organizational success.
Second, employee engagement was found to serve as an effective mediating variable.
Its role reinforces the impact of organizational culture and HRM practices on business performance, thereby confirming that engagement is not only an outcome of HR policies but also a strategic mechanism that translates intangible resources into measurable performance improvements.
Third, the results provide empirical evidence supporting the ResourceBased View (RBV) and the Job Demands-Resources (JD-R) model, indicating that intangible resources such as HR practices and organizational culture can be transformed into sustainable competitive advantage when effectively aligned with employee engagement.
Lastly, the practical implication of this research is that construction companies in Indonesia must prioritize fostering a supportive organizational culture and enhancing HRM systems to strengthen employee engagement.
Doing so will enable organizations to optimize resource allocation, improve overall performance, and ensure long-term competitiveness in an increasingly dynamic industry landscape.
In conclusion, employee engagement should be regarded not merely as an HR outcome but as a pivotal strategic mediator that bridges organizational practices with superior business performance.
REFERENCES