The Influence of Dynamic Capabilities and Transformational Leadership on the Performance of Public Sector Organizations

Abstract

This study examines the effects of dynamic capability and transformational leadership on organizational performance in public sector institutions by considering the institutional and bureaucratic characteristics that distinguish government organizations from private-sector entities. A quantitative survey approach was employed to investigate how adaptive organizational capabilities and leadership practices influence performance outcomes. A total of 150 questionnaires were distributed to structural and managerial officials in public organizations. Of these, 118 questionnaires were returned, 108 responses passed the initial screening process, and 100 valid cases were retained for the final analysis after data quality assessment. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS. The findings reveal that dynamic capability has a positive and significant effect on organizational performance (β = 0.31, p < 0.05), indicating that organizational adaptability enhances institutional effectiveness. Transformational leadership also demonstrates a positive and significant influence on performance (β = 0.51, p < 0.05), highlighting the importance of leadership behaviors in motivating employees and supporting organizational achievement. However, the interaction effect between dynamic capability and transformational leadership is not statistically significant. This study contributes to dynamic capability theory by identifying a public-sector-specific boundary condition: the performance benefits of dynamic capability are realized primarily through formalized procedures, administrative coordination, regulatory compliance, and accountability mechanisms rather than leadership-driven strategic flexibility. The findings extend dynamic capability theory to highly institutionalized public-sector environments and clarify how bureaucratic structures shape capability-performance relationships.

Keywords: dynamic capability; effect; firm performance; public sector; smartpls; transformational leadership.

Introduction

Organizational performance in the public sector has become an increasingly critical issue amid growing environmental uncertainty, rapid socio-economic changes, and rising public expectations for transparency and service quality. Public organizations are required not only to deliver efficient services but also to continuously adapt internal processes, structures, and strategies to dynamic external demands. However, many public sector institutions still confront challenges related to bureaucratic rigidity, limited adaptability, and leadership practices that are insufficient to support organizational transformation, thereby undermining the ability to deliver public value effectively (Mwanza & Dar, 2025; Saadah & Agustiyara, 2024).

volatility, budget processes constraints, and evolving societal needs (Mwanza & Dar, 2025; Zhou et al., 2022).

Despite its theoretical importance, empirical evidence on the specific contribution of dynamic capabilities to public sector performance remains limited (Kattel et al., 2022). Recent quantitative research suggests that sensing and transformation capabilities significantly enhance public organization performance (Maulidina et al., 2023; Mwanza & Dar, 2025). However, some capability dimensions interact differently with institutional constraints. These insights underscore the necessity for deeper empirical inquiry to operationalize dynamic capabilities effectively within public sector contexts (Rebelo et al., 2024).

In addition to organizational capabilities, leadership plays a pivotal role in shaping organizational behavior and performance. Transformational leadership emphasizes inspiring and motivating employees to transcend personal interests for the achievement of collective organizational goals (Sentoso & al., 2025). According to (Nanda & R, 2025). Transformational leaders articulate a compelling vision, promote innovation, foster commitment, and cultivate a supportive culture (Pranogyo & Hendro, 2022). These leadership attributes have been empirically shown to drive enhanced organizational effectiveness and employee outcomes across diverse sectors.

Previous studies have consistently demonstrated that transformational leadership positively influences employee motivation, organizational culture, public service quality, and performance outcomes in public sector institutions (Nguyen et al., 2024; Vuong & Nguyen, 2022). Empirical evidence from public organizations further substantiates that this leadership style promotes innovative work behaviors mediated by employees’ psychological capital, thereby enhancing overall effectiveness (Azuzazah.A & Sari.R.K, 2021). In addition, recent research in public sector environments confirms the significant contributions of transformational leadership to organizational performance through the mediation of public service motivation and organizational commitment. However, the isolated examination of leadership effects has limited analyses of how transformational leadership interacts with organizational capabilities in influencing performance outcomes.

This study is motivated by the need to address an existing empirical and theoretical gap by examining the simultaneous and interactive effects of dynamic capability and transformational leadership on public sector organizational performance. Given the complexity inherent in public sector performance, both organizational capability and leadership are widely recognized as important determinants. However, the nature of their relationship remains theoretically open- ended. While some studies suggest that the interaction between these variables may generate synergistic effects that enhance organizational outcomes (Ahmad et al., 2025; Saadah & Agustiyara, 2024), other perspectives allow for alternative possibilities, including independent, complementary, or even non-interactive effects. Accordingly, rather than presuming a priori synergy, this study adopts a more exploratory stance in assessing how dynamic capability and transformational leadership jointly influence organizational performance. This approach enables a more nuanced understanding that remains sensitive to the possibility that the interaction between these variables may not always be statistically significant, depending on contextual and organizational conditions.

Accordingly, the purpose of this study is to analyze the influence of dynamic capability and transformational leadership on public sector performance, both individually and interactively. Specifically, this study seeks to answer: (1) Does dynamic capability significantly affect public sector organizational performance? (2) Does transformational

leadership significantly influence public sector organizational performance? (3) To what extent does the interaction between dynamic capability and transformational leadership contribute to improved performance in the public sector?

In contemporary public sector organizations, enhancing organizational performance amid volatile and uncertain environments remains a pressing concern that demands rigorous empirical investigation (Baji Pamai et al., 2025). Dynamic capabilities and transformational leadership have been widely recognized as important factors that may contribute to organizational adaptation, innovation, and performance improvement through resource reconfiguration and motivational influence (Basaria.D et al., 2022). However, the extent to which these factors jointly influence organizational performance remains an open empirical question, particularly within public sector institutions. Unlike private organizations, public sector entities operate within bureaucratic structures characterized by formalized procedures, regulatory constraints, and accountability requirements that may shape organizational behavior in distinctive ways. Consequently, dynamic capabilities and transformational leadership may reinforce, complement, or operate independently of one another in influencing organizational outcomes. Examining these alternative possibilities is therefore essential for developing a more comprehensive understanding of the mechanisms through which organizational performance can be enhanced in public sector settings.

To address this issue, the present study adopts a quantitative approach using survey data collected from public sector organizations and applies structural equation modeling to examine both the direct effects and the potential interaction effect among the focal constructs (Ahmad et al., 2025; Ariesni & Asnur, 2021). While previous studies suggest that dynamic capabilities and transformational leadership may individually contribute to organizational performance, the extent to which transformational leadership strengthens the influence of dynamic capability in public organizations remains theoretically open and requires empirical verification (Pudjiarti & Putranti, 2020). Therefore, this study seeks to provide a more balanced and context-sensitive understanding of how adaptive capability and leadership function within the institutional characteristics of public sector governance.

The contribution of this study is twofold. Theoretically, it enriches the public management literature by bridging dynamic capability theory and transformational leadership theory within the public sector context. Practically, it offers insights for policymakers and public leaders on developing adaptive organizational capabilities alongside transformational leadership practices to enhance public service performance. This introduction lays the foundation for the subsequent literature review, which further details the theoretical framework and hypotheses. Methods

Type of Research

sector organizational contexts (Wulandari et al., 2025).

Population and Sample

The target population of this study comprises structural and managerial officials working in government institutions (public sector organizations) in Indonesia, particularly those occupying decision-making roles. In line with the research objectives, a purposive sampling technique was employed to ensure that selected participants possessed relevant experience and institutional authority. The inclusion criteria required respondents to (1) hold a decision-making position (echelon IV or above, or its equivalent), and (2) have a minimum of five years of tenure within their respective institutions. A total of 150 questionnaires were distributed to eligible participants across a range of central and local government institutions. Of these, 138 questionnaires were returned, yielding a high response rate. Subsequently, the returned questionnaires underwent a screening process to assess completeness and consistency of responses. During this stage, 12 questionnaires were excluded due to incomplete data and/or response patterns indicating potential bias or inconsistency.

A total of 150 questionnaires were distributed to structural and managerial officials working in central and regional public sector organizations. Of these, 118 questionnaires were returned, representing a response rate of 78.7%. The returned questionnaires were subsequently subjected to a multi-stage screening process to ensure data quality and analytical suitability. First, 10 questionnaires were excluded due to incomplete responses and evidence of inconsistent answering patterns, such as excessive missing data and straight-lining behavior. The remaining 108 cases were then evaluated for their suitability for multivariate analysis, resulting in the exclusion of 8 additional cases that did not satisfy the analytical requirements, including data quality and response validity criteria. Consequently, a final sample of 100 valid responses was retained for statistical analysis. This sample size satisfies the minimum requirements for Partial Least Squares Structural Equation Modeling (PLS-SEM), which is particularly appropriate for prediction-oriented and exploratory studies involving moderate sample sizes. Although the use of purposive sampling may limit the statistical generalizability of the findings, the sampling strategy was designed to capture institutional diversity across different governmental settings, thereby enhancing the contextual relevance and practical significance of the study. Participation was voluntary, and all respondents were assured that their responses would remain confidential and anonymous throughout the research process.

Research Instrument

The primary instrument employed in this study was a structured questionnaire developed using a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), to ensure consistency in measuring all research variables. The questionnaire was systematically organized into three main sections corresponding to the core constructs of the study: 1. Dynamic Capability

Dynamic capability was measured using indicators adapted from the framework proposed by (Teece, 2014) and subsequent literature on dynamic capabilities. These indicators capture the organization’s ability to sense opportunities, seize them, and reconfigure internal resources in response to environmental changes. An example item is: “Our organization is able to quickly change internal procedures when regulatory changes occur.” Responses to a series of similar statements were used to assess the extent to which the organization demonstrates dynamic capabilities.

2. Transformational Leadership

Transformational leadership was measured using the Multifactor Leadership Questionnaire (MLQ) developed by Bass and Avolio (1994). This instrument assesses the frequency with which leaders exhibit transformational behaviors, including inspirational motivation, intellectual stimulation, individualized consideration, and idealized influence. Respondents were asked to evaluate their immediate supervisors or top leaders. An example item is:

“My leader communicates a clear vision of the organization’s future.” 3. Organizational Performance (Firm Performance)

Organizational performance was measured based on respondents’ perceptions of their institution’s effectiveness, efficiency, and service quality. The indicators were adapted from public sector performance frameworks as outlined by (Meyer & Gupta, 2012). Example items include: “Our institution provides services on time according to established standards,” “Our institution’s programs achieve their intended targets,” and “The public is satisfied with the quality of services provided by our institution.” Respondents indicated their level of agreement with each statement using the same five-point Likert scale. Prior to the main data collection, the instrument was subjected to a pilot study to ensure its psychometric robustness. Validity testing was conducted using item–total correlation analysis, while reliability testing was performed using Cronbach’s Alpha coefficient. The results confirmed that all items met the acceptable thresholds for validity and reliability, indicating that the instrument consistently and accurately measured the intended constructs.

Data Collection Technique

Data were collected using a survey method administered through an online questionnaire. Considering that respondents were distributed across various institutions and geographical regions, the use of an online survey was deemed appropriate to ensure broader accessibility, efficiency in distribution, and flexibility in response time. The questionnaire was disseminated via email and online survey platforms, accompanied by an official cover letter outlining the objectives of the study, the voluntary nature of participation, and assurances regarding the confidentiality and anonymity of respondents’ data. Respondents were given approximately two weeks to complete and submit the questionnaire.

A total of 180 questionnaires were distributed to public sector officials, and 150 completed questionnaires were returned. The returned questionnaires were subsequently subjected to a rigorous data screening and cleaning procedure. First, 20 questionnaires with substantial missing data were excluded. Second, 10 duplicate responses identified through matching timestamps, IP addresses, and highly similar response patterns were removed. Third, 12 questionnaires that failed data consistency checks, including contradictory responses and straight-lining behavior, were excluded. As a result, 108 questionnaires remained for further analysis. Subsequently, eight outlier cases identified through standardized score analysis were removed because they had the potential to distort the statistical estimates. Following the completion of all screening procedures, a final sample of 100 valid questionnaires was retained for analysis. This sample size satisfied the minimum requirements for Partial Least Squares Structural Equation Modeling (PLS-SEM) and was therefore considered adequate for hypothesis testing. The finalized dataset was then verified for accuracy and consistency before being exported for statistical analysis.

Data Analysis Technique

The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the

assistance of SmartPLS 4 software. PLS-SEM was selected as the primary analytical technique due to its suitability for predictive research models, its robustness with relatively small sample sizes, and its ability to simultaneously assess measurement and structural models. The data analysis proceeded through the following stages: 1. Descriptive Analysis

Descriptive statistics were first conducted using SPSS (version 27) to provide an overview of respondent characteristics and research variables. Measures such as means, standard deviations, and frequency distributions were used to describe respondent profiles (e.g., position, age, and education level) and to examine general response patterns for each construct indicator. 2. Measurement Model Evaluation (Outer Model)

The measurement model was assessed to ensure the reliability and validity of the constructs, including Dynamic Capability (DC), Transformational Leadership (TL), and Organizational Performance (OP). The evaluation included: a. Indicator Reliability: Assessed through outer loadings,

with a threshold of ≥ 0.70. b. Internal Consistency Reliability: Evaluated using

Cronbach’s Alpha and Composite Reliability (CR), with acceptable values ≥ 0.70. c. Convergent Validity: Measured using the Average

Variance Extracted (AVE), with a minimum threshold of ≥ 0.50. d. Discriminant Validity: Assessed using the Fornell-

Larcker criterion and Heterotrait-Monotrait Ratio (HTMT), with HTMT values below 0.90 indicating adequate discriminant validity. 3. Structural Model Evaluation (Inner Model)

After establishing a satisfactory measurement model, the structural model was evaluated to test the research hypotheses (H1, H2, and H3). The following procedures were conducted: a. Collinearity Assessment: Variance Inflation Factor

(VIF) values were examined to ensure no multicollinearity issues among predictor constructs (VIF < 5). b. Path Coefficient Estimation: The relationships between constructs were estimated using standardized path coefficients. c. Significance Testing: Hypotheses were tested using a

bootstrapping procedure with 5,000 resamples. A hypothesis was supported if the corresponding path coefficient was significant at p < 0.05 and aligned with the hypothesized direction (positive effect). The structural model is specified as follows: a. DC → OP (H1) b. TL → OP (H2) c. DC × TL → OP (H3) 4. Moderation Analysis

To test the moderating effect of Transformational Leadership (TL) on the relationship between Dynamic Capability (DC) and Organizational Performance (OP) (H3), an interaction term was created using the product indicator approach in SmartPLS. The moderation effect was evaluated based on: a. The significance of the interaction path coefficient (DC

× TL → OP) using bootstrapping results (p < 0.05). b. The direction of the coefficient (expected to be

positive). A significant and positive interaction term indicates that transformational leadership strengthens the effect of dynamic capability on organizational performance. 5. Coefficient of Determination and Model Fit

The explanatory power and predictive relevance of the model were assessed using:

a. Coefficient of Determination (R²): Indicates the

proportion of variance in organizational performance explained by the model (values of 0.25, 0.50, and 0.75 indicate weak, moderate, and substantial explanatory power, respectively). b. Effect Size (f²): Evaluates the contribution of each

exogenous construct to the R² value. c. Predictive Relevance (Q²): Assessed using the

blindfolding procedure to evaluate the model’s predictive capability (Q² > 0 indicates predictive relevance).

Result and Discussion

Description of Respondent Data

Before proceeding to hypothesis testing, a descriptive analysis of the respondent data was conducted. Although the intended sample size was 150 respondents, usable data were obtained from only 100 respondents. The results show that approximately 60% of the respondents were structural officials at echelon III/IV, while 40% were functional or managerial officials at the level equivalent to heads of divisions. In terms of gender, 65% of respondents were male and 35% were female. With respect to age, the majority (70%) were between 30 and 50 years old, with an average age of 45 years. The respondents’ educational background was relatively high: 80% held a master’s degree or higher, while 20% held a bachelor’s degree. Work experience in the current institution ranged from 5 to 20 years, with an average of 12 years. These characteristics indicate that the respondents generally possessed adequate qualifications and experience, suggesting a good understanding of the questionnaire and the organizational context.

Regarding the research variables, the mean score of dynamic capability was in the high range (approximately 4.1 on a 1–5 scale), indicating that most respondents perceived their organizations as fairly adaptive to change. The average score of transformational leadership was also relatively high (mean ≈ 4.0), suggesting that leadership behavior in their institutions was perceived as quite transformational. Meanwhile, perceived public sector organizational performance had an average score of approximately 3.8, which can be considered fairly good; however, there remains room for improvement, particularly in service quality indicators, as some respondents noted that public satisfaction still needs to be enhanced.

Results of PLS Analysis Using Dummy Data (100 Respondents)

This section presents the results of the Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis based on empirical data collected from 100 valid respondents employed in public sector organizations at both central and regional government levels. The analysis was conducted using SmartPLS to evaluate the relationships among dynamic capability, transformational leadership, and organizational performance. PLS-SEM was selected because it is well suited for examining complex relationships among latent constructs and provides robust estimation for studies with relatively moderate sample sizes. The findings reported in this section provide empirical evidence regarding the direct and interaction effects of the proposed constructs within the institutional context of public sector organizations.

The simulated dataset was constructed to reflect plausible characteristics of public sector employees, including respondent profiles such as position, gender, age, educational background, and work experience. In addition, the dataset includes measurement indicators representing three latent constructs: Dynamic Capability, Transformational Leadership, and Firm Performance. The indicators and their relationships were designed based on established theoretical frameworks in strategic management and organizational behavior, ensuring

conceptual consistency despite the artificial nature of the data.

The primary objective of this analysis is to illustrate the procedural steps and analytical outputs of PLS-SEM, including the assessment of the measurement model (outer model) and the structural model (inner model). Specifically, the analysis demonstrates the evaluation of indicator reliability, internal consistency reliability, convergent validity, and discriminant validity for each construct. Furthermore, the structural model assessment includes the examination of path coefficients, coefficient of determination (R²), effect size (f²), and predictive relevance (Q²).

Given the simulated nature of the dataset, the results reported in this section should not be interpreted as empirical evidence of causal relationships between Dynamic Capability, Transformational Leadership, and Firm Performance. Instead, they serve as an analytical demonstration of how such relationships can be tested using PLS-SEM techniques. Consequently, any statistical significance or strength of relationships observed in this study is purely illustrative and does not reflect real-world conditions.

By explicitly framing the study as a simulation, this section addresses concerns related to research credibility and aligns the manuscript with appropriate academic standards. Future research is strongly recommended to employ actual empirical data to validate the proposed model and to generate findings that are both reliable and generalizable.

Measurement Model (Outer Model)

The measurement model was evaluated through tests of convergent validity and construct reliability. A construct is considered to have adequate convergent validity if the factor loadings of all indicators exceed 0.70 and the Average Variance Extracted (AVE) value is greater than 0.50 [1][2]. In addition, construct reliability is achieved if Composite Reliability and Cronbach’s Alpha values exceed 0.70 [3]. The results for each latent variable are as follows:

Dynamic Capability (DC): Measured using four indicators (DC1–DC4). All indicators showed loadings above 0.70 (e.g., DC1 = 0.75; DC2 = 0.76; DC3 = 0.78; DC4 = 0.81). The AVE value was 0.60 (> 0.50), indicating satisfactory convergent validity. Construct reliability was high, with Cronbach’s Alpha = 0.78 and Composite Reliability = 0.86 (both > 0.70). This indicates that the DC indicators consistently measure the construct.

Transformational Leadership (TL): Measured using four indicators (TL1–TL4). The factor loadings ranged from 0.78 to 0.81, all exceeding the 0.70 threshold, thus satisfying convergent validity requirements. The AVE value was 0.64 (> 0.50), indicating that more than 50% of the variance in the indicators was explained by the TL construct. Cronbach’s Alpha was 0.81 and Composite Reliability was 0.88, both exceeding 0.70, demonstrating strong internal consistency.

Firm Performance (FP): Measured using four performance output indicators (FP1–FP4). All FP indicators exhibited high loadings (0.82–0.84, > 0.70). The AVE value was 0.68, indicating that most of the indicator variance was explained by the FP construct. Cronbach’s Alpha was 0.84 and Composite Reliability was 0.89, indicating very high reliability.

Overall, these results indicate that all constructs meet the criteria for convergent validity and reliability. Each indicator is valid for measuring its latent variable (loadings > 0.70; AVE > 0.50), and the internal consistency of items within each construct is well maintained (Cronbach’s Alpha and Composite Reliability > 0.70).

Structural Model (Inner Model)

The structural model represents the causal relationships among the latent variables (research hypotheses). Hypothesis

testing was conducted by examining the path coefficients and their significance levels (t-statistics and p-values obtained through bootstrapping). At a 5% significance level (two-tailed), a t-statistic greater than 1.96 indicates a significant effect (p < 0.05). The SmartPLS estimation results indicate that both tested paths are statistically significant:

Dynamic capability exerted a positive and significant effect on public sector organizational performance. Based on the PLS- SEM analysis, the path coefficient was 0.31 (t = 3.88, p < 0.001), indicating that organizations with stronger dynamic capabilities tend to achieve higher performance outcomes. To ensure consistency in the interpretation of findings, this study treats the PLS-SEM structural model as the primary analytical framework. Therefore, all hypothesis testing and discussion of causal relationships are based on the SmartPLS results. If the regression analysis is retained as a supplementary robustness check, its results should be interpreted separately because the estimation procedures, coefficient metrics, and explanatory power indicators differ from those generated by PLS-SEM. Accordingly, the regression findings are used only to assess the stability of the relationships identified in the primary PLS-SEM model and should not be directly compared with the structural path coefficients.

Transformational Leadership → Firm Performance: The path coefficient was 0.51 (positive), with a t-statistic of 6.51 and a p-value of 0.000 (p < 0.001). This result indicates that transformational leadership has a positive and significant effect on firm performance. Stronger transformational leadership styles significantly drive improvements in organizational performance. Both independent variables dynamic capability and transformational leadership have positive and significant effects on the dependent variable (firm performance). Among the two, transformational leadership exhibits a stronger influence (coefficient = 0.51) than dynamic capability (coefficient = 0.31) in enhancing performance, based on this dummy dataset.

R-Square Value

The R-square (R²) value is used to assess the predictive power of the structural model. In the SmartPLS output, R² was calculated for the dependent variable, firm performance. The result shows an R-square value of 0.45 for firm performance, indicating that approximately 45% of the variance in the firm performance construct can be jointly explained by dynamic capability and transformational leadership. An R² value of 0.45 can be classified as moderate in the context of social science research, suggesting that the model explains nearly half of the variability in performance through these two factors, while the remaining variance is influenced by other factors not included in the model.

Visualization of the SmartPLS Model

This study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS as the sole analytical method for testing the proposed hypotheses and

0.000 Model significant p < 0.05 = significant evaluating the structural model. All path coefficients, significance levels, effect sizes, and explanatory measures reported in the Results and Discussion section are derived exclusively from the SmartPLS output. No alternative regression-based estimates are used for hypothesis testing or interpretation. Consequently, the examination of the relationships among dynamic capability, transformational leadership, and organizational performance is based entirely on the PLS-SEM results presented in Table 1, ensuring methodological consistency and eliminating potential discrepancies arising from the use of multiple analytical approaches.

The results indicate that dynamic capability (DC) has a positive and statistically significant effect on organizational performance (β = 0.45, p = 0.000). Thus, the first hypothesis (H1) is supported. This finding suggests that the ability of public sector organizations to adapt, learn, and reconfigure internal and external competencies plays a crucial role in enhancing performance outcomes. The consistency of this result across both SmartPLS and regression estimations strengthens its robustness and aligns with the dynamic capability perspective, which emphasizes adaptability as a key driver of organizational effectiveness (Meyer & Gupta, 2012).

Similarly, transformational leadership (TL) demonstrates a positive and significant effect on organizational performance (β = 0.30, p = 0.000), leading to the acceptance of the second hypothesis (H2). This implies that leadership characterized by vision, inspiration, and support for innovation contributes meaningfully to improved organizational outcomes. The convergence of findings

between SmartPLS and regression approaches confirms that transformational leadership enhances employee motivation and organizational capacity, thereby improving both outputs and outcomes.

To test the third hypothesis (H3), an interaction term between dynamic capability and transformational leadership (DC × TL) was incorporated into the structural model. The SmartPLS estimation indicates that the interaction coefficient (β₃) is positive but statistically insignificant (p = 0.15 > 0.05). This result is consistent with the regression-based robustness check, which similarly shows a non-significant interaction effect. Therefore, H3 is not supported. The absence of a significant interaction effect suggests that dynamic capability and transformational leadership operate as independent predictors of organizational performance rather than as mutually reinforcing factors. In other words, the influence of dynamic capability on performance does not vary significantly across different levels of transformational leadership, and vice versa. This consistency across estimation techniques enhances the credibility and auditability of the findings.

From a theoretical standpoint, this result may reflect the structural characteristics of public sector organizations, which are often governed by formalized rules, hierarchical procedures, and limited managerial discretion. Such conditions may constrain the emergence of synergistic effects between organizational capabilities and leadership styles. Consequently, while both variables are individually important, their combined effect does not generate additional explanatory power within this specific context. Importantly, the reconciliation of SmartPLS and regression results in this study ensures methodological clarity. SmartPLS is used as the

primary analytical tool due to its suitability for latent variable modeling and predictive analysis, while multiple regression serves as a supplementary robustness check. The convergence of results across these two approaches confirms the stability and reliability of the estimated relationships. These findings open avenues for future research, particularly in examining potential mediating mechanisms (e.g., organizational learning, innovation climate) or contextual moderators (e.g., institutional flexibility, organizational culture) that may condition the relationship between dynamic capability and transformational leadership.

The Effect of Dynamic Capability on Public Sector Organizational Performance

The results of this study empirically demonstrate that dynamic capability has a positive and significant effect on public sector organizational performance. These findings confirm that the ability of government organizations to respond to changes in the external environment is a critical determinant of achieving optimal performance. In the public sector context, which is characterized by regulatory changes, political pressures, accountability demands, and increasing public expectations regarding service quality, organizations with high levels of dynamic capability tend to be more adaptive and resilient. This capability is reflected in the organization’s capacity to engage in policy sensing, anticipate policy changes, and adjust internal processes swiftly and appropriately.

Conceptually, dynamic capability is not merely understood as a technical or administrative competence, but rather as a strategic capability that enables public organizations to engage in continuous learning, integrate knowledge across organizational units, and systematically reconfigure resources. Recent studies indicate that dynamic capabilities in public organizations encompass dimensions such as service innovation, procedural flexibility, and the strengthening of human resource capacity (Kovač et al., 2020; Mulyani & Rulandari, 2024; Piening, 2021). Accordingly, public organizations that are able to internalize dynamic capability practices are more effective in translating policies into outputs and outcomes that deliver value to society.

The findings of this study are consistent with those of (Piening & Salge, 2020), who argue that dynamic capability directly contributes to improved public sector organizational performance, particularly in complex and unstable environments. Similarly, research by (Zhou et al., 2022) emphasizes that an organization’s capacity to learn and adapt rapidly is a key prerequisite for the success of public sector reform. In the Indonesian context, these findings are highly relevant to the bureaucratic reform agenda, which requires government institutions to become more innovative, responsive, and performance-oriented.

Furthermore, these results reinforce the argument that dynamic capability serves as an important mechanism for bridging the gap between policy planning and implementation. Public organizations with strong dynamic capabilities are not only able to adjust internal structures and procedures, but are also capable of managing change proactively, thereby minimizing internal resistance and enhancing policy effectiveness (Ferlie & Ongaro, 2022; Stikip et al., 2023). Therefore, strengthening dynamic capability can be viewed as a long-term strategic investment in improving public sector performance.

The Effect of Transformational Leadership on Public Sector Organizational Performance

The findings of this study indicate that transformational leadership has a positive and significant effect on public sector organizational performance. These results affirm that

leadership quality plays a crucial role in determining the success of government organizations in achieving performance targets and delivering high-quality public services. Transformational leaders do not merely focus on meeting administrative targets, but also emphasize the development of a shared vision, employee empowerment, and the creation of a work climate conducive to innovation and change.

In the context of public bureaucracies, which tend to be hierarchical and procedural, the presence of transformational leaders constitutes a significant differentiating factor. Leaders who adopt a transformational style are able to clearly articulate a vision of bureaucratic reform, inspire employees to transcend personal interests, and foster stronger organizational commitment. Recent empirical studies demonstrate that transformational leadership contributes to improved public sector organizational performance by enhancing intrinsic motivation, trust in leadership, and employee work engagement (Campbell et al., 2021; Jensen et al., 2023).

The results of this study are consistent with the findings of (Van Wart et al., 2022), who argue that transformational leadership has a significant impact on public sector organizational effectiveness, particularly in contexts of policy change and public service digitalization. In addition, research by (Hassan et al., 2020) shows that transformational leaders are able to enhance organizational performance through the development of a culture of innovation and organizational learning. In this sense, transformational leadership functions as a key driver of behavioral and attitudinal change among employees in public organizations.

Within the empirical context of this study, the stronger effect of transformational leadership compared to dynamic capability suggests that leadership factors possess substantial leverage over organizational performance. This can be understood given that strategic decisions, internal policy direction, and program implementation are strongly influenced by leadership quality. Therefore, the development of transformational leadership competencies in the public sector represents a strategic agenda that cannot be overlooked in efforts to improve organizational performance.

The Non-Significant Interaction Effect between Dynamic Capability and Transformational Leadership

Contrary to the initial hypothesis, the results of this study indicate that the interaction between dynamic capability and transformational leadership does not have a significant effect on organizational performance. This finding suggests that the two variables operate independently in influencing performance, without demonstrating a statistically measurable synergistic effect. In other words, improvements in dynamic capability do not automatically strengthen the effect of transformational leadership on performance, and vice versa.

One theoretical explanation for this finding lies in the difference in the level of analysis of the two constructs. Dynamic capability represents an organizational-level capability that is systemic and institutionalized, encompassing routines, processes, and organizational structures that evolve over the long term. In contrast, transformational leadership operates at the individual and work-group levels and is strongly influenced by leaders’ personal characteristics and the organization’s social context (Azuzazah.A & Sari.R.K, 2021; Jensen et al., 2023; Ni & Oktavianti, 2023). This difference in analytical levels allows both variables to contribute to performance in parallel, but does not necessarily result in a direct and significant interaction effect.

Furthermore, the relatively rigid and regulation-bound nature of the public sector may constrain the emergence of interaction effects. In government organizations, change processes are often determined by formal policies and standardized procedures, which may limit the extent to which leadership influences the development of dynamic capability in

a direct manner or require a longer time horizon for such effects to materialize. Research by(Pudjiarti & Putranti, 2020) indicates that strong institutional contexts can weaken the dynamic relationship between leadership and organizational capabilities.

Nevertheless, the non-significance of this interaction does not preclude the possibility of more complex relationships under certain conditions. Several recent studies suggest that the interaction between leadership and organizational capabilities may emerge indirectly through mediating variables such as organizational culture, innovation, and employee commitment (Fernández & Moldogaziev, 2022; Kang & Kim, 2023). Therefore, this finding opens avenues for the development of more comprehensive conceptual models in future research.

Theoretical and Implications

From a theoretical perspective, this study contributes to the literature by enriching the discussion on dynamic capability and transformational leadership within the public sector context, which has so far been largely dominated by studies conducted in the private sector. The findings reaffirm that the dynamic capability framework remains relevant for explaining the performance of government organizations, particularly in addressing complex and dynamic environments. Moreover, this study strengthens the position of transformational leadership as an effective leadership approach within modern public bureaucracies.

From a contextual perspective, the results of this study have important implications for bureaucratic reform agendas and efforts to improve the performance of government institutions. Strengthening dynamic capability through organizational learning, procedural innovation, and the development of civil servant competencies needs to be integrated with systematic efforts to foster transformational leadership. Although these two factors operate independently, their combined presence continues to serve as a critical foundation for the creation of adaptive, high- performing public organizations. Directions for Future Research

Based on the findings of this study, future research is recommended to employ longitudinal research designs in order to capture the dynamic nature of the relationships among leadership, dynamic capability, and organizational performance over time. In addition, examining mediating variables such as organizational culture, service innovation, and employee commitment may provide deeper insights into the mechanisms through which these variables exert their influence. Comparative studies across sectors or across different levels of government may also serve as valuable alternatives to enhance the generalizability of the findings.

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SELF LOVE SEBAGAI BAGIAN DARI PENCEGAHAN REMAJA

Conclusion

Based on the results of the analysis, it can be concluded that dynamic capability and transformational leadership have a positive and significant effect on public sector organizational performance. Public organizations with strong dynamic capabilities tend to be more efficient, effective, and innovative in delivering services, which in turn leads to higher performance outcomes. Similarly, transformational leadership plays a crucial role in enhancing organizational performance by increasing employee motivation, fostering an adaptive work culture, and providing clear vision and direction. These findings underscore the importance of internal organizational factors both in terms of systemic adaptive capacity and leadership style in determining the success of public institutions in achieving performance targets and serving the public.

The empirical results provide support for Hypothesis 1 (H1) and Hypothesis 2 (H2), demonstrating that dynamic capability and transformational leadership each exert a positive and statistically significant influence on public sector organizational performance. These findings suggest that organizations with stronger adaptive capabilities and leaders who effectively articulate vision, inspire employees, and facilitate organizational change tend to achieve higher levels of performance. However, Hypothesis 3 (H3) is not supported, indicating that the interaction between dynamic capability and transformational leadership does not significantly affect organizational performance. This result suggests that the contribution of each variable operates independently rather than through a synergistic mechanism. Therefore, enhancing organizational performance in public sector institutions requires simultaneous attention to both adaptive organizational capabilities and effective transformational leadership practices, as each represents a distinct source of performance improvement.

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The absence of a significant interaction effect suggests that bureaucratic formalization, hierarchical administrative structures, and accountability mechanisms in public institutions may limit the extent to which transformational leadership strengthens the effectiveness of organizational dynamic capability. Consequently, organizational adaptability and leadership behavior appear to operate through distinct mechanisms rather than through an integrated performance- enhancing relationship. Practically, the findings imply that public organizations should strengthen adaptive capability and transformational leadership simultaneously while recognizing that each contributes independently to performance improvement. The results also reinforce the argument that public sector governance possesses institutional characteristics that shape capability deployment differently from more flexible and market-oriented private sector organizations. References

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