Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 3193-3209 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: fauziannor1272200006@email.untag-sby.ac.id Uncovering the dynamics of individual learning and employee adaptability in influencing innovation behavior Fauziannor1*, Ujianto2, Riyadi Nugroho3 1,2,3Faculty of Economics and Business, University of 17 Agustus 1945 Surabaya; fauziannor1272200006@email.untag-sby.ac.id (F.) ujianto@untag-sby.ac.id (U.) riyadi@untag-sby.ac.id (R.N.). Abstract: The success of organizations in the era of ever-changing business is greatly influenced by the adaptability, creativity, and innovation factors of employees, which are obtained through effective learning. Organizations that implement a learning culture encourage employees to adapt and internalize learning from past experiences. Employees who are active in training become more creative and adaptive, increasing their ability to deal with change. This study aims to explore the relationship between Individual Learning, Employee Adaptability, Employee Creativity, and Employee Innovation Behavior, especially in the State Civil Apparatus (ASN) in South Kalimantan. Through a quantitative approach with analysis using Partial Least Square (PLS), this study found that individual learning significantly affects employee adaptability and creativity, and contributes to their innovative behavior. The results of the study indicate the need for a longitudinal approach to understand the dynamics of changes in employee adaptability and creativity in the context of public services. This study identifies the importance of supporting factors such as management support and work environment that influence employee innovation. Keywords: Employee adaptability, Employee creativity, Innovation behavior, Individual learning, Public sector. 1. Introduction The success of organizations in a rapidly changing business era depends on adaptability, creativity, and innovation, which are achieved through effective learning processes at various levels. Organizations that prioritize learning and innovation create a culture that supports employee adaptability. Through the learning process, all elements of the organization can identify lessons from past experiences and apply them to face future changes. Employees not only learn individually, but also collectively, so they can internalize learning outcomes and adapt to the dynamics of the work environment. This process allows organizations to take the right steps in facing market and technological changes.(Agung Kurniawan & Suswanta, 2020; Agus et al., 2023; Comedy & Ferianto, 2023). Creativity and adaptability are direct outcomes of effective learning. Employees who are actively involved in training develop skills that facilitate creative approaches to problem solving. Increased adaptability helps employees adjust to change. Employees with a strong learning background tend to be more confident in proposing new ideas and implementing innovative solutions, which ultimately encourages innovative behavior in the workplace. In the public sector, learning plays a vital role in shaping employees’ vision and work ethic.(Muhtadin, 2023; Yusuff, 2023). Learning designed to support adaptability, creativity, and innovation has a significant impact on employee performance. By providing opportunities for employees to participate in training, organizations not only improve their competencies, but also create an environment that encourages intrinsic motivation. Learning that focuses on improving adaptive and creative abilities makes employees better prepared to face challenges, contribute positively, and improve organizational performance. The Supervisory Leadership Program (PKP) enhances individual learning for ASN, encouraging them to develop leadership skills through independent learning. PKP creates a work environment that 3194 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate supports employee growth by applying concepts learned in real situations. Through this learning, ASN are trained to think creatively and innovatively, generate new solutions, and improve the quality of public services. (Bakhtiar, 2023). With the industrial revolution 4.0, individual learning and commitment to self-improvement are key to facing complex adaptation challenges. Leaders also play a vital role in creating a climate of innovation and creativity, ensuring that organizations can adapt and thrive in a dynamic environment. Research in the last 10 years, reveals(Bagus et al., 2022).The study found that employee innovative behavior can be reflected by several dimensions, including: Use of computer technology. Use of available financial resources There is a close relationship between innovation and the use of technology, which is confirmed in civil servants in Badung Regency.(Fajar & Efendi, 2023). Spiritual leadership was found to have a positive effect on organizational performance. Organizational culture also has a positive effect on organizational performance. There is a positive effect of spiritual leadership on organizational culture, which is mediated by innovation behavior. The study noted that the people of Pamekasan Regency have a hard-working and innovative character in business. Spiritual values play an important role in their economic innovation behavior.(Ainulisany & Radikun, 2022).Knowledge sharing behavior has a significant role in mediating the relationship between organizational climate and innovative behavior in the workplace.(Riawan et al., 2021), the influence of Digital Learning: Digital learning has a positive and significant influence on workplace innovation (Y2) through individual readiness (Y1). Digital learning also has a positive and significant influence on individual readiness. Individual readiness shows a positive and significant influence on workplace innovation.(Sutopo et al., 2024), leadership support has a significant influence on proactive work behavior both directly and indirectly through work culture. Work culture functions as a mediator that strengthens the relationship between leadership support and proactive work behavior, thereby creating an environment that supports employees to behave proactively.(Yunus et al., 2021), learning organization has a positive and significant influence on innovative behavior in Indonesian Credit Guarantee Limited, both learning organization and work involvement have a significant influence simultaneously on innovative behavior.(Etikariena & Dewi, 2024).The Role of Readiness to Change: Readiness to change serves as a partial mediator in the relationship between digital learning orientation and innovative work behavior. This means that digital learning orientation not only directly affects innovative behavior but also through readiness to change.(Syarif, 2023).Influence of Individual Creativity: Individual creativity has a significant influence on innovative work behavior. The results of the study showed that increasing individual creativity can increase innovative work behavior by up to 92%. Job satisfaction also showed a significant influence on individual creativity, where increasing job satisfaction can increase individual creativity by up to 83%. Although there is a significant influence, the influence of job satisfaction on individual creativity is said to be low, which may indicate that other factors also contribute to individual creativity.(Umalihayati et al., 2022), visionary leadership, learning organization, creativity, and work innovation have a significant influence on lecturer performance. Innovative behavior functions as a mediator indicating that visionary leadership, learning organization, and creativity affect lecturer performance through innovative behavior. Of the 26 indicators studied, 1 indicator was found to be in good condition (which needs to be maintained or developed), and 25 other indicators are still weak and need to be improved, with the order of priority handling.(Syahmirza & Prawitowati, 2022), Employee engagement has a positive and significant effect on employee creativity. Employee engagement also has a positive and significant effect on employee performance. Employee creativity has a positive and significant effect on employee performance.(Dwi et al., 2024). Learning Agility has a significant influence on Employee Innovative Behavior with a significance value of 0.00. Work Engagement also shows a significant influence on Employee Innovative Behavior with a significance value of 0.00. The results of the analysis show that Fcount (88.921) is greater than Ftable (3.05), which indicates that Learning Agility and Work Engagement simultaneously have a significant influence on Employee Innovative Behavior.(Noerchoidah et al., 2022), learning orientation has a significant influence on creative self- efficacy and innovative behavior. This shows that a good learning orientation can increase employee self-confidence in creating and innovating. Creative self-efficacy has also been shown to have a significant influence on innovative behavior. This means that the higher an individual's belief in their 3195 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate creative abilities, the higher the innovative behavior they show.(Magdalena, 2014). individual character has a significant influence on career improvement. This is supported by employee statements indicating that continuing studies aims to develop careers, meet job demands, and increase knowledge. The learning environment has also been shown to have a significant influence on individual character and careers. This suggests that a supportive environment can help employees develop positive character and encourage advancement in their careers.(Suparjo et al., 2024). The study shows that work discipline has a significant influence on innovative behavior. This shows that disciplined health workers are more likely to demonstrate innovative behavior in their work. Work culture has a significant influence on performance. This shows that a positive and supportive work environment can improve the performance of health workers. Training also shows a significant influence on the performance of health workers. This indicates that increasing skills and knowledge through training has a positive impact on performance.(Angelica et al., 2022). The study showed a significant positive relationship between Transformational Leadership and Turnover Intention, indicating that transformational leadership style can affect employees’ intention to leave their jobs. A significant positive relationship was also found between Organizational Citizenship Behavior and Turnover Intention, indicating that organizational citizenship behavior can contribute to turnover intention. Job Autonomy and Supportive Management were positively and significantly associated with Organizational Citizenship Behavior. This suggests that job autonomy and good managerial support can enhance citizenship behavior among employees.(Ningrum, 2020).Innovative Behavior has a positive and significant effect on Career Success. This indicates that increasing innovative behavior can contribute to an individual's career success in the company. Innovative Behavior also has a positive and significant effect on Self-Efficacy. This indicates that individuals who behave innovatively tend to have higher self-confidence in their abilities. Self- Efficacy has a positive and significant effect on Career Success, indicating that an individual's self- confidence can contribute to their career achievement.(Etikariena, 2020). The main results of the study indicate that knowledge sharing behavior is significantly correlated with innovative behavior in the workplace (r = .69, t(214) = 13.99, p < .01). This indicates a strong relationship between the two variables. Knowledge sharing behavior can significantly explain the proportion of variance in innovative behavior scores in the workplace (R² = .48, F = 195.61). This means that 48% of the variation in innovative behavior scores can be explained by knowledge sharing behavior scores. This figure shows a fairly significant influence. Previous studies reviewed for the study of Employee Adaptability and Creativity of ASN Employees in South Kalimantan face several gaps that are important to identify. The gaps obtained include employee work behavior can fluctuate due to seasonal or situational variations that cannot be observed in a short period of time. Longer longitudinal research is needed to understand the dynamics and changes in adaptability and creativity of ASN employees in South Kalimantan. The purposive sampling technique used in this study can cause bias if the respondent selection criteria are not appropriate. If respondents do not represent the entire population, the results of the study may not be generalizable to all ASN employees in South Kalimantan. A random sampling approach can increase the representativeness of the research results. Cross-sectional research only provides a picture at one point in time. This does not allow for observation of changes or dynamics in Employee Adaptability (Z1) and Employee Creativity (Z2) over time. Longitudinal research is needed to explore how individual learning (X) and employee adaptability develop and influence innovative behavior (Y) in a sustainable manner, so it is necessary to consider individual learning variables (X) and work engagement as independent variables. Other factors that may influence innovative behavior, such as management support, work environment, and motivation, were not analyzed, thus requiring a more holistic understanding. This study offers an in-depth look at how the adaptability and creativity of ASN employees in South Kalimantan are influenced by various factors and how they contribute to innovative behavior in a more comprehensive manner.This study develops an in-depth approach to examine the relationship between Individual Learning, Employee Adaptability, Employee Creativity, and Employee Innovation Behavior in the context of the State Civil Apparatus (ASN) in South Kalimantan. In this study, the analysis stage begins with Outer Loading, ensuring that each indicator has strong validity with a value of > 0.70. This 3196 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate step is important to ensure the validity of constructs such as Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y). This study also validates the reliability and convergent validity using Composite Reliability and Average Variance Extracted (AVE), with a standard composite reliability value of > 0.70 and AVE > 0.50. Discriminant Validity testing using the Fornell-Larcker criteria ensures that each construct has adequate discriminant validity. In addition, this study will assess the model with Inner Model Evaluation through R Square and Adjusted R Square analysis to measure the influence of independent variables (Individual Learning) on mediation variables (Z1 and Z2) and dependent variables (Y). The R Square value of > 0.50 indicates a fairly good model strength. Path Coefficients are then used to measure the significance of the path with a t-statistic value of > 1.96 and a p-value < 0.05, ensuring that the identified influence is significant. F Square evaluation is also carried out to measure the magnitude of the effect of each variable, distinguishing between large effects (> 0.35), medium (0.15-0.35), and small (0.02-0.15). The uniqueness of this study lies in the Blindfolding test to measure Q Square, which shows predictive relevance in the context of ASN adaptability and creativity in South Kalimantan. This study not only evaluates the direct (partial) path between these variables, but also takes into account the mediation path, namely the influence of Individual Learning on Employee Innovation Behavior through Employee Adaptability and Employee Creativity. With this comprehensive model, the study offers new insights into how individual learning can influence ASN innovative behavior by increasing employee adaptability and creativity, which is important in enhancing organizational responsiveness and effectiveness in the public sector. This study aims to investigate the relationship between Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y) among State Civil Apparatus (ASN) in South Kalimantan. Through in-depth analysis, this study aims to identify how much influence individual learning has on employee adaptability and creativity and how both contribute to innovative behavior. The results of this study are expected to provide a better understanding of the factors that support innovation in the context of public services, especially in the ASN environment. This study uses a quantitative method with a path analysis approach to test the relationship between predetermined variables. The study was conducted through a survey involving ASN employees in South Kalimantan, using a questionnaire designed to measure the constructs of Individual Learning, Employee Adaptability, Employee Creativity, and Employee Innovation Behavior. Data analysis was carried out using statistical software to ensure the validity and reliability of the data obtained. With a comprehensive model, this study is expected to describe the dynamics of interaction between variables and provide valuable insights for employee development in the public sector. In theory, this study contributes to the human resource management literature by enriching the understanding of the relationship between individual learning and innovation in the public sector. The findings are expected to be used as a reference for further research in the context of employee adaptability and creativity, as well as presenting a relevant analysis model for similar studies. In practice, the results of this study can provide recommendations for organizational leaders in designing more effective employee development programs, by emphasizing the importance of individual learning as a key factor in driving innovation and improving ASN performance. 2. Research Methodology 2.1. Design This study uses a quantitative approach with an associative approach, which aims to identify and measure the relationship between existing variables. This associative approach is appropriate for research conducted at the Regional Human Resources Development Agency (BPSDMD) of South Kalimantan Province, with a focus on the adaptability and creativity of ASN employees. By using quantitative methods, this study can test hypotheses empirically and statistically to determine the extent to which the relationship between variables can be measured.(Alzahrani et al., 2024; Kante & Michel, 2023). The Partial Least Square (PLS) model is used to analyze the mediating role of variables 3197 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate in the influence of Individual Learning (X) on Employee Innovation Behavior (Y) through two mediating variables, namely Employee Adaptability (Z1) and Employee Creativity (Z2). PLS is an appropriate method for research with an associative approach because it is able to handle complex models with many variables and take into account direct and indirect relationships between these variables. This approach allows to test whether Employee Adaptability (Z1) and Employee Creativity (Z2) act as partial or full mediators in the relationship between Individual Learning (X) and Employee Innovation Behavior (Y)(Afsar et al., 2020; Jadhav & Ekbote, 2021; Tajuddin et al., 2015). This study is important to understand how individual learning can improve ASN employees' adaptability and creativity, which ultimately has a positive impact on their innovative behavior. Thus, the PLS approach not only measures the strength of the relationship between variables, but also explores how mediating variables affect the relationship, providing a comprehensive picture of the dynamics of employee adaptability and creativity in South Kalimantan. 2.2. Population and Sampling This study involved 132 respondents who were employees who participated in the 2023 Supervisory Leadership Training (PKP) at the Regional Human Resources Development Agency (BPSDMD) of South Kalimantan Province.(Saether, 2019a; Shafi et al., 2020). The selection of respondents was carried out using the census method or saturated sample, where the entire population of 160 PKP employees in 2023 was divided into four batches: Batch 1 (40 people), Batch 2 (20 people), Batch 3 (20 people), and Batch 4 (52 people). By using the census method, this study observed the entire population so that the results can be generalized directly to all employees who participated in the PKP training at the BPSDMD of South Kalimantan Province. This study aims to analyze the adaptability and creativity of ASN employees in South Kalimantan through the main variables, namely Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y). 2.3. Procedures and Data Collection Data collection for this study was carried out through two main methods, namely questionnaires and in-depth interviews. The questionnaire was distributed to all respondents totaling 132 employees who participated in the 2023 Supervisory Leadership Training (PKP) at the BPSDMD of South Kalimantan Province. This questionnaire was designed to measure variables such as Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y)(Novita & Anjaningrum, 2023; Saether, 2019b), using a Likert scale to facilitate quantitative data analysis. In addition, in-depth interviews were conducted with selected employees to gain a deeper understanding of their experiences, perceptions, and factors that influence their adaptability, creativity, and innovative behavior in the workplace. Data from both methods were integrated to obtain comprehensive and valid results. 2.4. Operational Variables The operational variables in this study include four main constructs: Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y). Individual Learning (X) is measured through learning initiatives, learning needs analysis, personal goals, learning resources, and learning strategies, with 9 questions (IL1–IL9). 3198 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate Table 1. Operational variables. No Construct Construct items Question items Item code Reference 1 Individual learning (X) 1) Self-study initiative 2) Learning needs analyst 3) Setting personal learning goals 4) Search for learning resources 5) Choosing the right learning strategy 9 grains IL 1 – IL 9 (Bourke & Roper, 2017; Xiaobao et al., 2023) 2 Employee adaptability (Z1) 1) Employee adaptation to changes in the work environment 2) Employee readiness to face new tasks 3) Employee flexibility in work approach (Z1.2) 10 grains EA 1 – EA 10 (Afsar et al., 2020; Agustin et al., 2023; Gaur, 2020; Poláková et al., 2023) 3 Employee creativity (Z2) 1) Creation of new and original ideas by employees. 2) Different views on seeing the problem 3) Dare to take risks inshare unconventional ideas 7 grains EC 1 – EC 7 (Afsar et al., 2020; Jadhav & Ekbote, 2021; Tajuddin et al., 2015) 4 Employee innovation behavior (Y) 1) Idea exploration 2) Idea generation 3) Idea championing 4) Idea implementation 6 grains Y1 – Y8 (Ghobakhloo et al., 2023; Siqueira et al., 2021; Wang et al., 2022) Employee Adaptability (Z1) includes adaptation to change, readiness to face new tasks, and flexibility in work approaches, with 10 questions (EA1–EA10). Employee Creativity (Z2) is assessed from the creation of new ideas, different perspectives, and the courage to share unconventional ideas, consisting of 7 items (EC1–EC7). Employee Innovation Behavior (Y) includes exploration, creation, submission, and implementation of ideas, with 6 questions (Y1–Y8). 2.5. Research Procedures This study with the Outer Loading stage, where this value must be > 0.70 to ensure the validity of the indicator against the construct (eg, indicators for Individual Learning (X), Employee Adaptability 3199 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y)). After that, Composite Reliability and Average Variance Extracted (AVE) are used to test reliability and convergent validity, with the expected composite reliability value > 0.70 and AVE > 0.50(Dash & Paul, 2021). Furthermore, the Discriminant Validity test (Fornell-Larcker Criterion) ensures that the construct has discriminant validity, where the square root AVE of each construct must be greater than the correlation between constructs. The next stage is the Inner Model Evaluation, which involves the analysis of R Square and Adjusted R Square to see how much the independent variable (Individual Learning (X)) affects the mediating variables (Z1 and Z2) and the dependent variable (Y), with an R Square value > 0.50 indicating a fairly strong model(Meesala & Paul, 2018; Zhang et al., 2024). After that, the Path Coefficients test is used to evaluate the significance of the path, where the t-statistic value > 1.96 (p- value < 0.05) indicates a significant effect. F Square is also evaluated to see the large effect of each variable (eg, Individual Learning (X) on Z1 and Z2) with the criteria > 0.35 (large), 0.15 - 0.35 (moderate), and 0.02 - 0.15 (small). Finally, the Blindfolding test for Q Square measures the predictive relevance of the model, where the Q Square value > 0 indicates good predictive relevance in the context of adaptability and creativity of ASN employees in South Kalimantan(Herberger & Oehler, 2024; Rahmadi & Mutasowifin, 2021; Yilmaz, 2018). 3. Results and Discussion 3.1. Results 3.1.1. Outer Model Outer loading and reliability parameters and validity measured using Cronbach's Alpha and Average Variance Extracted (AVE), these results show strong consistency and validity in the research model related to Employee Adaptability and ASN Employee Creativity in South Kalimantan. Figure1. Structural equation outer model. The outer loading values for the variables "Employee Adaptability" (EA), "Employee Creativity" (EC), "Employee Innovation Behavior" (EIB), and "Individual Learning" (IL) have outer loading values above 0.7, which means that each indicator has a strong and relevant relationship with the latent 3200 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate variables being measured. This shows that all indicators meet the established standards and are reliable in measuring their respective constructs. Table 2. Outer model value. Outer loading Outer loading standard Decision Cronbach's alpha Average variance extracted (AVE) Standard value Decision EA1 0.840 >0.7 Fulfilled 0.974 0.812 >0.5 Worthy EA10 0.860 >0.7 Fulfilled EA2 0.914 >0.7 Fulfilled EA3 0.923 >0.7 Fulfilled EA4 0.894 >0.7 Fulfilled EA5 0.929 >0.7 Fulfilled EA6 0.909 >0.7 Fulfilled EA7 0.917 >0.7 Fulfilled EA8 0.921 >0.7 Fulfilled EA9 0.899 >0.7 Fulfilled EC1 0.881 >0.7 Fulfilled 0.936 0.726 >0.5 Worthy EC2 0.832 >0.7 Fulfilled EC3 0.881 >0.7 Fulfilled EC4 0.904 >0.7 Fulfilled EC5 0.872 >0.7 Fulfilled EC6 0.871 >0.7 Fulfilled EC7 0.708 >0.7 Fulfilled EIB1 0.776 >0.7 Fulfilled 0.958 0.774 >0.5 Worthy EIB2 0.847 >0.7 Fulfilled EIB3 0.890 >0.7 Fulfilled EIB4 0.899 >0.7 Fulfilled EIB5 0.889 >0.7 Fulfilled EIB6 0.911 >0.7 Fulfilled EIB7 0.929 >0.7 Fulfilled EIB8 0.885 >0.7 Fulfilled IL1 0.762 >0.7 Fulfilled 0.941 0.681 >0.5 Worthy IL2 0.814 >0.7 Fulfilled IL3 0.777 >0.7 Fulfilled IL4 0.809 >0.7 Fulfilled IL5 0.857 >0.7 Fulfilled IL6 0.810 >0.7 Fulfilled IL7 0.857 >0.7 Fulfilled IL8 0.874 >0.7 Fulfilled IL9 0.859 >0.7 Fulfilled The Cronbach's Alpha value for all constructs (EA: 0.974, EC: 0.936, EIB: 0.958, and IL: 0.941) exceeds 0.7, indicating high internal consistency. This means that all items in each construct have good correlation and measure the same thing, namely adaptability, creativity, behavioral innovation, and individual learning. The AVE value for all variables is also greater than 0.5 (EA: 0.812, EC: 0.726, EIB: 0.774, and IL: 0.681), indicating that the constructs have good convergent validity. This means that most of the indicator variance can be explained by latent variables, so this model is suitable for measuring employee adaptability and creativity of ASN employees in South Kalimantan. "Individual Learning" (X) affects "Employee Adaptability" (Z1) and "Employee Creativity" (Z2), which ultimately 3201 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate affects "Employee Innovation Behavior" (Y) significantly. This model is valid and reliable in describing the relationship between individual learning and the adaptability, creativity, and innovation behavior of ASN employees in South Kalimantan. Fronell-Larcker criteria and Average Variance Extracted (AVE) values, the four variables in the study, namely Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y), show values that meet the eligibility criteria. The AVE of each variable is above the threshold of 0.50, which means that these variables have fairly good convergent validity. Specifically, Employee Adaptability (Z1) with an AVE value of 0.812 indicates that employee adaptability has a significant contribution to the absorption of variance in the model. Table 3. Value eligibility Fronell-Larcker criterion. Employee adaptability (Z1) Employee creativity (Z2) Employee innovation Behavior (Y) Individual learning (X) Average variance extracted (AVE) Decision Employee adaptability (Z1) 0.901 0.812 Worthy Employee creativity (Z2) 0.887 0.852 0.726 Worthy Employee innovation Behavior (Y) 0.778 0.872 0.879 0.774 Worthy Individual learning (X) 0.817 0.801 0.753 0.825 0.681 Worthy Employee Creativity (Z2) also has an AVE value of 0.726, indicating that employee creativity is closely related to individual learning and employee adaptability. This is important in the context of research on the adaptability and creativity of ASN employees in South Kalimantan, where effective individual learning (X) can increase employee adaptability (Z1) and creativity (Z2), which ultimately drives innovative behavior (Y) of ASN employees. The AVE value and Fronell-Larcker criteria indicate that these variables are suitable for use in the analysis, ensuring that the research instrument used is able to measure the construct accurately and in depth. This confirms that the development of individual learning among ASN employees in South Kalimantan plays an important role in increasing adaptability and creativity, which has a positive impact on innovative behavior in their work environment. 3.1.2. Inner Model Partial path analysis shows that the Individual Learning (X) variable has a significant effect on Employee Creativity (Z2) and Employee Innovation Behavior (Y), as well as on Employee Adaptability (Z1). The high Original Sample (O) and T Statistics values and P Values below 0.05 on the Individual Learning (X) path to Employee Creativity (Z2) (0.801; 23.861) and Employee Adaptability (Z1) (0.817; 28.474) indicate that Individual Learning (X) plays an important role in increasing employee creativity and adaptability. In addition, Employee Creativity (Z2) also has a significant and large effect on Employee Innovation Behavior (Y) (0.792; 7.321), which means that employee creativity directly drives innovation behavior. 3202 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate Figure 2. Structural equation inner model. However, the path from Employee Adaptability (Z1) to Employee Innovation Behavior (Y) showed insignificant results (P Value = 0.642), so this hypothesis was rejected. This shows that, although employee adaptability is important, in the context of ASN employees in South Kalimantan, adaptability does not directly affect employee innovative behavior. Instead, individual learning and employee creativity are more dominant in influencing innovation. Therefore, to improve ASN innovative behavior in South Kalimantan, organizations should focus on improving Individual Learning and Employee Creativity, because these two variables have a significant and positive influence on innovation, while Employee Adaptability needs to be further developed or perhaps combined with other factors to provide a greater impact on innovation. Table 4. Partial path hypothesis value. Partial path Original sample (O) T statistics (|O/STDEV|) P values Sig standard. Decision Employee adaptability (Z1) -> Employee innovation behavior (Y) -0.066 0.465 0.642 <0.05 Hypothesis rejected Employee creativity (Z2) -> Employee Innovation behavior (Y) 0.792 7,321 0.000 <0.05 Hypothesis accepted Individual learning (X) -> Employee adaptability (Z1) 0.817 28,474 0.000 <0.05 Hypothesis accepted Individual learning (X) -> Employee creativity (Z2) 0.801 23,861 0.000 <0.05 Hypothesis accepted Individual learning (X) -> Employee Innovation 0.173 2,710 0.007 <0.05 Hypothesis accepted 3203 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate behavior (Y) The results of the mediation path analysis in the study on Employee Adaptability and ASN Employee Creativity in South Kalimantan, there are two mediation paths analyzed. First, the mediation path Individual Learning (X) -> Employee Adaptability (Z1) -> Employee Innovation Behavior (Y) shows that the Original Sample (O) value is -0.054, T Statistics is 0.464, and P Values are 0.643. Because the P value is greater than the significance standard of 0.05, this hypothesis is rejected. This shows that individual learning does not have a significant effect through employee adaptability in increasing the innovation behavior of ASN employees in South Kalimantan. On the other hand, the second mediation path, namely Individual Learning (X) -> Employee Creativity (Z2) -> Employee Innovation Behavior (Y), shows significant results with an Original Sample of 0.634, T Statistics of 6.985, and P Values of 0.000. Because the P value is less than 0.05, this hypothesis is accepted. Table 5. Hypothesis value of mediation path. Mediation path Original sample (O) T statistics (|O/STDEV|) P values Sig standard. Decision Individual learning (X) -> Employee adaptability (Z1) -> Employee innovation behavior (Y) -0.054 0.464 0.643 <0.05 Hypothesis rejected Individual learning (X) -> Employee creativity (Z2) -> Employee innovation behavior (Y) 0.634 6.985 0.000 <0.05 Hypothesis accepted These results indicate that individual learning has a positive and significant influence through employee creativity in improving innovation behavior of ASN employees in South Kalimantan. This study reveals that although individual learning does not directly have a significant impact through adaptability, through employee creativity, individual learning is able to improve innovation behavior. This underlines the importance of encouraging creativity of ASN employees in South Kalimantan to improve innovation, while adaptability does not have a significant mediating role. Based on the results of statistical analysis in the study of employee adaptability and creativity of ASN employees in South Kalimantan, several constructs showed a significant contribution to employee innovation behavior. First, the Employee Adaptability construct (Z1) has an R Square of 0.668 and an Adjusted R Square of 0.666, which is included in the fairly good category. The Q Square value of 0.535 also shows good predictive relevance. This shows that employee adaptability can be well explained by related variables, such as Employee Creativity (Z2) and Individual Learning (X). The Employee Creativity construct (Z2) has an R Square of 0.642 and an Adjusted R Square of 0.639, both of which are included in the fairly good scale, and a Q Square of 0.460 which indicates that employee creativity also has good predictive relevance. This shows that the individual learning process (Individual Learning (X)) plays a very important role in increasing employee creativity. The F Square value of 2,013 on the Individual Learning (X) -> Employee Adaptability (Z1) path and 1,792 on the Individual Learning (X) - > Employee Creativity (Z2) path shows a large effect, underlining the importance of individual learning in strengthening employee adaptability and creativity. 3204 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate Table 6. Path value decision f², Q2 and R². Construct R square R square scale R square adjusted Adjusted R square scale Q square Q square scale Track F square F square scale Employee adaptability (Z1) 0.668 Pretty good 0.666 Pretty good 0.535 Good Employee creativity (Z2) -> Employee innovation behavior (Y) 0.532 Big effect Employee creativity (Z2) 0.642 Pretty good 0.639 Pretty good 0.460 Good Individual learning (X) -> Employee adaptability (Z1) 2.013 Big effect Employee innovation behavior (Y) 0.769 Very good 0.764 Very good 0.586 Good Individual learning (X) -> Employee creativity (Z2) 1,792 Big effect The Employee Innovation Behavior (Y) construct shows higher results with an R Square of 0.769 and an Adjusted R Square of 0.764, which is included in the very good scale. This indicates that employee innovative behavior is significantly influenced by their adaptability and creativity. The Q Square value of 0.586 also shows good predictive relevance, and the F Square value of 0.532 on the Employee Creativity (Z2) -> Employee Innovation Behavior (Y) path indicates that employee creativity has a large effect on innovative behavior. Overall, these results confirm that Individual Learning (X) has a significant influence on Employee Adaptability (Z1) and Employee Creativity (Z2), which ultimately affects Employee Innovation Behavior (Y). Efforts to improve the adaptability and creativity of ASN employees in South Kalimantan through individual learning can have a positive impact on employee innovative behavior. The SRMR in the Saturated Model shows a value of 0.056, which meets the eligibility criteria with a good category because it is below the threshold of 0.08. However, the SRMR in the Estimated Model reaches 0.098, which is still in the fairly good category (below 0.10), but needs to be considered to improve the model's fit. The d_ULS and d_G values in both models show good results, with lower values in the Saturated Model than the Estimated Model, indicating that the changes in this model are not significant. The Chi-Square in the Saturated Model and Estimated Model are 1734.115 and 1806.609 respectively, indicating that this model is acceptable, although a lower Chi-Square value is more desirable. The NFI (Normed Fit Index) is at 0.733 for the Saturated Model and 0.721 for the Estimated Model, which is still in the fairly good category (0.70 - 0.90). Table 7. Fit model eligibility. Parameter Saturated model Estimated model Evaluation scale SRMR 0.056 0.098 SRMR < 0.08 = Good d_ULS 1,855 5,740 Good d_G 2,899 2,999 Good Chi-square 1734.115 1806.609 Model accepted NFI 0.733 0.721 0.70 - 0.90 = Good enough 3205 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate In relation to Individual Learning (X), Employee Adaptability (Z1), Employee Creativity (Z2), and Employee Innovation Behavior (Y) in the context of Employee Adaptability and Creativity of ASN Employees in South Kalimantan, these results indicate that the model used is sufficient to explain the relationship between these variables. However, improvements in several parameters such as SRMR in the Estimated Model and improvements in NFI are needed to achieve a better level of model fit. This is important because understanding how individual learning (X) affects employee adaptability and creativity (Z1 and Z2), as well as innovation behavior (Y), requires a model that has a high level of fit to produce more accurate and applicable interpretations in the context of ASN in South Kalimantan. 4. Discussion It is important to understand the relationship between variables and how they influence each other, as well as to find opportunities for policy improvements or interventions that can be implemented in South Kalimantan. The importance of individual learning as the main foundation in developing ASN employee adaptability and creativity. The results of the analysis show that "Individual Learning" has a significant effect on "Employee Adaptability" and "Employee Creativity," each with a high T-statistic value (28.474 and 23.861) and P-Values below 0.05. This suggests that efforts to improve individual learning, such as self-study initiatives, learning needs analysis, and personal learning goal setting, can strengthen employee adaptability and creativity. In the context of ASN in South Kalimantan, the recommended strategy is to strengthen training programs that focus on developing individual skills and self-learning management to improve employee ability to deal with change and foster creative ideas. The study highlights the path between "Employee Adaptability" and "Employee Innovation Behavior" which shows the hypothesis is rejected. This path has an Original Sample value of -0.066, indicating a negative and insignificant relationship with a T-statistic of 0.465 and a P-Value of 0.642 (greater than 0.05). This indicates that although adaptability is important, adaptability alone is not enough to drive innovative behavior without other factors, such as creativity or organizational support. In this context, policies in South Kalimantan can be focused on creating a work environment that supports creativity and collaboration to increase innovative behavior, rather than relying solely on employee adaptability. It is necessary to focus on the importance of "Employee Creativity" in influencing "Employee Innovation Behavior." The analysis shows that "Employee Creativity" has a significant and positive influence on "Employee Innovation Behavior," with an Original Sample of 0.792, T-statistics of 7.321, and P-Values of 0.000. This confirms that employee creativity is a key factor in driving innovative behavior in the ASN environment of South Kalimantan. Therefore, the strategy that can be applied is to develop a work culture that encourages new ideas, as well as provide training that focuses on creative problem-solving techniques and the development of original ideas. Appreciating employee initiatives in putting forward new ideas is also important to increase employee confidence and courage in taking risks. This study is in line with(Agustin et al., 2023), inclusive leadership, open communication, and social support play an important role in strengthening employee adaptability skills during external changes, including the COVID-19 pandemic. Strategies for developing adaptability skills, such as understanding the concept of adaptability, implementing development strategies, and understanding the benefits for the company and employees.(Zuhaena & Harsuti, 2021), employee interactions involving a combination of high demands and high resources are considered ideal and contribute to innovative behavior. This suggests that the context of employee interactions influences the level of innovation in organizations. Innovative behavior emerges as a consequence of complex interactions between employees. Engaged employees tend to be more innovative because they implement coping strategies to deal with challenges that arise in the work environment.(Nurhayati et al., 2024), the influence of Organizational Culture: Organizational culture has a significant effect on teacher performance, with an original sample value of 0.163. Organizational culture also has a significant effect on teacher professionalism, with an original sample value of 0.267. Professionalism has a significant effect on teacher performance, with an original sample value of 0.292. There is a significant indirect effect between organizational culture and teacher performance mediated by professionalism, with an original sample value of 0.070 and a p-value of 0.009.(Khairunnisa et al., 2024).Significant Relationship. Psychological capital provides an effective 3206 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate contribution of 29% to innovative work behavior, while 71% is influenced by other factors not measured in this study.(Sani & Annisa, 2019).The Influence of Inclusive Leadership: The results of the study show that Inclusive Leadership has a positive and significant effect on Employee Innovative Behavior. This shows that inclusive leadership encourages employees to innovate. Influence on Perceived Organizational Support: Inclusive leadership also has a positive and significant effect on Perceived Organizational Support. This shows that the support felt by employees from the organization increases with inclusive leadership. Influence of Perceived Organizational Support: Perceived Organizational Support has a positive and significant effect on Employee Innovative Behavior. This means that when employees feel supported by the organization, they tend to exhibit innovative behavior.(Aini, 2022).Effect of Job Crafting: The results of the study showed that job crafting has a significant effect on creativity. This suggests that when employees actively change and adapt their jobs, it can increase their creativity. Job crafting also has a significant effect on work engagement. This indicates that employees who engage in job crafting are more engaged in their jobs. The study found that work engagement did not have a significant effect on creativity. This may indicate that work engagement alone is not enough to increase creativity.(Ghiffari & Purba, 2021).Mediation of Intrinsic Motivation: The results showed that intrinsic motivation mediates the relationship between CSE and employee creativity. This means that employees who have positive self-evaluation (high CSE) are more likely to have high intrinsic motivation, which in turn increases their creativity. The study found that learning organizational culture does not moderate the relationship between intrinsic motivation and employee creativity. This suggests that even though a learning culture exists, it does not affect how much intrinsic motivation contributes to creativity.(Hamdani Dalimunte, 2023).Influence of Social Capital: Describes how interpersonal networks and social relationships in the workplace can drive work innovation. Influence of Human Capital: Shows how individual knowledge, skills, and experience can enhance work innovation. Impact on Management Performance: Analyzes the extent to which work innovation contributes to improving employee management performance. On the mediation path, especially the path "Individual Learning" -> "Employee Creativity" -> "Employee Innovation Behavior" which shows significant results (Original Sample 0.634, T-statistics 6.985, P-Values 0.000). This shows that employee creativity acts as a strong mediator between individual learning and innovative behavior. In this context, policy adaptation that encourages ASN to participate in continuous and innovative learning programs can strengthen this path. In addition, creating an incentive system for ASN who successfully implement innovative ideas can be an effective strategy to strengthen this mediation effect, so that employees are more motivated to improve their skills and apply them in their work. On the path "Individual Learning" -> "Employee Adaptability" -> "Employee Innovation Behavior" which shows the hypothesis is rejected, with an Original Sample value of -0.054, T-statistics 0.464, and P-Values 0.643. This shows that adaptability alone, without being supported by creativity or appropriate organizational support, is not enough to transform individual learning into significant innovative behavior. Therefore, the government in South Kalimantan can develop programs that not only emphasize adaptability in work, but also encourage creativity as a key to transformation. Focusing on an integrative approach between technical training and creativity can help maximize the effects of individual learning on innovation. The study can be implemented in the long term to improve "Employee Innovation Behavior" among ASN. Given the results of the analysis that creativity has a significant role in innovative behavior, and adaptability does not show a direct influence, the strategy can be focused on creative development programs for ASN in South Kalimantan. Providing a forum such as workshops, training, and innovation competitions can improve the ability of ASN to generate and implement new ideas. In addition, creating a flexible work environment and supporting employee initiatives to learn and innovate is an important step. This strategy will ensure that ASN in South Kalimantan are not only able to adapt, but also become creative and innovative agents of change in regional development. 5. Conclusion and Suggestions This study on partial and mediation paths, it can be concluded that "Individual Learning" (X) has a significant influence on "Employee Adaptability" (Z1), "Employee Creativity" (Z2), and "Employee 3207 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 3193-3209, 2024 DOI: 10.55214/25768484.v8i6.2680 © 2024 by the authors; licensee Learning Gate Innovation Behavior" (Y). The T-statistics value for the path "Individual Learning" -> "Employee Adaptability" is 28.474 (P-Values 0.000) and for "Employee Creativity" is 23.861 (P-Values 0.000), indicating a very significant influence (P < 0.05). Meanwhile, the path "Employee Adaptability" -> "Employee Innovation Behavior" is not significant with T-statistics 0.465 and P-Values 0.642. However, "Employee Creativity" has a significant influence on "Employee Innovation Behavior" with a T-statistic value of 7.321 and P-Values of 0.000. In the mediation path, "Individual Learning" mediated by "Employee Creativity" shows a positive and significant influence on "Employee Innovation Behavior" (T-statistics 6.985, P-Values 0.000). In contrast, mediation through "Employee Adaptability" is not significant (T-statistics 0.464, P-Values 0.643). These results emphasize the importance of creativity in encouraging innovation of ASN employees in South Kalimantan. The study revealed that training and development programs for ASN employees in South Kalimantan need to focus on improving "Individual Learning" and "Employee Creativity" to maximize innovation. The government and organizations need to create a work environment that encourages creativity, provides access to learning resources, and provides incentives for employees who actively participate in innovation. Employee adaptability, although important, is not enough to directly encourage innovation. Therefore, an integrative approach that combines creative skills development and change management should be a priority in ASN training and development policies. Future research can further explore other factors that may mediate or moderate the relationship between "Individual Learning" and "Employee Innovation Behavior," such as organizational support, collaborative work climate, or the influence of transformational leadership. In addition, studies involving larger samples and variations in ASN job types can provide a more comprehensive understanding of the influence of work context on creativity and innovation. Further research can also evaluate the effectiveness of creativity-based training programs in various government agencies to identify the most effective strategies in improving employees' innovative abilities in various sectors. 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