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Improving Innovation Capabilities Based AA (Maula Famungka & Budhi Cahyon.
Improving Innovation Capabilities Based on Learning Orientation and Knowledge Sharing Maula Famungka.
& Budhi Cahyono.
Faculty of Economy.
Universitas Islam Sultan Agung (UNISSULA) Semarang.
Indonesia.
Email: maulafamungka.
std@unissula.
Faculty of Economy.
Universitas Islam Sultan Agung (UNISSULA) Semarang.
Indonesia.
Email: budhicahyono@unissula.
Abstract.
This study aims to test the hypothesis regarding the influence of learning orientation and knowledge sharing on innovativeness as an effort to strengthen the underlying theory.
The type of research employed is explanatory research, which emphasizes explaining the relationships between variables through hypothesis Responses were measured using a five-point Likert scale, ranging from 1 .
trongly disagre.
to 5 .
trongly agre.
The population of this study consists of all human resources (HR) at the Office of Supervision and Customs Services of Jenis Madya Pabean Tanjung Emas, totaling 203 employees, including both civil servants and non-civil servants.
From this population, a sample of 135 respondents was selected using a purposive sampling technique with the following criteria: .
being an active employee, either in structural or functional positions.
having worked for at least one year to ensure understanding of organizational culture, learning processes, and knowledge-sharing mechanisms.
being involved or having been involved in innovation activities or unit performance development, either formally or informally.
The results of this study confirm that learning orientation has a positive and significant effect on knowledge sharing.
Learning orientation also has a positive and significant effect on innovation capability.
Furthermore, the findings indicate that knowledge sharing has a positive effect on innovation Keywords: Innovativeness.
Knowledge.
Learning.
Orientation.
Introduction The era of globalization has led to increased competition across all sectors, with technological developments accelerating, resulting in intense business competition in both domestic and global markets.
Therefore, companies and organizations must have the ability to innovate to compete.
(Astrini et al.
, 2.
Innovation is the ability to apply creativity in order to solve problems and opportunities to enrich and improve life.
(Stauffer, 2.
Innovation is an organizational system that has activities for renewal and creativity in creating new services, products, ideas or processes.
(Dupont, 2.
Developing innovation in the workplace begins with developing individual creativity, while new ideas come from Vol.
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motivation, thinking, and implementation by individuals in the workplace.
(Marta Peris-Ortiz et al.
, 2.
Many previous studies on innovation performance have explored the factors that influence innovation performance, but the results remain mixed.
Empirical evidence suggests that learning orientation contributes positively to innovation.
(Gattermann Perin & Hoffmann Sampaio, 2.
Learning orientation has a positive influence on innovation, as stated by(Phorncharoen, 2.
A similar thing was also expressed by(Noerchoidah et al.
which confirms a positive relationship between learning orientation and innovation.
However, according to(Haq et al.
, 2.
Learning orientation does not fully impact innovation if it is not accompanied by adequate competency.
This result is supported by(Palumian et al.
, 2.
which states that learning orientation does not have a significant impact on innovation.
Based on previous research results, a research gap was identified.
Previous research was limited to the direct relationship between learning orientation and innovation.
This study explores the mediating role of the relationship between learning orientation and innovation performance to provide a more detailed picture of how learning orientation impacts innovation performance through the intervening variable of knowledge sharing.
Previous research has tested that knowledge donating and knowledge collecting have a significant influence on innovation capabilities.
(Mulyana et al.
, 2.
Knowledge sharing within the organization has a significant influence on exploitative innovation.
(Chen et al.
The Tanjung Emas Customs and Excise Supervision and Service Office (KPPBC) is required to demonstrate innovative performance, particularly in the implementation of export-import supervision and service duties.
One of the main instruments in supporting this performance is the utilization of the CEISA 4.
0 (Customs-Excise Information System and Automatio.
system, which includes several strategic services such as PIB (Import Notification of Good.
and PEB (Export Notification of Good.
notifications, manifest management, treasury systems, and shipment management.
However, based on field observations and internal data obtained, there remains a gap between the innovation targets and their implementation.
Several issues have emerged, such as frequent technical disruptions in the CEISA 4.
0 system, which cause delays in PIB and PEB data input, slow data integration between the manifest and shipment systems, and suboptimal synchronization with the treasury system in the customs and excise disbursement process.
In response to the limitations of CEISA 4.
0, starting in 2022, the Tanjung Emas Tax Office (KPPBC) introduced the "Gendhis Legi" application, designed to support services not yet covered by CEISA, such as requests for certain manual services, technical consultations, and document clarifications.
Although the application has been gradually implemented and Vol.
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officially launched in 2024, in practice, challenges remain, such as low employee adoption rates, uneven technical understanding of the application's features, and a lack of in-depth training for internal users.
Research Methods This type of research is conducted to test hypotheses with the intention of confirming or strengthening the hypothesis with the hope that it can ultimately strengthen the theory used as a basis.
In relation to the above, the type of research used is "Explanatory research" or research that is explanatory in nature, meaning this research emphasizes the relationship between research variables by testing hypotheses.
The description contains descriptions but the focus lies on the relationship between variables, namely learning orientation, knowledge sharing towards innovativeness.
Data collection conducted: Literature study.
Primary data in this study is the main data while secondary data is as supporting data.
Primary data is obtained through questionnaires, which consist of closed-ended questions and open-ended questions.
The decision to use open-ended or closed-ended questions depends greatly on how far the researcher understands the research problem (Kuncoro.
Open-ended questions are questions that give respondents the freedom to answer questions according to their own way of thinking (Kuncoro, 2.
Closed questions are questions where the answers have been limited by the researcher, thus closing the possibility for respondents to answer at length according to their own way of thinking.
Questionnaire distribution, is a direct data collection carried out by submitting a list of questions to respondents and handing them directly to the respondents.
This questionnaire distribution method is recommended for use because it has the advantage of being able to contact respondents who are difficult to meet, is cheaper, and respondents have time to consider their answers directly (Sekaran, 1992.
Cooper and Emory, 1.
Results and Discussion Respondent Description This study involved 135 employees at the Tanjung Emas Customs and Excise Supervision and Service Office.
The respondents' profiles are presented through statistical data from the questionnaire distribution.
All respondents willingly completed the questionnaire during the fieldwork, resulting in 135 completed questionnaires ready for use in the research data The description of the respondents in this study can be explained in four characteristics, namely based on gender, age, last education and length of service, which are explained .
Gender The characteristics of the respondents in this study can be described based on gender factors as follows:
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Respondent Characteristics Data Table by Gender Gender Frequency Man Woman Total Source: Data processing results, 2025.
Percentage Based on the respondent descriptions in the table, it can be seen that the majority of respondents were men, namely 92 people .
1%), while women numbered 43 people .
9%).
This composition illustrates that employees in the Customs and Excise environment are still dominated by men, which is in line with the characteristics of the work that often requires high mobility, field supervision, and physical endurance.
However, the proportion of women, which reached almost one-third, indicates the important role of women in supporting administration, service, and technical functions.
This balance of gender roles can enrich the variety of perspectives in completing tasks and improve overall organizational .
Age The characteristics of the respondents in this study can be described based on age factors as Respondent Characteristics Data Table by Age Age Frequency 25 - 30 years 31 - 40 years old 41 - 50 years old 51 - 60 years Total Source: Data processing results, 2025.
Percentage In terms of age, the majority of respondents were in the 31Ae40 age range, namely 51 people .
8%), followed by the 41Ae50 age group with 39 people .
9%), 25Ae30 years old with 34 people .
2%), and the remaining 11 people .
1%) aged 51Ae60 years.
This shows that the majority of employees are in the productive age phase, with relatively balanced energy and The dominance of middle age .
Ae40 year.
reflects the stability of a workforce that is already skilled but remains adaptive to change, thus having great potential in driving improvements in organizational performance.
Last education The characteristics of the respondents in this study can be described based on the level of education factor as follows:
Data Table of Respondent Characteristics According to Last Education Education Frequency Diploma Percentage Vol.
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Total Source: Results of data processing, 2025.
The table shows that the majority of employees have a bachelor's degree .
3%), followed by 24 with a master's degree .
8%), and 12 with a diploma .
9%).
The high proportion of bachelor's and master's degree graduates indicates a relatively good quality of human resources, thus supporting analytical skills, regulatory mastery, and innovation in carrying out service and supervisory functions.
This aligns with the demands of work in Customs and Excise, which requires technical and administrative expertise, as well as an understanding of international law and trade.
The higher the employee's education, the greater the opportunity to generate new ideas for improving work processes.
Length of work The characteristics of the respondents in this study can be described based on the length of service factor as follows:
Data Table of Respondent Characteristics According to Length of Service Years of service Frequency 1-10 years 11 - 20 years 21 - 30 years old > 30 years Total Source: Primary Data Processing Results, 2025.
Percentage In terms of length of service, the majority of respondents .
had 11Ae20 years of service .
8%), followed by 39 .
9%) with 21Ae30 years of service, 29 .
5%), and 16 .
9%) with more than 30 years.
This composition illustrates that the majority of employees have considerable experience, thus possessing a deep understanding of organizational procedures and challenges.
The presence of employees with more than 20 years of service is also important for maintaining the continuity of institutional knowledge.
Meanwhile, the presence of new employees with less than 10 years of service provides the potential for renewed ideas and technological adaptation.
This combination of seniority and new generations can increase synergy, although it needs to be managed to avoid gaps in mindset that can affect work effectiveness.
Descriptive analysis was conducted to describe respondents' perceptions of the variables Through this descriptive analysis approach, information was obtained regarding response patterns and respondents' tendencies toward the indicator items used as measuring instruments for the variables in this study.
The results of this analysis allow for the identification of trends and the general distribution of respondents' responses, thus providing a critical initial overview for understanding the characteristics of the variables Vol.
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The data is explained by providing a weighted assessment for each statement in the The respondent response criteria follow the following assessment scale:
Strongly Agree (SS) score 5.
Agree (S) score 4.
Quite Agree (CS) score 3.
Disagree (TS) score 2.
Strongly Disagree (STS) score 1.
Furthermore, from this scale, the data will be categorized into 3 groups.
To determine the score criteria for each group, it can be calculated as follows (Sugiyono, 2.
Highest score Lowest score Range = Highest score Ae lowest score = 5 - 1 = 4 Class interval =Range / number of categories = 4/3 = 1.
Based on the size of the class interval, the criteria for the three categories are: low category, score = 1.
00 Ae 2.
33, medium category, score = 2.
34 Ae 3.
66 and high/good category, with a score of 3.
67 Ae 5.
A complete description of each variable is presented below:
Research Variable Description Table No Variables and indicators Mean Standard Deviation Learning orientation Information Tall commitment to learning, open to new thoughts shared vision Knowledge sharing Sharing voluntarily Tall Tall Tall Tall Tall Communicate with everyone Tall Get all information easily and freely Tall Innovation capabilities emphasizes the ability to apply creativity to solve problems.
generate new ways of working creativity to improve performance.
Tall Tall Tall Tall Based on the data in the table, it can be seen that the overall average learning orientation score is in the high category with an overall mean of around 3.
The highest score is found in the openness to new ideas indicator .
, indicating that employees are relatively receptive to new ideas to support their work.
Meanwhile, the lowest score is found in the shared vision indicator .
, indicating that there is still room to strengthen the alignment of shared goals among employees.
In general, these results reflect that the learning culture is well established, but improving the shared vision aspect will further strengthen collective Vol.
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Knowledge sharing, measured using three indicators, resulted in an overall average score of 89, indicating that knowledge sharing practices in the workplace are progressing quite The indicator with the highest score was communicating with everyone .
indicating that open communication is running relatively smoothly.
Conversely, the indicator with the lowest score was voluntary sharing .
, indicating that some employees are still not fully proactive in sharing their experiences or knowledge.
This indicates that the knowledge sharing culture is strong, but further encouragement is needed to increase personal initiative in sharing knowledge without being asked.
Innovation capability was measured through three indicators, with an overall average of 94, the highest score compared to other variables.
The indicator with the highest mean was creativity for improving performance .
, confirming that employees have a strong orientation to innovate to increase work effectiveness.
The lowest score was for the indicator generating new work methods .
, although the difference was relatively small.
Overall, these findings indicate that employees' innovative capabilities are quite good, especially in the context of improving performance, although the development of new work methods still needs to be further improved.
Overall, all three variables showed a mean value above 3.
67, indicating they fall within the high/good criteria.
This indicates that respondents highly value learning orientation, knowledge sharing, and innovation capability.
The innovation capability variable ranked highest, indicating that employees tend to prioritize creativity to improve performance compared to knowledge sharing and learning orientation.
However, the lowest indicators for shared vision and voluntary sharing initiatives indicate the need for managerial intervention to strengthen a culture of collaboration and shared goals.
Structural Model Evaluation (Inner Mode.
The final analysis in PLS is the structural model analysis, or inner model.
In structural model analysis, hypotheses can be tested using t-statistics.
The test results can be seen from the structural model output, which examines the significance of the loading factors, which explain the influence of the Learning Orientation construct on Innovation Capability through the mediation of Knowledge Sharing as an intervening variable.
In this case, data processing was performed using SmartPLS v4.
0 software.
The results of this data processing are shown in the following image:
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SEM-PLS Inner Model Image Source: Results of data processing with Smart PLS 4.
Direct Influence Analysis This section presents the results of the research hypothesis testing conducted in the previous chapter.
To determine whether the hypothesis is accepted or not, you can compare the calculated t-value with the t-table, assuming that the calculated t-value is greater than the t-table.
The t-table value for a 5% significance level is 1.
The following table shows the results of the test of influence between variables using Partial Least Squares Path Coefficients Table Original sample (O) Sample mean (M) Standard
(STDEV)
Knowledge sharing -> 0.
Innovation capability Learning Orientation -> 0.
Innovation Capability Learning Orientation -> 0.
Knowledge sharing Source: Results of data processing with Smart PLS 4.
(|O/STDEV|)
P values 4,309 2,790 8,653 By presenting the results of the data processing, testing can then be carried out for each research hypothesis, namely:
Hypothesis Testing 1 H1: The better the learning orientation, the better the knowledge sharing.
In testing hypothesis 1, the original sample estimate value was obtained at 0.
This value proves that learning orientation has a positive effect on knowledge sharing.
This result is Vol.
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even more convincing because the calculated t value of 8.
653 is greater than the t table value of 1.
96, with a p value of 0.
000 <0.
This means that the learning orientation possessed by employees is able to encourage the formation of stronger knowledge sharing.
Thus, the first hypothesis which states that "The better the learning orientation, the better the knowledge sharing.
" can be accepted.
Hypothesis Testing 2 H2: The better the learning orientation, the better the innovation capability.
In testing hypothesis 2, the original sample estimate value was obtained at 0.
This value indicates that learning orientation has a positive effect on innovation capability.
This result is also supported by the t-test value obtained at 2.
790, greater than the t-table value of 96, and a significance value of p of 0.
005 <0.
Thus, it can be said that there is a positive and significant influence of learning orientation on innovation capability.
Therefore, the first hypothesis stating that "The better the learning orientation, the better the innovation " can be accepted.
Hypothesis Testing 3 H3: The higher a person's knowledge sharing, the higher their innovation capability.
In testing hypothesis 3, the original sample estimate value was obtained at 0.
This value indicates that knowledge sharing has a positive effect on innovation capability.
This is supported by the calculated t value of 4.
309, which is greater than the t table of 1.
96, and the p value of 0.
000 <0.
These results prove that the higher the knowledge sharing, the better the employee's innovation capability.
Thus, the third hypothesis stating that "The higher a person's knowledge sharing, the higher their innovation capability" can be .
Analysis of the Indirect Effect of Learning Orientation on Innovation Capability through Knowledge Sharing Mediation The indirect effect test was conducted to determine the influence of an exogenous variable (Learning Orientatio.
on an endogenous variable (Innovation Capabilit.
through an intervening variable, namely Knowledge Sharing.
The indirect effect of Learning Orientation on Innovation Capability through the mediation of Knowledge Sharing is depicted in the following path diagram:
Learning Innovation Knowledge Vol.
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Figure of the Path Coefficient of the Influence of Learning Orientation on Innovation Capability through Knowledge Sharing Information :
: Direct influence : Indirect influence The results of the indirect influence test from the calculation results with smartPLS can be presented in the following table.
Indirect Effect Test Results Table Original sample (O) Sample mean
(M)
Standard
(STDEV)
Learning Orientation -> 0.
Knowledge sharing -> Innovation capability Source: Results of data processing with Smart PLS 4.
(|O/STDEV|)
P values 3,390 The mediating effect of Knowledge sharing in relation to the variable of Learning Orientation on Innovation Capability is known to be 0.
The results of the indirect effect test produced a t-test of 3.
>1.
with p = 0.
001 < 0.
The conclusion of the test is that Knowledge sharing mediates the effect of Learning Orientation on Innovation Capability.
The results of this study confirm that a learning orientation fosters an open attitude toward learning, curiosity, and a willingness to accept feedback.
This process enhances knowledge sharing, which accelerates idea accumulation, enriches the organization's knowledge base, and enables recombinationAithe merging of old ideas into new solutions.
This further strengthens innovation capabilities because collective knowledge enables idea generation, teams more quickly find creative solutions, and achieve purposeful goals.
Discussion By presenting the results of the data processing, testing can then be carried out for each research hypothesis, namely:
Learning orientation towards knowledge sharing Vol.
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This study proves that learning orientation has a positive and significant effect on knowledge sharing.
This means that employees' learning orientation can encourage stronger knowledge sharing.
Previous research has shown that learning orientation has a significant influence on knowledge sharing practices (Shah et al.
, 2.
The measurement of the learning orientation variable in this study was measured by reflecting on three indicators:
Commitment to learning.
Openness to new ideas, and Shared vision.
These three aspects have been shown to have a significant contribution to knowledge sharing, which in this study was measured by three indicators: Sharing voluntarily.
Communicating with everyone, and Obtaining all information easily and freely.
The measurement results show that for the Learning Orientation variable, the indicator with the highest outer loading value is Openness to new ideas.
Meanwhile, for the Knowledge Sharing variable, the indicator with the highest outer loading value is Communicating with These findings indicate that the higher an individual's or organization's openness to new ideas, the better their ability to communicate with various parties.
This means that a culture of openness to new ideas, concepts, and insights will encourage broader and higherquality interactions, thus facilitating the process of knowledge exchange in the workplace.
This shows that innovation and communication are mutually reinforcing, with openness being the foundation for effective communication in supporting collaborative learning.
On the other hand, the measurement results also show that the indicator with the lowest outer loading value in the Learning Orientation variable is Commitment to Learning, while in the Knowledge Sharing variable is Voluntary Sharing.
This reflects that the higher an individual's commitment to consistent learning, the greater their tendency to voluntarily share knowledge with others.
This means that a strong enthusiasm for learning is not only beneficial for self-development but also encourages the growth of a proactive attitude in sharing knowledge without coercion.
Thus, increased commitment to learning will have a direct impact on strengthening a culture of knowledge sharing based on shared awareness and responsibility.
Learning orientation towards innovation capabilities.
This study demonstrates that learning orientation has a positive and significant impact on innovation capability.
This means that employees' learning orientation can foster stronger innovation capability.
Research by (Yoon & Jong Gyu Park, 2.
emphasizes that learning orientation can build trust and collaboration, which are essential elements in knowledge Measurement of variablesLearning orientation in this study was measured from the reflection of three indicators.
namely indicatorsCommitment to learning, openness to new ideas, and shared vision.
These three aspects have been shown to significantly contribute to innovation capability in this study, as measured by reflection on three indicators.
indicatorsEmphasizes the ability to apply creativity to solve problems.
generate new ways of working, and creativity to improve performance.
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The results of the study show that for the Learning Orientation variable, the indicator with the highest outer loading value is openness to new ideas.
Meanwhile, for the Innovation Capability variable, the indicator with the highest value is generating new ways of working.
These findings indicate that the greater the openness of individuals and organizations to new ideas or thinking, the greater the ability to create innovative ways of working.
This means that openness to fresh ideas is an important foundation in encouraging the birth of new, more effective work methods or procedures.
In other words, organizations that develop an open learning culture and are adaptive to change will more easily produce relevant and applicable work innovations.
On the other hand, the indicator with the lowest outer loading value in the Learning Orientation variable is commitment to learning, while the Innovation Capability variable emphasizes the ability to apply creativity to problem-solving.
These results reflect that a low commitment to learning will impact the weak ability to apply creativity to solve problems.
This means that the higher the commitment of individuals and organizations to undergoing a continuous learning process, the stronger their ability to utilize creativity as a solution to various challenges faced.
Thus, building a consistent commitment to learning is a prerequisite for improving problem-solving skills based on creative thinking.
Knowledge sharingtowards its innovation capabilities.
This study shows that knowledge sharing has a positive effect on innovation capability.
These results demonstrate that higher knowledge sharing, higher employee innovation Several other researchers have also confirmed the findings of studies related to learning orientation and innovativeness (Eljasik-Swoboda et al.
, 2019.
Gattermann Perin & Hoffmann Sampaio, 2.
Measurement of Knowledge Sharing Variables in this study it was measured from three indicatorsnamely indicatorsShare voluntarily.
Communicate with everyone, and Get all information easily and freely.
These three aspects have been proven to have a significant contribution to innovation capability in this study, as measured by the reflection of three namely indicatorsEmphasizes the ability to apply creativity to solve problems.
generate new ways of working, and creativity to improve performance.
The measurement results show that for the knowledge sharing variable, the indicator with the highest outer loading value is communicating with everyone, while for the innovation capability variable, the highest indicator is generating new ways of working.
These findings indicate that the better an individual's and group's ability to communicate openly with all parties, the greater the organization's opportunity to create new, more effective ways of This means that broad, open communication, not limited to specific groups, will encourage a more diverse exchange of ideas, thus giving rise to innovations in the form of work methods or procedures that are more efficient and adaptive to change.
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Meanwhile, the indicator with the lowest outer loading value for the knowledge sharing variable is voluntary sharing, and for the innovation capability variable, it emphasizes the ability to apply creativity to problem-solving.
These results indicate that the higher an individual's willingness to share knowledge voluntarily, the better the organization's ability to emphasize the application of creativity to solve problems.
This means that when a culture of sharing information, experiences, and skills is carried out without coercion, the knowledge transfer process will be more natural and productive.
This condition will enrich the base of creative ideas that can be utilized by the organization to find innovative solutions to the challenges faced, while strengthening long-term competitiveness.
Conclusion The purpose of this study is to empirically analyze and describe the influence of learning orientation and knowledge sharing on innovation capability.
Based on the discussion of the research results, the answers to the research questions are as follows: The results of this study confirm that learning orientation has a positive and significant influence on knowledge sharing.
This finding indicates that a commitment to continuous learning, openness to new ideas, and a shared vision among employees can strengthen knowledge sharing practices within an organization.
Thus, the stronger the learning orientation of employees, the stronger the knowledge sharing culture that is built.
This study proves that learning orientation has a positive and significant influence on innovation capability.
This means that when employees have a strong learning orientation, it will encourage an increase in the ability to apply creativity to solve problems, generate new ways of working, and develop creative ideas that contribute to improving overall organizational performance.
The results of the study indicate that knowledge sharing has a positive influence on innovation capability.
This means that the higher the willingness of employees to share knowledge voluntarily, the better their ability to communicate with various parties, and the easier access to information, the greater the potential for employees to improve innovation In other words, optimal knowledge sharing practices will be a catalyst for the creation of sustainable innovation in the workplace.
Mediation research findings indicate that a learning orientation fosters openness, curiosity, and a willingness to accept feedback, thus strengthening the knowledge sharing process.
This environment accelerates idea generation, enriches organizational knowledge, and enables the integration of existing knowledge into new solutions.
Ultimately, this accumulation and exchange of knowledge enhances innovation capabilities because teams are able to generate creative ideas, find solutions more quickly, and achieve goals more effectively.
References