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Abstract

In the evolving landscape of higher education, identifying key drivers of organizational performance is crucial. This study investigates the impact of intellectual capital on knowledge management and innovation and how these factors collectively enhance organizational performance. Conducted among top leaders at 21 state universities in Indonesia, this quantitative research used structured questionnaires validated by prior studies. The high response rate strengthens the reliability of findings analyzed using SPSS for descriptive statistics and Structural Equation Modeling (SEM) with SmartPLS 3.0 for hypothesis testing. The results indicate intellectual capital significantly influences knowledge management and innovation, which in turn positively affect organizational performance. Intellectual capital enhances both knowledge management and organizational performance, while effective knowledge management fosters innovation, further contributing to improved performance. The novelty of this research lies in its comprehensive integration of intellectual capital, knowledge management, and innovation within the context of higher education, providing empirical evidence of their interconnectedness and collective impact on organizational performance, which has been largely unexplored in previous studies. This study’s practical implications encourage strategic investments in intellectual capital and knowledge management, ultimately contributing to improved organizational performance and providing valuable insights for policy and decision-making in the higher education sector.

Keywords

Intellectual capital knowledge management innovation organizational performance performance enhancement strategic management O31 O32 M12 M14 O16 O33

Introduction

Managing an organization today is an incredibly intricate task due to the highly uncertain and constantly evolving environment in which organizations operate.¹ This complex landscape requires innovative methods of managing human capital and equipping them to handle the daily challenges and problems they encounter.² To navigate these dynamics effectively, organizations need to adopt a collaborative and inclusive approach to decision-making and human resource management. Developing a responsive and adaptive work culture is essential for bolstering organizational competitiveness amidst growing challenges.³ Thus, it is critical for an organization to focus on its performance.

Organizational performance reflects an organization’s ability to meet stakeholder needs and succeed within its environment, showcasing the outcomes of actions or activities undertaken by its members to gauge the extent to which organizational goals have been achieved.⁴ The increasing competition, need for effective and efficient performance, cost control, and productivity have made the evaluation of higher education institutions a significant issue.⁵ Evaluating organizational performance involves assessing outcomes based on the organization’s vision, goals, and developmental standards.⁶ In higher education, performance indicators are often used for evaluation purposes. For economic assessments in educational institutions, performance indicators prove to be more beneficial than conventional techniques.⁷ A basic conceptual framework views a university as a process transforming input into output, positioning it within a broader economic and social process.⁸

Intellectual capital comprises intangible assets that enable an organization to convert its material, financial, and human resources into competitive advantages.⁹ It is a vital driver of organizational performance and competitive advantage, allowing organizations to create, innovate, and adapt to changing market conditions. Intellectual capital has been shown to contribute to improved financial performance, market value, and competitive advantage. Effective management and utilization of intellectual capital are critical for an organization’s long-term success.¹⁰ Intellectual capital includes the collective knowledge possessed by all members of an organization, providing a competitive edge. This encompasses intellectual material, knowledge, information, intellectual property, and experience that can be utilized to generate wealth.¹¹ Previous research¹² highlight intellectual capital as one of the most crucial resources for organizational performance, influencing innovation and overall success. The concept of intellectual capital is regarded as an unseen yet valuable asset and a powerful competitive weapon impacting innovation performance.¹³

Innovation is a multi-dimensional concept encompassing various aspects of creativity, entrepreneurship, and technological advancement. It involves the development of new products, services, processes, or business models that create value for society. Innovation can be classified into various types, such as incremental innovation, radical innovation, and disruptive innovation, each with its characteristics and market impact. Innovation is essential for achieving superior performance.^14,15 Numerous studies have demonstrated the relationship between organizational innovation and performance, with innovation being crucial for sustainable success and economic growth.^16–19

Knowledge management is a strategic approach aimed at discovering, capturing, sharing, and applying knowledge within an organization to create structures capable of retaining, generating, and utilizing knowledge. This approach supports problem-solving and aids in achieving organizational goals.²⁰ Knowledge management involves identifying, organizing, storing, and disseminating information within an organization.²¹ It is supported by a knowledge base that provides a centralized location to store and easily access information. Enhancing knowledge management increases value creation within the organization, leading to improvements in the business model. Similarly, intellectual capital is a fundamental factor for value creation as it mirrors the evolution of business practices in new business models.²²

Previous research²³ argue that innovation also has the potential to generate economic value for organizations. Innovation as the creation of new opportunities for added value.²⁴ Transformational leadership is considered one of the most influential predictors that directly and indirectly affect innovation capability.^25,26 Leadership and leadership behavior are pivotal in fostering innovation capability.¹⁹ By nurturing a culture of innovation and supporting knowledge management practices, organizations can enhance their capacity to innovate and improve overall performance.

Universities, as organizations, face various challenges due to global competition, rapid changes in educational technology, and increased pressure regarding cost control and financing.²⁷ Indonesian state universities also lag significantly compared to their global counterparts. The disparity between national and global rankings reflects a significant challenge for Indonesian state universities in achieving international excellence standards. This issue is not only a challenge for Universitas Indonesia but also for all state universities in Indonesia. In the context of global competition in higher education, achieving higher global rankings has become an urgent necessity. To address this challenge, a comprehensive approach is required, and improving organizational performance becomes a strategic key. By implementing positive changes at the organizational level, Indonesian state universities can establish a strong foundation to achieve better global rankings, enhance competitiveness, and elevate Indonesia’s standing in international higher education. Organizational performance is regarded as the organizational capacity to access and manage various resources to achieve its goals and objectives.²⁸ Therefore, identifying and addressing relevant factors to improve organizational performance is crucial.

The novelty of this research lies in its comprehensive integration of intellectual capital, knowledge management, and innovation within the context of higher education, providing empirical evidence of their interconnectedness and collective impact on organizational performance, which has been largely unexplored in previous studies. This study’s practical implications encourage strategic investments in intellectual capital and knowledge management, ultimately contributing to improved organizational performance and providing valuable insights for policy and decision-making in the higher education sector.

Furthermore, the research questions (RQs) of this study are designed to reflect and also align with the hypotheses being tested, ensuring a comprehensive examination of the interconnectedness between intellectual capital, knowledge management, innovation, and organizational performance within universities.

(1) RQ1: How does intellectual capital impact knowledge management practices within universities?

(2) RQ2: In what ways does intellectual capital influence innovation in higher education institutions?

(3) RQ3: What is the relationship between intellectual capital and organizational performance in the context of universities?

(4) RQ4: How does effective knowledge management foster innovation within universities?

(5) RQ5: What role does knowledge management play in enhancing the organizational performance of higher education institutions?

(6) RQ6: How does innovation contribute to the overall organizational performance of universities?

Theoretical foundation and hypotheses formulation

Knowledge-based view as a strategies for competitive advantage in higher education

In the context of universities, the Knowledge-Based View (KBV) theory emphasizes that knowledge is a critical asset for creating new value, diversification, and competitive advantage.^29–31 Previous research³² asserts that knowledge is the only resource capable of providing a sustainable competitive advantage. Researchers³³ highlight that intangible factors like management capabilities, technical expertise, and organizational routines are crucial in determining university performance. In dynamic environments, knowledge-based resources are often more influential on performance than physical resources.³⁴

The knowledge management process, involving the identification, acquisition, storage, and dissemination of both tacit and explicit knowledge, is vital.³⁵ Emphasizing knowledge management in universities reflects top management’s support for knowledge creation activities, reinforcing the importance of these initiatives. It also enhances organizational members’ awareness of academic initiatives and supports IT strategies and projects reliant on intellectual resources.³⁶

Organizational performance in the university’s context is a complex and multifaceted concept, defined in various ways, including financial terms like revenue and expenditures, and non-financial terms such as efficiency, effectiveness, and the quality of education and services.³⁷ Another research³⁸ notes that without objective data, measuring university performance is challenging, but it can be approximated through staff and student perceptions of effectiveness, efficiency, job satisfaction, turnover, and loyalty.³⁹ A comprehensive understanding of university performance involves considering both financial and non-financial aspects, measured through various indicators, including staff and student perceptions.

Organizational performance encompasses financial, social, environmental, and global dimensions, which are interconnected and mutually influential. The concept of performance is future-oriented and tailored to reflect each university’s unique characteristics, making it subjective and context-dependent.⁴⁰ Understanding the internal and external factors that influence university performance, such as leadership, staff and student motivation, and academic culture, is crucial for universities striving to improve their performance and achieve their goals in a rapidly evolving global environment.

Intellectual capital in the university context

Intellectual capital is a set of intangible assets that enable an organization to transform its material, financial, and human resources into competitive advantages.⁹ In the context of universities, research findings^22,41 suggest that intellectual capital significantly influences aspects related to knowledge management. The influence of intellectual capital on knowledge management, which is a crucial aspect of handling organizational knowledge within academic institutions.⁴¹ Similarly, another research²² demonstrate that intellectual capital also affects knowledge management in universities. These findings collectively indicate that intellectual capital has the potential to influence knowledge management practices within academic settings. Consequently, there are strong theoretical reasons to believe that intellectual capital significantly impacts knowledge management in universities. Investigating the relationship between intellectual capital and knowledge management will provide a deeper understanding of how intellectual capital affects the management of knowledge within universities.

Moreover, studies by^42,43 have established that intellectual capital is a primary driver of innovation in academic institutions. The effective utilization of intellectual capital can inspire and facilitate innovation processes by optimizing the knowledge, skills, and experience of individuals within the university.⁴² Another research also emphasizes the significant positive correlation between intellectual capital and the level of innovation and value creation within university contexts.⁴³ These findings underscore the crucial role of intellectual capital in promoting innovation and enhancing a university’s ability to adapt and develop. Hence, the hypothesis that intellectual capital positively influences innovation is supported by these research findings.

On the other hand, the previous research results⁴⁴ indicate that intellectual capital does not have a significant effect on university performance. In contrast, another research⁴⁵ found that components of intellectual capital, such as human capital and organizational capital, significantly and positively influence university performance. These differing results suggest that the impact of intellectual capital on organizational performance may vary. Therefore, this research aims to empirically test the positive and significant influence of intellectual capital on university performance, drawing from these varied findings. Based on the discussed findings, the following hypotheses will be tested:

Intellectual capital positively affects knowledge management.

Intellectual capital positively affects innovation.

Intellectual capital positively affects organizational performance in universities.

Knowledge management in university context

Knowledge Management (KM) is the practice of creating value by leveraging intangible assets.⁴⁶ In the context of universities, its primary goal is to efficiently maintain and transfer crucial knowledge to faculty, staff, and students.⁴⁷ According to previous research,⁴⁸ KM functions within a university encompass intermediation, externalization, internalization, cognition, and measurement. Essentially, KM is the process of creating, sharing, using, and managing an institution’s knowledge and information to achieve its academic and operational goals. This comprehensive process involves identifying, acquiring, organizing, storing, retrieving, sharing, and utilizing knowledge and information.⁴⁹ Despite its benefits, KM faces several challenges, such as the need for a supportive environment that promotes KM at all university levels, fostering creative, critical-thinking, independent, and lifelong learners. As a result, KM is a multifaceted concept playing a vital role in stimulating educational improvement, technological progress, and economic growth. Understanding KM requires recognizing its various types, the challenges encountered, and the environments that nurture its development.

Previous research^50,51 lays a strong theoretical foundation for exploring the relationship between KM and university performance (UP). Previous research⁵⁰ conducted a systematic literature review across various academic institutions and locations, revealing a consistently positive and significant relationship between KM and UP. Similarly, another research⁵¹ conducted empirical studies analyzing the impact of different KM practices on university performance, finding that KM positively influences university performance. This underscores the importance of KM in enhancing university performance across different contexts and sectors. However, previous research⁵⁰ also highlight limitations in the existing literature, particularly regarding the diversity of research contexts and locations. Thus, further research is necessary to reinforce previous findings and deepen the understanding of how KM impacts university performance in diverse contexts.

KBV theory also provides a framework for studying the impact of KM on innovation within universities. KBV posits that knowledge is a critical resource that can grant universities a competitive advantage. Effective KM, which involves identifying, managing, and leveraging institutional knowledge, is crucial for fostering academic and administrative innovation. By creating an environment conducive to idea exchange, collaboration, and the application of new knowledge, KM drives innovation. Previous studies^52,53 found that KM positively impacts innovation, while another research⁵⁴ confirms that KM significantly enhances innovation. These findings collectively indicate that improvements in KM can positively influence a university’s innovation levels. Based on these findings, the following hypotheses are proposed:

knowledge management positively affects innovation.

knowledge management positively affects organizational performance in universities.

Innovation in university context

Previous research⁵⁵ shows that innovation intensity has a positive effect on university performance. These findings provide a theoretical basis for proposing the hypothesis that innovation has a significant and positive effect on university performance. The results of this study show the importance of innovation in improving university performance, which directly supports the proposed hypothesis. In addition, another research⁵⁶ also found that innovation contributes positively to university performance. These findings indicate that innovation plays an important role in improving university performance. Thus, the results of this study provide additional support for the hypothesis that innovation has a positive effect on university performance.

On the other hand, another research⁵⁷ found that a data-driven culture in universities has a significant moderating impact on academic innovation and process improvement, which in turn improves overall university performance. These results provide additional support for the hypothesis that innovation has a positive effect on university performance. Therefore, this research aims to strengthen previous findings and expand understanding of the relationship between innovation and university performance by directly testing the hypothesis that innovation has a significant and positive effect on university performance. So the following hypothesis is suggested:

innovation positively affects organizational performance in universities.

Based on references from the literature and hypotheses created after analyzing the latest literature, a research framework has been proposed as depicted in Figure 1.

Figure 1.

Research model hypothesis.

Methodology

Research design

This research employs a quantitative approach to measure the impact of intellectual capital, knowledge management, and innovation on organizational performance. A thorough literature review was conducted to design a questionnaire that accurately captures these variables. The questionnaire uses a five-point likert scale to measure respondents’ perceptions and attitudes. Structural Equation Modeling (SEM) analysis was utilized to test the hypotheses, given its ability to assess complex relationships between multiple variables simultaneously.⁵⁸ The SEM approach allows for a comprehensive analysis of the direct and indirect effects of intellectual capital, knowledge management, and innovation on organizational performance, providing robust and reliable results.⁵⁹

Participants of the research

The population of this study consists of top-level leaders at 21 state universities in Indonesia, chosen due to their strategic roles and decision-making capabilities. A total of 150 respondents were targeted, ensuring a representative sample size. Of these, 137 respondents provided complete responses, resulting in a response rate of 91.3%. This high response rate enhances the validity and reliability of the study findings.⁶⁰ The sampling technique employed was purposive sampling, aiming to select individuals who are most knowledgeable about the topics under investigation. Data were analyzed using SPSS software for descriptive analysis to profile the respondents and Structural Equation Modeling (SEM) with SmartPLS 3.0 for hypothesis testing.⁶¹ This dual approach ensures that the data are not only accurately described but also rigorously tested for causal relationships.

Research instruments and variable measurements

The data for this study were obtained through structured questionnaires designed based on established scales and validated in prior research.⁶² The questionnaire covered five variables: intellectual capital, knowledge management, innovation, and organizational performance, each with multiple indicators.

(1) Intellectual Capital: The indicators for human, structural, and relational capital were drawn from previous research,^63,64 who have extensively validated these measures in various organizational contexts. These components comprehensively capture the essence of intellectual capital by encompassing the knowledge, systems, and relationships crucial for effective organizational functioning.

(2) Knowledge Management: The indicators for knowledge acquisition, dissemination, and utilization were based on the framework proposed by previous research,⁶⁵ which is widely recognized for its robust application in knowledge management research. These indicators are pivotal in understanding how knowledge processes are managed and leveraged within organizations.

(3) Innovation: The measures for administrative, product, and process innovation were adapted from several previous research,^56,66 whose work provides a comprehensive approach to assessing innovation in organizational settings. These indicators ensure that all aspects of innovation, from internal administrative changes to external product and process developments, are considered.

(4) Organizational Performance: The indicators for faculty work utilization, external engagement, global partnership collaboration, and internationally accredited programs were adapted from IKU PTN Kemendikbud and previous research.⁶⁷ These indicators were selected because they provide a holistic view of performance metrics relevant to higher education institutions, encompassing both internal efficiencies and external collaborations.

The metrics and measurements used for the variables in this study are detailed in Table 1, providing a comprehensive overview of how each variable was operationalized and assessed.

Table 1.

Variable metrics and measurements.

Research variable	Indicator	Item	Source
Intellectual capital (X1)	Human capital (X1.1)	1) Faculty and staff have relevant experience to successfully fulfill their job responsibilities within the university (X1.1.1).	63,64
		2) Faculty and staff in this university are highly skilled in their respective work areas and functions (X1.1.2).
		3) The university provides well-designed training to enhance faculty and staff skills (X1.1.3).
		4) Faculty and staff in the university frequently generate useful new ideas and insights (X1.1.4).
		5) Faculty and staff in this university are creative in finding solutions to academic and administrative challenges (X1.1.5).
	Structural capital (X1.2)	1) The operational procedures in this university are efficient enough to support daily activities (X1.2.1).
		2) The university is capable of adapting to changes in the academic and administrative environment (X1.2.2).
		3) The information needed by faculty and staff is available and easily accessible (X1.2.3).
		4) The university’s systems and procedures support the development of ideas and innovation (X1.2.4).
		5) The organizational culture of the university is open and encourages creativity among faculty and staff (X1.2.5).
		6) The university invests in developing opportunities in new academic fields and markets (X1.2.6).
		7) There is good cooperation between departments within the university (X1.2.7).
	Relational capital (X1.3)	1) The university identifies and resolves issues through intensive communication and effective cooperation among relevant departments (X1.3.1).
		2) The university consistently maintains good interactions with all stakeholders, including students, alumni, and the community (X1.3.2).
		3) The university is capable of establishing and maintaining long-term positive relationships with students and other stakeholders (X1.3.3).
		4) The university has many highly competent and reliable academic and administrative partners (X1.3.4).
		5) The university has established long-term strategic partnerships that are mutually beneficial with various academic and industry partners (X1.3.5).
Knowledge management (Y1)	Knowledge acquisition (Y1.1)	1) The university recruits new faculty and staff as a source to acquire new knowledge (Y1.1.1).	65
		2) The university creates an open environment for faculty and staff to gain new knowledge (Y1.1.2).
		3) The university actively observes and adopts best practices in the higher education sector (Y1.1.3).
		4) The university continuously gathers information relevant to its academic and administrative operations (Y1.1.4).
		5) The university documents and defines the knowledge it possesses, as well as knowledge that is unavailable (Y1.1.5).
		6) The university acquires knowledge from various sources: Students, academic partners, and industry collaborations (Y1.1.6).
	Knowledge dissemination (Y1.2)	1) The university shares information and knowledge necessary to complete academic and administrative tasks (Y1.2.1).
		2) The university exchanges knowledge among faculty and staff to achieve its goals with minimal time and effort (Y1.2.2).
		3) The university develops information systems, such as intranets and electronic bulletin boards, to share information and knowledge (Y1.2.3).
		4) The university promotes the sharing of information and knowledge between team members and various departments (Y1.2.4).
		5) Knowledge is shared between administrators, faculty, and students (Y1.2.5).
	Knowledge utilization (Y1.3)	1) The university has methods to critically analyze and evaluate knowledge, generating patterns and new knowledge for future use (Y1.3.1).
		2) The university applies knowledge to meet critical competitive needs (Y1.3.2).
		3) The university has mechanisms to protect knowledge from inappropriate or illegal use both inside and outside the institution (Y1.3.3).
		4) The university has various methods to further develop knowledge and apply it to new academic and administrative situations (Y1.3.4).
		5) The university has mechanisms to filter, cross-map, and integrate various sources and types of knowledge (Y1.3.5).
Innovation (Y2)	Administrative innovation (Y2.1)	1) The university implements new structures or improves existing ones such as project teams, departments, or inter-departmental structures (Y2.1.1).	56,66
		2) Faculty and staff are able to try new ways of working while still adhering to university procedures (Y2.1.2).
		3) When the university changes administrative procedures, faculty and staff need time to adapt (Y2.1.3).
		4) The university encourages faculty and staff to collaborate with each other (team collaboration or sharing best practices) when necessary to be more effective in handling new administrative issues (Y2.1.4).
	Product innovation (Y2.2)	1) The university consistently emphasizes development and innovation (Y2.2.1).
		2) The university frequently updates the materials and methods used in faculty and staff training (Y2.2.2).
		3) The university continually strives to develop new programs or services for students, faculty, and staff (Y2.2.3).
	Process innovation (Y2.3)	1) The university endeavors to develop new technologies to enhance internal processes (Y2.3.1).
		2) The university uses the latest techniques/inputs in academic and administrative activities (Y2.3.2).
		3) The university acquires the latest machinery or equipment to support daily operations and work procedures (Y2.3.3).
Organizational performance (Y3)	Faculty work utilization and recognition (Y3.1)	1) The number of research projects that produce solutions or innovations applied by the community (Y3.1.1).	IKU PTN Kemendikbud & 67
		2) The level of faculty participation in community development activities or service projects (Y3.1.2).
		3) The number of international awards or recognitions received by faculty work (Y3.1.3).
	Faculty external engagement (Y3.2)	1) The number of scientific articles or conference presentations produced by faculty outside the campus (Y3.2.1).
		2) The percentage of faculty involved in joint research projects with institutions or industries outside the campus (Y3.2.2).
		3) The number of faculty collaborations with international educational or research institutions (Y3.2.3).
	Global partnership collaboration (Y3.3)	1) The percentage of students involved in international exchanges or dual programs with partner universities (Y3.3.1).
		2) The number of study programs that have formal cooperation agreements with universities or institutions abroad (Y3.3.2).
		3) Student evaluations related to the benefits and quality of the experience in international cooperation programs (Y3.3.3).
	Internationally accredited programs (Y3.4)	1) The percentage of faculty with experience studying or teaching abroad (Y3.4.1).
		2) The number of courses that are internationally recognized and can be accredited by global educational institutions (Y3.4.2).
		3) The level of student participation in international exchange programs or global academic activities (Y3.4.3).

In this study, all variables was treated as a second-order construct. For example, Intellectual Capital (IC) composed of three first-order sub-variables: Human Capital, Structural Capital, and Relational Capital. The results for these sub-variables were aggregated to reflect their contribution to the overall Intellectual Capital construct using a second-order confirmatory factor analysis (CFA). This approach allows us to capture the relationship between the sub-variables and the overarching construct of Intellectual Capital.

To ensure that the three sub-variables properly represent the second-order variable, we employed a reflective-reflective model. For example, the sub-variables reflect Intellectual Capital, and each sub-variable was measured through its respective items. This method helps us statistically validate how well Human, Structural, and Relational Capital contribute to Intellectual Capital as a whole. Through this, the significant influence of Intellectual Capital on other variables in the study can be understood as the combined effect of its sub-components. This hierarchical structure allows for a more nuanced understanding of how each element of Intellectual Capital impacts outcomes like Knowledge Management and Organizational Performance.

The questionnaires were distributed electronically to ensure a high response rate and to facilitate easier data collection. Electronic distribution also allowed for efficient tracking and follow-up with respondents to maximize participation.⁶⁸ Participants were assured of the confidentiality and anonymity of their responses to encourage honest and accurate answers. The electronic format ensured accessibility and convenience for respondents, allowing them to complete the survey at their convenience. This method also enabled the researchers to collect data quickly and efficiently, ensuring timely analysis and reporting.

Results

Validity and reliability testing

To ensure the validity and reliability of the research instruments, a pilot test was conducted with a small sample of respondents. This initial testing helped identify any ambiguities or issues with the questionnaire items, allowing for necessary revisions before full deployment.⁶⁹ The Cronbach’s Alpha coefficient was calculated to assess the internal consistency of the questionnaire items, with values above 0.7 indicating acceptable reliability.⁷⁰ Additionally, Exploratory Factor Analysis (EFA) was performed to verify the construct validity of the variables, ensuring that each set of items measured the intended construct accurately.⁷¹

Based on Table 2, Intellectual Capital (X1), Knowledge Management (Y1), Innovation (Y2), and Organizational Performance (Y3) are measured using specific items that demonstrate strong reliability and validity.

Table 2.

Cronbach’s alpha, composite reliability and AVE.

Variables	Indicators (Outer loading value)	Item (Outer loading value)	Cronbach’s alpha	Composite reliability	Average variance extracted (AVE)
X1	X1.1 (0.709)	X1.1.1 (0.712)	0.634	0.803	0.577
		X1.1.2 (0.708)
		X1.1.3 (0.698)
		X1.1.4 (0.701)
		X1.1.5 (0.701)
	X1.2 (0.828)	X1.2.1 (0.808)
		X1.2.2 (0.820)
		X1.2.3 (0.827)
		X1.2.4 (0.819)
		X1.2.5 (0.819)
		X1.2.6 (0.820)
		X1.2.7 (0.821)
	X1.3 (0.737)	X1.3.1 (0.735)
		X1.3.2 (0.735)
		X1.3.3 (0.730)
		X1.3.4 (0.734)
		X1.3.5 (0.736)
Y1	Y1.1 (0.949)	Y1.1.1 (0.947)	0.907	0.943	0.846
		Y1.1.2 (0.947)
		Y1.1.3 (0.939)
		Y1.1.4 (0.942)
		Y1.1.5 (0.948)
		Y1.1.6 (0.948)
	Y1.2 (0.961)	Y1.2.1 (0.958)
		Y1.2.2 (0.958)
		Y1.2.3 (0.960)
		Y1.2.4 (0.959)
		Y1.2.5 (0.949)
	Y1.3 (0.845)	Y1.3.1 (0.844)
		Y1.3.2 (0.839)
		Y1.3.3 (0.844)
		Y1.3.4 (0.809)
		Y1.3.5 (0.838)
Y2	Y2.1 (0.933)	Y2.1.1 (0.930)	0.876	0.924	0.802
		Y2.1.2 (0.930)
		Y2.1.3 (0.930)
		Y2.1.4 (0.930)
	Y2.2 (0.899)	Y2.2.1 (0.889)
		Y2.2.2 (0.899)
		Y2.2.3 (0.892)
		Y2.2.4 (0.899)
	Y2.3 (0.853)	Y2.3.1 (0.850)
		Y2.3.2 (0.850)
		Y2.3.3 (0.834)
		Y2.3.4 (0.834)
Y3	Y3.1 (0.851)	Y3.1.1 (0.832)	0.905	0.941	0.841
		Y3.1.2 (0.823)
		Y3.1.3 (0.819)
	Y3.2 (0.943)	Y3.2.1 (0.867)
		Y3.2.2 (0.908)
		Y3.2.3 (0.932)
	Y3.3 (0.954)	Y3.3.1 (0.921)
		Y3.3.2 (0.939)
		Y3.3.3 (0.940)
	Y3.4 (0.887)	Y3.4.1 (0.880)
		Y3.4.2 (0.876)
		Y3.4.3 (0.876)

For Intellectual Capital (X1), the Human Capital (X1.1) indicator has item loadings between 0.698 and 0.712. These items measure faculty and staff experience (0.712), skills (0.708), training (0.698), idea generation (0.701), and creativity in solving challenges (0.701). Structural Capital (X1.2) has item loadings from 0.808 to 0.821, covering operational efficiency (0.808), adaptability (0.820), accessibility of information (0.827), innovation support (0.819), organizational culture (0.819), investment in new fields (0.820), and inter-departmental cooperation (0.821). Relational Capital (X1.3) has item loadings ranging from 0.730 to 0.736, evaluating communication (0.735), stakeholder interactions (0.735), relationship-building (0.730), partner reliability (0.734), and strategic partnerships (0.736).

In Knowledge Management (Y1), Knowledge Acquisition (Y1.1) has very high item loadings between 0.939 and 0.948, assessing the university’s ability to recruit new knowledge (0.947), create an open environment for learning (0.947), adopt best practices (0.939), gather relevant information (0.942), document knowledge (0.948), and acquire knowledge from various sources (0.948). Knowledge Dissemination (Y1.2) shows high item loadings, ranging from 0.949 to 0.960, focusing on knowledge sharing within the university (0.958), information exchange (0.958), development of information systems (0.960), inter-departmental knowledge sharing (0.959), and communication between administrators and faculty (0.949). Knowledge Utilization (Y1.3) has item loadings between 0.809 and 0.844, evaluating the university’s ability to analyze knowledge (0.844), apply knowledge (0.839), protect knowledge (0.844), further develop knowledge (0.809), and integrate various knowledge sources (0.838).

Innovation (Y2) is measured through Administrative Innovation (Y2.1), which has very high item loadings of 0.930, assessing the implementation of new structures (0.930), ability to try new working methods (0.930), adaptability to administrative changes (0.930), and team collaboration (0.930). Product Innovation (Y2.2) has item loadings ranging from 0.889 to 0.899, assessing the development of new programs (0.889), training methods (0.899), and services (0.892). Process Innovation (Y2.3) shows item loadings between 0.834 and 0.850, focusing on technological development (0.850), adoption of new techniques (0.850), and acquisition of new equipment (0.834).

Lastly, Organizational Performance (Y3) is measured through Faculty Work Utilization and Recognition (Y3.1), with item loadings from 0.819 to 0.832, assessing research outputs (0.832), community service participation (0.823), and faculty recognition (0.819). Faculty External Engagement (Y3.2) shows loadings between 0.867 and 0.932, measuring scientific publications (0.867), joint research projects (0.908), and faculty collaborations (0.932). Global Partnership Collaboration (Y3.3) has high loadings between 0.921 and 0.940, evaluating student exchanges (0.921), international cooperation (0.939), and student feedback (0.940). Internationally Accredited Programs (Y3.4) items load between 0.876 and 0.880, focusing on faculty experience abroad (0.880), internationally recognized courses (0.876), and student participation in global programs (0.876).

All items from the questionnaire were retained in the SEM analysis, as they met the necessary criteria for validity and reliability without requiring elimination. Furthermore, to assess discriminant validity, the analysis revealed that the square root of the AVE for each construct was greater than the corresponding correlation coefficients with other constructs, as shown in Table 3.

Table 3.

Discriminant Validity (Square root of the AVE).

	X1	Y1	Y2	Y3
X1	0.760
Y1	0.619	0.920
Y2	0.600	0.907	0.896
Y3	0.648	0.908	0.825	0.917

Table 3 provides the discriminant validity results for the constructs used in this study, including intellectual capital (X1), knowledge management (Y1), innovation (Y2), and organizational performance (Y3). The diagonal elements in the table represent the square root of the average variance extracted (AVE) for each construct, while the off-diagonal elements represent the correlation coefficients between the constructs. The values on the diagonal (0.760 for X1, 0.920 for Y1, 0.896 for Y2, and 0.917 for Y3) are the square roots of the AVE for each construct. According to previous research,⁷² discriminant validity is confirmed if the square root of the AVE of each construct is greater than the highest correlation of that construct with any other construct. In this table:

• The square root of the AVE for intellectual capital (0.760) is greater than its correlations with knowledge management (0.619), innovation (0.600), and organizational performance (0.648).

• The square root of the AVE for knowledge management (0.920) is greater than its correlations with intellectual capital (0.619), innovation (0.907), and organizational performance (0.908).

• The square root of the AVE for innovation (0.896) is greater than its correlations with intellectual capital (0.600), knowledge management (0.907), and organizational performance (0.825).

• The square root of the AVE for organizational performance (0.917) is greater than its correlations with intellectual capital (0.648), knowledge management (0.908), and innovation (0.825).

These results indicate that each construct shares more variance with its own indicators than with other constructs. Consequently, the criteria for discriminant validity as set by previous research⁷² are met, confirming that the constructs in this study are both valid and reliable.

Goodness-of-fit testing

Before testing the hypotheses, a goodness-of-fit test was conducted. The goodness-of-fit test in this study utilized Q2 and Standardized Root Mean Square Residual (SRMR) metrics. A positive Q2 value of 0.964 indicates the presence of predictive relevance in the proposed model. In assessing model fit, the study adhered to the procedures established by previous research.⁷³ The SRMR value for the saturated model was 0.083, and for the estimated model, it was 0.097. Both values are below the 0.1 threshold, indicating an acceptable fit.⁷⁴ The goodness-of-fit results are presented in Table 4 below.

Table 4.

Goodness of fit results.

The goodness of fit index	Saturated model	Estimated model
SRMR	0.083	0.097
Q2	0.964

Hypothesis testing results

In this analysis, the relationships between the tested variables demonstrate significant results (the results summarized in Table 5). First, intellectual capital has a strong positive impact on knowledge management, with a path coefficient of 0.619. The high t-statistic (8.406) and the very low p-value (0.000) indicate that this effect is statistically significant. Intellectual capital also influences innovation, albeit with a weaker effect, as indicated by a path coefficient of 0.085. However, this relationship remains statistically significant with a t-statistic of 2.450 and a p-value of 0.014.

Table 5.

Hypothesis testing results.

Relationship between variables	Path coefficient	T-statistics	p-value	Conclusion
Intellectual capital → Knowledge management	0.619	8.406	0.000	H1 accepted
Intellectual capital → innovation	0.085	2.450	0.014	H2 accepted
Intellectual capital → Organizational performance	0.600	9.245	0.000	H3 accepted
Knowledge management → innovation	0.307	4.098	0.023	H4 accepted
Knowledge management → Organizational performance	0.520	7.196	0.000	H5 accepted
Innovation → Organizational performance	0.403	5.738	0.000	H6 accepted

Furthermore, intellectual capital shows a positive and strong relationship with organizational performance, with a path coefficient of 0.600. The high t-statistic (9.245) and low p-value (0.000) indicate that this influence is statistically significant. Knowledge management also has a significant impact on innovation, with a path coefficient of 0.307. Although the effect is moderate, the t-statistic of 4.098 and p-value of 0.023 indicate statistical significance. The influence of knowledge management on organizational performance is also significant, with a path coefficient of 0.520. The high t-statistic (7.196) and low p-value (0.000) affirm the statistical significance of this relationship. Lastly, innovation has a strong positive impact on organizational performance, with a path coefficient of 0.403. The t-statistic of 5.738 and the very low p-value (0.000) indicate that this relationship is statistically significant.

In conlusion, this analysis shows that intellectual capital, knowledge management, and innovation all have significant impacts on organizational performance, both directly and through inter-variable relationships. Every hypothesis tested in this model is accepted, underscoring the importance of these three factors in enhancing organizational performance. The results of hypothesis testing summarized in Table 5 below.

Discussion

Hypothesis 1: Intellectual capital positively affects knowledge management

The findings of this study confirm Hypothesis 1, demonstrating that intellectual capital exerts a significant and positive effect on knowledge management. This result is consistent with earlier studies^22,41 that also identified intellectual capital as a key driver in enhancing knowledge management practices. Comprised of human, structural, and relational elements, intellectual capital is essential for optimizing knowledge management systems in universities, enabling more efficient knowledge acquisition, dissemination, and utilization.

Intellectual capital, which includes human, structural, and relational components, plays a crucial role in effective knowledge management. Human capital enhances the ability to acquire, interpret, and apply knowledge, while structural capital provides the necessary systems and frameworks for knowledge storage and dissemination.²² Relational capital, through external networks and collaborations, allows organizations to access new insights and integrate them with internal knowledge. Together, these elements enable universities to optimize their knowledge management processes, aligning with previous research that highlights the significant impact of intellectual capital on knowledge practices.^22,41

The synergy of these three components—human, structural, and relational capital—creates a comprehensive and effective knowledge management system. When these elements are well-developed and integrated, universities can efficiently acquire, store, disseminate, and utilize knowledge, leading to better decision-making, innovation, and overall performance. The positive impact of intellectual capital on knowledge management highlights the strategic importance of managing intangible assets in the academic sector. Universities that recognize the value of intellectual capital and invest in its development are better positioned to navigate complex environments, adapt to changes, and maintain a competitive edge.

Hypothesis 2: Intellectual capital positively affects innovation

The results of this study support Hypothesis 2, demonstrating that intellectual capital positively influences innovation. This finding is consistent with previous research by,⁴² which identified intellectual capital as a critical driver of innovation in educational settings. Intellectual capital fosters innovation within universities by enhancing knowledge processes and creating an environment conducive to the generation and implementation of new ideas.

Human capital provides the creative input necessary for innovation. Universities with skilled and knowledgeable faculty and staff are better equipped to generate innovative ideas and develop new academic programs and research initiatives. This aligns with the previous findings,²³ who emphasized the importance of human capital in fostering innovation in academic institutions. Structural capital ensures that innovative ideas can be systematically developed and implemented. Universities with efficient processes, supportive organizational cultures, and advanced IT systems can facilitate the seamless flow of knowledge and support innovative activities.

Previous research⁴² highlighted that structural capital plays a crucial role in optimizing the use of knowledge, skills, and experiences within universities to drive innovation. Relational capital provides external connections and collaborative opportunities that support innovative activities. Universities that maintain strong relationships with industry partners, academic collaborators, and research institutions can access new ideas, technologies, and market trends, which can be integrated into their innovation processes. Another research²³ emphasized the importance of relational capital in creating a supportive environment for innovation.

The positive impact of intellectual capital on innovation underscores the importance of strategically managing intangible assets. Universities that recognize the value of intellectual capital and invest in its development are better positioned to foster a culture of continuous innovation. This strategic focus on intellectual capital aligns with the dynamic capabilities framework, which emphasizes the need for organizations to continuously reconfigure their resources and capabilities to address rapidly changing environments.¹

Hypothesis 3: Intellectual capital positively affects organizational performance in universities

The results of this study confirm Hypothesis 3, demonstrating that intellectual capital has a significant and positive impact on organizational performance. This finding aligns with previous research⁴⁵ and contrasts with the another results,⁴⁴ who found no significant effect. To understand this relationship more deeply, it is important to explore how intellectual capital as a comprehensive asset enhances organizational performance within universities.

Intellectual capital plays a pivotal role in enhancing organizational performance within universities.⁴⁵ By fostering a highly skilled workforce, streamlining internal processes, and cultivating strong external networks, intellectual capital contributes to improved decision-making, innovation, and overall productivity. The Resource-Based View²⁹ highlights intellectual capital as a key asset that provides competitive advantage, particularly in knowledge-driven sectors like academia. Universities that effectively manage and leverage their intellectual resources—through continuous development of human capital, efficient systems, and robust external collaborations—are better positioned to excel in performance, ensuring sustainable growth and adaptability in a rapidly changing environment.

Hypothesis 4: Knowledge management positively affects innovation

The results of this study support Hypothesis 4, indicating that knowledge management (KM) has a significant and positive influence on innovation. This relationship aligns with previous research,^52,53 who found that effective KM practices enhance innovation within organizations. Knowledge management involves the systematic processes of acquiring, disseminating, and utilizing knowledge within a university, fostering continuous learning and innovation.

Knowledge acquisition entails gathering relevant information from both internal and external sources, forming the foundation for new ideas. Dissemination involves sharing this knowledge across various organizational levels and departments, ensuring that it reaches those who can use it to innovate. Utilization is the application of this knowledge to solve problems, improve processes, and develop new academic programs or research initiatives. The KBV of the firm posits that knowledge is a fundamental resource for achieving competitive advantage.³⁰ Effective KM processes support the creation of an innovative environment within universities.

Previous reseach⁵² emphasized that KM practices such as knowledge sharing and collaboration significantly enhance an organization’s innovative capacity. When faculty and staff have access to a broad base of knowledge and are encouraged to share insights and collaborate, they are more likely to engage in creative problem-solving and generate innovative solutions. Similarly,⁵³ found that KM processes facilitate the development of new products and services by ensuring that relevant knowledge is accessible and actionable.

KM fosters a culture of continuous learning and improvement, which is critical for sustaining innovation. Universities that prioritize KM create an environment where faculty and staff are encouraged to seek out new knowledge, share what they learn, and apply this knowledge to their work. This culture supports the generation of new ideas and ensures that these ideas are refined and implemented effectively. The positive impact of KM on innovation highlights the importance of strategic management of knowledge processes in universities.

Hypothesis 5: Knowledge management positively affects organizational performance in universities

The study’s results support Hypothesis 5, demonstrating that KM positively affects organizational performance. This finding aligns with previous research,^50,51 which highlighted the positive impact of KM on organizational performance. Effective KM enhances organizational performance by improving decision-making, increasing operational efficiency, and fostering a culture of continuous improvement.

Decision-making is improved when faculty and staff have access to comprehensive and accurate knowledge, enabling them to make more informed choices. KM systems that store and disseminate critical information ensure that decision-makers at all levels have the data they need to respond to challenges and opportunities effectively. Operational efficiency is enhanced through the streamlined processes and reduced redundancies that effective KM practices promote. By ensuring that knowledge is easily accessible and shared across the university, KM helps to eliminate duplicated efforts and improve coordination, resulting in smoother operations, faster response times, and reduced costs.

Fostering a culture of continuous improvement is another crucial way in which KM impacts organizational performance. Universities that prioritize KM create an environment where faculty and staff are encouraged to continually seek out new knowledge and apply it to their work, leading to ongoing enhancements in processes, academic programs, and research initiatives. Previous research^50,51 found that universities with strong KM practices are better able to adapt to market changes and maintain competitive advantage.

The relationship between KM and organizational performance can also be understood through the lens of the KBV of the firm, which posits that knowledge is a fundamental resource for achieving competitive advantage.³⁰ KM directly contributes to the learning and growth of the university by enhancing faculty and staff capabilities and fostering a culture of continuous improvement. This, in turn, positively impacts internal business processes, student satisfaction, and overall institutional performance.

Hypothesis 6: Innovation positively affects organizational performance in universities

The findings of this study confirm Hypothesis 6, indicating that innovation has a significant and positive impact on organizational performance. This conclusion is supported by previous research,^55–57 all of which found that innovation contributes positively to organizational performance. Innovation drives organizational performance by enabling the development of new and improved academic programs, research initiatives, and administrative processes that meet stakeholder needs and create value.

Universities that prioritize innovation are better positioned to introduce unique offerings that differentiate them from competitors, thereby enhancing student satisfaction and institutional reputation. This competitive advantage is essential for capturing market share and driving enrollment growth. Moreover, innovation enhances operational performance by improving efficiency and effectiveness. Innovative processes and technologies can streamline operations, reduce costs, and increase productivity. For instance, the implementation of advanced educational technologies or innovative administrative practices can lead to significant improvements in efficiency and cost savings.

Innovation fosters a culture of continuous improvement, which is crucial for sustaining long-term success. Universities that encourage innovative thinking and problem-solving create an environment where faculty and staff are motivated to identify and implement improvements continuously. This proactive approach ensures that the university remains agile and responsive to changing educational demands and market conditions.

The relationship between innovation and organizational performance is further supported by the KBV of the firm, which posits that knowledge and innovation capabilities are fundamental resources for achieving competitive advantage.³⁰ By fostering innovation, universities enhance their dynamic capabilities, enabling them to adapt to new challenges and opportunities more effectively. Previous research⁵⁵ highlighted the role of innovation in driving overall institutional success, showing that universities with higher levels of innovation activity tend to perform better across various performance metrics.

In practical terms, these findings underscore the importance of fostering an innovative culture within universities. Leaders should prioritize investment in innovation, create supportive environments that encourage creative thinking, and implement processes that facilitate the development and execution of new ideas. By doing so, universities can harness the power of innovation to drive performance and achieve sustained success.

Implications of the research

Theoretical implications

This research provides substantial theoretical contributions to the KBV by empirically validating the positive impacts of intellectual capital, knowledge management, and innovation on organizational performance within the context of universities. By demonstrating the intricate relationships among these variables, this study enhances the understanding of how intangible assets drive competitive advantage and performance in higher education. The findings confirm that intellectual capital is a multifaceted resource that significantly influences innovation and performance, supporting the KBV theory’s assertion that knowledge is a critical organizational resource. Additionally, the study highlights the role of knowledge management in fostering innovation and improving organizational outcomes, further solidifying the KBV framework’s relevance in contemporary management research within academic institutions.

Practical implications

From a practical perspective, the findings underscore the importance of investing in and strategically managing intellectual capital and knowledge management to enhance innovation and organizational performance in universities. University leaders should prioritize developing human capital through continuous training and professional development to foster a skilled and knowledgeable faculty and staff. Furthermore, investing in robust structural capital, such as advanced IT systems and efficient processes, is crucial for supporting knowledge sharing and innovative activities within the university. Building strong relational capital through external partnerships and networks can provide valuable insights and resources that drive innovation in academic settings.

Universities are encouraged to create a culture that values continuous learning, knowledge sharing, and innovation. This involves implementing policies and practices that support knowledge management processes and encourage faculty and staff to engage in creative problem-solving. University leaders should focus on fostering an environment where innovation is embedded into the organizational fabric, ensuring that new ideas are continuously generated, refined, and implemented.

Conclusions

This study confirms the significant and positive impacts of intellectual capital and knowledge management on innovation and organizational performance, thereby validating the KBV theory within the context of universities. Intellectual capital, encompassing human, structural, and relational assets, provides a foundation for universities to generate, develop, and implement innovative ideas. Effective management of intellectual capital ensures that these resources are utilized optimally, fostering an environment conducive to continuous improvement and creativity. The study found that intellectual capital positively influences knowledge management, which in turn enhances innovation and organizational performance. By facilitating knowledge flow and collaboration, knowledge management enhances decision-making processes, operational efficiency, and overall organizational performance. Additionally, the findings confirm that innovation has a significant and positive impact on organizational performance, driving the development of new and improved academic programs, research initiatives, and administrative processes that meet the needs of students and other stakeholders.

The positive relationships identified in this study highlight the strategic importance of investing in intangible assets and cultivating a culture that values continuous learning and innovation in universities. Institutions that prioritize the development and management of intellectual capital and knowledge management systems are likely to maintain a competitive edge in today’s dynamic educational environment. This strategic focus enables universities to adapt to new challenges, seize opportunities for growth, and achieve sustained success. Moreover, the study underscores the necessity for university leaders to foster an innovative culture. By creating environments that encourage risk-taking, experimentation, and knowledge sharing, leaders can drive the innovation process and ensure that their institutions remain agile and competitive. The findings also emphasize the need for ongoing investment in training and development programs to enhance human capital, the implementation of advanced systems and processes to strengthen structural capital, and the cultivation of strong external relationships to build relational capital.

Research limitations

While this study provides valuable insights, several limitations should be acknowledged. First, the cross-sectional design of the study limits the ability to draw causal inferences between the variables. Longitudinal studies would provide a better understanding of the causal relationships and the dynamic nature of intellectual capital, knowledge management, and innovation over time. Second, the research was conducted within a specific university context, which may limit the generalizability of the findings to other educational institutions or geographical regions. Future research should consider diverse contexts to enhance the generalizability of the results. Third, the reliance on self-reported data may introduce biases such as social desirability or common method bias. Employing multiple data sources and methods, such as qualitative interviews or objective performance metrics, could mitigate these biases.

Recommendations for future research

Future research should expand the research context to include different types of educational institutions and geographical regions to enhance the generalizability of the findings. Exploring how intellectual capital and knowledge management practices vary across different universities and cultural contexts can provide a more comprehensive understanding of their impacts on innovation and performance. Additionally, incorporating multiple data sources and methods, such as qualitative approaches or objective performance metrics, can provide a richer and more nuanced understanding of the phenomena under study. For example, qualitative interviews with university leaders and faculty can offer deeper insights into how intellectual capital and knowledge management practices are implemented and perceived within academic institutions.

Exploring the potential moderating or mediating effects of other variables, such as organizational culture, leadership styles, or external environmental factors, would offer deeper insights into the mechanisms driving the relationships among intellectual capital, knowledge management, innovation, and performance. Understanding how these factors interact can help universities tailor their strategies to maximize the benefits of their intellectual capital and knowledge management investments.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Suparwadi

References

Teece

. Business models and dynamic capabilities. Long Range Plan 2018; 51(1): 40–49.

Cheung

MFY

Wong

. Transformational leadership, leader support, and employee creativity. Leader Organ Dev J 2011; 32(7): 656–672.

Schein

. Organizational culture and leadership. Hoboken, NJ: John Wiley & Sons, 2010.

Wang

. Relationship between knowledge management and organizational performance: a test on SMEs in Malaysia. Procedia - Soc Behav Sci 2016; 224: 184–189.

Ngoc-Tan

Gregar

. Knowledge management and its impacts on organisational performance: an empirical research in public higher education institutions of Vietnam. J Info Know Mgmt 2019; 18(2): 1950015.

Monye

Ibegbulem

. Effect of strategic planning on organizational performance and profitability. Int J Bus Law Res 2018; 6(2): 31–40.

Barrow

. Graduated inflationary universes. Phys Lett B 1990; 235(1-2): 40–43.

Haroon

Malik

. The impact of organizational communication on organizational performance. J Res Soc Sci 2018; 6(2): 140–152.

Quintero-Quintero

Blanco-Ariza

Garzón-Castrillón

. Intellectual capital: a review and bibliometric analysis. Publications 2021; 9(4): 46.

10.

Malikah

Nandiroh

. Intellectual capital and value of the firm: a systematic literature review. Int J Humanit Educ Soc Sci 2024; 3(4): 56–72.

11.

Stewart

. Using knowledge management practices in small business organizations [doctoral dissertation]. Walden University, 2021.

12.

Aman-Ullah

Mehmood

Amin

, et al. Human capital and organizational performance: a moderation study through innovative leadership. J Innov Knowl 2022; 7(4): 100261.

13.

Abualoush

Obeidat

Ali

, et al. The role of employees’ empowerment as an intermediary variable between knowledge management and information systems on employees’ performance. VINE J Inf Knowl Manag Syst 2018; 48(2): 217–237.

14.

Chen

Wang

Huang

. Effects of organizational innovation and technological innovation capabilities on firm performance: evidence from firms in China’s Pearl River Delta. Asia Pac Bus Rev 2020; 26(1): 72–96.

15.

García‐Morales

Lloréns‐Montes

Verdú‐Jover

. The effects of transformational leadership on organizational performance through knowledge and innovation. Br J Manag 2008; 19(4): 299–319.

16.

Al‐Hakim

Hassan

. Knowledge management strategies, innovation, and organisational performance: an empirical study of the Iraqi MTS. J Adv Manag Res 2013; 10(1): 58–71.

17.

Gunday

Ulusoy

Kilic

, et al. Effects of innovation types on firm performance. Int J Prod Econ 2011; 133(2): 662–676.

18.

Uzkurt

Kumar

Kimzan

, et al. Role of innovation in the relationship between organizational culture and frm performance. Eur J Innovat Manag 2013; 16(1): 92–117.

19.

Jia

Chen

Mei

, et al. How leadership matters in organizational innovation: a perspective of openness. Manag Decis 2018; 56(1): 6–25.

20.

Mukhlasin

Budi

. Analysis of measuring the level of readiness to implement knowledge management: a case study of financial education and training agency, ministry of finance. J Inf Syst 2017; 13(1): 11–20.

21.

Kumar

Singh

Haleem

. Critical success factors of knowledge management: modelling and comparison using various techniques. Int J Ind Syst Eng 2015; 21(2): 180–206.

22.

Elda

Patricia

Linda

. The impact of intellectual capital and knowledge management on competitive advantage. In: Sixth Padang International Conference On Economics Education, Economics, Business and Management, Accounting and Entrepreneurship (PICEEBA 2020). Atlantis Press, 2021, pp. 480–487.

23.

Martínez-Pérez

García-Villaverde

Elche

. The mediating effect of ambidextrous knowledge strategy between social capital and innovation of cultural tourism clusters firms. Int J Contemp Hospit Manag 2016; 28(7): 1484–1507.

24.

Schumpeter

. The theory of economic development. 1934.

25.

Uddin

Fan

Das

. A study of the impact of transformational leadership, organizational learning, and knowledge management on organizational innovation. Manag Dynam 2016; 16(2): 42–54.

26.

Lei

. Determinants of innovation capability: the roles of transformational leadership, knowledge sharing and perceived organizational support. J Knowl Manag 2019; 23(3): 527–547.

27.

Laurett

Mendes

. EFQM model’s application in the context of higher education: a systematic review of the literature and agenda for future research. Int J Qual Reliab Manag 2019; 36(2): 257–285.

28.

Smriti

Das

. Impact of intellectual capital on business performance: evidence from Indian pharmaceutical sector. Pol J Manag Stud 2017; 15(1): 232–243.

29.

Barney

. Firm resources and sustained competitive advantage. J Manag 1991; 17(1): 99–120.

30.

Grant

. Toward a knowledge-based theory of the firm. Strat Manag J 1996; 17: 109–122.

31.

Kogut

Zander

. What firms do? Coordination, identity, and learning. Organ Sci 1996; 7(5): 502–518.

32.

Nonaka

. A dynamic theory of organizational knowledge creation. Organ Sci 1994; 5(1): 14–37.

33.

Dess

Gupta

Hennart

, et al. Conducting and integrating strategy research at the international, corporate, and business levels: issues and directions. J Manag 1995; 21(3): 357–393.

34.

Miller

Shamsie

. The resource-based view of the firm in two environments: the Hollywood film studios from 1936 to 1965. Acad Manag J 1996; 39: 519–543.

35.

Argote

McEvily

Reagans

. Managing knowledge in organizations: an integrative framework and review of emerging themes. Manag Sci 2003; 49(4): 571–582.

36.

Templeton

Lewis

Snyder

. Development of a measure for the organizational learning construct. J Manag Inf Syst 2002; 19(2): 175–218.

37.

Verweire

Berghe

. Integrated performance management: a guide to strategy implementation. California: Sage Publications Inc., 2004.

38.

Kim

. Public service motivation and organizational citizenship behavior in Korea. Int J Manpow 2006; 27(8): 722–740.

39.

Brewer

Selden

. Why elephants gallop: assessing and predicting organizational performance in federal agencies. J Publ Adm Res Theor 2000; 10(4): 685–712.

40.

Elena-Iuliana

Criveanu

. Organizational performance-a concept that self-seeks to find itself. Ann 'Constantin Brancusi' Univ Targu-Jiu Econ Ser 2016; 4: 179–183.

41.

Lee

. Impact of intellectual capital on international trade: knowledge management and business processes as intermediaries. Ijirss 2022; 5(2): 101–111.

42.

Altindag

Fidanbas

Irdan

. The impact of intellectual capital on innovation: a literature study. Bus Manag Dynam 2019; 8(12): 1–12.

43.

Ling

. The influence of intellectual capital on organizational performance-knowledge management as moderator. Asia Pac J Manag 2013; 30(3): 937–964.

44.

Pigola

De Santi

da Costa

, et al. Intellectual capital on performance: a meta-analysis study enhancing a new perspective of the components. J Intellect Cap 2022; 23(6): 1379–1403.

45.

Nadeem

Farooq

Ahmed

. Does female representation on corporate boards improve intellectual capital efficiency? J Intellect Cap 2019; 20(5): 680–700.

46.

Sveiby

K-E

. Measuring intangible and intellectual capital: an emerging first standard. 1998.

47.

Leung

KKT

Tan

Wahid

. Ethical considerations in enhancing quality performance: a comprehensive review of the role of employee empowerment & involvement, communication, knowledge management and organizational culture. J Gov Integr 2023; 6(2): 564–576.

48.

Frappaolo

Toms

. Knowledge Management: from terra incognita to terra firma. Boston, MA: The Delphi Group, 1997.

49.

. Knowledge management & E-learning. Int J 2011; 3(3): 362–372.

50.

Bayari

Al Shamsi

Salloum

, et al. Impact of knowledge management on organizational performance. In: Proceedings of International Conference on Emerging Technologies and Intelligent Systems: ICETIS 2021. Springer International Publishing, 2022, vol 2, pp. 1035–1046.

51.

Obeso

Hernández-Linares

López-Fernández

, et al. Knowledge management processes and organizational performance: the mediating role of organizational learning. J Knowl Manag 2020; 24(8): 1859–1880.

52.

Lam

Nguyen

, et al. The relation among organizational culture, knowledge management, and innovation capability: its implication for open innovation. J Open Innov Technol Mark Complex 2021; 7(1): 66.

53.

Migdadi

. Knowledge management processes, innovation capability and organizational performance. Int J Prod Perform Manag 2022; 71(1): 182–210.

54.

Shaher

Ali

. The effect of entrepreneurial orientation and knowledge management on innovation performance: the mediation role of market orientation. Management Science Letters 2020; 10(15): 3723–3734.

55.

Hoai

Hung

Nguyen

. The impact of internal control systems on the intensity of innovation and organizational performance of public sector organizations in Vietnam: the moderating role of transformational leadership. Heliyon 2022; 8(2): e08954.

56.

Sciarelli

Gheith

Tani

. The relationship between soft and hard quality management practices, innovation and organizational performance in higher education. The TQM Journal 2020; 32(6): 1349–1372.

57.

Chatterjee

Chaudhuri

Vrontis

. Does data-driven culture impact innovation and performance of a firm? An empirical examination. Ann Oper Res 2024; 333(2): 601–626.

58.

Hair

Sarstedt

Ringle

, et al. An assessment of the use of partial least squares structural equation modeling in marketing research. J Acad Market Sci 2012; 40(3): 414–433.

59.

Byrne

. Structural equation modeling with AMOS: basic concepts, applications, and programming. New York, NY: Routledge, 2010.

60.

Sekaran

Bougie

. Research methods for business: a skill-building approach. New York, NY: Wiley, 2016.

61.

Kline

. Principles and practice of structural equation modeling. New York, NY: Guilford Publications, 2015.

62.

Likert

. A technique for the measurement of attitudes. Arch Psychol 1932; 22(140): 55.

63.

Uriguen

APA

Avolio Alecchi

. Impact of intellectual capital on organizational performance through intrinsic motivation in higher education institutions. Cogent Bus Manag 2023; 10(1): 2189772.

64.

Bontis

. Intellectual capital: an exploratory study that develops measures and models. Manag Decis 1998; 36(2): 63–76.

65.

Nonaka

Takeuchi

. The knowledge-creating company: how Japanese companies create the dynamics of innovation. Oxford, UK: Oxford University Press, 1995.

66.

Damanpour

. Organizational innovation: a meta-analysis of effects of determinants and moderators. Acad Manag J 1991; 34(3): 555–590.

67.

Kılıç

Uludağ

. The effects of transformational leadership on organizational performance: testing the mediating effects of knowledge management. Sustainability 2021; 13(14): 7981.

68.

Dillman

Smyth

Christian

. Internet, phone, mail, and mixed-mode surveys: the tailored design method. Hoboken, NJ: Wiley, 2014.

69.

Bryman

Bell

. Business research methods. Mason, OH: Oxford University Press, 2015.

70.

Cronbach

. Coefficient alpha and the internal structure of tests. Psychometrika 1951; 16(3): 297–334.

71.

Fabrigar

Wegener

MacCallum

, et al. Evaluating the use of exploratory factor analysis in psychological research. Psychol Methods 1999; 4(3): 272–299.

72.

Fornell

Larcker

. Evaluating structural equation models with unobservable variables and measurement error. J Mar Res 1981; 18(1): 39–50.

73.

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