# The extent of knowledge management practices using institutional memory and employees' individual work performance

Gertrude R Libertine

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Gertrude R Libertine. The extent of knowledge management practices using institutional memory and employees' individual work performance. Divine Word International Journal of management and Humanities, 2025, 4 (1), pp.1315-1339. hal-05135760

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Research in Management and Humanities

DWIJMH VOL. 4 NO. 1 (2025) ISSN: 2980-4817

Available online at www.dwijmh.org

Journal homepage: http://www.dwijmh.org

ORCID ID: https://orcid.org/0000-0001-6884-3504

# The extent of knowledge management practices using institutional memory and employees' individual work performance

Libertine Gertrude R. Macaspac: AQA Director, Divine Word College of Laoag, Philippines.

## ARTICLEINFO

Article history: October 20, 2024

Received: October 20, 2024

Received in rev. form. December 15, 2024

Accepted: January 25, 2025

Published: March 10, 2025

**Keywords:** knowledge management, creating, capturing, storing, sharing

JEL Classification: I 26

## ABSTRACT

This study examined the influence of knowledge management practices on individual work performance. A review of relevant literature provided a deeper understanding of the study's key concepts. The research focused on all employees of Divine Word College of Laoag and employed a descriptive-correlational research design. Data were collected using validated questionnaires and analyzed through descriptive and inferential statistics. Findings revealed that both knowledge management practices and individual work performance were rated high, with Pearson's r indicating a significant correlation between the two. However, the study acknowledged its limitations, particularly the restricted population and measured variables. Future research should explore additional dimensions of knowledge management practices and involve a larger sample for broader insights.

© 2025 by the authors. Licensee DWIJMH. This open-access article is distributed under the terms and conditions of the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/)

## Introduction

Organizational success and high performance can only be achieved through effective resource management. Resources encompass human resources, financial resources, and facilities, all of which play a crucial role in organizational efficiency. Human resources refer to employees' skills and knowledge, making it essential to hire individuals with the right competencies for the job. Financial resources, on the other hand, enable employees to perform their duties effectively by providing necessary funding. Facilities also play a critical role—regardless of employees' knowledge and skills, an organization that fails to provide adequate facilities is bound to struggle. Among these three elements, human resources are the most significant factor in determining an organization's success or failure (Richman, 2015; Okoye & Ezejiofor, 2013).

One of the most critical aspects of human resources is knowledge. Ensuring that employees acquire the right knowledge is a primary concern for management, particularly human resource managers. To facilitate this, human resource managers must develop strategies for creating, capturing, storing, and sharing knowledge. Organizations must implement structured programs and activities to share knowledge

<footnote>* Corresponding author. ORCID ID: 0000-0001-6884-3504</footnote>
effectively. Through training and development initiatives, employees gain the relevant knowledge necessary for performing their tasks efficiently (Richman, 2015).

A key concern for human resource managers is knowledge management, which involves systematically creating, capturing, storing, and sharing knowledge to enhance organizational performance. Knowledge exists within organizations in various forms—some of it is embedded in the minds of senior employees, while other knowledge is stored in data or records maintained by the institution (Nonaka, 1994). Knowledge is broadly categorized into tacit and explicit knowledge. Tacit knowledge is uncodified and resides in an individual's mind, shaped by personal experience, context, and practice, making it difficult to articulate. In contrast, explicit knowledge is codified and stored in documents or institutional repositories, forming an organization's institutional memory, which employees can access for reference (National Academies of Sciences, Engineering, and Medicine, 2007). Effectively managing both types of knowledge is essential for improving learning and organizational outcomes.

Knowledge management has emerged as a distinct field over the past three decades but remains under-researched and inconsistently applied across organizations. Although it has historical roots, determining its practical progression remains challenging (Spender, 2015). Many organizations struggle with creating, capturing, storing, and sharing institutional knowledge due to the absence of systematic processes that facilitate these activities. This gap results in inefficiencies, as employees lack access to essential knowledge that guides their tasks (Rezaei et al., 2021; Andreev, 2022). It is crucial for institutions to establish systems that systematically create, store, retrieve, share, and update knowledge accumulated over the years by experienced practitioners.

This study is motivated by the observation that many organizations fail to recognize the value of tacit knowledge, leading to a lack of programs that facilitate the transfer of expertise from seasoned employees to younger staff or new teachers (Bajracharya & Masdeu, 2006). Additionally, employees often struggle to locate institutional data and information necessary for decision-making (Human Resources, 2023). Therefore, this research investigates knowledge management practices through the lens of institutional memory and examines their impact on individual work performance. While knowledge management is a broad discipline, this study focuses specifically on the use of institutional memory within an organizational context.

The study is structured into several sections. The first section introduces the research by outlining its background and rationale. The second section presents a literature review, synthesizing relevant theories and concepts. The third section details the research methodology, including the study's design, population, setting, research instruments, data collection procedures, ethical considerations, and statistical analysis methods. The fourth section presents and analyzes the collected data, incorporating tabular representations followed by interpretations. The fifth and final section discusses the results in depth, highlighting their implications for both theory and practice.

## Literature review

This part presents the ideas from different literatures concerning knowledge, knowledge management, different practices of knowledge management, institutional memory and individual work performance.
## Knowledge

Before one can fully grasp the concepts and practices of knowledge management, it is essential to first understand the nature of knowledge itself. A clear understanding of this concept enables readers to appreciate knowledge management practices. Various scholars have attempted to define knowledge, leading to different interpretations (Johansson, 2015). Philosophers have taken diverse positions on the matter. Johansson defined knowledge as a justified true belief based on evidence and reliable procedures, a perspective aligned with naturalism. This view considers knowledge as empirical, obtained through scientific methods, and verified by various sciences (Kornblith, 2003).

However, this definition is contested by proponents of intuitionism, a metaphysical doctrine that asserts intuition as an independent source of knowledge. Intuitionists such as L.E.J. Brouwer (1881–1966), W.D. Ross (1877–1971), H.A. Prichard (1871–1947), G.E. Moore (1873–1958), and M. Dummett (1925–2011) argue that knowledge cannot be acquired solely through inference, observation, reason, or experience (Britannica, T. Editors of Encyclopedia, 2003). Instead, they contend that knowledge emerges from the mind as a priori insights (Stratton-Lake, 2020). The ongoing debate regarding the definition, origins, and classification of knowledge has led to various taxonomies, the most fundamental of which distinguishes between tacit (implicit) and explicit knowledge (Nonaka, 1994). This distinction has become a key concept in knowledge management.

Tacit knowledge resides in individuals' minds, shaped by past experiences, and is often difficult to articulate (Polanyi, 1966). In simple terms, people know more than they can express (Polanyi, 1966). Those who have been with an institution or organization for a long time are often considered subject matter experts, possessing valuable skills, knowledge, and experience within a specific field (Hopkins & Unger, 2017). These individuals accumulate expertise over time, refining their understanding of tasks and processes. However, they may not always recognize the value of their knowledge or be able to document it systematically. Donald Schön, as cited by Smith (2001, 2011), and Chris Argyris, as cited by Smith (2001, 2013), describe this phenomenon as "knowing in action"—people understand how to perform a task but may struggle to articulate their knowledge in writing.

Tacit knowledge is unstructured, non-verbalized, and embedded in personal experience and practice (Hedlund, 1994). However, it can be transmitted through training, mentorship, or direct interaction with experienced individuals. Semertzaki (2011) emphasized that tacit knowledge is highly personalized and is best shared through face-to-face conversations and social networking. Parsaye (1988) identified three primary methods for capturing tacit knowledge: expert interviews, learning by being told, and learning by observation. Converting tacit knowledge into a documented form—thereby making it explicit—ensures that it can be systematically stored and shared. O'Dell and Grayson (1998) noted that most knowledge begins as tacit, developed over time through trial and error. However, it often remains underutilized because organizations are unaware of the knowledge they possess (O'Dell & Grayson, 1998). This knowledge is embedded in business processes and organizational practices that have evolved and improved over time (King, 2009). Consequently, a core challenge in knowledge management is extracting and making tacit knowledge accessible to others.
Explicit knowledge, on the other hand, is codified and documented in various formats, including manuals, books, databases, and electronic records (King, 2009). Wei Choo et al. (2006) defined explicit knowledge as information that is systematically stored, explained, and disseminated through formal procedures and information technologies. Because explicit knowledge is structured and accessible, it can be easily shared among employees. It complements tacit knowledge and contributes to a more comprehensive understanding of organizational knowledge (Koné, 2021). Explicit knowledge is often written, logically organized, and acquired through hands-on experience, making it a critical asset for training and decision-making.

For the purposes of this study, knowledge is conceptualized as a combination of tacit knowledge—which cannot be treated merely as data (Mehrizi & Bontis, 2009)—and explicit knowledge, which includes both documented information and the undocumented expertise, skills, and experiences of professionals that contribute to decision-making and the achievement of organizational goals (European Guide to Good Practice in Knowledge Management, Part 1, 2004, p. 6). Spender (2015) argued that knowledge cannot be reduced to data alone and that attempting to define it narrowly is a strategic error. Therefore, a more holistic approach is required to effectively manage both tacit and explicit knowledge within organizations.

## Knowledge management and practices

The discussion on the significance of knowledge management dates back to the 1970s when Peter Drucker and Paul Strassman, followed by Karl-Erik Sveiby in the 1980s, highlighted the value of information and explicit knowledge as critical organizational assets (Spender, 2015). Over time, interest in knowledge management has evolved, recognizing knowledge as a competitive advantage. However, early scholars lacked concrete strategies for managing knowledge. During this period, Drucker and Sveiby explored the concept of knowledge workers and the role of knowledge within organizations. By the late 1980s, discussions on knowledge acquisition, knowledge engineering, and knowledge-based systems emerged, laying the groundwork for knowledge management (Wiig, 1997). The formal discourse on knowledge management (KM) gained traction in the Harvard Business Review in the late 1980s (Hansen, Nohria & Tierney, 1999). By the 1990s, knowledge management was widely recognized as a key business practice, with large corporations implementing KM solutions (Wiig, 1997).

Despite the development of knowledge management concepts, there remains no consensus on how to implement KM within organizations due to varying definitions of knowledge. One perspective views knowledge as explicit and focuses on technical approaches to acquiring knowledge from individuals, computers, repositories, and other technology-based networks such as email and groupware (Amidon, 1996). Another perspective considers knowledge more broadly, encompassing all knowledge-related aspects affecting organizational success (Wiig, 1997). Consequently, knowledge management extends beyond technical approaches, as knowledge resides in individuals' minds and is not entirely captured by computer systems. Tuomi (1999) argued that knowledge does not exist independently of a knower, leading to the distinction between tacit and explicit knowledge. Nonaka (1994) further classified knowledge into tacit knowledge—held in individuals' minds—and explicit knowledge—documented in books, repositories, and systems. Tacit knowledge includes cognitive and experiential elements, such as expertise and intuition, which influence actions (John & Cook, 2001).
The complexity of knowledge management stems from its interdisciplinary nature. Definitions vary across fields, with IT experts, library science scholars, and business professionals offering different perspectives. KM integrates disciplines such as organizational science, HR management, computer science, psychology, and sociology (Chang-Albitres & Krugler, 2005). It also intersects with competitive intelligence, customer relationship management, human-computer interaction, and information management (Australian Standards, 2005). Among these, library science and information management are closely aligned with KM theory due to their focus on organizing, preserving, and retrieving information. As a result, KM is often viewed as an umbrella integrating multiple disciplines (National Academies of Sciences, Engineering, and Medicine, 2007).

Girard and Sagology (2015) define KM as "the process of creating, sharing, using, and managing an organization's knowledge and information," emphasizing the importance of knowledge creation, sharing, and utilization. The Gartner Group, as cited by Duhon (1998), describes KM as "a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise's information assets," highlighting the systematic management of an organization's knowledge base (Koenig, 2018). The Australian Standard (2005) defines KM as "a trans-disciplinary approach to improving organizational outcomes and learning through maximizing the use of knowledge," underscoring the role of both social and technological processes. Stachera-Włodarczyk (2019) further argues that KM focuses on the creation and application of intellectual resources and practical skills.

This research paper defines KM as a learning process aimed at enhancing organizational outcomes through the effective use of both tacit and explicit knowledge. It emphasizes that knowledge exists within the organization and must be captured, stored, and shared for optimal utilization. Different KM approaches result in varying practices, with some organizations focusing on HR-driven strategies, such as training and exit interviews, while others employ computer-based systems for information storage and retrieval.

These variations are evident in corporate KM implementations. For instance, Dow Chemical Company employed a knowledge value chain model that transformed intangible intellectual assets into measurable patents (Lloyd, 1996). Siemens utilized groupware in research and development (R&D) to integrate knowledge into practice (Lloyd, 1996). This paper adheres to a comprehensive perspective on KM, recognizing it as a strategic process that involves creating, capturing, storing, and sharing both tacit and explicit knowledge within an organization.

## Institutional memory

To understand the meaning of institutional memory, it is important to define it based on dictionary and expert definitions. Searching for the term in dictionaries like Merriam-Webster, Cambridge Dictionary, and others yields little or no results, indicating that the concept is either relatively new or not yet widely recognized. The term has gained prominence due to the rise of knowledge management discussions.

Institutional memory has been defined by various organizations. The Society of American Archivists (SAA) (n.d.) defines it as "the information held in employees' recollections and experiences that provides an understanding of the history and culture of an organization, especially the stories that explain the reasons behind certain decisions or procedures." This definition emphasizes that institutional memory is
embedded in the experiences and decisions of employees, often remaining unwritten yet crucial for organizational continuity.

The United Nations (n.d.) defines institutional memory as "a collective set of facts, concepts, experiences, and know-how held by a group of people." This perspective extends beyond individual recollections to encompass group memory, highlighting that institutional experience is a shared and evolving process. Similarly, IGI Global (n.d.) defines it as "the collective knowledge and learned experiences of a group." The University of Cambridge describes institutional memory as "an information repository within institutions." These definitions collectively suggest that institutional memory consists of individual recollections, group experiences, and documented repositories that serve as a foundation for understanding past decisions and actions within an organization.

The National Academies of Sciences, Engineering, and Medicine (2007) defines institutional memory as "the body of knowledge, formal as well as informal, that is essential to the continuous and effective functioning of the agency at all levels." This definition captures both tacit and explicit knowledge, acknowledging the importance of both written records and unwritten practices.

Scholars studying knowledge management have also provided various definitions of institutional memory. Jackson (2010) defines it as "storing knowledge," which extends beyond formal repositories to include informal knowledge held by individuals and groups. Stein and Zwass (1995) view institutional memory as an information system, particularly emphasizing the role of advanced technologies in capturing and preserving organizational knowledge. Gibbons (2007) defines institutional memory as "the stored knowledge within the organization," a definition that implies a focus on formal documentation. Brownlie (2016) highlights that institutions possess founding aims, ideologies, official histories, and practices that are remembered and passed down over time.

From these definitions, it is evident that institutional memory is a multidimensional concept, encompassing both formal and informal knowledge. This paper adopts the definition provided by the National Academies of Sciences, Engineering, and Medicine (2007), which integrates tacit and explicit knowledge, individual and collective experiences, and both written and unwritten records. Institutional memory, in this regard, serves as a vital component of an organization's knowledge management framework, ensuring continuity and informed decision-making.

## Individual work performance

### The dimensions of individual work performance

Individual work performance is a primary concern for management, as organizational success depends on it. Given its significance, management must regularly monitor and evaluate employee performance to detect deviations from stated objectives as early as possible. Regular or real-time performance evaluations should be conducted to assess whether employees are fulfilling their tasks and whether their work contributes to achieving organizational goals (Armstrong, 2013; Murphy, 2019).

However, scholars have yet to reach a consensus on the dimensions of performance that should be evaluated, primarily because there is no universally accepted definition of individual work performance (Dalal, 2005). The lack of consensus on its definition creates confusion regarding which dimensions
should be measured. Different scholars have proposed various elements, many of which overlap with one another. Motowidlo (2003) defined job performance as "the total expected value to the organization of the discrete behavioural episode that an individual carries out over a specified period." This definition frames performance as the output of behavioral activities performed by employees over a certain period to achieve organizational goals. Strengthening this perspective, Gulino (2022) defined work performance as "the total of a worker's execution of assigned tasks," while Turanlıgil (2019) described it as "the overall expected value from employees' behaviours carried out throughout a set period." These definitions collectively highlight that work performance is primarily a result of behavioral activities.

Recent scholars align with earlier definitions, particularly that of Campbell (1990), who described individual work performance as "behaviours or actions that are relevant to the goals of the organization." This perspective views work performance as a means of achieving individual and organizational goals rather than focusing on the actual outcomes of these behaviors. Campbell (1990) emphasized that job performance is a behavioral matter, not an outcome-based one. His definition has influenced contemporary scholars, such as Kasemsap (2016), who defined work performance as "the work-related activities expected of an employee and how well those activities are executed." Ahmad (2011) described it as "the ability of workers to perform their job," while Karapinar (2017) defined it as "an appraisal report indicating how well an employee is fulfilling the expected related job activities." These definitions collectively suggest that work performance is strictly behavioral and does not encompass outcomes, as outcomes may be beyond employees' control (Campbell, 2013b). Furthermore, these definitions are applicable across different occupations, as they focus solely on behavior.

Drawing from Campbell (1990) and other scholars, the concern regarding which dimensions of work performance should be evaluated is now addressed—performance assessment should focus strictly on behavioral dimensions rather than outputs. However, since behavior itself remains an abstract and broad concept, the question persists: what constitutes work performance? To ensure its measurability, it must be clearly defined (Viswesvaran, 2002). The earliest effort to identify work performance dimensions was undertaken by Campbell in the 1980s (Campbell et al., 2001). Initially, Campbell identified five work performance dimensions in the military: physical fitness and military bearing, technical performance, peer leadership, supervisory leadership, extra effort/initiative, and personal discipline. Among these, only one dimension was specific to military work, while the others could be applied to various occupations. Later, in 1993, Campbell et al. (1993) expanded these five dimensions into eight: job-specific technical proficiency, non-job-specific technical proficiency, communication, demonstrated effort and initiative, personal discipline, facilitating peer and team performance, supervision/leadership, and management/administration.

Inspired by Campbell's (1990) work, Borman and Motowidlo (1993, 1997) consolidated these dimensions into two categories: task performance and contextual performance. Task performance refers to core responsibilities based on job descriptions, while contextual performance includes behaviors that, although not directly related to job responsibilities, support the organization. Similarly, Organ (1988) introduced organizational citizenship behavior as an additional dimension of work performance. Recognizing that these dimensions alone were insufficient, researchers such as Bennett and Robinson (2000), Berry et al. (2007), Gruys and Sackett (2003), and Dalal (2005) later introduced counterproductive work behavior as another dimension.
Summarizing these contributions, Koopmans et al. (2011) proposed three primary components of work performance: task performance, contextual performance, and counterproductive work behavior. Later, Koopmans et al. (2014) expanded these to four dimensions by adding adaptive performance. However, based on the judgment of the current researcher, this study focuses solely on the three dimensions proposed by Koopmans et al. (2011), excluding adaptive performance. These three dimensions are deemed most relevant to the present investigation.

Borman and Motowidlo (1993), as cited by Silong et al. (2013), defined task performance as “the effectiveness with which job incumbents carry out activities that contribute to the organization's 'technical core,' either directly by executing a part of its technical process or indirectly by providing it with needed materials or services.” This definition highlights the importance of competency and expertise in effectively performing job functions (Harrison, Newman, & Roth, 2006), which Campbell (1990) referred to as task proficiency or technical core. These behaviors directly impact task completion and contribute to the organization's technical core. An employee must possess the necessary knowledge and skills to perform assigned tasks effectively.

Doğru (2019) defined contextual performance as “the degree to which an employee behaves positively, consisting of volunteering for extra duties, helping coworkers, and cooperating with them with an expectation of a reward.” Organ (1988) classified these behaviors under organizational citizenship behavior. Contextual performance includes actions voluntarily performed beyond job descriptions and official responsibilities. These behaviors help maintain and enhance the organizational environment, thereby supporting employees in executing their primary tasks. While these actions are not formally required, they significantly contribute to an employee’s ability to perform core job functions. Studies indicate that contextual performance is linked to both task performance (Diaz-Vilela et al., 2015) and overall effectiveness (Griffin et al., 2001).

Fox and Spector (2005) defined counterproductive work behavior as negative actions that hinder an organization's ability to achieve its objectives and harm other individuals within the organization. Robinson and Bennett (1995) categorized these behaviors into those directed at the organization and those targeting individuals within it. Specific counterproductive behaviors include abuse, production deviance, sabotage, theft, and withdrawal (Spector et al., 2006, as cited by Ispas & Borman, 2015). Within workgroups, counterproductive work behavior may include laissez-faire leadership, neglecting supervision, violating group norms or policies, damaging work relationships, and imposing personal values on others (Braun & Hentschel, 2015). The primary aim of counterproductive work behavior is to disrupt organizational success. These behaviors encompass a broad range of deliberate actions intended to undermine workplace performance, often driven by hidden motives.
**Conceptual framework**

<figure><img src="image_4.png" /></figure>

Source: Ward (2007) and Koopmans, et al. (2013).

Figure 1: the conceptual framework explains the relationship between knowledge management practices and individual work performance. It indicates that the purpose of knowledge is for the attainment of organizational objectives which can only be realized through individual work performance.

**Statement of the problems**

The study determined the influence of knowledge management practices through using institutional memory on the individual work performance of employees.

Specifically, it answered the following questions:

1. What is the level of knowledge management practices in terms of

a. Creating knowledge management practice,

b. Capturing Knowledge Management Practices

c. Storing Knowledge Management Practice

d. Sharing knowledge management practice

2. What is the level of individual work performance of employees in terms of

a. Task performance

b. Contextual performance

c. Counterproductive behavior

3. Is there a relationship between knowledge management practices and individual work performance?
## Assumptions

The study assumes that knowledge management practices affect the individual work performance of the employees and they can be measured.

## Hypothesis

Knowledge is an asset because knowledge can help the organization or institution achieve its goals. Good knowledge management practices can affect organizational performance through individual work performance. Thus, the current study hypothesizes that knowledge management practices using institutional memory affect the individual work performance of employees.

## Research methodology

As required in scientific research, this study follows a systematic research methodology to ensure a structured and reliable investigation. According to Wilkinson (2000) and Leedy (1974), research methodology is an established process for conducting inquiry, involving specific methods to determine, select, and analyze data related to the research topic. Accordingly, this study employs various research methods, including the research design, data gathering instruments, population and locale of the study, data gathering procedures, and statistical treatment of data.

## Research design of the Study

This study employs a descriptive assessment and descriptive correlational research design. According to Ariola (2006), a descriptive correlational study aims to describe relationships among variables without establishing causal connections. Meanwhile, descriptive research focuses on providing a detailed account of a population, situation, or phenomenon. It is commonly used to describe profiles, frequency distributions, and characteristics of people, situations, or events. In essence, it answers the questions "what," "when," "how," and "where," but not "why" (McCombes, 2020).

## Locale of the study

The study was conducted at Divine Word College of Laoag, located in Laoag City, the capital of Ilocos Norte.

## Population

The respondents of this study were the employees of the college. Given the limited number of employees, total enumeration sampling was employed, meaning that all faculty members and staff of the college were included as respondents.

## Data gathering instruments

The study utilized validated questionnaires from Ward (2007) on preserving and utilizing institutional memory through knowledge management practices and Koopmans et al. (2013) on work performance. These instruments were adopted after obtaining formal permission from the respective authors.
## Data gathering procedures

To uphold the integrity of scientific research, data collection commenced only after obtaining approval from the college president. The researcher formally requested approval through a letter, and upon receiving consent, the questionnaires were distributed by the researcher's representatives. The collected responses were then compiled and submitted to the researcher for tabulation.

## Ethical procedures

The study adhered to ethical research standards. The Research Ethics Committee reviewed and approved the study, ensuring compliance with ethical guidelines and confirming that it posed no harm to human participants or the environment.

## Statistical treatment of data

The study employed both descriptive and inferential statistics for data analysis. The weighted mean was used to assess the level of knowledge management practices in relation to creating, capturing, storing, and sharing knowledge and individual work performance. Additionally, ANOVA (Analysis of Variance) was used to examine the correlation between knowledge management practices and individual work performance.

The following range of values and their corresponding descriptive interpretations were applied:

### Statistical Range Descriptive Interpretation

<table><tr><td>4.21-5.00</td><td>strongly agree/ Very High</td></tr><tr><td>3.41-4.20</td><td>Agree / High</td></tr><tr><td>2.61-3.40</td><td>Somewhat agree/ Moderate</td></tr><tr><td>1.81-2.60</td><td>Disagree/Low</td></tr><tr><td>1.00-1.80</td><td>Strongly disagree/Very Low</td></tr></table>

## Data presentation and analysis

The data are presented and interpreted following the statement of the problems of the study. The study intends to examine the influence of knowledge management practice on individual work performance. It specifically answers the following questions:

### Problem 1: What is the level of the knowledge management practices in terms of

a. creating knowledge management practice,

b. capturing knowledge management practices

c. storing knowledge management practice

d. sharing knowledge management practice

<table><caption>Table 1: Knowledge Management Practices</caption><thead><tr><th>Indicator</th><th>Mean</th><th>DI</th></tr></thead><tbody><tr><td><strong>Creating knowledge</strong></td><td></td><td></td></tr><tr><td>The institution encourages creative ideas to solve existing institutional problems</td><td>3.75</td><td>A/H</td></tr><tr><td>It allows flexibility in carrying out one's duties and responsibilities, not required to follow strict official rules and procedures.</td><td>3.44</td><td>A/H</td></tr></tbody></table>
<table><tbody><tr><td>It establishes an environment that supports brainstorming, trial and error and unstructured interaction</td><td>3.62</td><td>A/H</td></tr><tr><td>It allows freedom for employees to experiment and work autonomously.</td><td>3.77</td><td>A/H</td></tr><tr><td>Motivates employees/teachers to conduct collaborative research projects</td><td>3.67</td><td>A/H</td></tr><tr><td>Encourages employees/teachers to produce peer-reviewed research publications</td><td>3.61</td><td>A/H</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>3.64</strong></td><td><strong>A/H</strong></td></tr><tr><td><strong>Capturing knowledge</strong></td><td></td><td></td></tr><tr><td>The institution requires exit interviews for retiring or exiting staff, and the institution documents the results.</td><td>3.79</td><td>A/H</td></tr><tr><td>The institution has a policy about the ways to retain key workers.</td><td>3.62</td><td>A/H</td></tr><tr><td>Uses retirees' expertise by implementing formal programs to reemploy recent retirees, especially on a contract or part-time basis</td><td>3.72</td><td>A/H</td></tr><tr><td>Systematically records knowledge of employees on the verge of retirement by using video, interviews, and documentation</td><td>3.54</td><td>A/H</td></tr><tr><td>The institution encourages workers to mingle across department boundaries to facilitate knowledge transfer</td><td>3.59</td><td>A/H</td></tr><tr><td>Assign individuals to document expertise</td><td>3.51</td><td>A/H</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>3.63</strong></td><td><strong>A/H</strong></td></tr><tr><td><strong>Storing knowledge</strong></td><td></td><td></td></tr><tr><td>The institution has a clear policy for storing knowledge assets (Employees understand what data or information needs to be stored).</td><td>3.56</td><td>A/H</td></tr><tr><td>Employees generally understand how to get resources from their possession into storage. The process is well-defined for most resource types.</td><td>3.51</td><td>A/H</td></tr><tr><td>Storage practices are well-defined for some critical resources, such as legal or financial documents, but not necessarily for all.</td><td>3.63</td><td>A/H</td></tr><tr><td>The institution's electronic resources are stored in an institutional repository.</td><td>3.67</td><td>A/H</td></tr><tr><td>The institution defines retention periods for most resource types. The institution works with stakeholders such as legal counsel, professionals, managers, or historians—and also consults laws and regulations, plus records and knowledge management experts and best practices to determine appropriate retention policies (how long a record is kept in a repository).</td><td>3.90</td><td>A/H</td></tr><tr><td>The repository for electronic resources has adequate capacity for long-term storage of electronic resources and is reasonably secured against environmental damage, natural disasters, or intrusion, either computer-borne or physical.</td><td>3.62</td><td>A/H</td></tr><tr><td>Physical storage uses established records management or archival practices, with adequate shelving, durable boxes, folders, labelling, etc</td><td>3.85</td><td>A/H</td></tr><tr><td>The employees know where to find most resources that have been captured, stored, and preserved.</td><td>3.59</td><td>A/H</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>3.67</strong></td><td><strong>A/H</strong></td></tr><tr><td><strong>Sharing knowledge</strong></td><td></td><td></td></tr><tr><td>The institution has a practice of knowledge sharing through face-to-face skill training programs or roundtable discussions with the tacit knowledge experts</td><td>3.73</td><td>A/H</td></tr><tr><td>The institution has a regular program for orientation for new employees related to institutional policies and practices</td><td>3.65</td><td>A/H</td></tr><tr><td>The employees are given or provided copies of the policies of the institution so that they know</td><td>3.50</td><td>A/H</td></tr><tr><td>It encourages employees to share their expertise and connect with other team members who can learn from or build upon that expertise.</td><td>3.58</td><td>A/H</td></tr><tr><td>Create a learning platform to help workers/faculty learn new technologies or work methods that the institution is considering adopting in the future.</td><td>3.46</td><td>A/H</td></tr></tbody></table>
<table><tr><td>Gives employees signals that it's okay to step away from their desks, to talk to their colleagues, or to not always be working on a concrete task.</td><td>3.57</td><td>A/H</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>3.58</strong></td><td><strong>A/H</strong></td></tr><tr><td><strong>Overall Mean</strong></td><td><strong>3.63</strong></td><td><strong>A/H</strong></td></tr></table>

Source: Ward (2007)

Legend:

<table><thead><tr><td>Statistical Range</td><td>Descriptive Interpretation</td></tr></thead><tbody><tr><td>4.21-5.00</td><td>strongly agree/ Very High</td></tr><tr><td>3.41-4.20</td><td>Agree / High</td></tr><tr><td>2.61-3.40</td><td>Somewhat agree/ Moderate</td></tr><tr><td>1.81-2.60</td><td>Disagree/Low</td></tr><tr><td>1.00-1.80</td><td>Strongly disagree/Very Low</td></tr></tbody></table>

The data indicate that the institution's knowledge management practices received an overall mean rating of 3.63, categorized as "agree/high." This suggests that while the institution's knowledge management practices are not exceptionally high, they are consistently strong across all dimensions. Employees acknowledge that the institution engages in creating, capturing, storing, and sharing knowledge. They agree that it fosters creativity, encourages trial and error, supports experimentation, and motivates employees to conduct research and publish. Beyond formal research, knowledge creation occurs through individual and group discussions, where brainstorming enables employees to share diverse perspectives, enriching organizational knowledge and practices. In essence, knowledge is generated through interactions and synthesis (Rollett, 2003; Allard, 2004; Nonaka & Toyama, 2015).

However, knowledge management extends beyond thought showers. Capturing existing knowledge within the institution—particularly the tacit knowledge embedded in employees—requires deliberate strategies. This includes interviewing senior or retiring employees, retaining key figures, rehiring retirees, encouraging collaboration, and documenting expertise (Damij & Damij, 2013; Harkiolakis, 2013; Prasad, 2001). Once captured, knowledge must be effectively stored for future retrieval. A well-structured filing system should classify different types of information, ensuring accessibility for future users. This storage can be either physical or electronic (Agasi, 1981; Harkiolakis, 2013; Bennett et al., 2010, 2011; Xing et al., 2019; Braf, 2002).

Complete knowledge management practice does not end with storage—it must be shared to maximize its impact. Knowledge sharing fosters continuous learning and enhances organizational efficiency. It can take the form of roundtable discussions, orientation programs for new employees, provision of shared resources, technological tools, seminars, and informal interactions that encourage employees to exchange insights (Dupuy, 2004; Huysman & Wit, 2002; van den Hoff et al., 2003; Valeri, 2024; Lam et al., 2013; Chernenko, 2023).

By integrating these processes—creation, capture, storage, and sharing—the institution ensures that knowledge remains an asset that continuously evolves, informs decision-making, and enhances work practices.

**Problem 2: What is the level of individual work performance of employees in terms of**

a. Task performance

b. Contextual performance

c. Counterproductive behavior
<table><caption>Table 2: Individual work performance</caption><thead><tr><th>Indicator</th><th>Mean</th><th>DI</th></tr></thead><tbody><tr><td><strong>Task performance</strong></td><td></td><td></td></tr><tr><td>I managed to plan my work so that it was done on time</td><td>4.18</td><td>A/H</td></tr><tr><td>My planning was optimal</td><td>4.03</td><td>A/</td></tr><tr><td>I kept in mind the results that I had to achieve in my work</td><td>4.15</td><td>A/H</td></tr><tr><td>I was able to separate main issues from side issues at work</td><td>4.26</td><td>SA/VH</td></tr><tr><td>I knew how to set the right priorities</td><td>4.19</td><td>A/H</td></tr><tr><td>I was able to perform my work well with minimal time and effort</td><td>4.01</td><td>A/H</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>4.14</strong></td><td><strong>A/H</strong></td></tr><tr><td><strong>Contextual performance</strong></td><td></td><td></td></tr><tr><td>I took on extra responsibilities</td><td>4.10</td><td>A/H</td></tr><tr><td>I started a new task myself when my old ones were finished</td><td>4.11</td><td>A/H</td></tr><tr><td>I took on a challenging work task, when available</td><td>4.11</td><td>A/H</td></tr><tr><td>I worked at keeping my job knowledge up-to-date</td><td>4.16</td><td>A/H</td></tr><tr><td>I worked at keeping my job skills up-to-date</td><td>4.15</td><td>A/H</td></tr><tr><td>I came up with creative solutions to new problems</td><td>4.03</td><td>A/H</td></tr><tr><td>I kept looking for new challenges in my job</td><td>4.06</td><td>A/H</td></tr><tr><td>I did more than was expected of me</td><td>4.15</td><td>A/H</td></tr><tr><td>I actively participated in work meetings</td><td>4.16</td><td>A/H</td></tr><tr><td>I actively look for ways to improve my performance at work</td><td>4.29</td><td>SA/VH</td></tr><tr><td>I grasped opportunities when they presented themselves</td><td>4.17</td><td>A/H</td></tr><tr><td>I knew how to solve difficult situations and setbacks quickly</td><td>4.12</td><td>A/H</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>4.13</strong></td><td><strong>A/H</strong></td></tr><tr><td><strong>Counterproductive performance</strong></td><td></td><td></td></tr><tr><td>I complained about unimportant matters at work</td><td>2.99</td><td>SWA/M</td></tr><tr><td>I made problems greater than they were at work</td><td>2.70</td><td>SWA</td></tr><tr><td>I focused on the negative aspects of a work situation, instead of on the positive aspects</td><td>2.54</td><td>D/L</td></tr><tr><td>I spoke with colleagues about the negative aspects of my work</td><td>2.67</td><td>SWA</td></tr><tr><td>I spoke with people from outside the organization about the negative aspects of my work</td><td>2.65</td><td>SWA</td></tr><tr><td>I did less than was expected of me</td><td>2.62</td><td>SWA</td></tr><tr><td>I managed to get off from a work task easily</td><td>2.91</td><td>SWA</td></tr><tr><td>I sometimes did nothing, when I should have been working</td><td>2.68</td><td>SWA</td></tr><tr><td><strong>Composite Mean</strong></td><td><strong>2.72</strong></td><td><strong>SWA</strong></td></tr><tr><td><strong>Overall Mean</strong></td><td><strong>3.66</strong></td><td><strong>A/H</strong></td></tr></tbody></table>

Source: Koopmans, et al. (2013).

The data indicate that employees' individual work performance received an overall mean rating of 3.66, categorized as "agree/high." This suggests that while individual work performance is not exceptionally high, it is consistently strong. However, when analyzed separately, task performance and contextual performance were both rated high (4.14, 4.14), whereas counterproductive work behavior received a moderate rating (2.72).

This result aligns with expectations—strong task and contextual performance are essential for sustaining high work performance, while counterproductive behavior must be minimized. Task performance directly influences productivity by requiring technical knowledge and skills that contribute to achieving
organizational goals (Adekiya, 2023; Paulus, 1983; Wigglesworth, 2008). However, knowledge and skills alone are insufficient—positive work behavior, known as contextual performance, is equally crucial. Contextual performance consists of three key behaviors: helping others, supporting the organization, and demonstrating job dedication (Nikiforow & Wagener, 2020; Urdan, 2001; Borman & Motowidlo, 1997; Taibah & Ho, 2022).

A strong individual work performance profile also means fewer counterproductive behaviors. These negative behaviors hinder organizational success (Fatime et al., 2012; Ji & Yan, 2023; Beck-Krala, 2020; Fox et al., 2001). The findings indicate that employees exhibited lower counterproductive behaviors compared to their task and contextual performance levels, reinforcing a positive work environment and a commitment to organizational objectives.

**Problem 3: Is there a relationship between knowledge management practices and individual work performance?**

<table><thead><tr><th rowspan="2">Knowledge management practices</th><th rowspan="2"></th><th colspan="4">Individual work performance</th></tr><tr><th>Task performance</th><th>Contextual performance</th><th>Counterproductive performance</th><th>Overall</th></tr></thead><tbody><tr><td rowspan="2">Creating knowledge</td><td>Pearson correlation</td><td>.620**</td><td>.523**</td><td>.098</td><td>.579**</td></tr><tr><td>Sig. (2-tailed)</td><td>.000</td><td>.000</td><td>.153</td><td>.000</td></tr><tr><td rowspan="2">Capturing knowledge</td><td>Pearson correlation</td><td>.604**</td><td>.511**</td><td>.102</td><td>.571**</td></tr><tr><td>Sig. (2-tailed)</td><td>.000</td><td>.000</td><td>.139</td><td>.000</td></tr><tr><td rowspan="2">Storing knowledge</td><td>Pearson correlation</td><td>.677**</td><td>.569**</td><td>.084</td><td>.611**</td></tr><tr><td>Sig. (2-tailed)</td><td>.000</td><td>.000</td><td>.222</td><td>.000</td></tr><tr><td rowspan="2">Sharing knowledge</td><td>Pearson correlation</td><td>.389**</td><td>.347**</td><td>.213**</td><td>.505**</td></tr><tr><td>Sig. (2-tailed)</td><td>.000</td><td>.000</td><td>.002</td><td>.000</td></tr><tr><td rowspan="2">Overall</td><td>Pearson correlation</td><td>.638**</td><td>.543**</td><td>.138*</td><td>.497**</td></tr><tr><td>Sig. (2-tailed)</td><td>.000</td><td>.000</td><td>.044</td><td>.000</td></tr></tbody></table>

The table presents the correlation between different dimensions of knowledge management practices (creating, capturing, storing, and sharing knowledge) and individual work performance (task performance, contextual performance, and counterproductive behaviour).

The results indicate a strong positive correlation between knowledge management practices and task performance (r = .638, p = .000), highlighting that employees with access to well-managed knowledge resources perform tasks more efficiently. Among the four dimensions of knowledge management, storing knowledge has the strongest correlation with task performance (r = .677, p = .000), emphasizing that employees perform better when knowledge is systematically stored and easily accessible. Creating (r = .620, p = .000) and capturing knowledge (r = .604, p = .000) also show strong correlations, underscoring the importance of fostering innovation and retaining institutional knowledge for task execution. Sharing
knowledge, while still significant (r = .389, p = .000), has a lower correlation, suggesting that structured documentation and storage have a more direct impact on task performance.

In terms of contextual performance, which refers to employees' willingness to go beyond core responsibilities, a moderate to strong positive correlation was found (r = .543, p = .000). Storing knowledge again shows the highest correlation with contextual performance (r = .569, p = .000), suggesting that employees with well-documented knowledge are more likely to engage in extra-role behaviours. Creating (r = .523, p = .000) and capturing knowledge (r = .511, p = .000) also correlate strongly, indicating that a culture of knowledge generation and retention fosters proactive employee behaviour. Sharing knowledge (r = .347, p = .000) has the lowest correlation, reaffirming that structured storage and accessibility have a greater influence on employees' willingness to take on additional responsibilities.

For counterproductive work behaviour (CWB), the correlation with knowledge management practices is weak but still statistically significant (r = .138, p = .044), suggesting that better knowledge management practices slightly reduce CWB. Sharing knowledge has the highest negative correlation with CWB (r = -.213, p = .002), indicating that employees engaged in knowledge-sharing activities are less likely to exhibit counterproductive behaviours. Creating, capturing, and storing knowledge show weak, non-significant correlations with CWB, implying that while structured knowledge management helps with performance, its direct impact on reducing workplace negativity is limited.

**Results and discussion**

The findings of this study reveal that the institution's knowledge management practices are rated high across all four dimensions—creating, capturing, storing, and sharing knowledge—a trend that also applies to individual work performance. Pearson r correlation analysis further confirms a significant relationship between knowledge management practices and individual work performance. This underscores a crucial implication: enhancing individual work performance can be achieved by effectively implementing knowledge management strategies (Harb et al., 2024; Almuayad & Chen, 2024).

Knowledge management serves as a structured system for creating, capturing, organizing, storing, and sharing knowledge within an organization (North & Kumta, 2018; Harkiolakis, 2013; Maier, 2002). Knowledge creation extends beyond research and books—it thrives in environments that encourage employees to express creative ideas, experiment, and learn from failures. Therefore, fostering a workplace culture that promotes autonomy, creativity, and innovation is essential.

Capturing knowledge is equally critical, as a significant portion of institutional knowledge remains undocumented (Zamid et al., 2016; Mobus, 2022). Tacit knowledge—stored in the minds and experiences of senior employees—is invaluable for organizational growth (Damij & Damij, 2013; Harkiolakis, 2013). To harness this wealth of expertise, organizations must actively interview experienced employees, facilitate roundtable discussions, and organize knowledge-sharing seminars.

Once created and captured, knowledge must be stored systematically for future use. Effective record management ensures that past and emerging best practices are well-documented, classified, and easily retrievable (Wang & Meng, 2019; Wobeser, 1994; Lappin et al., 2021). A well-structured filing system
accelerates work efficiency and reduces stress by providing quick access to essential information when needed.

However, knowledge management does not end with storage—knowledge must be shared to drive continuous improvement. Knowledge should not be hoarded but actively disseminated to benefit all organizational members (Huysman & Wit, 2002; Lam et al., 2013). This can be achieved through regular thoughtshower sessions, seminars, roundtable discussions, and digital platforms that facilitate knowledge exchange.

Implementing knowledge management effectively boosts employee productivity and minimizes counterproductive work behaviors. The challenge for management is to create a work environment that fosters autonomy, openness, and a culture of knowledge sharing (Allen et al., 2024). Employees perform at their best when they have access to the right knowledge, and knowledge-sharing practices help align individual performance with organizational goals.

The study's findings call for a shift in leadership and management practices. A bureaucratic leadership style may hinder knowledge flow; therefore, adopting a transformational leadership approach that encourages open intellectual discussions is recommended. Additionally, HR policies on retirement and retention should be reconsidered to preserve institutional knowledge, particularly that of key senior employees. Finally, organizations should establish structured knowledge-sharing platforms and upgrade electronic filing systems to incorporate the latest technology, ensuring seamless knowledge access and management.

## Conclusion

This study explored the impact of knowledge management practices on individual work performance, revealing that both are rated high within the institution. The significant correlation found through Pearson r analysis underscores a key insight: effectively implementing knowledge management practices can directly enhance employee performance and productivity. By fostering a culture of knowledge creation, capture, storage, and sharing, organizations can empower employees, streamline operations, and drive overall success.

However, this study acknowledges its limitations, particularly the restricted sample size and scope of measured variables. Future research should expand the population size and explore additional dimensions of knowledge management to provide a more comprehensive understanding of its role in organizational performance.

**Author contribution:** The paper is written by the author

**Conflict of interest:** The author declares no conflict of interest over the paper to be published.
References

Adekiya, A. (2023). Perceived job insecurity and task performance: what aspect of performance is related to which facet of job insecurity? *Current Psychology*, 43, 1340-1358. https://doi.org/10.1007/s12144-023-04408-4

Agassi, J. (1981). Storage and communication of knowledge. In: *Science and society*. Springer.
https://doi.org/10.1007/978-94-011-6456-6_11

Ahmad, N. (2011). *Research-Based Insights Inform Change in IBM M-Learning Strategy*. Pennsylvania: IGI Global
Publisher of Timely Knowledge

Allard, S. (2004). Knowledge creation. In: Holsapple, C.W. (eds) *Handbook on knowledge management*. Springer.
https://doi.org/10.1007/978-3-540-24746-3_18

Almuayad, K.M.A., & Chen, Y. (2024). Effect of knowledge management on employee job performance in Yemeni Banking Sector: The mediating role of job satisfaction. *Journal of the Knowledge Economy*, 15(3). https://doi.org/10.1007/s13132-024-01791-6

Amidon, D.M. (1996). *The Ken Awakening: Management Strategies for Knowledge Innovation*. London: Routledge.

Ariola, M.M. (2006). *Principles and Methods of Research*. Manila: National Bookstore

Armstrong, M. (2013). *Managing performance: performance management in action*. World Journal of Education, 2 (1), 62-69.

Andreev, I. (2022). *Knowledge Management*. Valamis. Retrieved from https://www.valamis.com/hub/knowledge-management

Australian Standard (2005). *Knowledge Management—A Guide*, AS 5037-2005, 2nd ed. Australia: Standards Australia.

Bajracharya, P. & Masdeu, N.R. (2006). *Tacit knowledge transfer in small segment of small enterprise*. Retrieved from https://www.diva-portal.org/smash/get/diva2:21701/FULLTEXT01.pdf

Beck-Krala, E. (2020). Counterproductive work behaviors. In: Idowu, S., Schmidpeter, R., Capaldi, N., Zu, L., Del Baldo, M., Abreu, R. (eds) *Encyclopedia of sustainable management*. Springer. https://doi.org/10.1007/978-3-030-02006-4_212-1

Bennett, R.J., & Robinson, S.L. (2000). Development of a measure of workplace deviance. *Journal of Applied Psychology*, 85,349-60. https://doi.org/10.1037/0021-9010.85.3.349

Bennett, G., Fisher, M., Lees, B. (2010a). Storing information. In: *Objective-C for absolute beginners*. Apress.
https://doi.org/10.1007/978-1-4302-2833-2_13

Bennett, G., Fisher, M., Lees, B. (2011b). Storing information. In: *Objective-C for absolute beginners*. Apress.
https://doi.org/10.1007/978-1-4302-3654-2_11
Berry, C.M., Ones, D., & Sackett, P.R. (2007). *Interpersonal deviance, organizational deviance, and their common correlates: a review and meta-analysis*. *Journal of Applied Psychology*, *92*, 410-24.
https://doi.org/10.1037/0021-9010.92.2.410

Borman, W.C, Motowidlo S.J. (1993). *Expanding the criterion domain to include elements of contextual performance*. Jossey-Bass.

Borman W.C, Motowidlo S.J. (1997). Task performance and contextual performance: the meaning for personnel selection research. *Human Performance, 10*, 99-109. https://doi.org/10.1207/s15327043hup1002_3

Braf, E. (2002). Knowledge or information. In: Liu, K., Clarke, R.J., Andersen, P.B., Stamper, R.K., Abou-Zeid, ES. (eds) *Organizational semiotics*. Springer. https://doi.org/10.1007/978-0-387-35611-2_5

Braun, S. & Hentschel, T. (2015). *Group Process in Organization*. In International Encyclopedia of the Social & Behavioral Sciences (Second Edition). Elsevier

Britannica, T. Editors of Encyclopedia (2023, October 23). *Intuition*. *Encyclopedia Britannica*. Retrieved from
https://www.britannica.com/topic/intuition

Brownlie, S. (2016). *Institutional Memory*. In: *Mapping memory in translation*. Palgrave Macmillan.
https://doi.org/10.1057/9781137408952_7

Campbell, J. P. (1990). *Modelling the performance prediction problem in industrial and organizational psychology*. In M. Dunnette & L. Hough (Eds.), *Handbook of industrial and organizational psychology* (pp. 686-707). Consulting Psychologists Press.

Campbell, J. P., McCloy, R. A., Oppler, S. H., & Sager, C. E. (1993). A theory of performance: In N. Schmitt & W. C. Borman (Eds.), *Personnel Selection in Organizations* (pp. 35-70). Jossey-Bass.

Campbell, J.P., Hanson, M.A. & Oppler, S.H. (2001). *Modeling performance in a population of jobs*. Erlbaum

Campbell, J.P. (2013b). *Leadership, the old, the new, and the timeless: a commentary*. Oxford Handbook Online.,
401-22. https://doi.org/10.1093/oxfordhb/9780195398793.013.0024

Chang-Albitres, C.M. & P.E. Krugler (2005). *A Summary of Knowledge Management Information Gathered from Literature, Web Sites, and State Departments of Transportation*. Texas Transportation Institute.

Chernenko, M. (2023). Sharing your knowledge. In: *The rational software engineer*. Apress,
https://doi.org/10.1007/978-1-4842-9795-7_19

Dalal, R.S. (2005). A meta-analysis of the relationship between organizational citizenship behaviour and counterproductive work behaviour. *Journal of Applied Psychology, 90*, 1241-55. https://doi.org/10.1037/0021-9010.90.6.1241

Dalal, R.S. (2005). A meta-analysis of the relationship between organizational citizenship behaviour and counterproductive work behaviour. *Journal of Applied Psychology, 90*, 1241-55. https://doi.org/10.1037/0021-9010.90.6.1241
Damij, N., & Damij, T. (2014). Knowledge management. In: *Process management*. Springer.
https://doi.org/10.1007/978-3-642-36639-0_6

Diaz-Vilela, L.F. Rodriquez, N.D., Isla-Diaz, R., Diaz-Cebrera, D., Hernandez-Fernaud, E., & Rosales-Sacnchez, C. (2015). Relationships between contextual and task performance and interrater agreement: Are there any? *Plos One*, 10(10), https://doi.org/10.1371/journal.pone.0139898

Doğru, C. (2019). The effects of perceived organizational support and leader-member exchange on contextual performance: A study in the banking sector. In *handbook of research on contemporary approaches in management and organizational strategy*. IGI Global Publisher of Timely Knowledge

Duhon, B. (1998). It's all in our heads. *Inform*, 12, 8-13.

Dupuy, F. (2004). *Sharing knowledge*. Springer Nature.

Fatima, A., Iqbal, M.Z., Imran, R. (2013). Organizational commitment and counterproductive work behaviour: Role of employee empowerment. In: Xu, J., Yasinzai, M., Lev, B. (eds) *Proceedings of the sixth international conference on management science and engineering management*. Springer. https://doi.org/10.1007/978-1-4471-4600-1_57

Fox, S. & Spector, P.E. (2005). The stressor-emotion model of counterproductive work behavior. In S. Fox & P. E. Spector (Eds.), *Counterproductive work behaviour: Investigations of actors and targets* (pp. 151–174). American Psychological Association. https://doi.org/10.1037/10893-007

Fox, S., Spector, P.E. & Miles, D. (2001). Counterproductive work behaviour in response to job stressors and organizational justice: Some moderator and mediator test for autonomy and emotions. *Journal of Vocational Behavior*, 59(3), 291-309. https://doi.org/10.1006/jvbe.2001.1803

Gibbons, D. E. (2007-01-01). *Communicable crises: Prevention, response, and recovery in the global arena*. National Bookstore.

Girard, J.P. & Sagology, J.P. (2015). Defining knowledge management: Toward an applied compendium. *Online Journal of Applied Knowledge*, 3(1), 1-20.

Griffin, M., Neal, A. & Neale, M. (2001). The contribution of task performance and contextual performance to effectiveness: Investigating the role of situational constraints. *Applied Psychology*, 49(3), 517-533.
https://doi.org/10.1111/1464-0597.00029

Gruys, M.L., & Sackett, P.R. (2003). *Investigating the dimensionality of counterproductive work behaviour*. *International Journal of Selection and Assessment*, 11,30–42. https://doi.org/10.1111/1468-2389.00224

Gulino, D. (2022). *Assistive technologies and design for people with autism spectrum disorders: A selective overview*. IGI Global Publisher of Timely Knowledge. https://doi.org/10.4018/978-1-7998-7430-0.ch003

Hansen, M.T., Nohria, N. & Tierney, T. (1999). What's your strategy for managing knowledge? *Harvard Business Review*. Retrieved from https://hbr.org/1999/03/whats-your-strategy-for-managing-knowledge
Harb, Y., Alakaleek, W., & Shang, Y. (2024). The effect of knowledge management practices exploration and exploitation on individual performance and empowerment. *Journal of the Knowledge Economy, 15*, 1801–1822.
https://doi.org/10.1007/s13132-023-01165-4

Harkiolakis, N. (2013). Knowledge management. In: Idowu, S.O., Capaldi, N., Zu, L., Gupta, A.D. (eds) *Encyclopedia of corporate social responsibility*. Springer. https://doi.org/10.1007/978-3-642-28036-8_421

Harrison, D. A., Newman, D. A., & Roth, P. L. (2006). How important are job attitudes? Meta-analytic comparisons of integrative behavioral outcomes and time sequences. *Academy of Management Journal, 49*(2), 305-325.
https://doi.org/10.5465/AMJ.2006.20786077

Hedlund, G. (1994). A model of knowledge management and the N-form corporation. *Strategic Management Journal, 15*, (Special Issue), 73–90.

Hopkins, P. Unger, M. (2017). What is a subject matter expert? *The Journal of Pipeline Engineering, 16*(4), 227-230.

Human Resource (2023). *Institutional Knowledge*. VALAMIS. Retrieved from
https://www.valamis.com/hub/institutional-knowledge

Huysman, M. & Wit, D. (2002). *Knowledge sharing in practice*. Springer Nature.

IGI Global (n.d). *Institutional memory*. Retrieved from https://www.igi-global.com

Ispas, D. & Borman, W.C. (2015). *Counterproductive work behavior*. Elsevier

Jackson, P. (2010). Organizational memory: Storing knowledge. In Web 2.0 *Knowledge Technologies and Enterprise*. Elsevier.

Ji, H., Yan, J. Why does counterproductive work behavior lead to pro-social rule-breaking? The roles of impression management motives and leader-liking. *Asia Pacific Journal of Management, 40*, 1323–1339.
https://doi.org/10.1007/s10490-022-09818-9

Johansson, LG. (2016). Knowledge. In: *Philosophy of science for scientists*. Springer. https://doi.org/10.1007/978-3-319-26551-32

John, M.A. & Cook, L. (2001). *Review: Knowledge management and knowledge management system: A conceptual foundations and research issues*. *MIS Quarterly, 25*(1). 107-136.

Karapinar, P.B. (2017). *Well-Being at work: A comprehensive review about its predictors and outcomes*. IGI Global Publisher of Timely Knowledge

Kasemsap, K. (2016). *A unified framework of organizational perspectives and knowledge management and their impact on job performance*. IGI Global Publisher of Timely Knowledge

King, W.R. (2009). Knowledge management and organizational learning. *Annals of Information System, 4*.
https://doi.org/10.1007/978-1-4419-0011-1_1
Koenig, M.E.D. (n.d). *What is km? Knowledge management explained*. KM World. Retrieved from
https://www.kmworld.com

Kone, M.T. (2021). *What is explicit knowledge? IGI Global*.

Koopmans, L., Bernaards, C., Hildebrandt, V.H., de Vet, H. C., & van der Beek, A. J. (2011). Conceptual framework of individual work performance. *Journal of Occupational and Environmental Medicine, 53*(8), 856-66.
https://doi.org/10.1097/JOM.0b013e318226a763

Koopmans, L., Bernaards, C., Hildebrandt, V., van Buuren, S., van der Beek, A.J. and de Vet, H.C.W. (2013). Development of an individual work performance questionnaire. *International Journal of Productivity and Performance Management, 62*(1), 6-28. https://doi.org/10.1108/17410401311285273

Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., de Vet, H. C., & van der Beek, A. J. (2014). *Measuring individual work performance: identifying and selecting indicators*. Work (Reading, Mass.), 48(2), 229–238.
https://doi.org/10.3233/WOR-131659

Kornblith, H. (2003). *Knowledge and its place in nature*. *Notre Dame Philosophical Reviews: An Electronic Journal*.
Retrieved from file:///C:/Users/RAC/Documents/Knowledge.pdf

Lam, J., Li, K.C., Cheung, S.K.S. & Wang, F.L. (2013). *Knowledge sharing through technology*. Springer Nature.

Lappin, J., Jackson, T., Matthews, G. & Ravenwood, C. (2021). Rival records management models in an era of partial automation. *Archival Science, 21*, 243–266. https://doi.org/10.1007/s10502-020-09354-9

Leedy, P.D. (1974). *Practical research: planning and design*. Macmillan

Lloyd, B. (1996). Knowledge management: the key to long-term organizational success. *Long Range Planning, 29*(4), 576-80.

Maier, R. (2002). *Knowledge management system*. Springer Nature.

McCombes, S. (2020). Descriptive research. Scibbr. Retrieved from
https://www.scribbr.com/methodology/descriptive-research/

Mehrizi, M. H. R. & Bontis, N. (2009). A cluster analysis of the KM field. *Management decision, 47*(5), 792-805

Mobus, G.E. (2022). Capturing knowledge of the system. In: *Systems science: Theory, analysis, modelling, and design*. Springer. https://doi.org/10.1007/978-3-030-93482-8_8

Motowidlo, S. J. (2003). Job performance. In W. C. Borman, D. R. Ilgen, & R. J. Klimoski (Eds.), Handbook of psychology. *Industrial and organizational psychology, 12*, 39–53.

Murphy, K.R. (2019). Performance evaluation will not die, but it should. *Human Resource Management Journal, 30*(1), 13-31. https://doi.org/10.1111/1748-8583.12259

National Academies of Sciences, Engineering, and Medicine. (2007). *Preserving and using institutional memory through knowledge management practices*. The National Academies Press. https://doi.org/10.17226/14035.
Nikiforow, N., & Wagener, S. (2020). The contextual effect of completion on the effectiveness of performance feedback. *Journal of Business Economics*, 91, 61–90. https://doi.org/10.1007/s11573-020-00996-w

Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation. *Organization Science*, 5(1), 14-37.

Nonaka, I., & Toyama, R. (2015). The Knowledge-creating theory revisited: Knowledge creation as a synthesizing process. In: Edwards, J.S. (eds) *The essentials of knowledge management*. Palgrave Macmillan. https://doi.org/10.1057/9781137552105_4

North, K. & Kumta, G. (2018). *Knowledge management*. Springer Nature

Organ, D.W. (1988). *Organizational Citizenship Behavior: The Good Soldier Syndrome*. Lexington Books

Parsaye, K. (1989). *Intelligent databases*. Wiley.

Paulus, P.B. (1983). Group influence on individual task performance. In: Paulus, P.B. (eds) *Basic group processes*. Springer. https://doi.org/10.1007/978-1-4612-5578-9_5

Richman, N. (2015). Human resource management and human resource development: Evolution and contributions. *Creighton Journal of Interdisciplinary Leadership, 1*(2), 120-129.

O'Dell, C., & Grayson, C.J. (1998). *If only we knew what we know: identification and transfer of internal best practices*. *California Management Review* 40(3), 154–174.

Okoye, P.V.C. & Ezejiofor, R. A. (2013). The effect of human resources development on organizational productivity. *International Journal of Academic Research in Business and Social Sciences, 3*(10).

Polanyi, M. (1966). *The tacit dimension of knowledge*. Routledge.

Prasad, B. (2001). Languages for knowledge capture and their use in the creation of smart models. In: Roy, R. (eds) *Industrial knowledge management*. Springer. https://doi.org/10.1007/978-1-4471-0351-6_32

Rezaei, F., Khalilzadeh, M. & Soleimani, P. (2021). Factors affecting knowledge management and its effect on organizational performance: Mediating the role of human capital. *Advances in Human-Computer Interaction, 221*. https://doi.org/10.1155/2021/8857572

Rollett, H. (2003). Creating knowledge. In: *Knowledge management*. Springer. https://doi.org/10.1007/978-1-4615-0345-3_5

Semertzaki, E. (2011). *Knowledge Management*. In Special libraries as knowledge management centers. Elsevier.

Silong, A.D., Daryoush, Y., Omar, Z., & Othman, J. (2013). Improving job performance: Workplace learning is the first step. *International Journal of Education & Literacy Studies, 1*(1). http://dx.doi.org/10.7575/aiac.ijels.v.1n.1p.100

Smith, M. K. (2001, 2011). Donald Schön: learning, reflection and change. *The encyclopedia of pedagogy and informal education*. Retrieved from https://infed.org/mobi/donald-schon-learning-reflection-change/.
Smith, M. K. (2001, 2013). Chris Argyris: theories of action, double-loop learning and organizational learning. *The encyclopedia of pedagogy and informal education*. Retrieved from https://infed.org/mobi/chris-argyris-theories-of-action-double-loop-learning-and-organizational-learning/.

Society of American Archive (n.d). *Institutional Memory*. Retrieved from https://dictionary.archivists.org

Spector, P. E., & Fox, S. (2005). The stressor-emotion model of counterproductive work behavior. In S. Fox & P. E. Spector (Eds.), *Counterproductive work behaviour: Investigations of actors and targets* (pp. 151–174). American Psychological Association. https://doi.org/10.1037/10893-007

Spector, P. E., Fox, S., Penney, L. M., Bruursema, K., Goh, A., & Kessler, S. (2006). The dimensionality of counterproductivity: Are all counterproductive behaviours created equal? *Journal of Vocational Behavior, 68* (3), 446-460. https://doi.org/10.1016/j.jvb.2005.10.005

Spender, J.C. (2015). *Knowledge Management: Origins, history, and development*. In *for Advances in Knowledge Management*. Springer.

Stachera-Włodarczyk, S. (2019). *The concept of knowledge management in modern enterprises*. *Sciendo, 1*(1), 987-995. https://doi.org/doi: 10.2478/czoto-2019-0125

Stein, E. W., & Zwass, V. (1995). Actualizing organizational memory with information systems. *Information Systems Research, 6*(2), 85–117. http://www.jstor.org/stable/23011005

Stratton-Lake, P. (2020). Intuitionism in ethics. *Stanford Encyclopedia of Philosophy*. Retrieved from https://plato.stanford.edu/entries/intuitionism-ethics/

Taibah, D., & Ho, T. (2023). Improving Gen Z contextual work performance through Langford's leadership big 5 and structural empowerment. In: Alareeni, B., Hamdan, A. (eds) *Explore business, technology opportunities and challenges after the COVID-19 pandemic*. Springer. https://doi.org/10.1007/978-3-031-08954-1_76

Tuomi, I. (1999). *Data is more than knowledge: Implications of the reversed hierarchy for knowledge management and organizational memory*. In Proceedings of the Thirty-Second Hawaii International Conference on Systems Sciences, IEEE Computer Society Press, Los Alamitos, CA, 1999

Turanligil, F.G. (2019). *Work-life balance in the tourism industry*. IGI Global Publisher of Timely Knowledge. https://doi.org/10.4018/978-1-5225-5760-9.ch010

United Nations (n.d). *Institutional memory*. Retrieved from https://archive.unescwa.org

Urdan, T. (2001). Contextual influences on motivation and performance: An examination of achievement goal structures. In: Salili, F., Chiu, C.Y., Hong, Y.Y. (eds) *Student motivation*. Springer. https://doi.org/10.1007/978-1-4615-1273-8_9

Valamis (2022). *Knowledge Management*. Retrieved from https://www.valamis.com/hub/knowledge-management

Valeri, M. (2024). *Knowledge management and knowledge sharing*. Springer Nature.
van den Hooff, B., Elving, W., Meeuwsen, J.M., & Dumoulin, C. (2003). Knowledge sharing in knowledge communities. In: Huysman, M., Wenger, E., Wulf, V. (eds) *Communities and technologies*. Springer. https://doi.org/10.1007/978-94-017-0115-0_7

Viswesvaran, C. (2002). *Assessment of individual job performance: a review of the past century and a look ahead*. In: Anderson N, Ones DS, Sinangil HK, Viswesvaran C, eds. Handbook of Industrial, Work and Organizational Psychology. Vol 1: Personnel Psychology. Sage Publications Ltd; 110–126

Wang, H. & Meng, X. (2019). *Transformation from IT-based knowledge management into BIM-supported knowledge management: A literature review*. ScienceDirect.

Ward, M. (2007). *Preserving and Using Institutional Memory Through Knowledge Management Practices*. Washington: National Academic Press.

Wei Choo, C., Furness, C., Paquette, S., van den Berg, H.A., & Detlor, B. (2006). *Working with information: Information management and culture in a professional services organization*. Journal of Information Science, 32(6), 491-510. https://doi.org/10.1177/0165551506068159

Wigglesworth, G. (2008). Task and performance-based assessment. In: Hornberger, N.H. (eds) *Encyclopedia of language and education*. Springer. https://doi.org/10.1007/978-0-387-30424-3_171

Wilkinson, D. (2000). *The researcher's toolkit: The complete guide to practitioner research*. Routledge

Wobeser, G.A. (1994). Records and record keeping. In: *Investigation and management of disease in wild animals*. Springer. https://doi.org/10.1007/978-1-4757-5609-8_8

Xing, F., Cambria, E., & Welsch, R. (2019). Storage and update of knowledge. In: *Intelligent asset management*. Springer. https://doi.org/10.1007/978-3-030-30263-4_6

Zammit, J.P., Gao, J., & Evans, R. (2016). A framework to capture and share knowledge using storytelling and video sharing in global product development. In: Bouras, A., Eynard, B., Foufou, S., Thoben, KD. (eds) *Product lifecycle management in the era of the Internet of things*. Springer. https://doi.org/10.1007/978-3-319-33111-9_24

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