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The critical human behavior
factors and their impact on
knowledge management
system–cycles
Ameer Sardar Rashid
Business Information Technology, University of Sulaimani,
Sulaimani City, Iraq
Kifah Tout
Lebanese University, Beirut, Lebanon, and
Ammar Yakan
Jinan University, Tripoli, Lebanon
Abstract
Purpose –This study attempts to find out the impact of the human behavioral factors (HBFs) including
emotion, factors of deals with processes within and between groups as well as with the impact of these
processes on individuals’attitudes and moods, personality, beliefs and values, perception and motivation on
the knowledge management system–cycles (KMS-Cs) which comprises sharing; it considers findings from
social psychology and discusses their applicability in knowledge management (KM) research and practice;
social psychological concepts that strongly influence knowledge processes in organizations are first
introduced. It is creating, storing and transferring of academic staff while analyzing the certificates on the
acquired behaviors and knowledge which were involved in each of the communications, decision-making,
creating new ideas, providing new knowledge, idea diversity, progressing, enhancing and improving the
organization, using up-to-date technology and proactivity between the independent and dependent variables.
In order to test the study hypotheses, data of 219 respondents working at the University of Sulaimani were
collected. The results of the study revealed the academic staff psychology effect on KMS-Cs with a substantial
relationship between the HBFs and cycles of KM during academic and administrative work. Also, it surged
their academic staff efficiency through a conceptual model called KM behavior (KMB); knowledge management
systems (KMSs) are applications of the organization’s communication and information systems (CISs) designed
to support the various KM processes. They are generally not technologically distinct from the CISs but rely on
databases, such as those designed to put organizational participants in contact with recognized experts in a
variety of topic areas (Yakan, 2008; Al Hayani, 2020). Information technology (IT) used in KM is known as KMS.
In general, KMSs are computer systems that enable organizations to manage knowledge that is efficient and
cost-effective. KMS is a class of information systems applied to the management of organizational knowledge.
KMS is a system that increases organizational performance by enabling employees to make better decisions
when applying their knowledge as part of their daily business activities.
Design/methodology/approach –Research hypotheses Ho: HBFs and KMS-Cs are not correlated. H1: HBFs
have no impact on KMS-Cs. H2: certificates have no effect on HBFs and KMS-Cs. Data collection and sample
demographics: in this study, the relevant information for assessing the HBFs and their impact on the KMS-Cs
was gathered through a questionnaire survey. The HBF was measured using the following items: emotions,
attitudes and moods, personality, beliefs and values, perception and motivation. The knowledge management
cycle (KMC) was measured using the following items: knowledge sharing, knowledge creation, knowledge
storing and knowledge transfer. The total number of employees at the University of Sulaimani, Sulaimaniya, at
the time of data collection (May, 2019) was 117. Since the information available on the number of academic staff
at the University of Sulaimani is according to the departments, this study employed a proportionate stratified
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The author would like to thank the anonymous reviewers for their valuable comments and suggestions
to improve the quality of the article.
Funding: The author received no specific funding for this study.
Conflicts of interest: The author declares that they have no conflicts of interest to report regarding the
present study.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1463-7154.htm
Received 19 November 2020
Revised 2 December 2020
24 December 2020
19 January 2021
Accepted 28 January 2021
Business Process Management
Journal
© Emerald Publishing Limited
1463-7154
DOI 10.1108/BPMJ-11-2020-0508
random sampling method to select the number of academic staff from colleges and departments at the
University of Sulaimani. The total number of academic staff at the University of Sulaimaniis is 1,740. Therefore,
the appropriate sample size for this study is at least 5% of the population (i.e. 90 respondents) (Langham, 1999).
The questionnaire was administered personally through Google Form where questionnaires were collected
from the respondents. Examination of the response rate shows that the response rate for this study is excellent.
The research instrument consists of two main sections. The first section incorporates a nominal scale to
identify respondents’demographic information. The second section uses the five-point Likert-type scale from
fully disagree (1) to fully agree (5). All of the measurement items went through backward translation (translated
from English into Korean and back into English) to ensure consistency and to resolve discrepancies between
the two versions of the instrument (Mullen, 1995; Aldiabat et al., 2018). The participants were almost equal in
terms of gender, 59 were males and 58 were females. The certificate for each one of the PhD, MSc and BSc was
39 participants. The number of participants whose age was between 23 and 32 years was 26, between 33 and 42
years was 50, between 43 and 52 years was 29, between 53 and 62 years was 10 and above 62 years was 2.
Validity and reliability: in addition to the steps mentioned earlier to assess the validity and reliability of the
study tools, a further test was executed. The reliability to measure many inner variables in regularity,
Cronbach’s alpha is generally utilized in order to evaluate it and the value should exceed 0.70 for each variable
(Alharbi, and Drew, 2014) (Table 1). Cronbach’s alpha regards to the test of reliability of a skill for each of the
HBF and KMC.
Findings –The study is considered the organizations relationship between HBFs and KMS-Cs and the
influence of the factors on the cycles. So, the new ideas emerge to create knowledge about product development
among employees. The group experience works as an essential element (Grimsdottir and Edvardsson, 2018).
Knowledge resides in human minds and, as a result, employee behavior and explanatory skills are the key
drivers of KM (Prieto and Revilla, 2005). First, knowledge creation, sharing and storing is increased when the
organization has motivated the employees. Second, knowledge is shared rapidly when the employees have
owned a strong personality, new idea, impression and perception. Third, both the beliefs and values lead to
creating new knowledge when the employees obtained it inside the organization. Then, the emotion factors
illustrated the weak relation with knowledge sharing, knowledge creation, knowledge storing and knowledge
transfer.
Originality/value –Knowledge is considered as a great factor in achieving organizational goals (Hammami
and Alkhaldi, 2017). Therefore, this study has explained that knowledge is an essential element for employees
and organizations. Furthermore, it progresses the skills and capabilities during the job. Nevertheless, this
knowledge is impacted through human behaviors because the behavior evolves crucial factors that help the
academic staff to create, share, store and transfer the knowledge through motivation, perception, personality,
attitudes, moods, beliefs and values. Knowledge sharing is a culture of social interaction involving the
exchange of knowledge, experiences and skills of employees across the organization (Zugang et al., 2018).
Organizations need to pay particular attention to the method of communication used where knowledge
becomes useless if employees are not encouraged to study and use it in their daily activities (Boatca et al., 2018).
Knowledge sharing can be achieved by taking into account technical standards (KMS), social standards
(environment) and personality (motivation) (
€
Ozlen, 2017).
Keywords Knowledge management, Organizational behavior, Psychology, Human behavioral factors,
Knowledge management system–cycles
Paper type Research paper
1. Introduction
In an age of turbulent dynamic environment, organizations face stiff and unpredictable
competitions. Knowledge management (KM) plays a vital role in assisting organizations to
understand the rapidly changing environments and withstand threats while investing in
opportunities. Knowledge communication is often computer mediated: knowledge providers
do not directly share information with other people but contribute it to some kind of
repository. It is discussed what computer-mediated support can contribute to KM processes
in organizations with respect to both knowledge sharing and knowledge processing. The
organization develops its strategies based on a strong, flexible business structure that is
updated with changing environmental variables. We consider findings from social
psychology and discuss their applicability in KM research and practice. Social psychology
deals with processes within and between groups. Today organizations need to reach
knowledge through compiling information with experience which is available in the mind of
the individuals that are impacted by many human behaviors and support them to be wise to
make decisions. Thereby, human behavior is the study of the actions and factors of
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individuals in organizations where it seeks to replace the scientific method that relies on
expertise in the interpretation of individuals. Human behavioral factors (HBFs) are also
concerned with behavior related to the performance of work in organizations. Thus,
knowledge is generally considered that it requires a belief and is related to the reliability of the
method by which belief is produced and the notions of justification guaranteed or right to
believe (Davies, 2015). Knowledge brings benefits to both the owners and employees of an
organization. Time saved by locating and accessing information makes employees more
productive in developing their own skills (Roblek et al., 2013). The effective decisions, based
on quality knowledge from many sources of knowledge, tend to minimize stress and increase
their credibility and value. Therefore, knowledge is a mixture of experience, values,
contextual information and intuition that provides the reference model for evaluating and
capturing new information and experiences (Scalera and Serra, 2014). Also, the information is
transferred to knowledge once is processed in the minds of individuals. That information
becomes knowledge as soon as it is expressed and presented in the form of text, graphics,
words or other symbolic forms (Koivisto, 2018). KM is a prerequisite for the competitiveness
of enterprises in the modern business environment. Knowledge development has become
important for organizations to stay competitive (Xue, 2017). KM organizes and implements a
systemic process of acquiring, organizing and exchanging knowledge among employees to
effectively use knowledge (Karadsheh et al., 2009). KM initiatives are used to systematically
leverage information and expertise to improve responsiveness, innovation, skills and
organizational effectiveness.
KM has become critical. Information technology (IT) is one of the major organization-
sponsored KM initiatives but not enough to build learning skills (Prieto and Revilla, 2005).
Also, it has turned into a world apparatus frequently utilized by people, associations,
governments and intergovernmental associations for individual or authority exercises
(Aldiabat et al., 2018;Aldiabat et al., 2019;Ahmad et al., 2018). Knowledge and KM have a
strategy for achieving organizational goals. Recently, both of them have become vital local
and global problems in many organizations due to advanced economic competitions. KM can
coordinate and collaborate to improve organizational performance by creating, sharing,
maintaining and applying knowledge (Mohajan, 2017;Al Hayani and Ilhan, 2020a,b). The
processes of KM involve knowledge acquisition, creation, refinement, storage, transfer,
sharing and utilization. The KM function in the organization operates these processes,
develops methodologies and systems to support them and motivates people to participate in
them (King, 2009). Generally, KM process can be divided into four major processes and these
can be further classified into subprocesses (Anand and Singh, 2011): (1) knowledge capture
and creation is a process in which knowledge identification, capture, acquisition and creation
are done. (2) Knowledge organization and retention is a process in which knowledge in tacit
form may be codified in an understandable form to the extent possible. After doing this,
knowledge needs to be categorized and stored in repositories in a standard format for later
use. (3) Knowledge dissemination is a process which involves knowledge sharing among all
within the organization both tacit and explicit form. A combination of incentives and a
cooperative culture are the main supporting factors of knowledge dissemination. Also, (4)
knowledge utilization is a process of the application and use of knowledge in the organization
value-adding process. Here are the four stages of KM: first: process: create and generate;
second: technology: represent and store; third: knowledge: access, use and reuse. Finally,
people: disseminate and transfer (Mathew et al., 2012). KM is passed into many cycles like
sharing, creating, storing and transferring; nevertheless, it needs many channels to exchange
and transmit the knowledge, whether implicit or explicit knowledge between organizations,
employees or from one another. This study confirmed how the academic staff depends on
these cycles of KM with their behavioral factors at the University of Sulaimani. Therefore,
the people are the crucial factor in a KM initiative because without their involvement, the
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other two elements have little meaning (Mathew et al., 2012;Khalaf and Abdulsahib, 2019;
Rane and Umesh, 2020). The people bring to their work attitudes, skills, habits and
personalities that can be strengths or weaknesses depending on the requirements of the task.
Individual characteristics influence the behavior in a complex and significant way. Their
effects on task performance may be negative and may not always be mitigated by the design
of tasks (Health and Safety Executive, 2009). Therefore, organizational behavior (OB) is a
field of study devoted to the recognition, explanation and subsequent development of the
attitudes and behaviors of individuals (individuals and groups) within organizations.
Meanwhile, it is based on scientific knowledge and applied practices. OB is a continuous cycle
of recognition of areas of concern, explaining the short- and long-term implications of
each behavior and continuously developing best practices and strategies that can help an
organization become a robust, successful and dynamic entity (Kaifi and Noori, 2010). OB
studies the impact of individuals, groups and structure on behavior within organizations,
with the goal of applying this knowledge to improve the effectiveness of an organization. It is
a separate area of expertise with a common body of knowledge (Stephen and Timothy, 2013).
There are few studies that have been carried out to determine the HBFs affecting
knowledge management system–cycles KMS-Cs. There is a wide research gap concerning
the HBF role in the KMS-C. It considers most human factors related to the work inside the
institutions. This study is, therefore, crucial in terms of defining the relationship of the
academic staff human factors with the knowledge management chain (KMC). The main
contribution of this study using a survey distribution is to understand whether the key HBFs
of the academic staff (i.e. emotion, attitudes and moods, personality, beliefs and values and
motivation) are innate or required behaviors during the process of work in order to know to
what degree these factors have an influence on the creation, storage, sharing and transferring
the knowledge both implicit and explicit in the University of Sulaimani.
Finally, this study aimed at understanding and expounding many characteristics
involved with the adoption and efficiency of HBFs by the academic staff at the University of
Sulaimani and their effects on the KMS-Cs.
2. Literature review
Knowledge is a very personal concept and should not be used or stored unless for documents,
computer files and organizational information. Knowledge ranges from workers’experience to
technical innovations and economic changes. This is very important when considering the
timing and context of knowledge transfer. Organizations need to pay special attention to
management style and organizational culture. Employees need to feel important, respected and
motivated to learn and achieve higher levels of personal development, to deal with major
changes suchas work environment interventions (Boatca et al.,2018). Knowledge is an essential
source of sustainable competitive advantage for many organizations as it is considered one of
the most powerful factors in achieving organizational results. By supporting and strengthening
knowledge, knowledge flows smoothly to overcome resistance to change, and it reflects in all
business processes to achieve goals, improve business performance, increase success rates and
improve quality (Hammami and Alkhaldi, 2017). Knowledge is now a strategic factor in
creating a sustainable competitive advantage for the organization’s authorities, acquiring
knowledge only as an asset does not create value though. Sharing and disseminating
knowledge with other members inside and outside the organization will create space for
creating new and valuable knowledge assets (Gholipour et al.,2018). KM is a systematic
process, or set of practices, used by organizations to identify, capture, store, create, update,
represent and distribute knowledge for use, awareness and learning inside and outside the
organization (Stocking, 2018). KM is about developing organizational intelligence by enabling
people to improve the way they capture, share and use knowledge. This involves employing the
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ideas and experience of employees, customers and suppliers to upgrade organizational
performance (Kumar et al., 2014). Knowledge sharing is a collective behavior involving the
sharing of information. Knowledge sharing is the process by which people share their
knowledge and create new knowledge. The exchange of knowledge between individuals is a
process by which the knowledge of the individual is transformed into knowledge that allows
others to understand and use (Zugang et al., 2018;Aldiabat et al., 2019). Knowledge sharing
is proposed as a key element in KM to maintain organizational competitiveness. Knowledge
sharing practices contribute toorganizational and individual effectiveness through (1) qualified
knowledge management systems, (2) an enabling environment for knowledge sharing and (3)
organizational motivation for knowledge sharing. KM systems, appropriate knowledge-
sharing environment and strong organizational motivation for knowledge sharing affect
knowledge sharing. Successful sharing of knowledge increases the productivity of individuals
and organizations (
€
Ozlen, 2017;Rane and Bhadade, 2020a,b,c,d). Knowledge creation is a
dynamic social and collaborative process of interactions between explicit and implicit
knowledge (Buqais et al., 2018). Knowledge storage is the process of organizational memory
formation, in which knowledge is formally stored in physical systems that are informally
maintained as values, rules and beliefs associated with culture and organizational structure
(Buqais et al., 2018). It is a process of integrated knowledge exchange between the sender and
the recipient. Knowledge transfer is a process of donation and collection of knowledge between
different units of knowledge of the company (Al-Qdah et al.,2018;Rane and Bhadade, 2020a,b;
Khalaf and Abdulsahib, 2019;Xiang et al.,2021). Knowledge transfer is the process by which
one unit of an organization, such as a group or department, is affected by the experience of
another. Knowledge transfer is related to the effective readiness of people to live in a society,
namely, affect and be affected by these society members (member–member and member–
group relationships) (Alkhaldi, 2018). OB is the area of study that examines the influence of
individuals, groups and structures on behavior within organizations. Social life is largely
determined by organizations. Businesses, banks, schools, hospitals, sports clubs and
universities are all organizations (Jacobs, 2018). OB is the study of what people think, feel
and do within and around institutions. It examines employee behavior, decisions, perceptions
and emotional reactions. It examines how individuals and teams of organizations relate to each
other and their counterparts in other organizations (McShane and Von Glinow, 2018). There are
two basic typesof assumptions about OB. It is the nature of people and organizations. The basic
assumption about the nature of people includes individual differences, individual integrity and
enthusiastic behavior, individual value, selective perception and a desire to participate. The
basic assumption about the nature of organizations includes social order, mutual interests and
moral attitude (Basnet, 2019). Personality affects motivation through personal, emotional
stability, level of aggression and characteristics of an open mind or open-minded employee. It
has also been found that personality has a significant impact on OB, which affects
organizational tolerance, ergonomics and workethics (Nuckcheddy, 2018). Human factors have
been an area where psychologists have prevailed, and safety has been a discipline dominated
by engineers. However, this picture began to change; engineers and other professional groups
study, research and apply human factors, and psychologists have gone beyond experimental
and theoretical studies of human decision-making, behavior, etc. (Karanikas, 2017). The implicit
knowledge that a person acquires reaches to the beliefs at some point when a person obtains a
set of information that represents evidence and assists the person to reach a degree of truth. In
constructing this, the cognitive pyramid according to the proposed Islamic model can be
envisaged.This is also consistent with the researcher’s conclusion that the goal of science is “to
reach the truth to the heart.”As forthe beliefs, it has been referred to as a wordof beliefs within
the concept presented. This certainty does not occur with all people though. That is, if people
acquire certain knowledge, it will not necessarily mean the certainty of this science (Bashar,
2017). The critical point for fierce competition and survival of the organizations is the ability of
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management of employees’attitude and directing their behaviors toward organizational
purposes (Tas
¸kıran, 2019).
3. Human behavioral factors (HBFs)
Ajzen and Fishbein consider behavioral intentions as the immediate antecedents of the
corresponding manifest behaviors. Therefore, the best prediction of behavior is the intention
of a person to perform this behavior. The apparent simplicity of this approach, however, is
somewhat misleading (Holdershaw and Gendall, 2008). The Human Factors and Ergonomics
Society defines human factors as “a scientific discipline concerned with the understanding of
the interactions between humans and other elements of a system, and the profession that
applies the theory, principles, data and methods to the design in order to optimize human
well-being and the overall performance of the system”(Boatca and Cirjaliu, 2015).
The Human Factors and Ergonomics Society (hfes.org) is a professional organization that
promotes the discovery and exchange of knowledge about the capabilities and limitations of
humans to improve the design of systems and devices. The society is the meeting place for
research, teaching and practice; knowledge generation and knowledge translation (Lund
et al., 2005).
Human factors refer to environmental, organizational and occupational factors, as well as
human and individual characteristics that influence workplace behavior in ways that affect
health and safety. A simple way to take into account human factors is to consider three
aspects: work, the individual and the organization and their impact on people’s health and
safety behavior (Flin et al., 2009).
Psychology is a study of behavior and mental processes. Although it includes many
subdisciplines and theoretical perspectives whose methods, scope and fields of intervention
vary, the modern practice of psychology, both in academia and applied, uses scientific rigor in
the examination of human behavior (Caponecchia, 2012). Psychologists tend to study thought
and behavior in a rather pure and contactless environment (Wickens et al.,1997). Psychology is
the scientific study of mind and behavior. One of the most fundamental principles of integration
in the discipline of psychology is its focus on behavior, yet this is not often clearly explained to
students; effect, cognition and motivation are critical and essential; however, they are often
better understood and made relevant through their links to behavior (Buenaflor et al.,2013).
To understand the principles of OB, it is indispensable to emphasize the significance of
basic psychological contributions in defining (emotion and moods, attitudes, personality,
neliefs and values, perceptions and motivations). The human factors are as follows:
3.1 Emotions
Emotion refers to what extent to which an individual experiences the emotions in response to
a wide array of stimuli, intensely, and for a prolonged period (Lannoy et al., 2014). Emotions
are intense feelings directed at someone or something (Stephen and Timothy, 2017).
3.2 Attitudes and moods
Attitudes are evaluative statements, either favorable or unfavorable about objects, people or
events. They reflect how we feel about something or evaluative statements or judgments
concerning objects, people or events. Moods are less intense feelings than emotions and often
arise without a specific event acting as a stimulus (Stephen and Timothy, 2017).
3.3 Personality
Personality is the overall combination of characteristics that captures the unique nature of a
person as that person reacts to and interacts with others (Schermerhorn, 2010).
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3.4 Beliefs and values
Belief is thought that a person’s attitudes are formed in response to the acquisition of certain
beliefs. Beliefs are therefore the fundamental elements on which the conceptual framework of
Ajzen and Fishbein is based.
Values are broad preferences concerning appropriate courses of action or outcomes
(Schermerhorn, 2010).
3.5 Perception (cognitive)
Perception is defined as the cognitive process by which an individual selects, organizes and
gives meaning to environmental stimuli. Through perception, individuals attempt to make
sense of their environment and the objects, people and events in it (Ivancevich et al., 2014).
3.6 Motivation
It is the processes that account for an individual’s intensity, direction and persistence of effort
toward attaining goal events (Stephen and Timothy, 2017).
4. Knowledge management system –cycles (KMS-C)
Knowledge management systems (KMSs) are applications of the organization’s
communication and information systems (CISs) designed to support the various KM
processes. They are generally not technologically distinct from the CIS but rely on databases,
such as those designed to put organizational participants in contact with recognized experts
in a variety of topic areas (Yakan, 2008). IT used in KM is known as KMS. In general, KMSs
are computer systems that enable organizations to manage knowledge that is efficient and
cost-effective. KMS is a class of information systems applied to the management of
organizational knowledge. KMS is a system that increases organizational performance by
enabling employees to make better decisions when applying their knowledge as part of their
daily business activities (Assegaff and Dahlan, 2013).
From the definition of function of KMS above, we have highlighted two of the elements
that should exist in KMS. First, KMS should have the ability to connect people, it means using
hardware and software. KMS enables people to support interaction among people in
communities, communicate with them and making collaboration. Another KMS function is to
manage information/knowledge to assist people to reuse knowledge and make a better
decision with their knowledge.
The KMC is the transformation of knowledge information cycle that can be envisaged as
route of information organization. The KMC is a continuous process where information is
identified, obtained, refined, shared, used, stored and divested (Mohajan, 2017). There are
several KMCs: Wiig, Nonaka & Takeuchi’s Knowledge Spiral Model, Meyer and Zack,
Bukowitz and Williams and McElroy.
4.1 The Wiig KMC
This cycle, invented in 1993, is characterized by four major phases: “build, hold, pool, and
apply (Kayani and Zia, 2012):
(1) Building knowledge: acquire, analyze, recreate, synthesize, codify, model, organize the
new or/and existing knowledge, (2) holding knowledge: remember, accumulate and implant,
record in repositories of knowledge for future use, (3) knowledgepooling: coordinate, accumulate,
renovate, generate, access and retrieve the knowledge and (4) applying knowledge: complete
tasks, survey, describe, select, scrutinize, create, evaluate, decide and execute the knowledge.
4.2 Nonaka and Takeuchi’s Knowledge Spiral Model
This cycle was invented in 1944. Knowledge creation is in the conversion of tacit knowledge
into explicit knowledge and vice versa (Alkhaldi, 2015). Organizational knowledge creation is
adapted from a single transfer to multiple transmissions of explicit or tacit knowledge
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exchanges inside of a community of practice. These exchanges intermingle between explicit
and tacit knowledge inside the process creating value. The exchanges are navigated through
cognitive developed four-stage metamorphosis processes: socialization, externalization,
combination and internalization (Spangler et al., 2015). Socialization (tacit to tacit) is
connected with theories of organizational culture. While combination (explicit to explicit), is
rooted in information processing and internalization (from explicit to tacit), has associations
with organizational learning. Conversely, the concept of externalization (from tacit to explicit)
is not well developed. The limited analysis that does not exist is from the point of view of
information creation (Nonaka, 1994).
4.3 Meyer and Zack KMC
This cycle was invented in 1996. Meyer and Zack suggested that the production management
model is the best example to describe the KMC. Production involves the necessary
technologies, facilities and processes. The research and knowledge involved in the production
process would follow similar patterns of transformation and accumulate in a knowledge
repository where additional indexing links and cross-references would be applied to ensure
the integrity of the organizational knowledge as a whole. Zack’s KMC is as follows (Yakan
and Tout, 2011;Yakan, 2008):
First: knowledge acquisition: looks for the knowledge scope, breadth, depth, credibility,
accuracy, timeliness, relevance, cost, control and exclusivity. Second: knowledge refinement:
performs requisite modification and enhancement for efficient knowledge use. Third:
knowledge storage/retrieval: a vital stage of this KMC because it creates a connection
between the first two stages. Storage of information can be physical (hard notes, files) or
digital (soft files, database). Then, knowledge distribution: distribution means providing
information to users through various mediums (emails, telephone, fax and letters). And
finally, knowledge presentation and use: use the obtained information in the daily operations
of group and organization for better future output.
4.4 The Bukowitz and Williams KMC
This cycle was invented in 2000 and explains how companies generate, maintain and deploy a
strategically correct stock of knowledge to create value. According to this model, knowledge
consists of repositories, relationships, technologies, communication infrastructure, functional
skill sets, process know-how, environmental responsiveness, organizational intelligence and
external sources. These steps are aimed at long-term processes to adapt intellectual capital to
strategic needs. The seven steps described in Bukowitz and Williams KMC are getting
knowledge, using knowledge, learning, contributing to knowledge, assessing knowledge,
building and sustaining knowledge and divesting knowledge (Mohajan, 2017).
In the tactical stage, knowledge goes through four phases (Yakan and Tout, 2011):
(1) Get: where knowledge is assimilated from various sources.
(2) Use: focuses on best combining information creatively to foster organizational innovation.
(3) Learn: an organizational memory is created to promote organizational learning both
on the individual and group levels. Organizational learning is essential for knowledge
creation based on practices and lessons.
(4) Contribute: it is the knowledge transfer from employees’heads to the organizational
memory.
It is at this phase where individual knowledge is disseminated and shared across the
organization through a properly managed organizational memory that maintains knowledge
attribution, authorization and tracking.
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The strategic stage reveals a group and organizational interference on the total individual
contributions (Mohajan, 2017):
(1) Assess stage: it deals more with the group and organizational level. It is done for
intellectual capital. Assessment means the review of present intellectual or corporeal
assets (information, knowledge) against the future needs of individuals, groups and
organizations.
(2) Build and sustain step: it ensures that the organization’s future intellectual capital
will keep the organization viable and competitive by employing resources.
(3) Divest step: it is the final step of Bukowitz and Williams KMC. This is a let-go stage
wherein if the organization can better use their intellectual capital externally, it
should have means for it.
4.5 The McElroy KMC
This cycle was invented in 2003 and focuses on producing knowledge by formulating,
codifying and evaluating a problem claim. The last part of the cycle focuses on (Islam et al.,
2017;Hammami and Alkhaldi, 2017) (1) knowledge integration: dissemination, research,
teaching, knowledge sharing. This KMC focuses on filtering the knowledge generated to
ensure that it is relevant to the business, which contrasts with the traditional document
management that stored everything. (2) Organizational knowledge: organizational
knowledge is viewed as an inclusive business practice that focuses on the knowledge life
cycle, construction, capture, coding/decoding, communication and capitalization, the
construction and maintenance of flexible and fragmented knowledge infrastructures, the
relationship structure and the strategy with knowledge, ingenuity.
5. Research methodology and result
5.1 Research hypothesis
H0. HBFs and KMS-Cs are not correlated.
H1. HBFs have no impact on KMS-Cs.
H2. Certificates have no effect on HBFs and KMS-Cs.
5.2 Data collection and sample demographics
In this study,the relevant information for assessing the HBFs and their impacton the KMS-Cs
was gathered through a questionnaire survey. The HBF was measured using the following
items: emotions, attitudes and moods, personality, beliefs and values, perception and
motivation. The KMC was measured using the following items: knowledge sharing, knowledge
creation, knowledge storing and knowledge transfer. The total number of employees at the
University of Sulaimani, Sulaimaniya, at the time of data collection (May 2019) was 117.
Since the information available on the number of academic staff at the University of
Sulaimani is according to the departments, this study employed a proportionate stratified
random sampling method to select the number of academic staff from colleges and
departments at the University of Sulaimani. The total number of academic staff at the
University of Sulaimaniis is 1,740. Therefore, the appropriate sample size for this study is at
least 5% of the population (i.e. 90 respondents) (Langham, 1999;Milind and Umesh, 2017).
The questionnaire was administered personally through Google Form where questionnaires
were collected from the respondents. Examination of the response rate shows that the
Knowledge
management
system - human
behavior
response rate for this study is excellent. The research instrument consists of two main
sections. The first section incorporates a nominal scale to identify respondents’demographic
information. The second section uses the five-point Likert-type scale from fully disagree (1) to
fully agree (5). All of the measurement items went through backward translation (translated
from English into Korean and back into English) to ensure consistency and to resolve
discrepancies between the two versions of the instrument (Mullen, 1995;Aldiabat et al., 2018).
The participants were almost equal in terms of gender, 59 were males and 58 were females.
The certificate for each one of the PhD, MSc and BSc was 39 participants. The number of
participants whose age was between 23 and 32 years was 26, between 33 and 42 years was 50,
between 43 and 52 years was 29, between 53 and 62 years was 10 and above 62 years was 2.
5.3 Validity and reliability
In addition to the steps mentioned earlier to assess the validity and reliability of the study
tools, a further test was executed. The reliability test concerns to measure many inner
variables in regularity, Cronbach’s alpha is generally utilized in order to evaluate it and the
value should exceed 0.70 for each variable (Alharbi and Drew, 2014). Table 1. Cronbach’s
alpha regards to the test of reliability of a skill for each of the HBF and KMS-C.
5.4 Perception about human behavioral factors (HBFs)
This section provides results of the perceptions of the academic staff at the University of
Sulaimani regarding the HBFs that exist in their organization. These findings are based on
the strength of the employees’agreement with the items, which represent the different types
of HBFs that exist in an organization based on the previously discussed theory. From the
organizational human behavior theory,
(1) Questions 1–6 represented the emotion factor.
(2) Questions 7–10 represented the attitudes and moods factor.
(3) Questions 11–15 represented the personality factor.
(4) Questions 16–20 represented the beliefs and values factor.
(5) Questions 21–24 represented the perception factor.
(6) Questions 25–29 represented the motivation factor.
Human behavioral factors (HBFs) Knowledge management system–cycles (KMS-Cs)
Scale
Objects
number
Cronbach’s
alpha Scale
Objects
number
Cronbach’s
alpha
Emotion 6 0.714 Knowledge
sharing
7 0.738
Attitudes and
moods
4 0.943 Knowledge
creation
5 0.749
Personality 5 0.703 Knowledge
storage
4 0.778
Beliefs and values 5 0.739 Knowledge
transfer
5 0.707
Perception 4 0.716
Motivation 5 0.773
Overall reliability 29 0.871 Overall
reliability
21 0.866
Table 1.
Instruments reliability
Cronbach’s alpha of
HBF and KMS-C
BPMJ
Table 2 shows that the respondents in this study indicated the highest agreement toward the
human behavior emphasis on enthusiasm (mean [M] 54.56, standard deviation [SD] 50.70);
cooperation (M54.52, SD 50.52); feeling good (M54.62, SD 50.76); dealing calmly
(M54.62, SD 50.56); accepting others’ideas (M54.6, SD 50.62); be proactive (M54.5,
SD 50.70); be loyal (M54.6, SD 50.56); be responsible (M54.57, SD 50.59); making
progress (M54.56, SD 50.57); providing knowledge (M54.6, SD 50.65) and
accomplishing goals (M54.2, SD 50.82).
The items that have the weakest agreement based on an organization such as providing a
creative environment (M52.5, SD 51.13); being logical on decisions (M52.4, SD 51.09);
encouraging (M52.5, SD 51.05); relying on consultancy (M52.4, SD 51.05) and
promoting employees (M52.4, SD 51.05).
Based on the overall result, it can be concluded that the self-based human behaviors
dominate, whereas organization-based human behaviors were relatively weak.
5.5 Perception about knowledge management system–cycles (KMS-Cs)
This section provides results of the perceptions of the academic staff at the University of
Sulaimani regarding the KMCs that exist in their organization. These findings are based on
the strength of the employees’agreement with the items, which represent the varied types of
KM processes that exist in an organization based on the theory previously discussed. From
the KMS theory,
(1) Questions 1–7 represented knowledge sharing.
(2) Questions 8–12 represented knowledge creation.
(3) Questions 13–16 represented knowledge storing.
(4) Questions 17–21 represented knowledge transfer.
Table 3 illustrates that the respondents in this study indicated the highest agreement toward
the KM processes emphasis on creating new products (M54.2, SD 50.74); organization
encourage faster (M54.1, SD 50.72); conveying new ideas (M54.11, SD 50.63);
progressing organization (M54.04, SD 50.84); improving capabilities (M54.3, SD 50.73);
learning (M54.26, SD 50.70) and using technology (M54.0, SD 50.90).
The items that have the weakest agreement based on an organization are benefit from
knowledge (M52.5, SD 50.99); training (M52.2, SD 51.08); using cloud computing
(M52.7, SD 50.82).
Based on the overall result, it can be concluded that the KMS has a relatively positive
ranking.
5.6 First: finding a correlation between HBF and KMC
To test whether there is a correlation between HBF and KMC from the survey on the academic
staff at the University of Sulaimani. In order to analyze the nature of the data and variables,
descriptive statistics were conducted. The study illustrates the values of means and SD from
these analyses with n5117. For the HBF emotion (M54.3903, SD 50.48), attitudes and
moods (M54.3903, SD 50.53), personality (M53.42, SD 50.64), beliefs and values
(M54.48, SD 50.48), perception (M53.42, SD 50.64) and motivation (M53.24, SD 50.65),
with regards to KMC knowledge sharing (M53.33, SD 50.60), knowledge creation
(M53.83, SD 50.59), knowledge storage (M53.03, SD 50.78) and knowledge transfer
(M53.81, SD 50.57). A nonparametric correlation test using the Spearman rank correlation
coefficient was employed. The result of the correlation test can be seen in Table 4. The result
illustrates that correlation analysis suggested a strong and positive correlation between
Knowledge
management
system - human
behavior
Section 1: Human behavioral factors (HBFs)
No Questions
Fully
disagree
Partly
disagree Neutral
Partly
agree
Fully
agree SD Mean Rank
Emotion
1 I have enthusiasm for
my job
1% 1% 4% 30% 64% 0.70 4.56 1
2 I cooperate with my
colleagues in my job
0% 0% 1% 46% 53% 0.52 4.52 2
3 My job make me proud 2% 1% 6% 30% 62% 0.80 4.49 3
4 I have passion to be
famous in my job
0% 2% 8% 34% 56% 0.71 4.45 4
5 I like to make a surprise
during the work
0% 3% 13% 44% 40% 0.77 4.20 5
6 I am so glad in my job 2% 7% 6% 50% 35% 0.91 4.10 6
Attitudes and moods
7 I feel good when I invent
a new idea at work
0% 1% 1% 34% 64% 0.76 4.62 1
8 I always deal calmly
with my partners during
the work
0% 0% 0% 29% 72% 0.56 4.62 1
9 I feel relaxed inside the
organization
2% 8% 10% 50% 31% 0.94 4.0 2
10 My colleagues are
excited when we share
and exchange idea
2% 9% 31% 40% 18% 0.94 3.6 3
Personality
11 I accept different ideas if
they are better than mine
1% 0% 2% 35% 62% 0.62 4.6 1
12 I am proactive in my job 2% 0% 2% 41% 56% 0.70 4.5 2
13 I have enough freedom
to take a risky decision
inside the organization
8% 26% 26% 30% 11% 1.14 3.1 3
14 The organization
provides to me creative
environment
18% 43% 15% 21% 4% 1.13 2.5 4
15 The organization takes
the decision based on
logical judgments
21% 38% 23% 13% 4% 1.09 2.4 5
Beliefs and values
16 I have loyalty for my
organization
0% 0% 3% 33% 63% 0.56 4.6 1
17 I consider my job a
responsibility at the
organization
0% 0% 3% 38% 58% 0.59 4.57 2
18 I try to make progress in
my organization
0% 0% 5% 32% 62% 0.57 4.56 3
19 Ifeel I am helping society
during work
0% 1% 9% 41% 50% 0.68 4.4 4
20 I stay late at work
without any bonus
1% 7% 9% 27% 56% 0.96 4.3 5
(continued )
Table 2.
Summary statistics of
(HBF) including
rankings
BPMJ
many factors and cycles of the study at p50.01 and p50.05 significant level. The motivation
is highly and strongly positively correlated with the knowledge creation, sharing and storing
(r50.616**, n5117, p< 0.00), (r50.531**, n5117, p< 0.00) and (r50.530**, n5117,
p< 0.00), respectively, while it is positively and moderately correlated with the knowledge
transferring (r50.389**, n5117, p< 0.00). Personality and perception are highly and
significantly positively correlated with the knowledge sharing (r50.516**, n5117,
p< 0.00), whereas they are positively and moderately correlated with the knowledge creation,
storage and transferring (r50.462**, n5117, p< 0.00), (r50.319**, n5117, p< 0.00) and
(r50.414**, n5117, p< 0.00), respectively. Beliefs and values are highly and significantly
positively correlated with the knowledge creation (r50.578**, n5117, p< 0.00), whereas
there are positively and moderately correlated with the knowledge sharing (r50.387**,
n5117, p< 0.00). Attitudes and moods also are positively and moderately correlated with the
knowledge sharing and creation (r50.360**, n5117, p< 0.00) and (r50.464**, n5117,
p< 0.00), respectively. On the contrary, emotion showed a positive and weak correlation with
the knowledge sharing and creation (r50.286**, n5117, p50.001) and (r50.215*, n5117,
p50.001), respectively, whereas a negligible correlation is illustrated with the knowledge
storing and transferring (r50.120, n5117, p50.100) and (r50.026, n5117, p50.390),
respectively. Then, beliefs and values presented a weak correlation with the knowledge
transferring (r50.274**, n5117, p50.001), whereas a negligible correlation is illustrated
Section 1: Human behavioral factors (HBFs)
No Questions
Fully
disagree
Partly
disagree Neutral
Partly
agree
Fully
agree SD Mean Rank
Perception
21 I try to provide new
knowledge to enhance
the organization
0% 2% 3% 32% 62% 0.65 4.6 1
22 The employees have
privilege in the
organization
2% 10% 38% 39% 10% 0.88 3.5 2
23 The organization
encourages cooperative
employee
20% 32% 31% 15% 3% 1.05 2.5 3
24 The organization relies
on consultancy to take
decisions
24% 26% 35% 14% 2% 1.05 2.4 4
Motivation
25 I try to accomplish the
organization goals
2% 2% 9% 48% 39% 0.82 4.2 1
26 I trust my coworkers in
the organization during
the work
3% 11% 26% 47% 14% 0.95 3.6 2
27 The organization
encourages competition
between employees
7% 19% 41% 27% 6% 0.99 3.1 3
28 The organization gives
me the opportunity to do
my job well
9% 30% 26% 26% 9% 1.12 3.0 4
29 The organization
promotes me for my
innovation
23% 35% 27% 12% 3% 1.05 2.4 5
Source(s): academic staff survey at the University of Sulaimani Table 2.
Knowledge
management
system - human
behavior
Section 2: Knowledge management cycles (KMCs)
No Questions
Fully
disagree
Partly
disagree Neutral
Partly
agree
Fully
agree SD Mean Rank
Knowledge sharing
1 I attempt to create new
products and services
in my organization
0% 3% 9% 53% 35% 0.74 4.2 1
2 The organization
encourages me to
complete the new
product development
projects faster
0% 2% 17% 54% 27% 0.72 4.1 2
3 I make an effort to
increase firm
capabilities
3% 10% 28% 37% 22% 1.02 3.66 3
4 I try to reduce the
production cost in the
organization
4% 9% 23% 46% 18% 1.01 3.65 4
5 There is a face-to-face
communication
through networking
with other experts in
the organization
9% 21% 36% 21% 13% 1.15 3.1 5
6 The organization
benefits from the
knowledge acquired
from the employees
20% 30% 36% 14% 1% 0.99 2.5 6
7 The organization
improves my
capabilities through
training courses
30% 37% 19% 12% 3% 1.08 2.2 7
Knowledge creation
8 I convey new idea
through shared
experience in my
organization
0% 0% 15% 60% 26% 0.63 4.11 1
9 I progress the
organization with
activities like
(workshops, seminars,
etc.)
1% 3% 17% 48% 31% 0.84 4.04 2
10 I surpass the conflicts
that face the
organization,
individual and
environment
1% 4% 16% 52% 26% 0.83 3.99 3
11 I depend on the
colleagues inside and
outside the
organization
2% 7% 15% 50% 26% 0.92 3.9 4
12 My boss accepts my
new creative ideas
11% 17% 29% 37% 6% 1.11 3.1 5
(continued )
Table 3.
Summary statistics of
KMC including
rankings
BPMJ
Section 2: Knowledge management cycles (KMCs)
No Questions
Fully
disagree
Partly
disagree Neutral
Partly
agree
Fully
agree SD Mean Rank
Knowledge storing
13 The organization
renews and supports
new technology in your
organization
8% 16% 29% 41% 6% 1.04 3.3 1
14 The organization
depends on new
technology to transmit
knowledge among
employees
10% 22% 30% 33% 4% 1.06 3.0 2
15 The organization stores
its data in a data
warehouse
6% 21% 32% 32% 9% 1.07 3.2 3
16 The organization has a
cloud computing
11% 15% 62% 10% 1% 0.82 2.7 4
Knowledge transfer
17 Knowledge transfer
leads to improving
personnel capabilities
0% 4% 3% 50% 42% 0.73 4.3 1
18 Knowledge transfer
leads to learning
0% 3% 7% 52% 38% 0.70 4.26 2
19 I use technology to
transfer the knowledge
in my organization
1% 9% 11% 52% 27% 0.90 4.0 3
20 I transfer the new
knowledge in my
organization in order to
achieve the greatest
value for innovation
2% 10% 32% 40% 15% 0.93 3.6 4
21 The organizational
processes create
organizational
intergroup interactions
8% 19% 48% 22% 3% 0.93 3.0 5
Source(s): academic staff survey at the University of Sulaimani Table 3.
Knowledge management system–cycles (KMS-Cs)
Human behavioral factors
(HBFs)
Knowledge
sharing
Knowledge
creation
Knowledge
storing
Knowledge
transfer
Emotion 0.215
*
0.286
**
0.120 0.026
Attitudes and moods 0.360** 0.464** 0.112 0.152
Personality 0.516** 0.462** 0.414** 0.319
**
Beliefs and values 0.387** 0.578** 0.120 0.274
**
Perception 0.516** 0.462** 0.414** 0.319
**
Motivation 0.616** 0.531** 0.530** 0.389**
Note(s): **correlation is significant at the 0.01 level (one-tailed); *correlation is significant at the 0.05 level
(one-tailed)
Table 4.
HBF and KMC
correlation analysis of
the variables of
study (n5117)
Knowledge
management
system - human
behavior
with the knowledge storing (r50.120, n5117, p50.098). Finally, attitudes and moods
illustrated a negligible correlation with the knowledge storing and transferring (r50.112,
n5117, p50.115) and (r50.152, n5117, p50.051), respectively. Based on independent
and dependent, the result shows that all independent variables were also positively and
moderately correlated with each other.
In conclusion, and referring to Table 5, the result shows a strong and significant positive
correlation between HBFs and KMS-C.
5.7 Second: findings of applying the simple linear regression test between HBF and KMC
The study shows the application of a simple linear regression that was calculated to influence
KMC based on the HBF. A significant regression equation was found (F(1.115) 572.992,
p< 0.000) within R
2
of 0.410. The academic staff predicted KMC is equal to 0.704 þ0.725 HBF.
KMCs increased as each HBF was increased. The R
2
value represents the simple correlation
and is 0.64, which indicates a high degree of correlation between KMC and HBF. The R
2
value
indicates how much of the total variations is in the dependent variable. In this case, the HBFs
had an impact on KMCs with 41%. If we observe Durbin–Watson, the value is 1.968. So, we
can say this assumption has been met as it is presented in Table 6. The relative order of
preference of the predictive factors of KMC depends on HFB based on the beta values given in
Table 7. It can be synopsized as follows: HBF (β50.640). This factor is statistically
significant at a 5% level of significance as the p-value corresponding for four factors is below
0.05. Thus, HBF had an impact on KMC.
Table 8 is the ANOVA table, which reports how well the regression equation fits the data
(i.e. predicts the dependent variable):
The residuals statistics (Table 9) summarize the nature of the residuals and predicted
values in the model. It is worth glancing at so that you can get a better understanding of the
spread of values that the model predicts and the range of error within the model. A histogram
of the residuals (Figure 1) suggests that they are normally distributed. The P-P plot (Figure 2)
is a little more reassuring. There does seem to be some deviation from normality between the
observed cumulative probabilities of 0.2–0.6 and 0.8–0.9, but it appears to be minor. Overall,
there does not appear to be a severe problem with nonnormality of residuals.
A histogram of the residuals (Figure 1) suggests that they are normally distributed. The
P-P plot (Figure 2) is a little more reassuring. There does seem to be some deviation from
normality between the observed cumulative probabilities of 0.2–0.6 and 0.8–0.9, but it
HBF KMC
HBF Pearson correlation 1 0.640
**
Significance (one-tailed) 0.000
N117 117
KMC Pearson correlation 0.640
**
1
Significance (one-tailed) 0.000
N117 117
Note(s): **correlation is significant at the 0.01 level (one-tailed)
Model RRsquare Adjusted Rsquare Std. error of the estimate Durbin–Watson
1 0.640
a
0.410 0.405 0.37498 1.968
Note(s): a. predictors: (constant), HBF; b. dependent variable: KMC
Table 5.
Nonparametric
correlations (Spearman
rank correlation
coefficient)
Table 6.
Model summary for
HBF and KMC
(Y1) model
BPMJ
appears to be minor. Overall, there does not appear to be a severe problem with nonnormality
of residuals.
5.8 Third: findings of analysis of variance (ANOVA) for HBF and KMC
The test of normality of the study tools was statistically significant, which was above (0.05)
for both of the HBF and KMC based on the certificates used (Kolmogorov-Smirnova to HBF
(p50.197), KMC (p50.200) and Shapiro–Wilk to HBF (p50.266), KMC (p50.551)). Their
study demonstrates the application of a one-way ANOVA between HBF and KMC based on
the academic qualifications. The one-way between-groups ANOVA was performed to
compare the impact of certificates on each of the HBF and KMC. Participants were divided
into three groups based upon their academic qualifications (group1: PhD, group 2: MSc,
group 3: BSc). HBF illustrated that the outcome variable was found to be normally distributed
and equal variance is assumed based upon results of Leven’s test (F(114) 51.436, p50.242).
There was a statistically significant difference in HBFs for the three certificates groups
F(2,114) 522.760, p50.000). Statistical power that was very large was equal to 1.00. Post hoc
comparisons using the Tukey honestly significant difference (HSD) test indicated the mean
score for the PhD group (M54.18, SD 50.32, 95%) was significantly different from the MSc
group (M53.73, SD 50.42, 95%). The BSc group (M53.67, SD 50.35, 95%) did not differ
significantly from the MSc group. With regards to KMC, the outcome variable was found to
be normally distributed and equal variance was assumed based on the results of Leven’s test
(F(114) 52.774, p50.067). There was a statistically significant difference in KMCs for the
three certificates groups F(2,114) 59.356, p50.000). The magnitude of the difference in the
means and the effect size was large (partial eta squared 50.141). Statistical power that was
Model Sum of squares df Mean square FSignificance
1 Regression 11.238 1 11.238 79.922 0.000
b
Residual 16.171 115 0.141
Total 27.409 116
Note(s): a. dependent variable: KMC; b. predictors: (constant), HBF
Model
Unstandardized
coefficients Standardized coefficients
tSignificanceBStd. error Beta
1 (Constant) 0.704 0.315 2.235 0.027
HBF 0.725 0.081 0.640 8.940 0.000
Note(s): a. dependent variable: KMC
Minimum Maximum Mean Std. deviation N
Predicted value 2.8193 4.2285 3.5012 0.31126 117
Residual 0.94477 1.36662 0.00000 0.37336 117
Std. predicted value 2.191 2.337 0.000 1.000 117
Std. residual 2.519 3.644 0.000 0.996 117
Note(s): a. dependent variable: KMC
Table 8.
Analysis of variance
(ANOVA) between
HBF and KMC
Table 7.
Result of multiple
regressions
(coefficients
a
)
Table 9.
Residual statistics
for model
Knowledge
management
system - human
behavior
very large was equal to 0.976. Post hoc comparisons using the Tukey HSD test indicated the
means score for the PhD (M53.76, SD 50.37, 95%) was significantly different from the MSc
(M53.38, SD 50.56, 95%). The BSc (M53.37, SD 50.41, 95%) did not differ significantly
from the MSc certificates as it is evident in Table 10.
Normal P-P Plot of Regression Standardized Residual
Dependent Variable: KMC
Expected Cum Prob
Observed Cum Prob
0.0
0.0
0.2
0.4
0.6
0.8
1.0
0.2 0.4 0.6 0.8 1.0
Figure 1.
Histogram of
standardized model
residuals
Figure 2.
P-P plot of
standardized model
residuals
BPMJ
The post hoc test illustrated the alpha level of 0.05 to determine if the pairs of certificates
are significantly different from one another. The PhD is compared to the MSc. This value is
less than 0.05, which was 0.000. So, those two certificates are significantly different from
one another. The PhD is compared to the BSc. This was less than 0.05, which was 0.000. So,
those two certificates were also significantly different from one another. So, we would make
a conclusion that the certificates have an effect on the HBF; there is a statistically
significant effect. The MSc is compared to the BSc. This value is greater than 0.05, which
was 0.774. So, these two certificates are not significantly different from one another. We can
make a conclusion that they are not significantly different from one another. However, by
looking at the pairs of certificates, we can detect that the MSc is not significantly different
from the BSc, but the PhD is strongly different from the MSc and BSc, as it is evidenced in
Table 11.
The post hoc test illustrated the alpha level of 0.05 to determine if the pairs of certificates
are significantly different from one another. The PhD is compared to the MSc. This value is
less than 0.05, which was 0.000. So, those two certificates are significantly different from
one another. Then, the PhD is compared to the BSc. This is less than 0.05, which was 0.000.
So, those two certificates are significantly different from one another. So, we would make a
conclusion that the certificates have an effect on the KMC; there is a statistically significant
effect. The MSc is compared to the BSc. This value is greater than 0.05, which was 0.996. So,
these two certificates are not significantly different from one another. We can make a
conclusion that they are not significantly different from one another. However, by looking
at the pairs of certificates, we can detect that the MSc is not significantly different from the
BSc, but the PhD is significantly different from the MSc and BSc, as it is evidenced in
Table 12.
Categories Certificates NMean Std. deviation FSig
HBF PhD 39 4.18 0.32 22.760 0.000
MSc 39 3.73 0.42
BSc 39 3.67 0.35
KMC PhD 39 3.76 0.37 9.356 0.000
MSc 39 3.38 0.56
BSc 39 3.37 0.41
Dependent
variable Human behavioral factors (HBFs)
(I) certificates Mean difference (I-J) Std. error Significance
b
95% confidence interval for
difference
b
Lower bound Upper bound
PhD MSc 0.4538* 0.08294 0.000 0.2568 0.6507
BSc 0.5105* 0.08294 0.000 0.3135 0.7074
MSc PhD 0.4538* 0.08294 0.000 0.6507 0.2568
BSc 0.0567 0.08294 0.774 0.1403 0.2537
BSc PhD 0.5105* 0.08294 0.000 0.7074 0.3135
MSc 0.0567 0.08294 0.774 0.2537 0.1403
Note(s): Based on estimated marginal means. The error term is mean square (error) 50.134; *the mean
difference is significant at the 0.05 level
Table 10.
Descriptive statistics
and ANOVA results of
the participants’
responses to the HBF
and KMC
Table 11.
Multiple comparisons
between PhD, MSc and
BSc certificates in HBF
using Tukey HSD
Knowledge
management
system - human
behavior
The study has tested three hypotheses using correlation, linear regression and ANOVA as
it is observed from Table 13. The consequences appeared in correlation (the HBFs are
positively and strongly correlated to the KMS-Cs). Further, the study designates that the
HBFs have an influence on the KMS-Cs. Similarly, certificates have an effect on HBFs and
KMS-Cs.
6. Discussion and implications
The study has explained the organizations relationship between HBFs and KMS-Cs and
the influence of the factors on the cycles. So, the new ideas emerge to create knowledge
about product development among employees. The group experience works as an
essential element (Grimsdottir and Edvardsson, 2018). Knowledge resides in human
minds and, as a result, employee behavior and explanatory skills are the key drivers of
KM (Prieto and Revilla, 2005). First, knowledge creation, sharing and storing is increased
when the organization has motivated the employees. Second, knowledge is shared rapidly
when the employees have owned a strong personality, new idea, impression and
perception. Third, both the beliefs and values lead to creating new knowledge when the
employees obtained it inside the organization. Then, the emotion factors illustrated the
weak relation with knowledge sharing, knowledge creation, knowledge storing and
knowledge transfer.
In general, all HBFs like emotion, attitudes and moods, personality, beliefs and values,
perception and motivation had an impact on knowledge creation that is a collaborative
method of interactions between knowledge and behavior (Buqais et al., 2018). While the
factors of motivation, perception and personality had a strong relation on knowledge sharing.
Therefore, knowledge-sharing behavior includes the factors that influence a person’s
Dependent
variable Knowledge management system–cycles (KMS-Cs)
(I) certificates Mean difference (I-J) Std. error Significance
b
95% confidence interval for
difference
b
Lower bound Upper bound
PhD MSc 0.3812* 0.10291 0.001 0.1368 0.6256
BSc 0.3897* 0.10291 0.001 0.1454 0.6341
MSc PhD 0.3812* 0.10291 0.001 0.6256 0.1368
BSc 0.0086 0.10291 0.996 0.2358 0.2530
BSc PhD 0.3897* 0.10291 0.001 0.6341 0.1454
MSc 0.0086 0.10291 0.996 0.2530 0.2358
Note(s): Based on observed means. The error term is mean square (error) 50.207; *the mean difference is
significant at the 0.05 level
Analysis Hypothesis Results
Correlation The human behavioral factors are significantly correlated with the knowledge
management system–cycles
64%
Linear
regression
The human behavioral factors have an impact on the knowledge management
system–cycles
41%
One-way
ANOVA
The certificates have an effect on the human behavioral factors and knowledge
management system–cycles
0.000
Table 12.
Multiple comparisons
between PhD, MSc and
BSc certificates in KMC
using Tukey HSD
Table 13.
Hypothesis statement
results
BPMJ
behavior to share knowledge. Many theories have been applied to the study of knowledge
exchange behavior, including logical action theory (theory of reasoned action [TRA]),
planned behavior theory (theory of planned behavior [TPB]) and social exchange theory
(SET) (Razak et al., 2016). While the factors of motivation, perception and personality had a
relationship on knowledge transferring as for the study of Gholipour et al. (2018) transferring
with other members in the organization will produce space for creating new and valuable
knowledge assets. Personality is an important topic that must be addressed by management
as it seeks to increase employee motivation and enhances OB in the workplace (Nuckcheddy,
2018). As for the beliefs, it has been referred to as a word of beliefs within the concept
presented. However, these beliefs do not happen with all people. That is, if people acquire
certain knowledge, it does not necessarily mean the certainty of this science (Bashar, 2017).
The motivation factor had a significant impact on all of the cycles of KM. In other words,
motivation encourages the employees to create a new idea, learn and use new technology,
improve skills and develop capabilities and accomplish the organization targets. The
personality and perception factors have an impact on knowledge sharing, creating and
storing which pushes the employees to be proactive, provide new knowledge and be humble
for accepting diverse idea. Each of the beliefs, values, attitudes and moods merely had an
impact on the knowledge creation to be feeling good, dealing calmly, having loyalty and
responsibility for their duty.
As a consequence, the creating link between cycles of KM and HBFs is determinated to a
new conceptual model called KM behavior (KMB), as is declared in Figure 3.
7. Conclusion
Knowledge is considered as a great factor in achieving organizational goals (Hammami and
Alkhaldi, 2017). Therefore, this study has explained that knowledge is an essential element
for employees and organizations, Furthermore, it progress the skills and capabilities during
the job. Nevertheless, this knowledge is impacted through human behaviors because the
behavior evolves crucial factors that help the academic staff to create, share, store and
transfer the knowledge through motivation, perception, personality, attitudes, moods, beliefs
and values.
Knowledge sharing is a culture of social interaction involving the exchange of knowledge,
experiences and skills of employees across the organization (Zugang et al., 2018;Khalaf et al.,
2020a,b).
Organizations need to pay particular attention to the method of communication used
where knowledge becomes useless if employees are not encouraged to study and use it in their
Knowledge
Creation
Knowledge
Sharing Knowledge
Storage
Knowledge
Transfer
Motivation
Perception
Personality
Motivation
Motivation
Perception
Personality
Beliefs & Values
Motivation
Attitudes & Moods
Perception
Personality Figure 3.
Conceptual model of
knowledge
management
behavior (KMB)
Knowledge
management
system - human
behavior
daily activities (Boatca et al., 2018). Knowledge sharing can be achieved by taking into
account technical standards (KMS), social standards (environment) and personality
(motivation) (
€
Ozlen, 2017).
The research illustrates that whenever motivation is increased, knowledge sharing,
creating, storing and transferring will be increased. Knowledge sharing rapidly rises when
the academic staff reaches to high cognitive abilities and personality. The beliefs and values
had a crucial role to create knowledge while the academic staff adheres to their job where they
could participate in the creation of new ideas and knowledge. Also, attitudes, moods, beliefs
and values did not affect knowledge storing and transferring. Emotion had no influence on
KMS-Cs.
It is assumed that the self-based human behaviors dominate, whereas organization-based
human behaviors were relatively weak. Also, the KM processes have a relatively robust
ranking.
It is concluded that the academic staff psychology has an impact on the KMS-Cs, with the
significant relationship between the factors of human psychology with knowledge cycles.
Therefore, HBF was crucial to increase the KMC efficiency that could be named knowledge
behavior (KB). There is a mixture of connections between HBFs and KMCs. It is also
investigated from the gaps that have been between the academic staff behaviors and their
KM. Moreover, regulatory authorities should be more careful with respect to the reasons for
the poor behavior factors in an attempt to improve the academic staff knowledge, where this
study illuminates the factors and cycles that cause this problem. Therefore, overcoming this
drawback by means of a logical relationship between instructors’behavior and knowledge
cycles.
Knowledge transfer in organizations suggests itself through diverse mechanisms,
training, communication, observation and interactions with the senders and receivers
(Alkhaldi, 2018;Khalaf and Sabbar, 2019). Therefore, the University of Sulaimani should
create a conducive environment to improve, encourage and promote the instructors and
depend on the logical decisions, consultancy, opening training courses whether academic or
administrative. Furthermore, implementing new technology to share and transfer knowledge
through cloud computing. The academic staff members need to be mindful of their behaviors
to raise all aspects of the knowledge creating, storing, sharing or transferring.
ORCID iDs
Ameer Sardar Rashid http://orcid.org/0000-0003-1422-1878
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Corresponding author
Ameer Sardar Rashid can be contacted at: ameer.rashid@univsul.edu.iq
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