FACTORS AFFECTING KNOWLEDGE MANAGEMENT

FACTORS AFFECTING KNOWLEDGE MANAGEMENT
AT A PUBLIC HEALTH INSTITUTE IN THAILAND


VALLERUT POBKEEREE*
Department of Public Health Administration
Faculty of Public Health, Mahidol University, Bangkok, Thailand
E-mail: vallerut@gmail.com

PATHOM SAWANPANYALERT
National Institute of Health, Department of Medical Sciences
Ministry of Public Health, Nonthaburi, Thailand
E-mail: pathoms@dmsc.moph.go.th

NIRAT SIRICHOTIRATANA
Department of Public Health Administration
Faculty of Public Health, Mahidol University, Bangkok, Thailand
E-mail: nithats@gmail.com


This knowledge management (KM) study focuses on factors affecting KM at a Ministry of Public Health institute. The developed questionnaires were distributed to all institute staff. Four major factors were investigated in the survey: Organizational Culture, Information and Technology, KM Content, and Administration and Management. Statistical analysis was used to calculate the relationships among factors and KM according to the KM model from the Thai Knowledge Management Institute. There was a 78.8% response rate. Organizational Culture, Information and Technology, and Administration and Management were found to be significant factors associated with KM. In addition, other elements within these factors had a significant relationship with KM. However, KM content, organizational structure, and conflict did not have a significant relationship with KM. The authors found quality management systems i.e. ISO 9001, ISO 17025 or ISO 15189 played an important role in KM at the institute. The authors also found drawbacks and room for KM improvement in the institute. The results in this paper can be used as knowledge-based evidence to enhance and improve the institute’s routine operation and its performance.
Keywords Public health, Knowledge management, Thailand
1. Introduction
Any organization that would like to be a learning one needs to accept changes and learn to keep vital knowledge within its personnel as a living information network (Buckman, 2004). Knowledge is identified as power and provides a competitive resource for any organization that wants to be successful in their goals and functions. Building a knowledge-driven organization is therefore a milestone of any ministry in the country.
As a national public health laboratory providing services for the whole country, becoming a learning organization is also a goal of the Thai National Institute of Health (NIH). In order to become a learning organization, KM needs to be initiated.
The NIH is an important institute located in the Department of Medical Sciences, Ministry of Public Health (MOPH). Crucial functions of the institute are to carry out important medical science research for the Ministry, to provide day-to-day services
on diagnostic testing for confirmation laboratory tests and to serve as a national reference laboratory for other ministry departments/divisions.

* Corresponding author: Vallerut Pobkeeree; contact: vallerut@gmail.com; Tel: +6687-512-8644
2. Research Objectives
This study looks at four major factors; Organizational Culture, Information and Technology, KM Content, and Administration and Management that can be significantly related to KM in the NIH. The objective is to find which factors and their internal elements affect KM at the institute. Moreover, the authors have attempted to make staff opinions known in order to provide evidence-based information to improve KM activities in the future.
2.1. The defined terms of independent and dependent variables
The independent variables are the following four major factors and their elements:
• Organizational Culture refers to any element which could affect the culture of the organization and reflect the institute’s approach to KM work. In this study, they are trust among colleagues, participation, motivation or incentives, leadership, organizational structure, communication, organizational climate and personal attitude.
• Information and Technology (IT) refers to infrastructure, IT management, and accessibility of data, information and knowledge within the institute.
• KM Content refers to the selected topic to which will be used to carry out KM activities.
• Administration and Management refers to the policy on KM or plan to implement or create a KM position at the institute, information on KM evaluation to personnel in the institute and staff evaluations.
These major factors have been previously formulated and mentioned in a few studies (Syed-lkhsan and Rowland, 2004, Chua and Lam, 2005, and Oliver and Kandadi, 2006). For some, organizational culture is the most important factor affecting how KM will proceed (Ardichvili et al., 2006 and Al-Alawi et al., 2007). Slagter (2007) found that elements of organizational culture i.e. trust, leadership style, structure and motivation were critical success factors in KM in senior employees of the studied company. Kulkarni et al. (2007) determined that organizational support structure was also a contributing factor to the success of KM. Since there are many elements affecting organizational culture that impact KM in organizations, these elements were put into the study questionnaire.
IT is another crucial factor for public health organizations but Slagter (2007) did not find technology was important to KM among her older subjects. The Association of State and Territorial Health Office in the US (ASTHO, 2005) found many challenges with this factor. For example, no verification process for public health records, obsolete hardware, incompatible software, inadequate training etc.
The two other factors are KM Content and Administration and Management. Choosing relevant, useful and up-to-date content for the KM project is as important as dealing with other factors. Evaluation of work is also an attribute in the factor of Administration and Management. If an organization does not make a systemic effort to evaluate its own tasks, it is unlikely to succeed with its KM project.
The dependent variable in this research refers to the tuna (fish) model of KM from the Knowledge Management Institute (KMI) of Thailand (Phasukyud, 2004). The tuna or KM model comprises three components: the head of the fish is Knowledge Vision (KV), the body is Knowledge Sharing (KS) and the rear part is Knowledge Asset (KA). KM is structured and shown in the right hand box (Figure 1) in the conceptual framework.
Figure 1 Conceptual framework of the study

KV is defined as the organization’s goal of implementing and proceeding with KM. The organization needs to have a reason to implement KM and decide if the goal is in the common interest of its staff. Initiatives from top management are also considered as a vision of the organization.
KS is the largest and the most difficult part of the model. Each individual has to feel that he/she would like to share and when he/she shares, they will learn. The key of KM is this KS (Phasukyud, 2004 and Al-Alawi et al., 2007).
KA is the knowledge repository of an organization. It is generally referred to as either IT or each individual who has embedded intelligence in him/her (Ichijo and Nonaka, 2007 and Phasukyud, 2004) as an intangible asset. This study emphasizes the tangible knowledge handled by IT as KA which would be ready for use in the organization. The study does not focus on the intangible or non-IT asset because the research questionnaire does not cover and measure intangible knowledge.
3. Research Methodology and Design
The hypotheses of the study were designed with regard to the four major factors and their elements.
HA: There is a significant relationship between Organizational Culture and KM
HB: There is a significant relationship between Information Technology and KM.
HC: There is a significant relationship between Content and KM
HD: There is a significant relationship between Administration and Management and KM.
To test these hypotheses, the authors created an appropriate questionnaire which consisted of the factors, elements and KM components of the KM model. (Phasukyud, 2004). Moreover, the Knowledge-Based View (KBV) theory suggested that obtaining and using appropriate knowledge is important to comprehending organization performance. (Morgan, et al. 2003) The theory highlighted the two types of knowledge, tacit and explicit knowledge, which interact with each other. Both types of knowledge were elaborated in this study’s discussion on how knowledge flows in the institution along with the KM model of Takeuchi and Nonaka (2004).
The developed KM questionnaire was designed to acquire staff opinion on factors and elements affecting KM and was distributed to all NIH staff. A range of agreement from a Likert scale was employed from strongly agree (5 points) to strongly disagree (1 point). Two items were provided for each model construct and an average was calculated.. The content validity of the questionnaire was investigated by three KM experts. The reliability test was calculated using Cronbach’s coefficient alpha (Crawford, 2005) and the alpha was 0.88.
4. Data Analysis and Results
Although the respondents belonged to the same organization (NIH), they were distinct by the fact that they were divided into 34 sections, each with a different task within the organization. 386 out of 490 questionnaires were returned, which was a response rate of 78.8%. Interviews occurred with only some staff or section chiefs who were available and who volunteered because of time constraints. Twenty individuals were interviewed and provided their opinions, comments and suggestions. The data was analyzed by SPSS version 11.5 for Windows. Personal characteristics are shown in Table 1. Pearson correlation (r) was used to compute relationships among the major factors and their elements and KM. Other major factors affecting KM and its components (KV, KS and KA) were analyzed using bivariate correlation. Elements of major factors were analyzed using the same statistics. The arithmetic mean ( ) and standard deviation (SD.) of these factors and elements were also employed to assess the participants’ opinions.
Summaries of responses to the factors and their respective elements that affect KM are shown in Table 2. 40 % (data not shown here) of participants were not sure if the current Organizational Structure could support the institute’s KM activity; the mean of this element was the lowest ( = 2.92) and the SD. was the highest (SD.= 0.93). The high SD. could indicate low accuracy of the data. The same was true for Conflict where 44 % of respondents were not sure whether conflict among staff could affect KM.
Table 1. Personal Characteristics
Personal characteristics Result (%)
Gender:
Male 27.2
Female 72.8
Age (years)
21-30 49.7
31-40 25.4
41-50 18.2
51-60 6.7
Education
Lower than bachelors 26.7
Bachelors 56.2
Masters and higher 17.1
Work experience at the institute (years)
< 1 11.7
1-5 42.5
6-10 15.0
>10 30.8
Job characteristics
Administration & Management 17.8
Academic development 10.9
Laboratory (routine & research) 63.5
Other services 7.8
Table 2. Mean and Standard Deviation of Participants' Opinion Level
Factors Affecting KM
SD. Interpretation
Organizational Culture
Participation 3.69 0.58 Agree
Trust 4.32 0.60 Strongly agree
Motivation 3.87 0.82 Agree
Leadership 4.00 0.63 Agree
Organizational structure 2.92 0.93 Somewhat agree
Communication 4.29 0.61 Strongly agree
Organizational climate 3.71 0.84 Agree
Personal attitude 3.73 0.74 Agree
Information Technology
Infrastructure 3.85 0.72 Agree
IT admin. & management 3.67 0.78 Agree
Accessibility 3.80 0.70 Agree
Content
Content selection 3.56 0.83 Agree
Administration and Management
Policy 3.44 0.81 Agree
Management aspect 3.93 0.66 Agree
Evaluation 3.80 0.65 Agree
Conflict 3.07 0.88 Somewhat agree

Table 3. Pearson Correlations between KM and its Components
KS KA KM
r Sig. r Sig. r Sig.
Knowledge Vision (KV) 0.603 0.000 0.590 0.000 0.845 0.000
Knowledge Sharing (KS) -- -- 0.662 0.000 0.879 0.000
Knowledge Asset (KA) -- -- -- -- 0.871 0.000






Table 3 shows that all KM components are significantly related on their own and also among each other.
Table 4 summarizes the four major factors and their respective elements that affect KM. The authors found there were significant relationships between KM and three factors; Organizational Culture, Information Technology, and Administration and Management. Therefore, hypotheses HA , HB and HD are accepted (p < 0.001). But HC is rejected which means there was no significant relationship between KM and Content (Content selection). In addition, there were some elements within the major factors that had no significant relationship to KM (namely organizational structure and conflict) as shown in the same table. The remaining elements had a significant relationship to KM (p < 0.001).
In addition, it was also found that there were significant relationships between the KM components (KV, KS, and KA) and the three factors - Organizational Culture, Information Technology, and Administration and Management - (data not shown here). These results could infer that most organizational factors have positive relationships to KV, KS, and KA, which means if there are any changes in the factors this could result in a similar change to KV, KS and KA. However, the study could not determine the magnitude of the change.



Table 4. Summary of factors and their elements affecting KM

Factors Affecting KM Knowledge Management (KM)
Pearson Correlation Sig.
Organizational Culture 0.375 0.000
Participation 0.103 0.045
Trust 0.227 0.000
Motivation 0.201 0.000
Leadership 0.273 0.000
Organizational structure -0.069 0.175
Communication 0.234 0.000
Organizational climate 0.298 0.000
Personal attitude 0.278 0.000
Information Technology 0.378 0.000
Infrastructure 0.200 0.000
IT admin. & management 0.376 0.000
Accessibility 0.277 0.000
Content -0.043 0.404
Content selection -0.043 0.404
Administration and Management 0.368 0.000
Policy 0.340 0.000
Management aspect 0.217 0.000
Evaluation 0.429 0.000
Conflict -0.085 0.098
5. Discussion
5.1 Knowledge management through the KM model

Knowledge Vision: This is usually initiated by senior or top management of the institute. Their vision corresponds to the department’s or ministry’s strategy to make the institute become a learning organization. Kreitner and Kinicki (2005) mentioned that a learning organization has various attributes i.e. innovative, knowledge acquisition, or knowledge transfer. If the behavior of people in the organization adheres to these attributes then the organization could overcome barriers to accomplishing its goals. Knowledge vision also includes an organization’s mission. An organization should know its direction and mission in order to generate knowledge (Ichijo and Nonaka, 2007). It should also know its strengths and weaknesses and even if the situation changes, the knowledge vision usually does not change. This is because it is created as a result of meetings and discussions and senior management have invested significant amounts of thought, time and effort. The NIH has its own regular clients from both the public and private sectors and attempts to satisfy them through a quality management system (QMS) which will be mentioned below in the section on KA.
Knowledge Sharing: Knowledge sharing is knowledge transfer (Al-Alawi et al., 2007) and the authors investigated how knowledge was transferred and how some individuals learned. When a new test was performed in a particular laboratory and when someone from that laboratory had learned through training from outside their lab, that person would perform or demonstrate the test for their colleagues who had not attended training or did not know the test method. Laboratory personnel learn from a tacit to tacit knowledge connection as a socialization step, as highlighted in the SECI model (Takeuchi and Nonaka, 2004). The model of knowledge is created through tacit and explicit knowledge interaction. After each individual had learned, their embedded tacit knowledge was formulated as documents or records as explicit knowledge in order to allow others to study or learn from them. This corresponds to externalization (from tacit to explicit knowledge). When lab personnel learn concepts and express them as report documents, manuals or other forms of explicit knowledge such as meetings, usual conversation, or a conference, this process is considered to be what Takeuchi and Nonaka (2004) called combination (explicit to explicit knowledge) in their model. After lab personnel have learned through all three processes they develop more technical know-how, absorb and internalize explicit into tacit knowledge within individuals and become more valuable to the laboratory. This last process is called internalization (explicit to tacit knowledge) and the conversion between tacit and explicit knowledge has then formed a spiral of knowledge creation through those four processes. The institute can therefore obtain practical and new knowledge to turn into new routines by knowledge conversion (Takeuchi and Nonaka, 2004).
Knowledge Asset: Knowledge asset of the institute is both tangible and explicit knowledge e.g. Standard Operating Procedure (SOP), Work Instruction (WI), paper documents or documents from artificial intelligence (Metaxiotis et al., 2003), and intangible, as tacit knowledge e.g. real intelligence of human resources of the institute. Bowditch and Buono (2001) noted that more than half of the knowledge in an organization is in tacit form. Explicit knowledge needs to be expressed as a knowledge asset through active commitment of staff and their chiefs. Interestingly, each laboratory section conforms to requirements of the QMS prior to KM implementation and those requirements have an important role and add outstanding value to knowledge asset as well as KM. The system adheres to the requirements of the International Organization for Standardization (ISO). The authors found various sections had implemented ISO 9001 (Quality Management Systems - Requirements) or ISO 17025 (General Requirement for the Competence of Testing and Calibration Laboratories) or ISO 15189 (Medical Laboratory - Particular Requirements for Quality and Competence) in their laboratories. This system is an institute policy that has been implemented across sections. Generally each section has adhered to one of these standards in setting up its laboratory. Therefore, many processes and activities have a strengthened knowledge management program within the section. These ISO requirements have been taken seriously and facilitated knowledge flows and developed best possible practice in the institute.

5.2 Organizational factors and their elements

There were one factor and two elements (Table 4) that did not have a significant relationship to KM (p> 0.05): organizational structure (in Organizational Culture), content selection (in KM Content); and conflict (in Administration and Management).

Organizational structure: The institute’s structure is a hierarchy structure and this attribute could constrain knowledge sharing (Riege, 2005). However, our study found that the structure did not have a significant relationship to KM (Table 4, p = 0.175). The institute has two committees involved in KM: one is a steering committee as its members are from top management; the other is a working group committee. The staff in both committees who are assigned to work on this KM also have their routine functions. Oliver and Kandadi (2006) called this kind of structure a hybrid KM structure. They did not find any specific type of structure that could be best for KM activity. From Table 2, the organizational structure scored the lowest mean which could be interpreted as staff did not know how the structure is relevant to KM.

Content: It is known that tacit knowledge is context-specific (Takeuchi and Nonaka, 2004) and difficult to formulize and transfer. Both tacit and explicit knowledge are found in individual laboratories at the institute. Each laboratory has its own specific tests to perform and some of them are quite complicated. The authors found that it was hard to implement KM or select a KM topic applicable across the whole institute. Therefore, the content had no significant relationship to KM. However, this factor might not be accurate since it only contained one element (Table 4, content selection).

Conflict: Conflict could have positive or negative outcomes depending on its intensity and how it was solved (Kreitner and Kinicki, 2004). If working groups have little conflict their performance or outcomes would not be productive or creative. On the other hand, if there is too much conflict, it could destroy performance. Staff at the institute agreed that conflict occurred and 30% of the staff thought there were people who had too many things to do in their daily tasks and felt indifferent to KM activity. Many did not realize they had implemented KM many times as part of their routine job. No matter what conflict happens among staff, KM activity will carry on. It is quite beneficial to the institute that conflict does not have any significant relationship with KM since conflict is quite common among sections or staff. It has helped them find new approaches to working together without too much tension or effect on KM activities.
Factors and elements that have a significant relationship to KM (p< 0.05) are described below.

Participation: Even though participation had a significant relationship to KM, some section chiefs believed that staff did not sincerely agree to participate in KM activities across the institute but had politically agreed to participate since they were expected to and were persuaded that KM could benefit their routine. Explicit knowledge as a result of KM activity was included in departments’ websites as well as the ministry’s website. One interviewee mentioned that she did not know if staff from other sections would access the websites and make use of the information and knowledge.

Trust: When people trust they tend to open their minds and accept other people’s thoughts, opinions and information (Bowditch and Buono, 2001). The respondents in this study trusted their colleagues especially when they had trouble relating to their jobs, but the level of trust was not measured. Ichijo and Nonaka (2007) wrote that the more people trust each other the more knowledge would be transferred, and trust is directly associated with successful organizational innovation. This is compatible with Rhodes et al. (2008) findings that trust among staff had increased tacit knowledge transfer.

Motivation: In the private sector, bonuses and pay incentives usually motivate staff. In the public sector, non-financial awards or recognition programs are generally used. Nevertheless, one interviewee said he did not believe that the top management of the institute or the ministry had provided sufficient motivation. Difficult tasks by some staff did not even get verbal recognition, which could cause low job creativity or poor performance. Some staff perceived this as insincerity of top management.
Leadership: We found top management across the institute supported KM activities in terms of providing time and budget across the institute. Singh (2008) found that certain leadership styles had a significant relationship to KM of an organization. Bryant (2003) and Crawford (2005) also stated there was an apparent relationship among transformational leadership and KM. Additionally, a leader can maintain an organizational culture in order to help facilitate knowledge transfer in an organization. Janson and McQueen (2007) wrote about interviews with 31 leaders who innovatively succeeded in their jobs. The leaders used tacit knowledge, collected from their routine practice and experience, to facilitate conversations with their staff, an action which cannot be explained in explicit knowledge.

Communication: Formal and top-down (vertical) communications are usually practiced in the institute among top management and sections. Informal and horizontal communication occurs within laboratory sections by verbal communication. The communication within the institute normally used hardcopy letter, internet, intranet and e-mail for information and knowledge. These approaches of communication are also true in Plessis (2007) study. Effectiveness and efficiency of communication within the institute were not been investigated. Many staff mentioned they usually do not know details of other laboratory sections. Despite this, they at least know who can be contacted when knowledge is needed through informal conversation. A more structured or formal communication should be conducted to gain a significant impact of KM in the institute.

Climate: The climate is a measurement of staff’s expectations on what the organization should be in terms of supporting knowledge sharing. The study showed the institute’s climate has provided sufficient physical space and an appropriate psychological environment for staff to interact with each other. This climate can be referred to as “Ba” in this study. Nonaka and Toyama (Ichijo and Nonaka, 2007) defined ‘Ba’ as not only space for knowledge sharing, but also as the context where knowledge is created, transferred and utilized. Ba emerged through interactions between staff in the organization. Staff can see other staff physically interact with other staff in projects and meetings.

Attitude: Personal attitude is important to organizational performance for quality and quantity of outcomes. It can influence individuals to behave in a particular way instead of another (Bowditch and Buono, 2001). Having knowledge does not help a person get promoted at the institute. It is individual competency related to his/her publication and seniority regarding hierarchy in the organization chart that would be considered in getting a higher position. Liebowitz and Chen (2003) found people in a public organization usually kept knowledge for their own personal career path. Another study (Sun and Scott, 2005) found that 71 % respondents fear to lose ownership or fear to lose control of knowledge.

Information and Technology: This factor and its elements were significantly related to KM as consistent with a previous study (Rhodes et al., 2008). The institute has sufficient IT infrastructure and web connection is available, but most staff usually use the internet rather than intranet. This is especially true since when a particular task is complete, staff put their explicit knowledge on the department website rather than the intranet. When asked one interviewee said “Some people believe that some staff or section chiefs intend not to put details of their work on the website or intranet and use computer storage limitation as an excuse. It seems that knowledge put on a department website is more appropriate and useful to the public rather than to staff in the institute”. Another statement: “I think the hardware of the institute should be upgraded and more e-mail account space should be provided according to staff position”. Another statement was “Staff use of the department e-mail account is compulsory but space is very limited. Top management and clerks have the same account size”. IT is an aspect of KA and forms a tool to store the institute’s explicit knowledge especially data and information as part of the document control, which requires incorporated electronic and hardcopy documents. The quality management system of ISO requires a great focus on documents as well as KM, in order to transform tacit to explicit knowledge so that staff can learn. However, the documentation for ISO requirements is sometime laborious and a drawback to KM. Staff found they have to spend time on records and documents rather than actual testing itself.

Policy: KM policy was put in writing and a steering committee was formed to develop approaches for KM implementation. The committee consists of middle managers who are usually section chiefs. The group functions are to develop and manage a variety of KM activities e.g. selecting a KM topic that can be implemented across the institute; for example, laboratory safety. The staff need training on the issue and the working group needs to find particular trainers from within and outside the institute. The KM working group committee tries to encourage lab personnel and other staff to learn about the topic and apply it to day-to-day tasks. Not all staff have a chance to participate in every selected KM topic. In addition, knowledge transfer from experienced or highly skilled staff and from personnel about to retire should be accounted for with a clear policy.

Administration and Management: The administration and management section’s work is generally reactive to internally oriented tasks rather than proactive. One interviewee said “Many times, work at the institute is on an ad-hoc basis”. This is typical of any public institute in a developing country. Staff have to obey the department’s or the ministry’s top management. Another one said “There should be management directions with regard to a clear approach to KM practices in the section”.

Evaluation: The questionnaires mentioned personal performance evaluation and work evaluation in general. The personal performance evaluation was usually led by each section chief who asked each staff member to evaluate themselves first, after which the section chief evaluated them. They discussed strengths and weaknesses in relation to work performance as well as completing an evaluation form. Furthermore, staff competency is included in the performance evaluation in order to ensure that staff are actively involved in understanding all test processes. In addition, the work evaluation is done according to the institute’s key performance indicators and the Office of the Public Sector’ development indicators as well as the requirements of ISO 9001 (very general management), ISO 17025 (specific to the laboratory field) and ISO 15189 (very specific to medical laboratories).
6. Conclusions and Recommendations
There is a significant relationship between KM and three major factors and some, but not all, of their elements;
• Organizational Culture: participation; trust; motivation; leadership; communication; organizational climate; and personal attitude.
• Information and Technology: infrastructure; IT administration and management; and accessibility.
• Administration and Management: policy; management aspect; and evaluation.
To serve the rapid changes occurring in the public health sector and assist the institute in becoming a true learning organization, the institute should provide in-depth understanding of KM to its staff to help facilitate managing knowledge in practice and document any best possible practice. The institute has a unique feature in its ISO certified laboratories which has contributed significantly with KM activity. The research was conducted on staff perceptions and individual perspectives. Further study could involve clients of the institute or other organizational factors that could impact KM. The findings do not represent other public health institutes and they may not be extrapolated to other public sectors in the country. However, the results could encourage further KM activities and future surveys.

Acknowledgements: The authors thank Assoc. Prof. D. Sujirarat, Assoc. Prof. P. Luksamijarulkul, Dr. B. Sriwanthana for their suggestions and special thanks to all interviewees and respondents of Thai National Institute of Health for their collaboration.

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