Knowledge Sharing System Model for Higher Learning Institutions: Case Study

Saad Abdullah Haryani Haron General Directorate of Health Affairs in Hail Faculty of Computer and Mathematical Sciences Ministry of Health University Technology Mara (UiTM) Hail, Saudi Arabia Shah Alam, Malaysia captiansaadasa@yahoo.com haryani@tmsk.uitm.edu.my

Abstract- This study aims to propose a knowledge sharing system model for Higher Learning Institutions based on academicians knowledge sharing behavior. This research was carried out in four stages which are determined the knowledge acquisition, collected the data, data analyses and finding, and development of a knowledge sharing system model. The proposed knowledge sharing system model solves the problem of capturing relevant knowledge which exists in current knowledge management systems through identify and categorize knowledge being real shared by academicians in Higher Learning Institutions. The proposed knowledge sharing system model could enable Higher Learning Institutions to exploit and utilize the real knowledge being shared among their academic staff. Also, the research comprehensive analysis and findings would expand an area of knowledge sharing system in academic institutions, particularly, universities which might still theoretically and empirically not sufficiently covered. Finally, a practical further research recommendation was provided to those who interest to conduct a research on the knowledge sharing system area.

Keywords; Higher Learning Institutions; Knowledge sharing; Knowledge sharing system, academicians; system model.

I. INTRODUCTION Over the past ten years, numerous organizations have adopted knowledge managements because they play an essential actor for their success, including higher education [2]. Nevertheless, the knowledge management field is still remains unclear, even though that it has received some attention from practitioners and academics [13]. More specifically, there are a few research on knowledge management in Malaysia public sectors [15], and the questions on how to generate, how to capture, how to exchange and use of knowledge effectively in organizations become a large concern for both management practice and research [13,16]. There are many challenges in knowledge management attempt like enhancing knowledge creation and sharing [4] and understanding factors that influence knowledge management systems adoption as well as diffusion [14]. The universities are knowledge intensive environments and it has played an important role in exchange knowledge, and accordingly, they need to adopt a proactive approach to knowledge management [3]. It has been argued that knowledge management system can prove to be a promising technological management tool to improve performance of the academic institutions in the area of teaching, research, as

well as in the administrative services [9]. On the other hand, the sharing knowledge process is not merely depending on technology, it is also depending on other factors such these factors that related to the human being. Human dimension of knowledge management in many literatures mostly neglected [22].

A. Problem Definition Few researchers have explored and examined the knowledge sharing behaviors in a Higher Learning Institution's (HLI) [2]. One of the main problems in knowledge management that has been recently recognized is the knowledge sharing [5] because it influences on the organization's capacity to benefit from their employees' knowledge and to add it to organizational asset [6]. According to [7], in an academic set up, to ensure that academicians are able to realize and share their knowledge to their fellow member, there is need for implementing an effective knowledge management. The successful HLIs are those that continually generate new knowledge and distribute it through their knowledge systems [8]. However, most HLI face the difficult task of integrating their institutional knowledge for enhancing and improving knowledge sharing activities [9]. Previous studies in implementing and applying knowledge management have been focused on a technological issues [37] but insufficient attention has been given to the human aspects and factors [22, 38]. The way in which knowledge workers create, disseminate and manage information, might be more important than the technology aspect [39]. Researchers argue that the knowledge movement across both individual and organizational boundaries, into and from knowledge repositories are ultimately dependent on knowledge sharing behaviors of workers’ [11]. Therefore, for effective use of knowledge management technology as well as the people management practices need to be considered [10]. Besides, the knowledge management systems should be able to capture and classified the real knowledge that is often being shared and diffuse among their intended end-user. [19] mention that most of knowledge relevant to an organization is not included and represented in systems. In public academic institutions, it is still unknown how knowledge far it has been captured [28]. To ensure continuity and accelerate institutional learning, the capturing

2013 International Conference on Advanced Computer Science Applications and Technologies

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DOI 10.1109/ACSAT.2013.27

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and making the institutional knowledge available is necessary [18]. According to [1] the productivity of professionals responsible for systems development will be increased, and the quality of the delivered system greatly enhanced, if the systems linking directly to the user requirements. With the current existence problem of capturing the relevant knowledge in knowledge management systems and meet the user needs, this research aims to study the academicians knowledge sharing behavior and model their behavior into a Knowledge Sharing System (KSS).

B. Significance of the Study The study contributes is developing a KSS model in higher-education institutions based on understanding academicians knowledge sharing behavior in the HLI and model their behavior into a KSS.

II. LITERATURE REVIEW Many HLIs turn to information and communication technologies and one of these communication technology is a knowledge management system [12]. However, several issues and topics are still have not been empirically explored enough by the researchers in the knowledge management systems [14]. Several organizations continue facing challenges on how to improve the knowledge sharing of the employees, how can they benefit from others expertise before in doing the similar tasks, and how can prevent the employees from reinventing the wheels [17]. While the knowledge itself is the main content of a knowledge management system, an overall knowledge management system includes also processes, strategies, and culture [20]. Because the continuing problem of capturing organizational knowledge in the current knowledge management system, new solutions need to be explored [21]. A study conducted in a public university in Malaysia by [34] to identify and describe a knowledge types being shared among academicians. They found that the academicians share three main types of knowledge which are Corporate knowledge (Includes Disciplinary knowledge and Operational knowledge), Social knowledge (Includes Culture knowledge, Spiritual knowledge, and Common Interest knowledge), and Encoded knowledge (Includes knowledge in both electronic and written format). In their research [35] found that the academicians share their knowledge through two main methods which are synchronous as well as asynchronous. Totally fourteen synchronous methods that academicians share their knowledge through include Expert visits, Peer consultation, Lectures, Conferences, Seminars, Colloquiums, Working groups, Workshops, Research teams, Senate meetings, Coffee shop talks, Dinner discussions, Regular meeting, and Phone conversation. The three main asynchronous (virtual) methods include Personal Blogs, Email, and Web sites. [36] found that the academicians share their knowledge through

three main knowledge sharing networks. These networks are Business Club Network (Includes academicians at local and international universities, workers in government organization, workers in private organizations), Personal Network (Includes Colleagues, Friends, and Students) and Research Network which includes several research groups. A research [31] results reveal seven main motivations for academician to share their knowledge with others. These motivations are build reputation, acknowledgement (Includes gain rewards, get a promotion, and recognition), to be knowledgeable (To learn), reciprocity, vision and mission, be a mentor, personal beliefs (Includes culture, sense of responsibility, and religion). From academicians perspective's, there are twelve features they believe it is important to be included in a KSS which intended to develop for them. These features are alert user about new added (RSS), support multi-media (Text, pictures, videos), interconnection of wide disciplines (Able to connect users from different disciplines), accessibility (Easy to access), categorize the contents, interactivity, offer expert information, reliable, easy to use, multi-level, efficient search engine, offer consultation services [30].

III. METHODOLOGY Based on the results of studies [31,34,35,36] that have been conducted by researchers which represent the academicians knowledge sharing behavior, this research as a part of studies mention above, aim to model this behavior into a KSS. The research approach was a descriptive qualitative research. Because the aim of this research is to describe comprehensively and build in depth understanding of knowledge sharing behavior among the academicians and develop a KSS model based on their behavior, thus, a qualitative approach is the most appropriate. Using qualitative research has advantages, for instance, it can contribute to a theoretical and empirical advancement [23]. Purposeful technique was used to determine the research participants. In a qualitative study, the purposeful sampling is the main technique which enables the researcher to choose the most productive sample in order to answer the questions of research [25]. When conducting a qualitative research, the researcher should consider the finding validity [26]. The research result to be reliable and valid, a high level of integrity has been done to minimize the bias threat. For example, the study participants had been given a freedom to accept the participation or deny it. Participants who accepted the participation, they had a choice to hold the interview in the most suitable place and time for them. A schedule of all interview was prepared in a standard manner for all participants, allowing minimal allowances for researcher’s bias. Also, steps were taken in a credible scholarly. Some strategies to promote qualitative research validity have suggested by [27]. Two main strategies to promote qualitative have been used in this study. These strategies are the Low Inference Description and Data Triangulation.

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For this study, the Low Inference Description strategy was tested through include the views of study participants by using direct quotations from their responses to research questions. [27] describes that "A verbatim is the lowest inference descriptor of all because the participants' exact words are provided in direct quotation" (p. 285). The Data Triangulation strategy was used through conducting many interviews in different places and times. "Another important part of data triangulation involving collecting data at different times, at different places, and with different people" [27, p. 289].

IV. DATA ANALYSIS The primary data were collected through academicians from one of the public universities in Malaysia. This university has been chosen since it is one of the largest Malaysian universities with roughly 480 academic programs conducted by both coursework as well as research modes. So, that would offer opportunities for rich and deep understanding and describing the real behavior of knowledge sharing among its academic staffs. The data were collected from the participants over a six month period through conduct a face-to-face semi-structured interview. "The key idea behind qualitative research is to learn about the problem or issue from participants and engage in the best practices to obtain that information" [24, p. 47]. The data were collected through fifteen participants. The sample size in qualitative research is often small [32,33]. Two participants' having an Associate Professor position and thirteen were having a Professor positions', three of them are deans. The study respondents have different disciplines and they work in different faculties in the university. Although they work in various faculties, the conclusion is that they have been a homogeneous participant group because all of them were academicians. During the data collection and coding, other activities were recorded and considering. For instance, in the interview, the participants have been encouraged to discuss and talked more through probing questions. The interview questions were focused and developed based on understanding the research problem through reviewing and examining of related literatures. The qualitative researcher "do not tend to use or rely on questionnaires or instruments developed by other researchers" [24, p. 45]. The interviews were conducted until the participants no longer provided differing or new information, and data saturation developed in the answers. The next step was an open coding analysis of the interview data. As a case study with qualitative approach, the study procedure established an analysis as well as coding of the respondents' answers to the research question. In the coding process, an electronic recording device has been used to tape all the interviews, and then, transcribed them into a text format. The participants' responses were reviewed several times in order to identify and determine the concepts. The main concepts were identified through free coding into categories and

subcategories. [24] explains that the qualitative researcher "review all of the data and make sense of it, organizing it into categories or themes" (p. 45). The categorization process has been achieved based on a group of similar participant's responses together. "After coding, the data were subject to constant comparison and analysis. The constant comparative method is a technique that allows the researcher “to group answers to common questions, analyze different perspectives on central issues” [29, p. 367].

V. MODEL DEVELOPMENT A. The Knowledge Sharing System Model Developing Based on the conducted interviews with the real End-users (academicians), it is substantial to develop a KSS model to efficiently and effectively share knowledge in HLI. Nevertheless, the applications and components of the proposed system model may require the HLIs to apply some changes that may require more cost and efforts, which such these changed not easily to be applied by some of them. The final system model technological components divided into six major layers and each layer include a number of components to perform the layer functions. These layers are User Layer, Access Layer, Application Layer, Knowledge Base Layer, Service Layer, and Repositories Layer. Figure 1 in Appendix A illustrates the final KSS model layers and components which has been developed based on academicians knowledge sharing behavior.

B. Description of the Knowledge Sharing System Model Layers and Components The User Layer is starting-point where the users interact with other system layer. It enables the user from using and benefit from the system. The academicians can share knowledge with other users through three types of knowledge networks which are Business Club network, Research network, and Personal network. The User layer content nine knowledge sharing influential factors which include reputation builds, acknowledgement, personal beliefs, to be knowledgeable, reciprocity, present of vision and mission, to be a mentor. The second layer is Access layer. This layer enables user to access into the system and benefit from its services. The access process includes registration and authentication. Through the Application layer, the academicians are able to access to tools that are provided by the system. The collaborative tools enable academicians to communicate synchronous and asynchronous with the other. The capturing tool allows academicians to add (store), edit, categorize knowledge, while retrieval tools allow users to access and search for knowledge that has been stored in the system repositories and retrieve it. The Knowledge Base layer determines the kinds of knowledge that academicians could create, store, use, search, and share with other users. It includes also the processes that academicians or other user could use to manipulate all the system contents start from creating and end with store different type of data include text, picture, and

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videos. Through the fifth layer, the users could utilize and employ a variety of collaborative applications and communication tools to share and exchange their knowledge synchronous and asynchronous. Synchronous through, for example, E-meeting which allows the academician to make synchronous conversation. Asynchronous enables the academicians to contact other through other tools, such as email and blog. This layer also provides the academicians with other services such as create new group, RSS, ask for a consultation, searching, and offer a list of expert information to contact them and benefit from their experiences and perceptions. Finally, Repositories layer encompasses an enterprise warehouse which includes several small databases for storing data. Each database allocated for each type of knowledge. These databases could be able to store variety forms of knowledge such as videos, pictures, and text.

C. Advantages of the Developed Knowledge Sharing

System Model This KSS model as figure 1 (Appendix A) shows was

developed and proposed based on the actual academicians knowledge sharing behavior as well as based on their need. There are eight advantages for this model. A summary of these advantages is listed below:

1. The proposed KSS model represents the end-users knowledge sharing behavior in term of knowledge type they share, knowledge networks, knowledge platforms and knowledge motivation. Thus, the proposed system model will fill the prior knowledge sharing and management system that did not really developed based on the end-users behavior and need.

2. The proposed KSS model represents and classifies all knowledge types that being shared among academicians. The proposed system model differentiates between three types of knowledge that have been emerged directly from the participants, instead of using some traditional existing classification. The classifications and sub-classification of knowledge in this study are more meaningful and understandable by the user since it related to their area and culture.

3. The proposed KSS model represents exactly the real people and group whom academicians currently share with instead of traditional believe that academicians share normally with other academicians and students. Thus, in the proposed KSS model, it is suggested to open communication channel with all whom academician share with after determining and announce the using policies from the system owner (i.e. Higher Learning Institutions).

4. The proposed KSS model offers a variety of collaborative tools, which enable the end-users to share with others in different ways. For instance, the academicians can share their knowledge synchronous through virtually face to face meeting via E-meeting feature. Besides, the proposed system model was provided by several asynchronous channels and tools to enable the academicians to share their knowledge at any time and from any place. All these communication tools and channels are placed in solely one interface. Offer several communication tools and channel in

a single interface would make the sharing and exchanging knowledge much easier. For instance, it provides the user by email account, blog, consultation services through offering an expert list information. The proposed system model is provided by the 'Rich Site Summary' (RSS) feature which provide the interested user periodically with latest knowledge added to the system. Additionally, the proposed system model also provide by the feature that enable academicians to open new research or interest group through 'Create New Group' feature.

5. The proposed KSS model provides a clear structured procedure for data capture, share, use, search, and store since it has a special database for each type of knowledge.

6. The proposed KSS model regards a human factors that may influence the users' knowledge sharing behavior. It considers, for example, users build reputation, reciprocity, their willingness to be Knowledgeable, and incentive monetary and non-monetary rewards as appear in figures 2,3,4, and 5 respectively in the (Appendix A). These factors could encourage and increase the knowledge sharing activities among users.

7. It provides a comprehensive component that would enable the users to exchange their knowledge in different and easy ways. It also proposes a clear relationship among users.

8. This KSS model was developed after extensive review the previous knowledge management and sharing system models literatures with the aiming to identify its drawbacks and avoid them. For instance, some of the previous knowledge management system shortcomings are that it does not represent the real need of end-user nor capture the types of knowledge being shared among employees in the organization as has been explained in chapter 1. Such these problems have been avoided in this proposed KSS model.

VI. Conclusion & Future Work Recommendations This study extends prior research by developing a knowledge sharing system model based on academicians knowledge sharing behavior. The proposed KSS model addressed several features that come from the real end- user, the academicians. The KSS model that has been developed in this research would solve existed knowledge sharing system problems. The Higher Learning Institutions could exploit and utilized this proposed KSS model for sharing knowledge among their academicians and between academicians and their knowledge sharing networks. This case study focused on proposed a KSS model based on academicians knowledge sharing behavior in Higher Learning Institutions in term of the type of knowledge being shared, how they share it, with whom they share, and why they share it. However, it is recommended to study knowledge sharing behavior among other staff in the Higher Learning Institutions such as for example non-academic staff and model their behavior into a system. A suggestion for further improvement of the proposed KSS model are provided.

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Acknowledgement The research paper authors introduce their thankfulness to the Saudi Ministry of Higher Education for their moral supporting and encouraging.

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Appendix A

Figure 1. The Knowledge Sharing System Model

Figure 2. Building Reputation Model Figure 3. The Reciprocity Model

Figure 4. Knowledgeable Model Figure 5. Acknowledgement Model

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