Factors Influencing Employees Knowledge Sharing Behaviour within an Investment Firm in Kuwait - Case Study Example

DBA THESIS PROPOSAL FACTORS INFLUENCING EMPLOYEES’ KNOWLEDGE SHARING BEHAVIOUR WITHIN AN INVESTMENT FIRM IN KUWAIT SALEH AL-OTHMAN TABLE OF CONTENTS1 INTRODUCTION 1 1.1 COUNTRY BACKGROUND 2 2 RATIONALE FOR SELECTION OF TOPIC 3 3 SOCIAL EXCHANGE THEORY 4 4 PROBLEM DEFINITION 6 5 RESEARCH OBJECTIVES 6 6 RESEARCH QUESTIONS 7 7 RESEARCH MODEL 7 8 STUDIED VARIABLES 9 8.1 INDIVIDUAL COGNITION 9 8.1.1 Perceived Benefits 9 8.1.2 Organizational Commitment 9 8.2 INTERPERSONAL INTERACTION 10 8.2.1 Social Interaction 10 8.2.2 Trust 11 8.3 ORGANIZATIONAL CONTEXT 11 8.3.1 Organizational Support 11 8.3.2 Reward Systems 12 8.4 INFORMATION TECHNOLOGY 13 9 RESEARCH METHODOLOGY 13 9.1 QUANTITATIVE RESEARCH 14 9.2 QUALITATIVE RESEARCH 14 9.3 QUESTIONNAIRES 15 10 DATA ANALYSIS 16 11 STUDY IMPLICATIONS 17 12 GNATT Chart 17 References 19 1 INTRODUCTION Sharing of knowledge is commonly agreed as an important process in the settings of an organization, even if they are project teams, formal work groups or communities of practice. Organizational settings usually exist to achieve a collective outcome, for example delivering physical or intellectual products and/or services. They are created or emerge as there is no single actor involved in sharing knowledge can form the collective result alone. In different organizations, sharing of knowledge may be seen as the behavior whereby a person willingly offers other individuals in the organization with right to use his or her experiences and knowledge. Sharing of knowledge entails a wider range of multi-faceted and complex behaviors. For instance, while the knowledge and information sharing tools are offered by technology, the likeliness of doing so is not certainly taken advantage of. Various studies have revealed that sharing of knowledge is made by various factors, including the person’s attitude and values towards knowledge sharing, the organization’s culture and the technology nature (Oliver, 2008). As sharing of knowledge is presumed to be volitional and voluntary, a single emphasis of previous research has been on the intention, willingness or propensity of an individual sharing knowledge with another individual. The current research approaches propensity concept of sharing in two ways. In one way, propensity to knowledge sharing is part of self-identity expression, so that if being considered as knowledgeable is significant in self-identity, then a person is encouraged to share knowledge. In a second way, sharing is a subjective norm. It is seen as a disposition of sharing that creates a personal norm or attitude. Sharing of knowledge fits in human decision making class that occurs in outcome interdependency circumstances, where decisions are seen to have common significances for the good of all involved parties. This leads to the theory of social exchange and also identifying the motivational factors of individuals towards knowledge sharing. 1.1 COUNTRY BACKGROUND This study will be done in the Kuwait Financial sector and particularly in the one of the most prominent investment firms in Kuwait. Kuwait has relatively a good financial structure. Figure 1 can shed more light into the financial sector layout. Figure 1: Kuwait’s Financial Sector Source: cbk.com (2013) As shown in figure 1, there are 11 local banks and 10 international banks. In addition to this the figure also shows the split of Islamic and conventional local banks. There are six Islamic banks in Kuwait compared to five conventional banks. This shows the focus on Islamic finance due to the demand. When to comes to investment firms in Kuwait, the number is much larger. According to a report by Capital Standards (2010), there are 100 investing companies in Kuwait. The focus on Islamic finance in investment firms is also high as 54 of the 100 firms follows Islamic finance. Of these 51 of these are publicly listed in the Kuwait Stock Exchange. Kuwait economy is relatively stable. The country relies heavily on its oil production and exports and over 80% of the country’s revenue comes from oil. During 2009 he oil prices decreased and hence there was a economic crisis and this was sorted out by government intervention and providing a stimulus packing of KWD 1.5 billion as a means to stabilize the financial sector. This crisis hit the investment sector as well and there was a loss of KWD 864 million in this sector. The reports by Capital Standards (2010) also states that companies such as Dar Investment and Global Investment House were hit heavily by this crisis and faced major debt repayment problems. This upheaval caused lack of major problems in the market and customers started to lose their confidence in the market and this lead to slow trading activities especially in the securities of investment firms. This impacted further decline in the asset value. But prior to the financial crisis, the investment firms were doing well and between the years of 2003 to 2007, there was strong growth in this sector. Kuwait has the largest number of investment firms than the other nations in the Gulf Cooperation Council (GCC). Based on the research, Capital Standards (2010) provides the following recommendations for the investment firms. They recommend that investment companies should reassess their business model and there is need for the investment firms to diversify and identify stable sources of income. Investment firms need to focus on customer needs and create products and services that match customer needs and expectations. This is an overview of the financial and investment structure in Kuwait. 2 RATIONALE FOR SELECTION OF TOPIC Davenport and Prusak (1998) dispute that while transferring knowledge is the objective; the technique used needs to suit the social processes and organizational culture. Moreover, De Long and Fahey (2000) assert that various contextual dimensions shape the mindset of people and their consistent relationships. They go on to argue that, sharing of knowledge is frequently not natural as individuals ascertain that their knowledge is important and valuable. In general, individuals possessing vast knowledge are not willing to share with others. A main knowledge transfer enabler is social interaction among members of an organization who depend on knowledge transfer for driving performance and supporting innovation. Due to this, a lot of papers have reported outcomes on factors affecting the intention of sharing knowledge and behavior centered on some theories like the Social Exchange Theory or the Reasoned Action Theory. Among different theories, social exchange is seen to be popular as it explains knowledge sharing. This theory asserts that people share their knowledge due to their view of the benefit to be achieved from such behavior. People in organizations providing an environment supporting positive perceptions are possible to share their knowledge. This rationale for this research is therefore to identify the organizational environment, social process and factors that enable employees to share their knowledge. Understanding these factors leads to my organizational gaining competitive 3 SOCIAL EXCHANGE THEORY The social exchange theory is a usually used theoretical base for examining the knowledge sharing behavior of a person. As seen in this theory, people control their interactions with others centered on self-interest analysis of the benefits and costs of this interaction. Individuals seek to increase their benefits and reduce their costs when they exchange resources with (Molm, 2001). It is not necessary for these benefits to be tangible as people may participate in an interaction with the anticipation of reciprocity (Liang et al. 2008). In these types of exchanges, individuals assist others with the common expectation of returns in the future, like acquiring desired resources by using social reciprocity. In maximizing the achieved resources, people may form social relationships with others by knowledge sharing. Davenport and Prusak (1998) have examined behavior of sharing knowledge. They have also outlined some potential benefits of regulating such behaviors. These benefits are; job security, job, promotional aspects and future reciprocity. From this viewpoint, sharing of knowledge will be affected positively when a person expects to get some future benefits by reciprocation (Cabrera et al. 2006). Past researches have described factors linked to the social exchange theory that are effective in clarifying behavior of sharing knowledge among people. These include; organizational contexts, personal cognition and interpersonal interaction. For instance, Kankanhalli et al. (2005) thought that a perceived benefit of a person is among the major factors encouraging employees to share knowledge to electronic knowledge sources. According to Ma and Agarwal (2007), knowledge contributed by individuals to a virtual community varies on the satisfaction level they develop from being community members. Chiu et al. (2006) conducted a study of interpersonal factors like trust, social interaction and type of reciprocity on sharing knowledge in virtual community. Furthermore, Kim and Lee (2006) have observed the organizational context for clarifying sharing of knowledge. Pai (2006) used the backing of top management to observe the connection between sharing of knowledge and using of IT/IS strategic planning. In addition, Watson and Hewett (2006) examined the consequence of increased knowledge influence in an organization. Even though other studies have revealed that the social exchange theory can explain successfully the knowledge contributors’ behavior, the present study has specific drawbacks. Kim and Lee (2006) established that reward systems were major variables that had an influence on employee knowledge-sharing abilities. However, Lin (2007) stated that the willingness of employees to share their knowledge with others was not affected by organizational rewards. These contradictory answers frequently lead to issues in both practical implementation and theoretical interpretation. In knowing what outcomes are probably correct and if the social exchange theory can understand knowledge sharing behavior of people, this study recommends a comprehensive social exchange model that comprises factors in three different dimensions, organizational context (organizational reward and support system), individual cognition (organizational commitment and perceived benefits) and interpersonal interaction (social interaction and trust). Additionally, IT support is also added to examine if their moderating effects exist. 4 PROBLEM DEFINITION A lot of academics and practitioners have assumptions that since sharing of knowledge is crucial for achieving the collective outcome, individuals will share their knowledge as a necessity of their work requirements. However, many companies and institutions have seen that sharing of knowledge is not happening in practice, regardless whether a person-to-person or a person-to-document strategy is followed (Hansen, et al. 1999). For a company, knowledge sharing among their employees has different benefits: it allows the organization to develop on previous knowledge and experience, respond more swiftly to difficulties, improve new insights and ideas, and evade doing the same mistakes done previously. On the other hand, for a person, knowledge sharing is a more unclear proposition. It needs effort and time to share knowledge. There is a lot of worry on the loss of knowledge earned in a hard way, and uncertainty on how the knowledge will be received and put so that others may use. Due to this tension between individual ambivalence and organizational intent, sharing of knowledge in organizations becomes a bigger challenge (Cyr & Choo, 2011). At the individual level, this tension dynamics are played out, but while many studies have observed systems and methods that can enable sharing of knowledge, there is minimum study on the factors influencing the willingness of a person to share knowledge with the others in an organization. 5 RESEARCH OBJECTIVES Organizational knowledge sharing studies normally look at two kinds of knowledge exchange conditions. The first condition refers to retrieving and contribution of knowledge by employees to and fro a knowledge repository or a central database (Cress et al. 2007). Knowledge found in a system is said to be a public good. It is seen as a public resource whereby every person may benefit, but needs voluntary contributions for it to exist. The public good insight of sharing knowledge is common in studies on implementing knowledge management systems but it may not talk on the individual perception effectively (Cabrera and Cabrera, 2002; Galletta et al., 2003). The other knowledge exchange situation takes place when employees share knowledge with others what they have learnt or made. This situation is not the same from the past systems-mediated method whereby a social presence of another person is viewed. Hereby, the main interests of the research are the motivational factors increasing the willingness of a person to share knowledge. Bock et al. (2005) studied the knowledge sharing literature and revealed different levels of motivational factors: organizational, individual and group. At the personal level, the attitude of an individual towards sharing of knowledge, the self-worth sense of an individual by sharing and the anticipated reciprocal connections from others are the main factors that affect behavioral intention of sharing knowledge. In this research we focus on the individual perspective of knowledge sharing and how organizations can motivate employees to share knowledge. 6 RESEARCH QUESTIONS What is the significance of individual cognition (perceived benefits and organizational commitment) on knowledge sharing? Does interpersonal interaction (social interaction and trust) enable employees to share their knowledge? How does organizational context factors such as organizational support and reward systems impact the knowledge sharing? What is the significance of information technology on knowledge sharing? 7 RESEARCH MODEL The proposed research mode for this research has been adopted based on reviewing various literatures on knowledge sharing. The variables that are studied in this research are studied are factors that enable and promote knowledge sharing among employees in the organization. Figure 1.1 shows the proposed research model. Figure 1.1: Proposed Research Model The proposed research model (figure 1.1) has independent variables, moderators and the dependent variable which is knowledge sharing. The independent variables are classified into three categories: 1. Individual Cognition: The variables that are considered under this category are perceived benefit and organizational commitment. 2. Interpersonal Interaction: The variables studied under interpersonal interaction are social interaction and trust. 3. Organizational Context: The variables studied under organizational support and reward systems. The moderating variable in this research is information technology and the dependent variable is knowledge sharing behavior. Details of these are discussed in the next section. 8 STUDIED VARIABLES Based on the proposed research model (figure 1.1), following are the variables that are being studied. 8.1 INDIVIDUAL COGNITION Individual cognition comprise of two variables – perceived benefits and organizational commitment. A summary of these variables and their hypotheses will be provided in this section. 8.1.1 Perceived Benefits In the social exchange theory, the important dimension is individual cognition that may include organizational commitment and perceived benefits. Perceived benefits are the subjective perception of an individual gaining from the behaviors (Forsythe, 2006). Davenport and Prusak (1995) asserted that behavior of sharing knowledge may be inspired by perceived benefits. Other individuals expect that their assistance will assist them improve their prominence in the social group and form a good repute. Different people offer their knowledge as they have positive sociability feelings (Wasko and Faraj, 2005). Therefore, individuals may be motivated by the anticipation of personal benefits in sharing their knowledge to others. Based on these arguments, the first hypothesis is: H1a: knowledge sharing behavior of an individual is positively connected to perceived benefit. 8.1.2 Organizational Commitment Organizational commitment (OC) refers to positive attitude toward the organization and to the quality of the relationship between the employee and the organization. It is clearly seen that organizational commitment is related to various organizational behaviors such as helpfulness, job satisfaction, turnover and sense of obligation (Meyer et al. 1993; Liang et al. 2008). Wasko and Faraj (2005) assert that on the shared membership basis, commitment of an individual to a collective denotes to a sense of responsibility to assist others in that community. It is also backed by evidence provided by Rocha et al. (2008) who provided various empirical studies linked OC to other work-related variables. For example, Mathieu and Zajac (1990), in their meta-analysis, pointed out the most common OC links: as an antecedent (personal characteristics, role states, job characteristics, organizational characteristics and group/leader relations); as correlated (motivation, job involvement, job satisfaction, stress and occupational commitment); as a consequence (job performance, intention to leave, lateness and turnover). More recent studies highlight the positive correlation between OC and Organizational Citizenship Behavior (Meyer et al. 2002), willingness to share knowledge and engagement in extra-role behavior (Storey and Quintas, 2001; McKenzie et al. 2001). It may play a significant role in boosting people to share their knowledge. Based on these arguments, the second hypothesis is: H1b: the knowledge sharing behavior of an individual is positively connected with organizational commitment. 8.2 INTERPERSONAL INTERACTION Within interpersonal interaction there are two variables that are being studied – social interaction and trust. In this section the relevance of these two factors will be discussed along with the hypothesis. 8.2.1 Social Interaction Social interaction is a channel for information and resource flows. When exchange partners involve themselves in social interactions, the greater is the frequency, breadth and intensity of exchanged information. Hall (2003) indicated that various exchanges between parties may be viewed due to social interaction. Social interaction in forms of face-to-face communication, conversation, verbalization, discussing, and dialoguing has been determined as a main perquisite for knowledge sharing, and especially for tacit knowledge sharing as stated by Panahi et al. (2012). These authors add that social interaction can be in person or even virtual. An important role is played by social media a lot of individuals’ life and lot of information and knowledge is being shared through the social media platforms. This also shows the importance of information technology in social interaction, which can also be applied to knowledge sharing. Other authors such as Chiu et al. (2006) and Inkpen and Tsang (2005) have also found social interaction to significantly influence knowledge sharing. This is because social interaction enables individuals to increase the depth, breadth, and efficiency of the knowledge they share with one another. Based on these arguments the hypothesis for the third hypothesis is: H2a: Social interaction is positively associated with an individual’s knowledge-sharing behavior. 8.2.2 Trust Trust is another factor that has been identified as an enabler to knowledge sharing (Amayah, 2013; Liang et al. 2008). Trust discusses various precise beliefs primarily involving the capability, integrity and generosity of the other party (Chiu et al. 2006). Trust is important for the social exchange process in the social exchange theory. Exchange relationships are created and maintained by trust, which result to sharing good quality knowledge. Liang et al. (2008) goes on to state that when trust is existent between two individuals, they are more prepared to involve them in cooperative interaction. The study by Amayah (2013) focuses on tacit knowledge and therefore she states that for tacit knowledge to be transferred successfully there must be trust and mutual understanding. Studies by Ardichvili et al. (2003) found that participants who were more inclined to use the knowledge made available if they trusted it to be an objective and dependable source of information. Thus, due to trusting one another, individuals become more open to one another (Garavan et al. 2007). It makes individuals to share their knowledge and be willing to collaborate with others (Liao, 2006; Sharratt and Usoro, 2003). Based on these arguments the forth hypothesis is: H2b: Trust is positively associated with an individual’s knowledge-sharing behavior. 8.3 ORGANIZATIONAL CONTEXT Organizational context has two variables - Organizational Support and Reward Systems. An overview of Reward Systems and Organizational Support will be provided in this area. 8.3.1 Organizational Support This is a broad view that an organization cares for the good of its employees and also values the contribution made by them (Liang et al. 2008). The perspective of social exchange undertakes that the relationship between the employer and the employees is made on the effort trade and loyalty for benefits like recognition, pay and support. Hence, organizational backing, direct or indirect, is an important factor in the concept. Coworker and Supervisor backing is a personal measure of the encouragement degree offered to and experienced by an employee in sharing work related problems solutions by using communication such as electronic and face to face meetings in sharing knowledge. The fifth hypothesis is based on the organizational support, where: H3a: Organizational support is positively associated with an individual’s knowledge-sharing behavior. 8.3.2 Reward Systems Reward systems that offer members reasons of shaping their behavior or improving their learning performance are important (Pham and Swierczek, 2006). Rewards in an organization can vary from financial incentives like increased bonuses and salaries to rewards that are not monetary like innovative promotions and concrete rewards. Normally, these organizational rewards are performance-based and can increase the motivation of an employee (Kharabsheh, 2007). Many researches have argued that for knowledge sharing to be successful in an organization, a reward system needs to be present. For instance, Bartol and Srivastava (2002) observed the duty of monetary rewards in boosting knowledge sharing in organizations. They further observed four knowledge sharing mechanisms and established a positive connection between sharing of knowledge and monetary rewards. Bartol and Srivastava (2002) claimed that the method of giving knowledge to databases is the most acquiescent to rewards contingent on different knowledge sharing behaviors. This is due to the reward allocator prospects of measuring the knowledge sharing behaviors. Kugel and Schostek (2004) observed the influence of financial rewards on sharing of knowledge in Siemens. They asserted that financial rewards appeared to have an instant effect on motivation in knowledge sharing. On the other hand, these authors claimed that the standards of the shared knowledge can be lesser, and the approach that the shared knowledge is non-collective good and private is required. They noted that when financial rewards are removed, sharing of knowledge will lessen Reward is therefore an enabler to knowledge sharing and therefore the sixth hypothesis is: H3b: Reward systems are positively associated with an individual’s knowledge-sharing behavior. 8.4 INFORMATION TECHNOLOGY The infrastructure of information technology includes the technology tools that support the effort of knowledge sharing (Bechina and Bommen, 2006). Smith (2003) states a very clear connection between sharing of knowledge and technology. Information Technology makes possible the relationships enabling sharing of knowledge, but employees are not encouraged sharing their knowledge. Technology needs to be seen as a way of facilitating knowledge sharing. While technological tools can be put in place by organizations, there is no assurance that they will be used by the employees effectively. This reveals a human aspect in these tools. For instance, organizations create knowledge maps whereby communication modes and expertise fields are put in a human resource system. This facilitates employers in accessing employees with the required expertise in solving their issues (Desouza and Awazu, 2003). This tool can assist employees to go through geographic boundaries (Desouza and Awazu, 2003). Knowledge sharing technology tools are discussion forums, groupware, electronic bulletin boards, intranets, knowledge directories, databases, electronic mail, intelligent search engines, virtual conference rooms, personal web pages, libraries among others (Alavi and Leidner, 2001; Bender and Fish, 2000). The seventh hypothesis is for the moderator. H4: Use of IT-based knowledge management systems moderates the relationship between the studied independent variables and individuals knowledge-sharing behavior. 9 RESEARCH METHODOLOGY This research aims to adopt both empirical and non-empirical designs. In other words, primary and secondary data will be collected for this research. The sources of secondary data will be articles, books, internet and other published resources and this will form the literature review on KM and related topics. The literature review will be the background towards carrying out the research as the research framework and conceptual model will be generated from these. The primary data will be collected from employees in the organization through surveys, followed by interviews with the managers. Emphasis is on the primary data that will be collected for this research. The primary data collection consists of a mixed methodology wherein both quantitative and qualitative research methods are used. The use of these two methods will be on two phases. The first phase will quantitative research method. 9.1 QUANTITATIVE RESEARCH Quantitative research method tackles numeric information, which is usually machine-readable and can be derived from accepted statistical tests and models. In this method, usually, the information is collected by asking the similar questions to an exact trial population and recording their answers correspondingly in numeric codes or actual numbers (Saunders et al. 2007). A survey will be carried out and to collect the data. The data collection instrument will be self-administered questionnaires designed using closed-ended questions and five point Likert scale questions. This will be talked on the next sections. 9.2 QUALITATIVE RESEARCH Qualitative research method is a detailed description where the researcher knows only a rough knowledge about the subject. In this analysis the researcher himself / herself is gathering data, which is time consuming. (Saunders et al. 2003). Qualitative research is used to help explain a phenomenon. It is designed to understand and find to how reasons through explanations. Qualitative data can also help to derive the opinion, experience and feelings of the individual and attempts to describe a social phenomenon as they occur. Qualitative research follows a deductive approach and is aimed towards testing the research theories. Data collection is done through personal interaction with the respondents (Hancock, 2002). The process in the second phase which is based on a qualitative research method, is to collect data from managers through personal face-to-face interviews. The interviews will be semi-structured and therefore will use questions to guide the interviews. The questions will be prepared based on the findings of the quantitative data analysis. 9.3 QUESTIONNAIRES Questionnaires are very useful in survey data collection. The term ‘questionnaires’ are used in a general way to include all techniques of data collection in which each person is expected to respond to the same set of questions in a predetermined order (Saunders et al. 2003). To ensure validity and reliability of the question, an experimental test will be done on 8-10 employees and managers. The pilot test results will indicate the ease of understanding the questions and also how the respondents answer each of the questions / statements. As indicated earlier, the questionnaire will be designed to be self-administered. The questionnaires will be designed using professional survey websites such as QuestionPro.com, SurveyMonkey.com or similar websites. The use of such websites ensures mandatory controls and the data can be collected either in an Excel format or SPSS data format. The questionnaire website link will be emailed to every employee, supervisor and manager in the investment firm. The questionnaire will have a covering letter that describes the objective of the survey and will provide in writing the assurance of anonymity and confidentiality. The questionnaire will collect a few demographic variables such as age, gender, nationality, job position, and number of years in the organization, but not personal information that discloses the respondents identify will be collected. In addition to this the use of survey websites ensures that email address or other information of the individual is also not disclosed that will jeopardize the respondents’ credibility or reputation. The collected data will be statistically analyzed by using SPSS and the results will be discussed in the data analysis chapter. The findings will be used to carry out the second phase of the primary data collection. This will be a qualitative research method. The interviews will also be based on questions and therefore would be a semi-structured approach. The used of questions helps to focus on particular aspects that need clarifications and enhancements to the research. In addition to this the semi-structured approach allows the user to add more information and also the researcher to ask more questions as a means of clarifications. The interviews are with the department heads (managers) and these managers will be assured confidentiality to make sure that their private information is not exposed. If the managers are not comfortable in doing interviews in their offices, the interviews will be carried out in a coffee shop or other places where they can speak openly and without bias. 10 DATA ANALYSIS The quantitative data analysis is carried out using statistical software such as the SPSS (Statistical Package for Social Sciences). Following are the proposed types of statistical analysis that will be carried out on the quantitative data. Descriptive Analysis: The descriptive analysis will provide understanding into the responses of each demographic variables and the five point scale Likert statements. Crosstab Analysis: This type of analysis is used to understand the relationship of response between two variables. Correlation Analysis: The correlation analysis is mainly used to understand the correlation significance between the variables Factor Analysis: The factor analysis is used for data reduction and to understand data redundancy. The factor loading is used to understand the significance of each five point Likert scale statement. Regression Analysis: Regression analysis is used to understand the importance of dependent variable to independent variable. One-way ANOVA and Independent Sample T-Test: One-way ANOVA and Independent sample T-Test is used to understand the significance of demographic variable on the studied variable. 11 STUDY IMPLICATIONS Knowledge is important for managers and decision makers, to make the right decision and also for employees to function better in their jobs. Knowledge sharing will help, elevate the use of knowledge and create a learning environment in the organization through which employees can be more productive and managers can be more efficient in managing their teams and carrying out efficient decisions. In addition to all this, knowledge needs to be managed so that it can be beneficial to the organization and its employees for its usage in different scenarios. Through this research, the researcher aims to create a knowledge sharing environment by identifying the enablers of knowledge sharing in the organization. By understanding the factors that enable knowledge sharing, the management can be provided the recommendations that need to be implemented to ensure successful knowledge sharing and gaining competitive advantage. 12 GNATT Chart Following is the proposed stages and timeline for the thesis. Proposed Dissertation Stages and Timeline References Alavi, M., and Leidner, D.E. (2001). Review: knowledge management and knowledge management systems: conceptual foundations and research issues, MIS Quarterly, Vol. 25, No. 1, pp. 107-136. Amayah, A. T. (2013). Determinants of knowledge sharing in a public sector organization, Journal of Knowledge Management, Vol. 17, No. 3, pp. 454-471 Ardichvili, A., Page, V. and Wentling, T. (2003). Motivation and barriers to participation in online knowledge-sharing communities of practice, Journal of Knowledge Management, Vol. 7 No. 1, pp. 64-77 Bartol, K.M. and Srivastava, A. (2002). 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