As the population ages, increasing number of vulnerable older people are living alone in own home, sheltered housing or residential care. The needs of the older people are constantly changing and there is need for long term support. Older people living in sheltered housing with complex and high needs require access to services with a network of different types of support; high staff cover and supervision. Supported people introduced floating support to aid people with high and complex needs. Floating support aimed at preventing homelessness among people with high difficulties; and intensive support, with out-of-hours cover, for people with high needs. Housing services, social services’, ‘health services’ have to liaise and coordinate the services being provided. Knowledge sharing will help ease of the tensions and demands among the agencies.
This paper, which is based on an on-going PhD project, begins by examining the field of sheltered housing for the elderly, discusses floating support and the key prayers providing the support. This is followed by analysis of knowledge sharing and potential factors that are important to a successful knowledge-sharing in providing floating support to the services provider. This paper concludes that , trust, motivation, effective communication, shared mindsets, training and leadership are the critical for effective knowledge sharing in provision of floating support in sheltered housing for the elderly. Effective gathering and sharing knowledge and information between supported Housing providers, social services and health and Care agencies through the establishment of the Knowledge sharing initiatives.
Knowledge sharing, sheltered housing, floating support and Provisions
Nowadays Knowledge is regarded as a strategic resource in organizations, and thus the leverage of knowledge is a key managerial issue. Knowledge creation, sharing and dissemination are the main activities in knowledge management. This study examines the influence the social and technological factors such as learning culture and IT use, could have on knowledge sharing of King Fahd University of Petroleum and Minerals (KFUPM) students. A cross-sectional survey was used as a methodology for data collection and 137 valid responses were collected from all the three categories of students that include graduates, undergraduates and preparatory students. The study shows that there is a significant positive relationship between the student learning culture and IT use on student knowledge sharing. The study limitations, practical implications, along with directions for further research are discussed..
Despite the strong interests among practitioners, there is a knowledge gap with regard to online communities of practice. This study examines knowledge sharing among critical-care and advanced-practice nurses, who are engaged in a longstanding online community of practice.
Lack of knowledge and sharing knowledge with each other was also reflected on (Table 2 and Appendix). The participants from the specialized unit for demented people spoke about their lack of knowledge concerning demented people in general and they wanted more training. Their practical knowledge gained through long experience was put forward by the supervisor. Lack of resources, principally lack of time was another topic for reflection (Table 2 and Appendix). The participants spoke about the work with demented pensioners as time-consuming and that they hardly ever had the time they wanted, for instance to sit down and talk to the pensioners.
The descriptions presented during the sessions and derived from practical experience could also support other staff who are dealing with the complexity of caring for demented people. The participants were given the opportunity of sharing their own knowledge with each other through comparing how they handled various tasks. Several studies show that staff who are given the opportunity to share their practical knowledge with others gain a wider variety of experience, attitudes, new ways, views and solutions to problems (Bulechek & McCloskey 1985, Kadushin 1985). Johns (1995) emphasized that reflective practice always needs to be guided and that clinical supervision is central to the process of learning. ‘Clinical supervision offers an ideal milieu for the guidance of reflective practice just as reflective practice offers an ideal method to structure what takes place within clinical supervision’ (Johns 1995). The benefits of these reflective discussions are not the focus of this study. It seems reasonable, however, to assume that such well-designed discussions also help the nurses to achieve high quality care.
(Olsson and Hallberg 1998)
Effective knowledge sharing is vital to successful provision of floating support in sheltered housing for the elderly.
There is still little knowledge available about home-based professional care for demented people and how to support it from a managerial point of view. In order to develop clinical supervision techniques further and to understand the home care staff’s specific problems in their caring for demented people living in their own homes, it seems useful to study the content of supervision sessions. The professionals’ narratives during such sessions may contribute to a deeper understanding of professional home care for the demented.
It is estimated that the best solution for elderly demented people is to stay at home, since their known environment can better support the maintenance of their personal lives and values. Staying at home supposedly gives demented people an opportunity to maintain ADL-performance, and promotes the individual’s sense of self and integrity (Zgola 1988, Kihlgren 1990). Studies from Canada and the USA show that demented people remain in their homes during the major part of the disease (Alessi 1991, Gallo et al. 1991). It may well be that the circumstances are the same in Sweden. No studies, however, have been located. Usually demented people who stay at home are cared for by their own families (Dellasega 1991) and this is known to cause strain on the family caregiver (Given et al. 1990, Pushkar Gold et al. 1995). The family caregiver also seems to benefit from increased satisfaction and self-esteem related to taking on and carrying through the responsibility for their demented family member and they do not necessarily worry about their demented next of kin, as they tend to do if the demented becomes institutionalized (cf Stephens et al. 1991). On the other hand the family caregiver may suffer from social and affective limitations in his/her life especially at the beginning of the next of kin’s disease (Grafstrom et al. 1992) and Saveman et al. (1993) show that there is a risk of abuse of elderly people in informal care. Home care staff may have the opportunity to relieve such strain.(Olsson and Hallberg 1998)
(Olsson and Hallberg 1998)
Research on outcomes in supported housing has been very limited and most published studies are descriptive, rather than evaluative. Cost-effectiveness has generally not been investigated. The outcomes most commonly evaluated are satisfaction and quality of life.
A recent GOSW research review has concluded that:
§ There are some beneficial effects of supported housing, particularly in relation to quality of life that could lead to improved health;
§ There is a lack of research into health related outcomes, such as re-admission rates or clinical symptoms;
§ The objective of promoting independence, as stated in the South West Regional Housing Strategy, should be assessed formally;
§ There is a need for formal evaluation of supported housing schemes to ensure that the projects meet the needs of the clients and the wider population.
In the area of knowledge management, many studies have been devoted to investigating how to design an effective knowledge-sharing system in organizations. These studies emphasized the importance of various aspects to the success of the knowledge-sharing system and provided us with hints concerning what critical factors we should consider in the design of a knowledge-sharing system for group learning. In this study, we aim at exploring the critical components of a successful knowledge-sharing system and influential aspects we should consider in the design of a system for group learning. To achieve this task, we conducted an experiment during a semester-long course. The participants in the experiment were the final-year undergraduate students of a business school in Hong Kong. Finally, several factors important to the success of a knowledge-sharing system were identified. Implications for teaching and learning were also provided.
Knowledge sharing, group learning, critical success factor
Knowledge sharing among students is believed to be an effective approach to facilitate studying and improve their academic performance. Therefore, how we should carry out successful knowledge sharing in the classroom is a meaningful topic and should be given some attention. To build a knowledge-sharing system is an approach worthy of effort in conducting effective knowledge sharing in school. However, which system aspects merit consideration is still a problem under investigation. Based on previous research, the present study explores potential factors that are important to a successful knowledge-sharing system and discusses some implications for academic teaching and learning.
In the area of knowledge management, many studies have been done to investigate how to establish an efficient system for sharing knowledge in organizations. These studies emphasized the importance of various aspects to the success of knowledge sharing system. For example, Almeida et al’s study (2002) emphasized the availability of multiple mechanisms, formal and informal, to share and transfer knowledge so as to flexibly and simultaneously move, integrate and develop technical knowledge. Besides, the organizational culture that is capable of supporting the flow of knowledge was also addressed as an important factor. Another study by Nelson and Cooprider (1996) empirically tested the relationships between IS performance and mutual trust and influence among IS groups and their line customers. They found that mutual trust can facilitate knowledge sharing and can then increase shared knowledge. Bryant’s paper (2003) mainly studied the role of leadership in organizational knowledge management by comparing the effect of transformational leadership and transactional leadership on knowledge sharing. The involvement of high technology in knowledge sharing is addressed by Huber’s study (2001) that claimed that some of the barriers to knowledge sharing can to a certain extent be raised by utilizing appropriate technologies.
A few studies noted the role of motivation in knowledge sharing. Most of them discussed the different effects of both extrinsic and intrinsic motivation on knowledge sharing. It was believed that extrinsic motivation is a short-term approach and cannot create a lasting commitment to sharing knowledge (Kohn, 1993). Moreover, extrinsic motivation is also inappropriate if the knowledge shared is mainly tacit in nature (Osterloh et al., 2000). In Hansen’s paper (2002), the results showed that project teams who could conveniently access related knowledge from other units by virtue of pre-existing relationships could complete their projects faster than those who failed to do so. Thus, pre-existing relationships are also a facilitating factor due to their shortening the path among units who possess related knowledge. Lastly, a common language is also believed essential for effective knowledge sharing so that knowledge producers and recipients can achieve fluent and accurate communication in exchanging ideas and knowledge (Ali, 2001).
For this study, we planned an experiment that was conducted during a course and lasted for whole semester. The participants in the experiment were the final-year undergraduate students of a business school. For the purposes of this experiment, we separated all students into different groups with each group consisting of five to six students. We then assigned relevant project topics to different groups and asked them to finish the projects by the end of semester. At the beginning, we counseled the participants that sharing knowledge is an effective way of improving performance and encouraged them to share their knowledge with their group mates as much as possible during the projects.
A questionnaire was designed to test the participants’ perceptions concerning knowledge sharing based on their experience acquired in the group projects. The questionnaire consisted of two parts. In the first part, we selected eight factors based on past studies, including knowledge-friendly culture, motivational practices, multiple available channels, leader supportiveness, trust, pre-existing relationship, common language and level of technology. Participants were asked to indicate the extent to which each of these factors is important to the success of knowledge sharing. The second part had four items: Email, Knowledge repository, Face-to-face (F2F) meeting and Formal seminar. We ask participants to indicate the frequency with which they used each of the above methods to share knowledge with their group mates. We distributed the questionnaire to 91 students in a course and finally obtained 75 usable samples for further data analysis.
The mean, max and min values for each of the eight variables in the first part are summarized in Table 1. In addition, we conducted a series of paired t-tests to statistically compare every possible pair of means. Based on the results of the t-test (Table 2), we categorized the eight factors into five different groups: knowledge-friendly culture and motivational practices, multiple available channels and leader supportiveness, trust, pre-existing relationship and common language, and, lastly, level of technology.
Trust Culture Motivation Channels Leader Relation Language Tech
MEAN 6.04 5.84 5.76 5.52 5.51 5.12 5.27 4.71
MAX 7 7 7 7 7 7 7 7
MIN 3 4 4 3 4 3 3 1
Importance MAX ———————————————————————————— MIN
Motivation 2.71 0.92
Channels 4.36 2.66 2.31
Leader 5.18 3.42 2.32 0.12
Relation 6.54 6.11 5.16 2.95 3.04
Language 6.31 4.22 3.66 1.98 1.96 0.95
Tech 9.28 8.41 6.83 5.03 5.73 2.70 3.50
t-value Trust Culture Motivation Channels Leader Relation Language Table 2. Results of paired t-test ( p < .05)
In each above group that contains more than one factor, the factors are not statistically different from each other. For example, the knowledge-friendly-culture factor is perceived as equally important as the factor on motivational practice. We then prioritized these five groups in terms of their importance to the success of knowledge sharing by comparing their mean level. Obviously, building trust is the most important factor and the level of technology the least, as shown in Table 1.
The mean, max and min values of the second part of the dataset are exhibited in Table 3. We also worked out the percentage of responses that rated the item more than 4 points. By referring to this percentage and checking the corresponding mean values, we can obtain information concerning how many of participants at least frequently used each method to share their knowledge with others. To conclude, F2F meeting is the most frequently used approach to sharing knowledge. Formal seminars, on the contrary, were the least used.
F2F Email Repository Seminar
MEAN 5.83 5.41 4.48 3.00
MAX 7 7 7 7
MIN 4 2 2 1
Frequent Usage 94.7% 85.3% 46.7% 21.3%
Our study has essential implications for course teaching and learning. Our study suggests that in order to facilitate knowledge sharing among students, building trusting relationships is the first and most important step to take. Such trust can be built and strengthened via gradual mutual understanding. Therefore, there should be various opportunities and occasions for students to get to know each other. In this way, improved trust due to good understanding can raise the psychological barriers to communication and can then increase the students’ willingness to share knowledge. Moreover, a healthy culture should be fostered among students that learning from others and sharing what you know with others is the right thing to do and an effective way of improving study. In this arena, instructors play a particularly critical role. As for the sharing activity itself, increasing interactive communication between students is still an ideal way of proceeding. Whether in class or after class, students should be provided with adequate opportunities for face-to-face discussions without the presence of instructors so that they can actively share knowledge during these discussions. Frequent formal seminars are not an effective approach for sharing knowledge because they hardly communicate with each other to exchange opinions and thoughts during the seminars.
Ali, Y. (2001). The intranet and the management of making and using skills. Journal of Knowledge Management, 5, 338-348.
Almeida, P., Song, J. and Grant, R. M. (2002). Are firms superior to alliances and markets? An empirical test of cross-border knowledge building. Organization Science, 13, 147-161.
Bryant, S. E. (2003). The role of transformational and transactional leadership in creating, sharing and exploiting organizational knowledge. Journal of Leadership & Organizational Studies, 9, 32-44.
Hansen, M. T. (2002). Knowledge networks: Explaining effective knowledge sharing in multiunit companies. Organization Science, 13, 232-248.
Huber, G. P. (2001). Transfer of knowledge in knowledge management systems: unexplored issues and suggested studies. European Journal of Information Systems, 10, 72-79.
Kohn, A. (1993). Why incentive plans cannot work. Harvard Business Review, 71,54-63.
Nelson, K. M. and J. G. Cooprider (1996). The contribution of shared knowledge to IS group performance. MIS Quarterly, 20, 409-432.
Osterloh, M. and Frey, B. S. (2000). Motivation, knowledge transfer, and organizational forms. Organization Science, 11, 538-550.
10 Critical Success Factors in Building Communities of Practice
Many companies are discovering that the real gold in knowledge management is not in distributing documents or combining databases. In the last few years many companies have used the internet and other new information technology to link professionals across the globe to share documents or compare data. But many are discovering that the real value in knowledge management is in sharing ideas and insights that are not documented and hard to articulate. This undocumented, hard-to-articulate knowledge is what has been called tacit knowledge (Polanyi, 1958). A group of systems designers for a computer company tried to share their knowledge by storing their documentation for client systems in a common database. They soon discovered that they did not need each other’s documentation. They needed to understand the logic other system designers used — why that software, with that hardware and that type of service plan. They needed to understand the thinking of the other system designers. A petrophysicist trying to interpret unusual data from a deep sea oil well needed help from a colleague who had seen similar anomalies and could help him think through how to interpret it. Only in the course of the discussion were they able to understand the anomaly. A geologist faced with an array of new seismic tools needed to know which would be most useful in his particular application. A product development team at an auto company found through their internet that another development team had developed and rejected a design ideas similar to one they were considering. They needed to understand the reasons for the rejection and get feedback from the other team on the approach they were considering. A sales manager working with a particularly difficult client needed to know how sales managers for other product lines had dealt with that client. In all these cases people needed tacit knowledge; knowledge that was not documented, that their peers had never previously articulated, and that needed to be thought about to be shared (McDermott, 1999a).
Using typical knowledge management methods to leverage tacit knowledge often results in information junkyards and empty libraries. At the heart of most knowledge management efforts is an attempt to document and share information, ideas and insights so they can be organized, managed and shared. But documenting tacit knowledge frequently does more harm than good. When a major computer company first introduced its knowledge site, it asked field engineers to place their files in a common database. But, like many other companies, this company soon discovered that their staff did not want to hunt through many, redundant entries. As one engineer said, "My own file cabinet is bad enough, why would I want look through everyone else’s file cabinet." Rather than a resource, the company had created an information junkyard, full of potentially good material that was too much trouble to sort through. The field engineers wanted someone familiar with their discipline to assess the material, decide what is important and to enrich the documents in the database by summarizing, combining, contrasting, and integrating them. This would make the junkyard useful. Another company instructed their professional staff to document key work processes so others could easily learn from them. Most staff felt their work was too varied to capture in a set of procedures, but eventually they completed the task. Within a year the database was populated, but little used, an empty library. Most people found the information to be too general to be useful. The help they needed was still in the experience — the tacit knowledge — of their peers.
Ironically one of the oldest elements of organization is key to leveraging tacit knowledge, communities of practice. Communities of practice are groups of people who share information, insight, experience, and tools about an area of common interest (Wenger, 1998). A community’s focus could be on a professional discipline — like reservoir engineering or biology — a skill — like machine repair — or a topic — like a technology, an industry, or a segment of a production process. In a manufacturing company, for example, communities were formed around steps in the production process. Shell Oil Co.’s New Orleans operation, which is organized into cross-functional teams, formed them around key disciplines and topics that cross individual teams. Communities of practice have always been part of the informal structure of organizations. They form spontaneously as people seek help, try to solve problems, develop new ideas and approaches. Some say that spontaneous communities of practice have always been the real vehicle through which technical knowledge spreads through organizations. Spontaneous communities of practice are informal. People participate in them as their interest, time and energy dictates. Although they usually gel around a particular topic or domain, the specific issues they focus on change over time, as the needs and interests of their members change.
Communities are held together by passionate interest and value. Communities of practice frequently form around topics community members have invested many years in developing; topics they are often passionately interested in, a science, a craft or a manufacturing process. But communities of practice are not just celebrations of common interest. They focus on practical aspects of a practice, everyday problems, new tools, developments in the field, things that work and don’t. So people participate because the community provides value. Community members frequently turn to each other to help solve technical problems, like interpreting anomalous data. Because they are often linked, not only to each other but also to suppliers, universities and others outside their organization communities of practice, they often keep members informed of new developments in the field. Because community members share a common technical interest, they can share ideas and concerns with others who really understand. And praise from community members is often the most meaningful because technical peers really understand the difficulty of the work or the brilliance of an analysis. As a result, people often have a great deal of their professional identity tied up in their communities.
Communities of practice link people in many ways. Communities frequently link people with a common interest who do not have regular day-to-day contact. For example, in Shell Oil’s New Orleans operation, communities link people who work on different teams. In this double knit organization (McDermott, 1999b) teams are the core organizational structure. Communities form around technical disciplines and topics that draw people from many teams. Each community operates in its own way, but the Turbodudes community is fairly typical. The Turbodudes draw people from different disciplines (geology, geophysics, petrophysics, reservoir engineering) who are interested in a particular kind of geological structure common in the Gulf of Mexico, turbidites. The Turbodudes stay together through five key components: a coordinator, mentors, a weekly meeting, presentations by outside vendors, and a website that stores topics discussed at previous meetings. For the last two years the Turbodudes have met every Tuesday at 7:30 in the morning, before the other organizational meetings begin. Typically twenty to forty people come to the meetings. While there are often many new faces at the meetings, there is a core group of ten high-contributors who make most of the meetings. The meetings seem very informal. The coordinator asks who has a question or problem. After a short presentation, others offer their observations, describing the logic or assumptions they made in formulating those observations. A technical specialist takes notes on her computer. The following day meeting notes are posted on the community’s website. While the meeting only lasts an hour, people often leave in small groups hotly engaged in discussions of the meeting’s topic. But these meetings are not as informal as they seem. Between meetings the coordinator "walks the halls" connecting people with others who share similar concerns, following up on the meetings topics, and finding topics for the next meeting. To keep discussions focused on cutting edge topics and to keep senior community leaders engaged, the community developed a mentorship program for people new to the field. The mentorship program provides an avenue for basic questions and distributes the job of educating new community members in an equitably.
Communities thrive on trust. One of the main dynamics of the Turbodudes and many other communities of practice is that members ask for and offer help solving technical problems. Regularly helping each other makes it easier for community members to show their weak spots and learn together in the "public space" of the community. Having frank and supportive discussions of real problems frequently builds a greater sense of connection and trust between community members. As they share ideas and experiences, community members often develop a shared way of doing things, a set of common practices, and a greater sense of common purpose. Sometimes they formalize these in guidelines and standards, but often they simply remain "what everybody knows" about good practice. In the course of helping each other, sharing ideas, and collectively solving problems, "everybody" often becomes a trusted group of peers.
Communities of practice are ideal vehicles for leveraging tacit knowledge because they enable person-to-person interaction and engage a whole group in advancing their field of practice. As a result, they can spread the insight from that collaborative thinking across the whole organization
Communities of practice are a new/old kind of organizational form. Even though communities of practice have been part of organizations for many generations, we have only recently begun to understand their dynamics and tried to intentionally develop them. Because they are organic, driven by the value they provide to members, organized around changing topics, and bound by people’s sense of connection, they are very different from teams and other organizational forms most of us are familiar with (McDermott, 1999b; Wenger & Snyder, 2000). The challenges they pose and the factors in making them successful are also different.
There are four key challenges in starting and supporting communities capable of sharing tacit knowledge and thinking together. The management challenge is to communicate that the organization truly values sharing knowledge. The community challenge is to create real value for community members and insure that the community shares cutting edge thinking, rather than sophisticated copying. The technical challenge is to design human and information systems that not only make information available but help community members think together. And the personal challenge is to be open to the ideas of others and maintain a thirst for developing the community’s practice.
Ten factors, dealing with each of these challenges, are critical to the success of communities of practice. Without them, communities tend to flounder or fail.
1. Focus on topics important to the business and community members.
2. Find a well-respected community member to coordinate the community.
3. Make sure people have time and encouragement to participate.
4. Build on the core values of the organization.
5. Get key thought leaders involved.
6. Build personal relationships among community members.
7. Develop an active passionate core group.
8. Create forums for thinking together as well as systems for sharing information.
9. Make it easy to contribute and access the community’s knowledge and practices.
10. Create real dialogue about cutting edge issues.
Knowledge management, like total quality and reengineering has become the latest of management fads. Many professionals have found that if they just keep their heads low they can escape the extra work and impact of these fads. With so many pressures drawing on their time, it is often hard to get the attention of professional staff. Four factors can communicate that management really does support knowledge-sharing communities.
To show that communities of practice are important, form them around topics at the heart of the business, where leveraging knowledge will have a significant financial or competitive impact. Communities of practice at Shell, a very technically oriented company, started around technical topics. At a manufacturing company, we formed the first communities around major steps of the manufacturing process. But the topics also need to be ones people feel personally passionate about. In the team-oriented structure at Shell, forming communities around disciplines gave people a chance to talk to peers about topics dear to them. As one geologist said, "With so many meetings that aren’t immediately relevant to your work, it’s nice to go to one where we talk about rocks."
Communities are held together by people who care about the community, who have some heartfelt interest in the topic and the people who participate. In a well-known study of networking in new product development, Allen (1979) found that project engineers used information from technical consultants and suppliers more readily when it was funneled through an internal gatekeeper. In spontaneous communities, where there is no organizational attempt to support them, an individual or small group spontaneously takes on the job of holding the community together. They keep people informed of what each other is doing and create opportunities for people to get together to share ideas. This role is also critical to the community’s survival. We have found that successful community coordinators are well-respected members of the community. They are usually senior practitioners, but not usually the world leading experts. Since their primary role is linking people, not giving answers, being a leading expert can be a detriment to effectiveness. What’s most important in a coordinator is that they are able to connect with community members on a human level. For a large, vibrant community, this role is often full time. It should at least be a substantial part of the coordinator’s job. We have found that when it is less than a quarter of their job, coordinating the community falls off their plate.
One of the great limiting factors of a community’s effectiveness at sharing knowledge is the time people have to participate. In the short term, sharing ideas and insights is usually less pressing than team and individual responsibilities. So community participation, even when very valuable, can easily be surpassed by more pressing tasks. Allied Signal supports learning communities by giving staff time to attend community meetings, funding community events, creating community bulletins, and developing a directory of employee skills. One management team addressed this issue by folding community participation into their planning and budgeting activity. They agreed on the number of person/years they would budget for communities for the year. This allocation was based on the centrality of the community to the annual business goals, the number of problems teams were experiencing in the community’s domain, and the potential for cost savings, cycle time reduction and quality improvement in the area. Most major communities were budgeted two to four technical people. Out of that most communities had a full-time leader. Community members who felt that they would be core contributors could then opt to have a percentage of their time allocated to the community. This insured that the time they spent on community activities was specifically allocated and would not interfere with their team responsibilities. It also insured that the time and energy they invested in the community would count in their performance appraisal.
To make sharing knowledge acceptable and routine, match your core cultural values rather than try to change them. Failures in implementing knowledge management systems are often blamed on the organization’s culture. It is argued that people were unwilling to share their ideas or take the time to document their insights. But organizational culture is hard to change. It rarely yields to efforts to change it directly, by manipulating rewards, policies, or organizational structure. A recent study of corporate culture and knowledge management (McDermott and O’Dell, 2000) found that however strong your commitment and approach to knowledge management, your culture is stronger. Companies successful at sharing knowledge did not try to change their culture to fit their knowledge management approach. They build their knowledge management approach to fit their culture. They describe knowledge management as a way to enable people to pursue something that the organization and its members already valued. This made sharing knowledge a more natural step that required less convincing than a direct change campaign. At American Management Systems (AMS), for example, "leveraging" what you know by educating colleagues, writing, helping others, and teaching junior staff members has been central to the company since its inception. "Leveraging" what you know is how you build a reputation as a world class thought leader. Without evidence of leveraging it is not possible to be promoted to partner. As a senior AMS manager said, "It’s not what you know that gives you power; it’s what you share about what you know that gives you power." As a result, AMS has always had many informal communities of practice, through which people found and offered help. When the company was small and housed in a single location, this informal networking was a natural part of people’s daily work. Now that AMS has grown and has offices around the globe, informal networking is more difficult. The "coffee pot" just does not scale to a global level. The AMS community building staff described their efforts as legitimating what already existed, providing structures, leadership, and software to extend people’s ability to "leverage," even though those structures and systems have greatly increased the documenting and sharing knowledge.
The greatest danger to growing communities is for them to lose energy and drift into apathy, letting the coordinator carry all the responsibility for community care-taking. When the coordinator moves on to other interests or work, then the community can easily fall apart. The greatest danger to successful communities is that they become too enthralled with their own success and see their work as that of "preserving the practice" from change. Several factors can help keep the energy of the community going, get others involved it, and keep the community on the cutting edge of its field.
Getting respected thought leaders involved as soon as possible, preferably from the start, is one of the key ways to build energy in the community. Building a community usually starts with finding, nurturing and developing the networks that already exist. Typically there are key players who either have an important specialized knowledge or who are well-connected and influential members of that network. Involving these people is important because they legitimate the community, drawing in other members. One of Shell’s global networks had to involve a group that had developed an important new technology. Many people said that they would not participate unless this group did. Everyone wanted access to their ideas and technology. As it turned out, they were relatively inactive members of the global community. But once the community was running, it realized that participation of the group was not as central as they thought it would be.
Build energy though community contact. Of course documented reports, templates, tips, analyses, proposals, etc. are helpful to most community members. But live contact is key to building a sense of commonality, enthusiasm and trust. In addition to individual meetings and web connections, create opportunities for the community as a group to share ideas. Most of Shell’s global communities have face-to-face contact one to three times a year. These are rarely meetings of the whole community. Usually they involve coordinators or groups who specialize in subtopic of the community. Several of Shell’s global communities also hold biweekly teleconferences. This creates more of a relationship, even when people are spread across the globe. In addition these events punctuate the community’s life. By creating events, they give the community a sense of history. However the community develops, a common history gives it a chronology, time and the possibility of progress. Without events it is hard for the community to see itself move through time. So physical events are important to building the ongoing energy of the community.
Contact — and the social connection and obligation that comes with it — is key to ongoing community success. The coordinator of one of our most vibrant global communities said, "This is all about relationships. People don’t really contribute to the community because it is good for the company. They do it because I ask them to." Successful coordinators visit community members, find out what they are working on, refer or introduce them to other community members, bring in new ideas and find opportunities for the community to develop its practice. They keep the community energy up by building one-on-one relationships among community members strong. The Turbodudes’ coordinator tracks the number of people who attend the meetings and has found that the strongest predictor of high attendance is how much time he spent the previous week walking the halls. Successful coordinators build and maintain these personal connections outside official community meetings. When people come to the meeting they are already connected with some members of it and can focus their energy on exciting cutting edge issues. Even when the community’s topic is very scientific or theoretical, it is the human connection that builds a base for effective knowledge sharing.
Participation in communities varies. Most have a core group of high contributors, a large group of "lurkers," who listen but add little, and a larger group of peripheral members who only participate occasionally. When we first discovered this distinction, we thought we should encourage even participation. But soon discovered that the lurkers often get great value without taking away from the core contributor’s interaction. Many lurkers say that they use the community to find out who is working on what or learn about the field and make contact later.
More important than balancing participation is to build an active core group. Active core group members not only contribute but often feel responsible to help develop the community by inviting or easing participation of people they know. In one global community, a core group member is a conduit for people who are less comfortable in English, the community’s common language. He posts questions and loads documents for them, slightly editing them as he gdoes. In another community, a core group member calls people he thinks would benefit from items posted on the community’s website and helps them connect to it. Active core group members are potential successors to the coordinator. Core group members are not always world leading experts on the topic. What makes them effective is their heartfelt caring about the topic and the community. Coordinators can develop a core group by involving them in meeting planning, asking them to take over some meetings, host subgroups, or organize elements of the website. The most important thing in developing potential core group members is to give them visibility in the community without requiring them to spend much extra time.
There is so much good technology for collaborating and sharing information that it is tempting to focus on the functionality of products. But the real challenge is to design the social side of information technology.
Ease of use has little to do with software functionality. As the market bursts with many different kinds of knowledge management software we find two things particularly important to communities. First, software should make it easy for community members to connect with each other, contribute to and use information from the community’s knowledge base. Ease of use is more about how the software integrates with people’s daily work, the knowledge they need to share, the way they think about their community’s domain and how they move about in it, than with specific features of the software itself. Shell’s global communities chose software that was less than ideal for organizing documents because some people were already using it and others were at least familiar with it. But ease of use is more than the software itself. One local team that was very active in their global community said that the reason they contributed so much was because they chose to use the same software for storing team documents as the community used. Thus, saving for the team or posting for the community involved the same number of steps. Familiar software reduces the friction in connecting to the community and its space.
An interesting way to think about communication within a community is in terms of friction. Friction is the resistance or difficulty you face in trying to connect, contribute or find help. The greater the friction, the less likely people will take the time to connect or at least connect regularly. One of the reasons local face-to-face communities are so much easier to start and maintain than global ones is that there is very little friction: walk down the hall and look for someone to talk to. It took a global community member in Nigeria 20 minutes to connect to the community website because their bandwidth was so narrow. A lot of friction. Even though he did not need to be typing in at his computer the whole time, he found the experience of connecting painful and did so much less frequently than other community members. To have a global teleconference one coordinator needed to participate in both evening and morning sessions. The more special effort it takes to connect, the more friction you need to fight. Always try to keep friction at its lowest level.
Easy integration, which sometimes translates into standardization, needs to be balanced with making the community space familiar and easy to move about in. Community space needs to be organized according to some principles or taxonomy. A good taxonomy should be intuitive for those who use it. This means it should reflect the natural way community members think about their field or topic. Like the architecture of a building, a taxonomy enables people to move about within a bank of information, find familiar landmarks, use standard ways to get to key information, create their own "cowpaths," and browse for related items. Different communities are likely to have different natural taxonomies, not only in the key categories through which information is organized, but also in the way that information is presented. A group of geologists, who often work with maps, wanted their website to be a picture. They think in pictures. A group of reservoir engineers wanted their website to be organized like a spreadsheet. They think in tables. The key to making information easy to find is to organize it according to a scheme that tells a story about the discipline in the language of the discipline.
The most valuable and vibrant community events focus on solving problems rather than presenting practices. But openly discussing problems, sharing half-baked ideas, or thinking aloud in public doesn’t come naturally to most of us. As one community member said, "It’s hard to talk about your problems in front of a lot of people you don’t know." The personal challenge for most community members is to develop this capacity.
Relationship happens in true discussion, not report outs on best practices. In the beginning stages of community development, we often orchestrate community meetings so a senior, well-respected community member asks for help and people we know have some insights to offer are in the room. This helps legitimate the discussion of problems. Even when we "stage" the event, the request needs to be real and the discussion genuine. After several rounds of well-respected community members requesting help, others usually start asking. The coordinator finds potential requests and solutions while "walking the halls" and asks these people to come to the meeting prepared to discuss the issue. During the meeting the coordinator lightly facilitates the discussion by asking people the logic of their suggestions. This helps the community discuss assumptions, alternative assumptions and think together rather than engage in a battle of positions.
Sometimes a community does not have enough connection and trust for this approach to work. There we have focused on building trust one-on-one before building it with the whole community. To build trust among a group of sales managers, we divided them up in to a series of three person discussions, sharing problems and solutions. We chose the groupings carefully to first build on then extend the trusting relationships within the group. Only after many rounds of relationship-building in three person groups did the whole community begin to trust each other enough to talk openly. Even though the coordinator only participated in a few of these discussions, he gained credibility with the group by orchestrating what was for them a painless transition from mistrust to connection.
Communities of practice present an odd irony. They have always been part of the informal structure of organizations. They are organic. They grow and thrive as their focus and dynamics engage community members. But to make them really valuable, inclusive and vibrant, they need to be nurtured, cared for, and legitimated. They need a very human touch. As leaders, organizational designers and support staff, we have little experience in how to develop this sort of organic organizational element. Too much support and they lose their appeal to community members. Too little and they wither. The challenges they pose and the factors that help them thrive are different from the factors most of us as organizational leaders, designers and support staff are used to working with.
It is ironic that information technology has made possible for us to imagine people sharing ideas and insights across the globe as easily as across the hall. But since knowing is a human act, the heart of sharing is finding a common interest, making real connection, caring for each other thinking, and building a community that trusts each other enough to ask for help and share half-baked ideas. It is ironic that for the first time in history, information technology has made global community possible, but that it takes acts of the human heart to make it real.
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Nowadays Knowledge is regarded as a strategic resource in organizations, and thus the leverage of knowledge is a key managerial issue. Knowledge creation, sharing and dissemination are the main activities in knowledge management. This study examines the influence the social and technological factors such as learning culture and IT use, could have on knowledge sharing of King Fahd University of
Petroleum and Minerals (KFUPM) students. A cross-sectional survey was used as a methodology for data collection and 137 valid responses were collected from all the three categories of students that include graduates, undergraduates and preparatory students. The study shows that there is a significant positive relationship between the student learning culture and IT use on student knowledge sharing. The study limitations, practical implications, along with directions for further research are discussed.
knowledge sharing, learning culture, IT use, knowledge management
Knowledge is recognized not only as the most important resource in organizations (Liao et al. 2004) but as one of the primary sources of competitive advantage (Stewart 1996). Knowledge is critical to the long term sustainability and success of any organization (Nonaka and Takeuchi 1995). The importance of knowledge is eminent to both public and private organizations, particularly educational/learning institutions such as universities (John 2001). The leverage of knowledge is a managerial and strategic issue. As reservoir of knowledge, higher learning institutions are no longer just providing knowledge to students, but also managing and blending together as well as sharing such knowledge among the students.
Thus, knowledge sharing is inevitably challenging and important concept in higher learning institutions. Knowledge creation, sharing and dissemination are the main activities in knowledge management. Being part of knowledge management (KM) process (Kim and King 2004), Knowledge sharing (KS) is the exchange of experience, events, thoughts or understanding of anything. In general, people expectations from knowledge sharing are to gain more insights and understanding about concepts or practical applications, thereby improving learning and expertise. Thus, knowledge sharing can be considered as a significant ingredient for mutual learning and intellectual development to students.
To stay competitive in the education industry, institutional members must promote knowledge sharing (Kumar 2005). Conversely, the competitive nature of learning institutions, among others, may hinder the knowledge sharing among the students. Thus, studies on both barriers and enablers of knowledge sharing in learning institutions may be relevant not only for adding to the literature, but to the policy makers of such institutions. Literature search shows that limited studies where available on the factors that promote and limit knowledge sharing among students.
With the increasing investment of Information Technology (IT) in educational institutions, one expects such investments to have positive impact on the way knowledge is disseminated. Possibly, the level as well as the use of Information Technology (IT) may support knowledge sharing capabilities (Ipe 2003) in institutions of learning. However, investment in technology may not be the only factor that could enable knowledge sharing. Other factors, social and cultural, in particular are worth considering. In this respect, support of one another, learning culture, might in a collectivistic society, like Saudi Arabia, promotes the willingness of students to share knowledge among themselves (Maccoby 2003).
Literature search shows that limited studies where available on the factors that promote and limit knowledge sharing among students. Similarly, the literature search revealed that, to date, no such study was undertaken in Saudi Arabia. Hence, the focus of this study is to examine the relationship of some dimensions of learning culture and Information Technology (IT) on students’ knowledge sharing.
This study is unique and original, not only for being one of the first in Saudi Arabia, but for being one of the few that examines how both technological and social and cultural factors together serve as antecedents of knowledge sharing. Next, the research objectives and significance of the study will be presented. Then, section two examines the relevant literature. Section three discusses the research methodology. Section four provides findings and implications. Finally, section five concludes the paper and recommends future research directions.
In a bid to assess the impact of learning culture and use of information technology on students’ knowledge sharing in KFUPM, the study specifically aims at:
1. Determining the impact of learning culture on the students’ knowledge sharing.
2. Evaluating the role of IT on students’ knowledge sharing.
3. Assessing the level of knowledge sharing and learning culture of the KFUPM students and
4. Assessing whether knowledge sharing and learning culture differ among demographics of KFUPM students.
Literature search revealed that, to date, no research has been conducted on the role of learning culture and use of IT in promoting knowledge sharing in the Kingdom of Saudi Arabia. Thus, the result of this study may be relevant to various stakeholders in the Kingdom. To the government authorities of education in the Kingdom, the understanding of how knowledge is been shared (Brown and Duguid 2000) is important in attaining the government strategic plan of transforming the country to knowledge-based economy. Hence, the findings of the study with respect to the level of the knowledge sharing will be of great significance to this end.
The management of KFUPM may also find the results of the study of immense practical benefits because there is a need, in the first place, to know those factors that impact knowledge sharing among students before embarking on any strategy and program of supporting knowledge management in the university.
From an academic perspective, this study’s insights will add to the existing literature on the impact of learning culture and IT use on knowledge sharing in general; and in Saudi Arabia in particular where none exist. Therefore, the study is of significant value to practitioners and scholars alike.
Organizational success in today’s dynamic and fiercely competitive environment depends largely on the ability to leverage knowledge to develop competitive capabilities to aid in developing new products, services and processes that outperform those of rivals (Kogut and Udo 1992, Nickerson and Zenger 2004, Szulanski 1996). Knowledge is regarded as a fluid mix of framed experiences, values, contextual information, and expert insights that provide a framework for evaluating and incorporating new experiences and information (Davenport 1997). Many other definitions are abound (Davenport 1997). With respect to categorization of knowledge, there is no consensus in this regard. Researchers have identified different types of knowledge (Nonaka and Takeuchi 1995). The most common classification, however, is between explicit and tacit knowledge (Nonaka 1994).
While it is easy to transmit explicit knowledge through formal language, it is much difficult on the other hand to convey tacit knowledge (Nonaka and Takeuchi 1995). This is because explicit knowledge can be made readily available in the form of files, library collections, or databases (Nonaka and Takeuchi 1995).
However, tacit knowledge is difficult to express in words or to codify in documentation. It mainly resides inside individuals’ brains (Hlupic and Rzevski 2002). It is the personal knowledge that is embedded in individual members and used by them in performing their work (Argote and Paul 2000).
It should be noted that knowledge is not an end in itself, but rather means to an end. Thus, only by harnessing and exploiting the collective wisdom and knowledge of their members can organizations adapt and develop innovative processes, products, tactics and strategies (Alavi et al. 2005/2006, Maccoby 2003).
A technique widely championed by organizations in order to achieve this end is knowledge management. Knowledge management demands that knowledge should be obtained, produced, shared, regulated and leveraged by a steady conglomeration of individuals, processes and IT (Benbya and Belbaly 2005).
Knowledge sharing, as a dimension of knowledge management, is in turn defined as the provision or receipt of task information, know-how and feedback regarding a product or procedure (Cummings 2004).
Knowledge sharing can also be seen as a social interaction culture, involving the exchange of employees’ knowledge, experiences, and skills through the whole department or organization. Knowledge sharing comprises a set of shared understandings related to providing employees access to relevant information and building and using knowledge networks within organizations (Hogel et al. 2003). It is the voluntary dissemination of acquired skills and experience to the rest of the organization (Ipe 2003).
At the individual level, knowledge sharing is referred to as the talking to colleagues to help one get something done better, more quickly, or more efficiently (Lin 2007). Sharing of knowledge at the individual level is the most critical to an organization, even though it may exist at other levels of an organization that include team and organizational levels (Lukas et al. 1996). Individuals can realize synergistic results greater than those achievable individually by sharing their knowledge (Cordoba and Isabel 2004).
Moreover, knowledge sharing occurs not only at the individual level, but at the organizational level as well (Lin 2007). For an organization, knowledge sharing is capturing, organizing, and transferring experience-based knowledge that resides within the organization and making that knowledge available to others in the organization (Lin 2007). A firm can successfully achieve promotion of knowledge sharing culture not only by directly incorporating knowledge in its business strategy, but also by changing employee attitudes and behaviors to promote willingness and consistent knowledge sharing (Connelly and Kelloway 2003, Lin and Lee 2004).
There are several antecedences, organizational and otherwise, to knowledge sharing. These factors include the organizational structure, organizational culture, leadership, information systems (Davenport and Prusak 1998, Bock, et al. 2005, Ardichvili et al. 2006), avoidance of embarrassment (Burgess 2005), obligation, trust, and identification (Faraj and Wasko 2002), individual ability (e.g. subject expertise, tenure) (Wasko and Faraj 2005), greed, self-efficacy (Lu et al. 2006), extrinsic rewards, fear of punishment (Burgess 2005), expected rewards, expected associations, expected contribution (Bock and Kim 2002), perceived costs, extrinsic benefits, intrinsic benefits (Kankanhalli et al., 2005), anticipated extrinsic rewards, anticipated reciprocal relationships, sense of self-worth (Bock et al. 2005) among others. The outcome of knowledge sharing that includes productivity, task completion time, organizational learning (Argote 1999, Argote et al. 2000, Cummings 2004), enhancing innovation performance and reducing redundant learning efforts (Scarbrough 2003) have been examined by a number of studies. Conversely, the absence of knowledge sharing is likely to undermine knowledge management efforts (Calantone et al. 2002).
Both private and public organizations are increasingly recognizing the importance of culture as an essential prerequisite for readiness and willingness to learn (Calantone 2002). Simply, culture can be referred to as a system of shared values and assumptions. It influences employee interaction, organizational functioning, and even decision making in organizational settings (Lukas et al. 1996).
Culture is of great importance to the learning organizations including universities (Carleton 1997). It influences or inhibits, directly, the quality of learning (Szulanski 1996), which is of utmost concern in institutions of higher education. According to Johnston and Hawke (2002), learning culture can be defined as the existence of a set of attitudes, values and practices within an organization which support and encourage a continuing process of learning for the organization and/or its members. A learning culture is said to exist in an environment where teamwork, collaboration, creativity, and knowledge processes exist that have a collective meaning and value (Joo 2007). For an organization to improve its performance, it requires a learning culture (Kumar 2005). Hence, development of learning culture is becoming a dominant theme in the strategic plans of many organizations today (Walsham 2002).
Developing a learning culture could help in gathering, organizing, sharing, and analyzing the knowledge of individuals and groups across an institution in ways that directly affect its performance (Kumar 2005). Learning culture benefits a whole organization and certain teams within the organization and it is essential in moving an organization to a learning one (Cohen 1990) which usually support knowledge sharing.
Researches that focused on factors affecting knowledge sharing have identified the relevance of learning culture, among other variables (John 2001). In higher educational institutions, in particular, learning culture is needed for the institutions to create and disseminate knowledge that is necessary for the development of such institutions. Development of such learning culture in learning institutions may also create opportunities in accessing and sharing the right knowledge at the right time and in the right location to stay competitive in the global educational environment (Kumar 2005). Hence, it can be hypothesized that:
H1: The level of learning culture has positive effect on students’ knowledge-sharing behavior. 2.3 Information Technology
The role of the information technology (IT) in sharing knowledge has been a center of debate (Maccoby 2003). While some investigators are of the opinion that knowledge management (KM) initiatives could be successful without using IT tools (Mohamed 2006, Hislop 2002), other researchers have, however, identified IT as a variable that could impact knowledge sharing (Huysman and Wulf 2006) for the fact that technology is one of the important pillars of knowledge management (Maccoby 2003). Haldin-
Herrgard (2000) maintained that a great deal can be done through modern IT to diffuse explicit knowledge. It is also becoming easier nowadays to capture tacit knowledge with the aid of retrieval technologies (Kumar 2005).
A study by Pai (2006) that examined the relationship between the effectiveness of IS strategic planning (ISSP) and knowledge sharing found that top management support for ISSP has a strong significant effect on knowledge sharing behavior. A separate study in South Korea by Kim and Lee (1996) also found, among others, that both employees’ usage of IT applications and friendliness of the IT systems significantly impact employee knowledge-sharing capabilities. It can, therefore, be expected that individuals with more usage and favorable perception of IT may demonstrate more knowledge sharing behavior (Kumar 2005). Hence, it can be hypothesized that:
H2: The level of students’ utilization of IT has a positive effect on students’ knowledge-sharing behavior. Based on the study objectives which were substantiated by the reviewed literature, the hypotheses of the study are eventually developed. These hypotheses are translated into the theoretical model depicted in
In a bid to examine the impact of learning culture and IT use on students’ knowledge sharing in KFUPM, the study undertook a survey questionnaire method. The survey instrument reflected the conceptual framework depicted in 1.
To ensure generalization of the study findings, the questionnaires were administered based on stratified random sampling to KFUPM students. A total of 200 surveys were hand-delivered to the graduates, undergraduates and preparatory students from all the academic departments in the University. A total of 142 questionnaires were returned; of which five incompletes were discarded. The final number of usable questionnaires was 137, representing 68.5% response rate.
All the constructs of the study were measured from items adapted from previous studies, with some alterations to account for the peculiarity and setting of the study. To improve the reliability and validity, multiple-item measures were used for all of the variables. Responses were recorded along a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) for all the items in the questionnaire. Learning culture was measured using 6 items adopted from Cordoba and Isabel (2004). The six items were meant to be grouped into meaningful cluster(s) by conducting factor analysis. Students’ IT usage was measured using 6 items from Kim and Lee (1996) and 1 item specifically designed for this study was added. Finally 6 items were adapted from Kim and Lee (1996) as a measure of students’ knowledgesharing.
The survey questionnaires were distributed to each of the three categories of students, graduates, undergraduates and preparatory students. Preparatory students are those students that are undergoing one year course toward starting their main bachelor degree. Undergraduates are those that are pursuing their four year bachelor degree courses. Both the preparatory and the undergraduate students are from different regions of the country, which makes the sample relatively homogeneous. On the other hand, graduate students are those students pursuing their postgraduate programs that include MBA, MS and PhD. The unique characteristic of the graduate students of the university is that they include students from different countries, not only from Saudi. The cosmopolitan nature of this category of the students may reflect the perception of students across different societies, hence enabling the study findings to be more generalized.
It can be inferred from Table 1, that 30.15% of the respondents were graduate students, 63.97% undergraduates, and the remaining 5.88% preparatory students. With respect to the GPA, it can be seen that only about 15% of the respondents have GPA of more than 3.75 and 16% with GPA of 3.51 – 3.75. On the other hand, over 50% of the respondents’ GPA is between 3.00 – 3.25 and less than 3.00. This seems to be quite representative of the population.
Several major steps were carried out to enhance the reliability and validity of the variables. Factor analysis was first made for this purpose. Reliability was then utilized to check the internal consistency of the scales involved in the study. Coefficient alpha analysis was used to determine the extent to which items making up each measure were homogenous and loaded on the same scale (Allen and Yen 1979). Cronbach’s alpha has been suggested to be the preferable measure of index reliability. The scales used in this study were checked for their internal consistency.
Content Validity which determines the adequacy of the sample characteristics in describing the study measures (Nunnally 1978) has been established in the study. This is because the questionnaire used in this study built upon existing research where the scale items were found to be valid. For the construct validity, one technique widely used to assess such validity of an instrument is factor analysis (Kerlinger 1973). Various items that represent each dimension were analyzed to see if they are properly assigned to the appropriated scale (Carmines and Zeller 1980). Two criteria were used to identity the factor scales. First, all scale items that loaded less than 0.40 were removed. Second, a construct with the highest eigen value would be represented by a factor. For the learning culture, all the items were found to be correlated with the factorial groups produced with the factor loading more than 0.40. Out of the 6 items, two factors emerged as can be seen in Table 2. The correlation result between these factors shows that the two factors are significantly correlated at 99% level of confidence. Thus, one factor was selected that represent the learning culture construct and named learning culture in KFUPM. This factor is the one with the highest eigen value of 2.844 and the percentage variance explained of 47.403 as depicted in Table 2.
From Table 3, it is evident that the Cronbach’s alpha of the construct, learning culture in KFUM is 0.777. Since according to the guideline of Nunnally and Bernstein (1994) the value of 0.7 or above is an acceptable reliability coefficient, hence the construct has exhibited adequate reliability. With respect to the Students’ IT usage, the result of the factor analysis indicates that one item has less than 0.40 factor loading. The item was hence dropped. The remaining five items eventually yielded a single factor with 0.678 Cronbach’s alpha. Though the Cronbach’s alpha not up to 0.70, the factor could still be considered reliable since it very close to .70 (Koch et al. 2005, Graham and Nafukho 2007, Chang and Lin 2007). Some of the items used for measuring IT use are those provided by the university (KFUPM) such as the WebCT, and other systems that are specifically designed by the university authority to promote learning. Other IT items used by students for knowledge sharing and learning include the email tools available in KFUPM Intranet and the Internet. Similar to IT usage, one item of the knowledge sharing has less than 0.40 factor loading value. The item was dropped and the remaining 5 items yielded one factor. The Cronbach’s alpha reliability for these five items was 0.744, which can be considered quite reliable (Nunnally 1978).
Recall that the first and the second objectives of the study are to determine the impact of each of the learning culture and IT use on students’ knowledge sharing respectively. Since the appropriate analysis that assesses the influence of independent variable(s) on dependence variable is regression analysis, two simple regression analyses were run to test the two proposed hypotheses. The choice of the simple regression analysis in assessing the impact of both learning culture and IT use on the dependent variable is that each of the two variables has a single dimension. Moreover, The R2 of both learning culture and IT use models explains knowledge sharing behavior of students in KFUPM. From the results of the regression in Table 4, it can be deduced that the learning culture in KFUPM, which has a positive coefficient Beta, as hypothesized has significant relationship with students’ knowledge sharing. Hence, the first hypothesis is fully supported that learning culture has positive impact on the students’ knowledge sharing in KFUPM.
Similar finding was achieved from the regression analysis result in same Table 4 of the positive influence of IT use on the students’ knowledge sharing in KFUPM. The second hypothesis is equally supported. Furthermore, the R2 of the two regression models, which are 0.487and 0.151, indicate that 48.7% and 15.1% of the overall student knowledge sharing is explained by the learning culture and IT use independent variables respectively.
Furthermore, the result of regression in Table 5 shows which Information Technologies items more used for knowledge sharing. It can be inferred that the coefficient (beta value) of the item "It is easy for me to use the university’s information systems without extra training" is higher showing this IT items contributes more to knowledge sharing and the least item that impact knowledge sharing is "I regularly use the KFUPM’s databases ( e.g., library e-database, etc)".
a. Predictors: Information Technology Items b. Dependent Variable: Knowledge Sharing To answer the research question of the level of knowledge sharing and the learning culture of the students, one-sample t test analysis was undertaken. Since the scales for knowledge sharing and learning culture are all on 5 point Likert scales, the test value of 3 was used and the result in Table 6 shows that all the means are significantly different from neutral value 3. These findings indicate that the students are more inclined toward satisfaction than dissatisfaction with both the knowledge sharing and the learning culture.
The last research objective aims at examining how the learning culture and the knowledge sharing of the students differ according to the demographics. The results of the ANOVA in Table 7 below report such relationships. The results indicate that the level of the knowledge sharing among students is not significantly different with respect to both the students’ GPA and their category because the p > 0.05.
This implies that the students share knowledge irrespective of their GPA or their category. However, with respect to the learning culture in KFUPM, ANOVA results in Table 6 show that the level of learning culture in KFUPM is significantly different among students with different class of GPA, though no significance difference exists between different categories of students.
The findings of the study of the impact of both learning culture and IT use on knowledge sharing among students has important implications to the management of KFUPM as well as other sister institutions. The reason is that because in their effort to enhance knowledge sharing which is inevitable in promoting learning (Graham and Nafukho 2007, Haldin-Herrgard 2000) the management of KFUPM and other higher institutions should opt to at least instill the culture of learning as well as invest more in IT and ensure more usage of IT by their students.
The finding of learning culture as a contributor to knowledge sharing shows that knowledge sharing factors do not depend solely on technology. In fact, the study finding that learning culture accounts by about 48.7% to knowledge sharing against IT use that accounts by only 15.1% is of practical implication and implies that effort toward promoting learning culture may be more viable in promoting sense of knowledge sharing between the students. To achieve this, there is need to organize some orientation courses, seminars among others to instill the etiquette of positive learning culture in the students. It can be envisaged that it may be wise to consider integrating learning culture in the course syllabi design. In the same vein, the finding with respect to the demographics that level of the knowledge sharing of the students is the same irrespective of their GPA and their category implies that, when designing a knowledge sharing program it can be standardized to all students in the university.
Based on the study results and discussion, it could be concluded that the usage of IT and learning culture are significant variables that affect student knowledge sharing in higher institutions, and KFUPM in particular. The presence of learning culture as the major contributor shows that knowledge sharing factors do not depend on technology alone. It is suggested that in a bid to improve student knowledge sharing, the appropriate authorities and decision makers need to commit efforts and programs that could enhance learning culture and IT usage among students. In spite of the originality of this study for being one of the few that examined the influence of social and technological factors together, learning culture and IT use, on student knowledge sharing in the Kingdom of Saudi Arabia, it suffers from some limitations that are common to many other researches.
One of the chief limitations is that the sample size is relatively small and needs to be increased. To account for the sample size limitations of the study, further studies can consider respondents from several universities, possibly including female respondents, to ensure more generality of the findings. In addition to the learning culture, further studies can expand this study to include other factors that may impact students’ knowledge sharing. Also, the impact of IT on collaborative learning is another area where further research could be viable.
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