Determinants o KMS Success in Omani Organisations - Assignment Example

Running Head: determinants of KMS success in Omani organizations Name Course Lecturer Date Question 1 Whether the Factors Will Differ From Those Which Influence AKM Success The determinants of knowledge management system success are knowledge culture, organisational infrastructure, technical infrastructure, management support, vision clarity, reward policy and economic return. These factors are very essential ion the success of KMS. These factors will not differ from those which influence the knowledge management success. Knowledge management is an integrated and formalized approach to identifying and managing organization’s knowledge assets. Successful implementation of knowledge management has a huge impact on the success of KMS. The impacts of implementation in terms of performance improvement and the related benefits are very significant to an organisation. Knowledge management is very important to an organisation’s current performance and its future performance. As such, it is important for organisations to view their businesses as knowledge intensive. The factors that influence KMS success in Omani organisations does not differ from those which influence KM success. Management support and commitment is critical to KM success, it is very important. Organisational and technical infrastructures are also critical in the success of KM. Management support and commitment plays a critical role in ensuring success in knowledge management just like in any other initiative in an organisation. Its impact on knowledge management is even more pronounced as it is relatively essential to the future of the organisation, it determines the competitiveness of the organisation in the near and long term future (Han & Park, 2009). The leadership in an organisation should model the behaviour and characteristics they want to instill and promote among the employees and the initiative. The management support is also responsible for ensuring that the whole KM success initiative have the necessary infrastructure and resources needed. Without the input, commitment and support of the management, KM cannot be successful. This is because there would not the resources needed for its implementation and growth (Cabrera & Cabrera, 2005). As such, management support and commitment in any organisation is very important in the success of KM. Knowledge culture is equally important in KM success just as it is important in KMS success in Omani organizations. In knowledge management success, there must be creation of shared background, expectations, non-bureaucratic rules and social customs that compel behaviours. These underlying beliefs, while exactly articulated, hugely influence the perception of actions and communication among the employees. This culture is highly influential in KM success. For KM too be success, there must be creation of time, and the employees must work effectively. The KM initiative created must save time for employees and not burden them with a lot of work (Watson & Hewett, 2006). This helps employees to be effective on their work. The reward policy is also critical in KM success. To encourage and motivate the employees, an organisation must maintain a balance between explicit and intrinsic rewards. A good balance between these rewards encourages employee behaviour. Encouraging employees to share KM knowledge would increase their knowledge management understanding, this is essential in KM success. Reward policy helps and motivates personnel to find value in KM and hence increase their commitment and desire to grow it. In addition, reward policy sustains the participation of personnel. They develop sense of respect when they see their expertise in application. As such, reward policy is essential in KM success in any given organisation (Kulkarni et al., 2007). Similarly, organisational and technical infrastructure is essential in KM success just like in KMS success in Omani organizations. KM cannot be successful without a solid organisation and technical infrastructure. The KM personnel cannot be able to share information on the required scale. Notably, focusing too much on information technology may hinder KM success. KM is not a software application, having a platform to share information as well as to communicate is part of KM success. As such, an organisation should not focus too much on information technology but the whole initiative consisting of developing, communication, sharing and using knowledge (Juang et al., 2008). Likewise, vision clarity determines the success of knowledge management in any organisation in Oman or any other country. A KM without vision and clear objective will lead to any destination; this is not measurable and hence not possible to define KM success. A successful KM must have clear vision and objectives. A clear vision must articulate the user’s needs; it pays particular attention to user’s needs. Creating a clear vision involves having processes in place to acquire, validate, manage as well as deliver relevant information when needed and where it is needed. Aligning KM system with its objectives is essential in having a clear vision (Benbya, 2008). Essentially, vision clarity is essential in KM success. It helps an organisation or the KM personnel to have purpose. This provides measure and sense of direction, this determines KM success. Moreover, vision clarity helps an organisation to work towards achieving the set objectives. Therefore, any Km result will not be considered a success unless it meets the objectives and goals set in the beginning. Consequently, vision clarity is essential in KM success like in KMS success (Benbya, 2008). Question 2 How Would The Effect On The Study Results Be If Another Approach To Selecting Sample Was Employed Or The Sample Size Was Increased Or Reduced? If another approach to selecting the sample was employed it would have changed the effects. First, usi1ng another approach to select sample would have given different results. However, the results would not have different much with the used approach. This is because each approach has its own unique limitations when selecting samples. These limitations, unique to each approach, would be manifest in the samples selected (Maier & Hädrich, 2011). Nevertheless, the results would not differ much. Increasing the sample size would be positive to the results. This is because the more the samples the more reliable the results. As such, increasing the sample size would increase reliability. In this case, increasing the sample size would make the results more reliable. Considering that there are several organizations in Oman using and adopting KMS (Rinkus et al., 2005). As such, increasing the number of organizations, both nonprofit and profit oriented organisations would have increased the reliability of KMS success. In addition, it would justify and make information obtained to be more appropriate, this is because it would considerably reduce margin of error and sample size. Increasing the sample size is also important as it makes it easier to boost statistical power of the tests and hence obtain more accurate results. As such, it is important to increase the number of organisations being studied. It would not only increase precision of measuring data obtained from the organizations but it would also influence statistical power. Consequently, the power can then be improved by reducing the measuring error in the data obtained. This directly increases reliability of KMS success measure being assessed (Paik & Choi, 2005). On the other hand, reducing the sample size would reduce reliability of the results. Reduced sample size does not challenge the null hypothesis and hence would leave a lot of important information. Additionally, reducing the sample size increases sampling error in the results. This also makes it harder to detect the inherent error in reduced sample size. Conversely, when the numbers of organisations are reduced in this study, the probability of rejecting the wright hypothesis decreases and instead increase the chances of rejecting the null hypothesis (Han & Park, 2009). The tests power of rejecting the null hypothesis is considerably reduced and thus increases the probability of incorrectly rejecting the null hypothesis when it is false (does not determine the KMS success). Still, the significant level for the determinants reduces significantly. Bearing in mind that he determinants power is highly influenced by the choice of significance level, the amount of data available and the size of the effect being measured, it considerably reduces the influence on the tests power. For example when the number of organisations is reduced, the tests may fail to reject the null hypothesis if true difference exists between two organizations being compared. The sample becomes too small to differentiate the effects (Maier & Hädrich, 2011). Question 3 How Omani Managers, Researchers and Students Benefit From the Study Results The study results will give managers a very good tool of measuring return on investment. Return on investment is a very appealing yardstick of value due to its compelling simplicity and self-evident meaning. The results would help managers on how to stimulate the productivity of employees by making them to be more effective in their work rather than working hard (Kulkarni et al., 2007). Managers are bombarded with constant stream of data every day. This overload of data makes this study results increasingly more important. The key reasons why these results are important to managers are facilitating decision making capabilities, building learning organizations by way of making learning a routine and stimulating culture change and innovation. These results offer managers a wealth of information. However, processing overwhelming amounts can gate in the managers way of achieving high quality decisions. These results help managers to make decisions about their organizations, the productivity of the business as well as increasing effectiveness. Importantly, the results will help managers to know how best to run a successful knowledge management system. They will know how to maintain it as well as how best to keep improving it for getting high returns from the system (Paik & Choi, 2005). The results will help managers to actively manage organizations by stimulating change of culture and innovation by way of encouraging free flow of ideas. One critical process of successful KMS is sharing of information. KMS cannot be successful without sharing information; managers help personnel in an organisation to freely exchange and share ideas. These ideas and information helps personnel to develop management skills, business minded leadership as well as focused workshops. As such, the results would help managers to embrace change as well as encourage insight and ideas, these often leads to innovation even for small organizations (Cabrera & Cabrera, 2005). These results are particularly important to students, the results gives students a learning experience as well as very important insights on how to runs a successful knowledge management system. The results will not only give students a new thinking dimension but also a new encounter of enhancing effectiveness. The results unleash new ideas and creativity in students (Juang et al., 2008). They increase their knowledge and understanding about knowledge management systems. This is especially important because the results are from a practical research study. As such, it offers practical determinants to KMS success. In addition, the results will facilitate students, especially those in Omani, to have evolution of more intelligent enterprises as well as develop smart engaging mechanisms. This prepares them very well to undertake employment after their studies. For researchers, the results will help them to speed innovation and decision making. The researchers will be able to create more responsive, adaptive, flexible and dynamic systems. The results will help results to create virtual networked enterprises. It will give them an opportunity to improve management and processing of data for better decision making in organizations (Watson & Hewett, 2006). References Benbya, H. (2008). Knowledge management systems implementation: Lessons from the Silicon Valley. Hind Benbya, Knowledge Management Systems Implementation: Lessons From The Silicon Valley, Neal-Schuman Publishers. Cabrera, E, F, & Cabrera, A, (2005). Fostering knowledge sharing through people management practices: The International Journal of Human Resource Management, 16(5), 720-735 Han, K. H., & Park, J, W, (2009). Process-centered knowledge model and enterprise ontology for the development of knowledge management system: Expert Systems with Applications, 36(4), 7441-7447. Juang, Y. S., Lin, S. S., & Kao, H, P, (2008). A knowledge management system for series-parallel availability optimization and design: Expert Systems with Applications, 34(1), 181-193. Kulkarni, U. R., Ravindran, S., & Freeze, R. (2007). A knowledge management success model: theoretical development and empirical validation: Journal of management information systems, 23(3), 309-347. Maier, R., & Hädrich, T, (2011). Knowledge Management Systems. Paik, Y., & Choi, D, Y, (2005). The shortcomings of a standardized global knowledge management system: the case study of Accenture. The Academy of Management Executive, 19(2), 81-84. Rinkus, S., Walji, M., Johnson-Throop, K. A., Malin, J. T., Turley, J. P., Smith, J. W., & Zhang, J. (2005). Human-centered design of a distributed knowledge management system. Journal of Biomedical Informatics, 38(1), 4-17. Watson, S, & Hewett, K, (2006). A Multi‐Theoretical Model of Knowledge Transfer in Organizations: Determinants of Knowledge Contribution and Knowledge Reuse*. Journal of management studies, 43(2), 141-173. Read More