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The Impact Of Knowledge Management Systems Business Essay

Knowledge Management Systems (KMSs) are becoming indispensable in today's corporations. The vast interest in Knowledge Management concept comes from the role it plays in facilitating organizations' activities. To define KMS, it is necessary first to define knowledge management. Shannak (2010) identifies Knowledge Management as "The process of capturing information and experience of individuals and the organization and distributing it to wherever it can produce benefit. In other words, Knowledge Management is a technique that seeks to improve the performance of individuals and organizations by making use of the present and future value of knowledge assets". In more details, (Kumar and Thondikulam, 2005) describes Knowledge Management as "The process of capturing and making use of a firm’s collective expertise anywhere in the business within the framework of trading partners – on paper, in documents, in databases (called explicit knowledge), or in people’s minds (called tacit knowledge)".

Knowledge Management handles the knowledge within an organization in a process of four steps: first is the knowledge entry into the system called Knowledge Creation, secondly, storing knowledge into the system known as Knowledge Retention, thirdly, the transfer of knowledge between the parts of the system and finally applying knowledge in decision making and different business processes known as Knowledge Utilization (Rolland, 2004).

According to Alavi (2001) Knowledge Management Systems are referred to as "emerging line of systems targets professional and managerial activities by focusing on creating, gathering, organizing, and disseminating organization's knowledge".

In today global competitive world, companies started to realize the importance of knowledge as a way to gain and maintain competitive advantage. Researches have concluded that the only dependable thing for a firm in the future world is knowledge, the way it uses it, how fast it acquires new knowledge and impends it in its business processes.

Considering knowledge management as a business practice in modern commercial banks is a strong indicator of its success. Banks and other competitive financial organizations' recognized that knowledge is power (Cross and Weller, 2001). The Knowledge covers the range from the organization's intellectual capital to daily business transactions data.

Most commercial service banks aim to improve their customer satisfaction and increase their revenue as result. Therefore, Knowledge management has become a necessary skill for them to survive in a critical competitive market in the 21st centaury. Moreover, it becomes essential to assign a person to handle and manage knowledge creation, storage and transfer. This person is also responsible for the creation and implementation of strategy to utilize and benefit from the business knowledge.

The main fields of knowledge management applications in businesses are risk management, marketing management, customer relationship management and performance measurement, Wide banks increased their investments in Knowledge Management systems such as Decision Support Systems, Data Warehouses and Data Mining. (Jayasundara, 2008). However, this study focuses on how the KMS provide the appropriate decision analysis tools to specific decision makers.

Due to the importance of KMS in financial sectors and the vital role it plays in helping knowledge workers making effective and just-in-time decisions, this paper highlights the importance of knowledge management integration in the financial sectors and studies the relationship between the proper use of KMS and the effectiveness of decision making process. This research is divided into several sections as follows:

Section 1: Introduction: provides an overview of the whole research, it starts with a general background of knowledge management and then moves to the use of KMS in financial organizations and the role it plays in enhancing the decision making process.

Section 2: Literature Review: describes existing studies similar to this research and how they contribute in the process of defining, gathering and analyzing the required data.

Section 3: Methodology: describes the research method used to complete this study, followed by the research questions, hypothesis and research design.

Section 4: Study Problem: specifies the current problem and the difficulties that organizations face when trying to make decisions based on the help provided by the KM System.

Section 5: Result and Analysis: in this stage, the data will be collected and entered into the SPSS software for further statistical analysis, and then the final results will be explained in more details with the use of graphs and equations.

Section 6: Discussion and Recommendations: this section discusses the final results, and makes some suggestions to improve the current situation.

2. Literature Review

Knowledge Management is a widely addressed concept by many authors. Marr and his partners (2003) defined Knowledge Management as a business process through which organizations, with their stakeholders, create, acquire, capture, share and use their collective knowledge towards enhancing organizational learning and performance, and sustaining their intellectual capital.

Siemieniuch and Sinclair (2004) clearly identified Knowledge Management as a pillar in the seven bases of organizational effectiveness, Thus KM can lead to many organizational benefits like better problem solving and decision making, improved customer services, increasing profits, better stuff attraction, more innovation and greater creativity (Squier and Snyman , 2004).

Zhenfeng Chen (2010) recognized two main categories of Knowledge: explicit knowledge and tacit knowledge. According to the British philosopher Michael Polanyi, explicit knowledge mainly refers to the structure knowledge expressed by text, images and symbols, which can be taught verbally and learned by textbooks, reference materials, databases, etc. Tacit knowledge only exists in people's minds, which is difficult to express by words, symbols, images media. The management of explicit knowledge is relatively easy; you can use information systems, such as code and database to set knowledge base. The explicit knowledge is achieved through teaching, training. Its sharing depends on electronic information systems. The explicit knowledge is the basis for innovation. But the management of tacit knowledge is relatively more difficult. Tacit knowledge contains many knowledge cheats such as the work of know-how, experience, perspective and values, which implies more innovative ideas. These are the essence of the core competitiveness.

Young and others (2007) considered three perspectives of knowledge management; strategic knowledge management – deals with pinpointing opportunities to find, distribute and transfer knowledge related to long term goals of an organization; tactical knowledge management finds, distributes and transfers knowledge for the medium term organizational goals; operational knowledge management is associated with daily or short term operations.

According to Jungpil & Mani (2001), a lot of effort has been focused on developing software applications to capture knowledge such as data warehousing and document repositories linked to search engines to support the digital capture, storage, retrieval and distribution of an organization’s explicitly documented knowledge. However, the development and implementation of KMS that embrace the whole organization, including knowledge resulting from its relations with other institutions with which it collaborates and which also incorporate the management of tacit knowledge, is a more complex affair that has still not been satisfactorily resolved (Heinrichs, & Lim, 2005).

Kumar and Thondikulam (2005) illustrated that the main objective of a knowledge base is to facilitate standardization and relieve management of routine decision-making tasks, while Sutrisna and others (2003) considered the fundamental objective of any variation management system is to anticipate, recognize, evaluate, resolve, control, document, and learn from past variations in ways that support the overall viability of the project in hand.

Wang and Ahmed (2007) indicated that KM benefits are to build dynamic capabilities and innovative capabilities. As an emphasis, Hung (2009) includes enhancing dynamic capability and influencing overall organization performance.

Liu and Young (2007) discussed key information models and their relationships in manufacturing decision support in three different scenarios. The researchers confirmed that global manufacturing businesses are benefiting from the information and knowledge support provided by modern IT tools such as Product Life Cycle Management (PLM), Enterprise Resource Planning (ERP), and Customer Relations Management (CRM).

Harris (2009) research showed that only a few KM systems provide the necessary decision support throughout product development and in most cases are more geared to specific tasks with stand alone functionality. Also available knowledge management systems do not provide the means to identify, capture, formalize, present and utilize tacit knowledge.

Murray and Myers (2006) indicated that many business organizations expenditure on KM is due to rise to over 6 percent of revenues over the next few years because they are recognizing that they are on the threshold of a knowledge-based economic revolution.

Skyrius (2001) highlighted the decision maker's attitudes towards different factors influencing the quality of business decisions; these factors include information sources, analytical tools, and the role of information technologies.

Handzic (2001) also focused on the impact of information availability on people's ability to process and use information in decision making tasks. He indicated the increased availability of information had an impact on both efficiency and accuracy of business decisions.

Vencatachellum and Jeetah (2008) focused on the state of Knowledge management among the commercial banks in Mauritius, their study indicated that a majority of respondents (70%) claimed they were familiar with the KM term but 60% of them did not give a valid KM definition. Moreover, all the banks had a formal strategy, and consider it important for achieving organizational effectiveness, but only 30% had a formal KM strategy. While Widen-Wulff and Suomi (2003) focused on the insurance sector and studied the knowledge management practices of 15 Finnish insurance companies of different sizes and product portfolios. Their analysis showed that effective knowledge sharing has a positive correlation to business success.

Finally, Shannak (2010), research highlighted the effect of KMS on the strategic decisions, the researcher chose engineering offices sector in Jordan, and the study indicated that the availability of KM technique can be of a great benefit in improving the efficiency of the operating and managerial activities and the success of KMS depends on the decision makers trust in the provided knowledge.

From the above review, it is concluded that Knowledge Management is a wide spread concept and it is addressed by many authors, and it can be defined as the business process through which organizations create, organize and share knowledge. Also, there are two types of knowledge: explicit and tacit. Moreover, many studies showed that organizations have started to realize the impact of knowledge management systems on the efficiency of decision making tasks, but a complete understanding of this relationship has not been fully achieved. It is noticed that several researches of KMS focused on the availability of information and information technologies and their contribution to the quality of the resulted decisions.

3. Methodology

This research investigated the impact of Knowledge Management System on supporting decision makers in commercial banks. Moreover, it uses the empirical method to quantify the knowledge sources that may be used in decision-making process. The descriptive method is also used to gain a better understanding of the problem and describe these sources based on data collection and statistical analysis.

This study also aimed to answer some rising questions regarding the research factors and their relationships as following:

How is the trust that decision makers put in the KMS affect the decision making process?

How is the availability of required information technologies affect the decision making process?

Is their any statistical relationship between coordination between departments of the bank and the effectiveness of the decision making process?

Is their any statistical relationship between each of the independent variables and the decision making process?

Group of factors that affect the use of knowledge Management System in the decision making process were studied. These factors include: availability of required information technologies, coordination between departments, trust of decision makers, suitability of information to the organization business and to the decision maker, and consistency of information. Those factors are obtained from a similar study conducted by Shannak (2010). The relationship between these factors and the decision making process is illustrated in the figure 1; it shows that the previous five independent factors can affect the dependent variable (decision making process) either positively or negatively.

H1

Information Technologies

H3

Suitability of information

Consistency of information

Trust of decision makers

Decision Making Process

Coordination between departments

H2

H4

Dependent Variable

H5

Independent Variables

Figure 1: The relationship between the research factors.

After having the research questions and factors, the research studied several assumptions or hypothesis that can be proved or disproved based on the data collection and experimental results, it considered the following hypothesis:

Hypothesis 1:

H0: There is no significant statistical relationship between the required Information technologies and the decision making process.

H1: The required Information Technologies have a significant statistical relationship with the decision making process.

Hypothesis 2:

H0: There is no significant statistical relationship between the coordination between the departments and the decision making process.

H2: The coordination between the departments has significant statistical relationship with the decision making process.

Hypothesis 3:

H0: There is no significant statistical relationship between the trust of decision makers and the decision making process.

H3: The trust of decision makers has significant statistical relationship with the decision making process.

Hypothesis 4:

H0: There is no significant statistical relationship between the suitability of KMS information and the decision making process.

H4: The suitability of KMS information has significant statistical relationship with the decision making process.

Hypothesis 5:

H0: There is no significant statistical relationship between the consistency of KMS information and the decision making process.

H5: The consistency of KMS information has significant statistical relationship with the decision making process.

Hypothesis 6:

H0: There is no significant statistical relationship between the all of the independent variables and the decision making process.

H6: There is a significant statistical relationship between all of the independent variables and the decision making process.

3.1 Research Design

This study uses the qualitative method to analyze and interpret the collected data. First, data regarding the research factors were collected using a questionnaire. It contains 12 questions, and each question has five options: (5= Strongly Agree, 4= Agree, 3= Neutral, 2= Disagree, 1= Strongly Agree). A non-random sample of 50 decision makers from the target banks (Bank of Bahrain and Kuwait, and Bank Muscat International) were invited, the sample includes Information System Officers, operational managers, financial managers and executive officers. Each participant was asked to answer the questionnaire individually. Secondly, the questionnaire papers will be collected, and the data will be analyzed and entered into the computer using SPSS Software for statistical analysis. Based on the findings, the researcher will determine the effectiveness of the current KMS of the bank, and make some suggestions to improve the Knowledge-handling activities in the decision making process.

4. Study Problem and Importance

There is no doubt about the contribution of Knowledge Management in business success. Banks and Insurance companies in Bahrain recognized that knowledge is one of the most important factors that affect business value. Based on this, one would think that Knowledge Management is something that banks are skilled in because of the service-based nature of their business, but actually few of them take knowledge management seriously, while a greater number of industrial companies do.

Moreover, many of these organizations are not aware of the importance of KMS in enhancing the quality of decision making process, and the company's business value consequently. Thus, this study is intended to help them understand how Knowledge Management Systems help individuals in organizations make effective decisions and how they can leverage business knowledge more effectively.

On the other hand, only a few KM systems provide the necessary decision support throughout product development as mentioned by (Harris, 2009), so this study is focused on helping organizations understand the relationship between investing in the appropriate information technologies and the quality of the resulted business decisions.

5. Result and Analysis

In this section, the research data were collected using questionnaire, and then the answers were entered into the SPSS software, followed by analysis for each question to investigate the relationship between the dependent and independent variables and accept or reject the hypothesis accordingly. The focus in the analysis will be on three independent variables including: The availability of information technologies, coordination between departments and trust of decision makers as following:

The First hypothesis (H1): The required Information Technologies have significant statistical relationship with the decision making process.

Two questions were used to test this hypothesis:

Question 1: The knowledge management system can process the required collections of data and analyze it to produce patterns.

The following table shows the frequencies for this question:

The knowledge management system can process the required collection of data and analyze it to produce patterns

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Neutral

13

26.0

26.0

26.0

Agree

25

50.0

50.0

76.0

Strongly Agree

12

24.0

24.0

100.0

Total

50

100.0

100.0

Table 1: The frequencies of the first question

Table 1 illustrates that out of 50 respondents, half of them (50%) agreed with the above statement, 24% of them strongly agreed with it, and the remaining were neutral.

Question 2: The knowledge management system provides the technologies needed to support managerial and operational activities (hardware, decision support tools, data management system, internet, intranet, groupware, knowledge management software).

The next table depicts the frequencies for this question:

The knowledge management system provides the technologies needed to support managerial and operational activities

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Neutral

11

22.0

22.0

22.0

Agree

27

54.0

54.0

76.0

Strongly Agree

12

24.0

24.0

100.0

Total

50

100.0

100.0

Table 2: The frequencies of the second question

It is noticed from this figure that, more than half of the respondents (54%) agreed with the pervious statement, 24% of them strongly agreed with it, and 22% were neutral.

The next step involves testing the hypothesis based on the result generated from the SPSS regression function. To make this possible, the above two question were combined into one variable (The availability of Information technology) and the results of the regression are as following:

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

2.347

1

2.347

6.924

.011a

Residual

16.273

48

.339

Total

18.620

49

a. Predictors: (Constant), The availability of information technologies

b. Dependent Variable: The efficiency of decision making process

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

2.316

.555

4.171

.000

The availability of information technologies

.361

.137

.355

2.631

.011

a. Dependent Variable: The efficiency of decision making process

Based on the above tables resulted from regression function, it is noticed that the value of Sig = 0.011 (< 0.05) and F = 6.924 (> 1.9) which means that the null hypothesis (H0) is rejected and the alternative hypothesis (H1) is accepted.

The Second hypothesis (H2) is: The coordination between the departments has significant statistical relationship with the decision making process.

This hypothesis can be tested by two questions:

Question 3: The decisions generated by the knowledge management system are based on the information collected from various departments.

The frequencies of this question are shows in the next table:

The decisions generated by the knowledge management system are based on information collected from various departments

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Disagree

5

10.0

10.0

10.0

Neutral

11

22.0

22.0

32.0

Agree

24

48.0

48.0

80.0

Strongly Agree

10

20.0

20.0

100.0

Total

50

100.0

100.0

Table 3: The frequencies of the third question

The above table illustrates 48% of the respondents agreed with the pervious statement, 20% of them strongly agreed with it, 22% were neutral and 10% disagreed with it.

Question 4: The knowledge management system has direct support to your department during decision making process.

The following table contains the frequencies for this question:

The knowledge management system has direct support to your department during decision making process

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Disagree

1

2.0

2.1

2.1

Neutral

9

18.0

19.1

21.3

Agree

30

60.0

63.8

85.1

Strongly Agree

7

14.0

14.9

100.0

Total

47

94.0

100.0

Missing

System

3

6.0

Total

50

100.0

Table 4: The frequencies of the fourth question

Table 4 shows that the majority of the respondents (60%) agreed with the above statement, 14% strongly agreed with it, 18% were neutral and only 2% disagreed with it. Also 3 respondents (6%) left the question with no answer.

To test the second hypothesis, the two questions were combined together, and then regression function was used. The resulted tables are shown below:

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

1.132

1

1.132

3.108

.084a

Residual

17.488

48

.364

Total

18.620

49

a. Predictors: (Constant), Coordination between departments

b. Dependent Variable: The efficiency of decision making process

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

2.853

.521

5.473

.000

Coordination between departments

.235

.133

.247

1.763

.084

a. Dependent Variable: The efficiency of decision making process

The above table shows that the value of the Sig= 0.084 (> 0.05) which means that there is no significant relationship between coordination between departments and decision making process in the target banks. As a result, the alternative hypothesis (H2) is rejected and the null hypothesis (H0) is accepted.

The third hypothesis (H3): The trust of decision makers has significant statistical relationship with the decision making process.

Two questions were asked to test this hypothesis:

Question 5: Do you trust the information provided by the Knowledge management system in making critical decisions?

The next table demonstrates the frequencies for this question:

Do you trust the information provided by knowledge management system in making critical decisions

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Disagree

3

6.0

6.0

6.0

Neutral

16

32.0

32.0

38.0

Agree

25

50.0

50.0

88.0

Strongly Agree

6

12.0

12.0

100.0

Total

50

100.0

100.0

Table 5: The frequencies of the fifth question

The pervious table shows that half of the participants (50%) agreed with the question, 32% were neutral, 12% of them strongly agreed and 6% disagreed.

Question 6: Do you have an advanced knowledge-based system that enhances trusts in decision making process?

The following table shows the frequencies for this question:

Do you have an advanced knowledge-based system that enhances trusts in decision making process

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Disagree

2

4.0

4.4

4.4

Neutral

22

44.0

48.9

53.3

Agree

20

40.0

44.4

97.8

Strongly Agree

1

2.0

2.2

100.0

Total

45

90.0

100.0

Missing

System

5

10.0

Total

50

100.0

Table 6: The frequencies of the sixth question

It is clear from the above table that about half of the respondents (44%) were neutral, similar number (40%) agreed with the question, and few of them (4%) disagreed, (2%) strongly agreed, and 5 respondents (10%) left the question without answer.

The third hypothesis is tested using regression function after the two questions were combined into one variable as following:

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

1.639

1

1.639

4.632

.036a

Residual

16.981

48

.354

Total

18.620

49

a. Predictors: (Constant), Trust of decision makers

b. Dependent Variable: The efficiency of decision making process

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

2.625

.534

4.918

.000

Trust of decision makers

.315

.146

.297

2.152

.036

a. Dependent Variable: The efficiency of decision making process

It is noticed from the above tables that the value of Sig = 0.036 (< 0.05) and the value of F = 4.632 (> 1.9) and that means the alternative hypothesis (H1) is accepted and the null hypothesis (H0) is rejected.

The Sixth hypothesis (H6): There is a significant statistical relationship between all of the independent variables and the decision making process.

This hypothesis is tested using the regression function to determine the impact of all the independent variables on the decision making process and the resulted tables are shown below:

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

4.111

3

1.370

4.345

.009a

Residual

14.509

46

.315

Total

18.620

49

a. Predictors: (Constant), Coordination between departments, Trust of decision makers, The availability of information technologies

b. Dependent Variable: The efficiency of decision making process

The ANOVA table shows that the value of the Sig= 0.009 (> 0.05) and the value of the F= 4.345 (> 1.9), which means that there is a significant relationship between all the independent variables (coordination between departments, Information technologies, trust of decision makers) and decision making process. Thus, the alternative hypothesis (H6) is accepted and the null hypothesis (H0) is rejected.

6. Discussion

- The study showed that the availability of required information technologies is significantly related to the decision making process and it has noticeable benefits in improving the quality of decision activities. This result is compatible with many similar studies; one of them is Shannak (2010) research which indicated that the availability of KM technique can be of a great benefit in improving the efficiency of the operating and managerial activities. Also, Skyrius (2001) highlighted the importance of information sources, analytical tools, and the role of information technologies in the quality of business decisions. Another study that agreed with the above result is Liu and Young (2007) who confirmed that many organizations rely on various IT tools in developing their KM systems to support their decision activities, these tools include Product Life Cycle Management (PLM), Enterprise Resource Planning (ERP), and Customer Relations Management (CRM). Based on this, banks in Bahrain should enlarge their investment in the required information technologies to help their managers make the appropriate decisions which will ultimately increase their business value and profit.

- It was also found that the more than half (62%) of the respondents trust their KMS in making critical decisions, whereas (6%) have no trust in their KMS. On the other hand, about (42%) were aware of advanced KMS and it enhances their trust, but (44%) were neutral and (10%) were unaware of advanced KMS system.

- The final results showed that there is a significant relationship between the trust that decision makers put the knowledge management system and the efficiency of decision tasks. Shannak (2010) reached that same result and he confirmed that acceptance and trust of decision makers in the Knowledge management system and the information obtained from it represent a major aspect in business success.

- The study also indicated that the coordination between departments has no impact on the decision making process which means decision makers did not depend on the system to coordinate with other departments and distribute business decisions to their subordinates. One reason for this might be due to the fact that most of the chosen bank's branches are very small and they contain no more than 15 employees setting in the same department. Also, what might contribute to this result is that (6%) of the participants left the fourth question (related to coordination between departments) without answer and it could be because they did not understand it well.

- The study revealed that all the independent variables, when combined together, have significant impact of on the decision making process.

- The results were also affected by the fact that some respondents were unaware of the knowledge management system. Moreover, some of them were bored and did not care to read the questions very carefully as noticed by the questionnaire distributor and observer.

- Finally, It is noticed that banks in Bahrain have started to understand the benefits of KMS and it is contribution to business success, but still there are some obstacles related to people and system development.

7. Conclusion and Recommendations

Based on the findings of this study, it is concluded that knowledge management system used in commercial banks in Bahrain has a noticeable impact on the efficiency of decision tasks, and business value as a result. The availability of information technologies enhances the quality of decision activities. Also, the trust of decision makers affects the efficiency of decision tasks. Finally, the coordination between departments has no impact on the efficiency of the decision process and this could be because most of the chosen branches are very small and does not contain several departments.

Considering the pervious results and conclusions, the researcher recommends the following:

Commercial banks in Bahrain should increase their investments in developing KM systems and pay attention to KMS planning and development to make sure that it can support the creation, organization and distribution of business knowledge within the bank efficiently.

Banks should educate their managers and knowledge worker about the importance of KMS and how it can increase their performance and business success. This could be achieved by conducting seminars, workshops, and training courses.

Proper testing for the KMS should be performed after installation to ensure issues such as user's acceptance and system speed are managed efficiently.

Adequate training for top managers, executives and employees that are using the KMS to prepare them for the system and capture their technical and trust problems and solve them accordingly.

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