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Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 574
EXPLAINING THE LEVELS OF KNOWLEDGE PROCESSING IN
KHUZESTAN TELECOMMUNICATIONS DEPARTMENT USING THE
ROUGH SETS THEORY
Masoud PourKiani1,
*Siavash Rezaei
1 and Farhad Gheisari
2
1Department of Management, Kerman Branch, Islamic Azad University, Kerman, Iran
2Department of Management, Baghmalek Branch, Islamic Azad University, Baghmalek, Iran
*Author for Correspondence
ABSTRACT
This study has investigated the processing of knowledge in Khuzestan Telecommunications Department
and examined its relationship with the critical determinant in the organization such as task (task variety,
task analyzability and task interdependency), organization culture (solidarity and autonomy) and
information technology. The study population included 510 employees who are aware of the knowledge
management. Based on Cochran's formula, the sample size was 200 people. To collect the data, a
questionnaire designed by Prof. Seok Woo Sung with the reliability coefficient of 0.93 was used. In this
study, in order to reduce the data and draw conclusions from them, the Rough set theory (RST) was used.
After determining the maximum and minimum points of responders and decision variables, the decision
table is established and then it was standardized. The compatible and incompatible cases were identified
at a later stage. Then the resolution matrix was formed. The results show that if the task analysis is at a
low level, the process of knowledge will be at a low level. When the variable of task diversity, integration
and application of information technology of organization are at an intermediate level, the process of
knowledge of organization will be at an intermediate level. If the task dependency and independency of
organization are at a high level, the process of knowledge of organization will be at a high level.
Keywords: Information Technology, Knowledge Management, Knowledge Processing Styles
INTRODUCTION
In recent years, knowledge is considered as an important strategic resource of companies and
organizations. Their growth, development and continued survival in competitive arena depend on
processing and management of intellectual capital and its application in order to create value in
organization. Today, the use of traditional management methods has been expired. A new perspective has
been emerged on "the knowledge organization” and "knowledge-based economy" in the life of
organizations. The Knowledge organization in which people learn how to learn together and each
individual is a creative human being as well as a knowledge-creator and the knowledge-based economy
(unlike traditional economies in which the capital and labor were important), the intellectual capital or
knowledge capital, which are a set of skills, experiences, talents and capabilities of the employees of an
organization, are the most important part. This knowledge brings about value for organization and causes
the organization growth and development.
In recent years, much attention has been paid to the use of knowledge effective strategies to support
knowledge management processes within the organization. But, little attention has been paid to the
selection and implementation of such strategies in organizational units which play a vital role in
knowledge management processes (acquisition, creation, transfer and application of knowledge). Since
the organizational units are different in terms of the type and nature of tasks, the prevailing culture of
their environment, and their technology, it is natural that they use different ways of knowledge processing
to be match with their construction and activities. Most companies and organizations do not regard the
fact that different work units require their own special style to process the knowledge according to the
nature of their task and employ a style and an overall strategy in all of their business units. This leads to
complications and irreparable harm such as the loss of knowledge as a result of intellectual capital
withdrawal, loss of organizational learning, decision-making speed reduction, low speed of responding
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 575
the needs, environmental changes and reduced productivity and profitability of the organization. Despite
the large investments of companies and organizations such as Alborz Insurance Company to manage the
knowledge effectively and maintain the intellectual capital in organizations, the lack of a proper style of
knowledge processing in working units leads to the loss of these precious investments.
The purpose of this study is to help organizations especially the Khuzestan Telecommunication
Department to have a correct knowledge processing by determination of the appropriate level for each of
the factors influencing it.
Research Literature
Knowledge Processing Styles
A strategic knowledge shows the organization's overall approach to coordinate resources and knowledge
talents in accordance to its strategic thinking needs. With this method, the gap between what companies
need to know about strategies implementation and what they really know and act upon can be reduce.
Zack (1999) suggests that the organizations and businesses have recognized that, to consolidate their
presence in the competitive, they should clearly manage their knowledge capital and talent and select the
knowledge management tools for its implementation. Such organizations should have a broad and global
view and a tendency towards joint management of knowledge. Knowledge processing styles of working
units are different depending on the type of knowledge (implicit, explicit), a unit of knowledge
management (such as different parts of creation, transmission, storage and use of knowledge) deals with
it. The unit that deals with explicit knowledge prefers changing its style from the unit coding process
which deals with tacit knowledge toward personalization style and using its own employee’s tacit
knowledge to solve the problems (Song, 2008). Hansen et al., (1999) have been classified the
organizational general approaches toward knowledge management practices into two strategies;
codification and personalization.
Codification Style
The codification strategy emphasizes the use of written knowledge by individual registration approach. In
this method, the knowledge has been obtained from its owners and it has been recorded and stored in the
database to be reused. Companies which care about the codification strategy, invest heavily in
information technology. In this style, people retrieve and used the encoded Knowledge which has been
recorded in databases, electronic cabinets, manuscripts and manuals, without any contacts with the
knowledge owners. Therefore, the codification style creates an intellectual capital by transforming the
individual knowledge into the structured capital. By providing tools for effective storage and retrieval of
the knowledge, the codification style promotes the knowledge recording and reusing and provides an easy
access to knowledge at all organization borders (Gamlgard and Reiter, 2005; Scholes and Job, 2001, Song
and Tang, 2006). The codification style largely facilitates the searching and retrieval of the knowledge.
By effective implementation of "routine and repetitive operations" in a written form (such as manuals,
databases, repositories, etc.), the organizational units can benefit from the advantages of knowledge
codification. The purpose of codification is to transform the organizational knowledge in such a way that
to be accessible for those who need it. In the simplest sense, the knowledge must be encoded to be
organized, explicit, portable and easy to understand as much as possible.
Personalization Style
Personalization process style simulates the learning and knowledge creation through the collective
interaction with experts and colleagues. This style strongly depends on individuals’ ability and their
willingness for interaction and sharing their knowledge. Personalization includes various learning process
such as face to face communication, informal conversations and accumulated collective experiences
(Principe and Tel, 2001; Sung and Tang, 2006; Zola and Winter, 2002). This approach is appropriate
when a unit is constantly dealing with knowledge that cannot be coded (Hansen et al., 1999). Each unit
commonly relies on the extensive interactions between members to share and exchange the knowledge
(Song, 2008). This strategy does not focus on registered knowledge of database, but focuses on dialogue
between individuals. Knowledge can be exchanged in brainstorming session and interactions of
individuals. In this approach, the knowledge transferring happens not only through face-to-face
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 576
interactions but also through the electronic communication such as networks of individuals. The company
that follows this style or strategy attempts to communicate and transfer knowledge by an individual to
others. The purpose of these companies is to take advantage of this knowledge to be remained in the
minds of employees.
Companies that use this strategy invest less in the field of information technology compared to firms that
create a database. The purpose of Information Technology is to facilitate the conversation and exchanging
the Knowledge. Thus, the knowledge does not become the structural capital, but it enjoys the
unconditional freedom in the organization. The companies, which benefit from this style of processing,
concentrate on individuals’ direct conversation and try to build a social network for individuals to
communicate with each other in a normal manner. Knowledge which is not coded or cannot be coded can
be transmitted by other methods such as negotiations or personal networks. This style also makes it easier
to transfer the tacit knowledge since the statement of this kind of knowledge is difficult in the handbook
and databases but can be transmitted over the personal relationships easier. Furthermore, this style is
coordinated with the ideals propounded by people like Chris Argyris and Peter Senge on organizational
learning and inclusive organizations. These two people emphasize the importance of giving employees
more freedom and responsibility. To improve learning, Senge emphasizes the focus on decentralization
and free communications which were limited due to the organization. Personalization strategy supports
these kinds of learning in which the individual negotiations and communications have enough space for
new diverse ideas (Fisher, 2001). A proper understanding of the knowledge processing concept and styles
can occur through bilateral cooperation and interaction.
The Organizational Factors affecting the Knowledge Processing
Task
Task is a specified work activity to achieve the target. To overcome the uncertainty and provide the
information processing needs, the organizational units may implement formal and informal procedures.
Some internal units of the organization may choose different styles. This depends on the type of
knowledge (implicit or explicit) these units need in doing their tasks. The units’ tasks can be evaluated in
the following three aspects: “task variety”, “task analyzability” and “task interdependency” (Daft and
Lengel, 1986, Daft and Macintosh, 1981; Peru, 1967).
1. Task Variety
The task variety is related to the number and frequency of exceptions, unexpected and non-predictable
events that take place over time on a task (Daft and Macintosh, 1981). In a work unit with a high level of
work diversity, it is expected that the individuals devote much of their time to learn and exchange the
knowledge, as they do for searching and learning the knowledge, to be able to deal with unexpected
events (Daft and Lengel, 1986, Daft and Macintosh, 1986).
2. Task Analyzability
The task analyzability is related to the extent to which a task can be broken into smaller components
(Ahuja and Karli, 1999). The analyzable tasks have a lot of rules and procedures especially in the fixed
environment where the tasks are considerably routine and repetitive and individuals can organize their
activities and tasks efficiently.
3. Task Interdependency
The task interdependency is related to the extent to which individuals require other people information
and support to do their work. With the increased need to assist colleagues in carrying out tasks, the task
interdependency increases. The task interdependency may differ between members of a single
organization or between different units. In any case, the task interdependency is closely associated with
the transmission of information (Song, 2008). A unit with a high degree of task interdependency indicates
that its members can do their tasks perfectly by sharing the knowledge and resource with their colleagues.
Organization Culture
The organization culture is a set of beliefs, values and assumptions common to the members of an
organization which shape the way of thinking, decisions and actions. The organization culture is an
important factor in the success of knowledge management, because it does not only specify the valued
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 577
knowledge, but also it determines the kind of knowledge which should be kept in order to maintain the
competitive advantage. The cultural variables in this study consist of "solidarity" and "autonomy" which
play a critical role in the success of knowledge management functions.
1. Solidarity
In this study, the solidarity is related to the ability of a unit to “follow the common goals without
considering the social relations”. Solidarity among members of similar organizations which follow the
common goals is based on shared experiences. A powerful form of mass culture and knowledge sharing
can increase the probability of the knowledge management functions success in working units by
encouraging the members to participation, interrelation and collaboration (Ahuja, 2000; Alavi et al.,
2006; Lee and Choi, 2003). Solidarity among members of a unit or between different units creates a
strong feeling of confidence and facilitates the knowledge exchange through an extensive interaction such
as formal and informal communication.
2. Autonomy
The autonomy is related to the freedom of an individual or group of individuals in planning their tasks
and establishing the rules and procedures for implementing them. Previous studies indicate that the
autonomy has a strong relationship with the success of knowledge management functions. High level of
autonomy facilitates the development of decentralized networks. It also encourages open communication
between colleagues. The workers with knowledge autonomy often try to propose new ideas and utilize
new skills to develop their competencies. They tend to express their thoughts, experiences and beliefs
(Song, 2008).
Information Technology
The information technology plays a key role in facilitating knowledge flow in organizations. By
improving the knowledge codification and reducing the communication costs, IT can improve
organizational efficiency and effectiveness. Employees can use IT in order to have easy access to prior
knowledge, finding and absorbing new knowledge and easy receiving the expertise in specific areas. In
the firms that rely heavily on knowledge registration and reuse, information technology can facilitate the
acquisition, storage, retrieval, sharing and exchange of knowledge resources (Hansen et al., 1999).
The Research Model
This study has investigated the processing of knowledge in Khuzestan Telecommunications Department
and examined its relationship with the critical determinant in the organization such as task (task variety,
task analyzability and task interdependency), organization culture (solidarity and autonomy) and
information technology.
Figure 1: The research model (Song, 2008(
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 578
Figure 2: Basic model of research considering the decision table
Research Question
How do the organizational factors determine the level of knowledge processing in Khuzestan
Telecommunications Department?
MATERIALS AND METHODS This research is an applied research in terms of the purpose and it is descriptive in terms of the method of
data collection. In this study, two types of variables; decision and conditional, have been considered. The
conditional variables include task variety, task analyzability and task interdependency, solidarity and
autonomy and information technology. The decision variable is the level of knowledge processing. The
Rough Sets Theory was founded in the early 1980s by Professor Zdzislaw Pawlak. This theory deals with
the analysis of the data table. The main objective of Rough set analysis is to obtain the approximate
concepts of acquired data. This method is a powerful tool for mathematical reasoning in cases of
uncertainty. It provides some methods for eliminating or mitigating irrelevant and surplus information and
knowledge of databases. This process eliminates redundant data without loss of essential data of the
database. As a result of data reduction, a set of summarized and meaningful rules can be obtained which
make the decision much easier for decision maker (Ziarko, 1993). To run Rough Sets, the information is
usually displayed in the form of a flat sheet. The columns present the features, the rows present the
objects and the cells contain features values for each object. These types of tables are called information
systems or decision tables. So, in each decision table, the features can be divided into two categories:
1. Decision features (D)
2. Conditional or positional features (C)
Accordingly, the decision tables can be revealed as DC=TU, =S , where Result =D ,
an,…ai,,…a2,a1, =C and xn,…x3,x2,x1, = U (World Series) (Jarvinen, 2004).
In each row of the decision table, the decision rules can be achieved in the form of if ...... then....... . In
this way, for example if: a1=1,a2=1,a3=2,a4=1,a5=2,a6=1 then d=1.
Accordingly, two types of rules are applicable in a decision table:
1. Incompatible rules (conflicting rules): These are the rules with the same positional features but
different decision features.
2. Compatible rules (similar rules): These are the rules which are not incompatible.
Based on these two rules, the position and decision equivalence classes can be written. After the
formation of resolution matrix, the reduced set can be inferred.
The study population included 510 employees, of Khuzestan Telecommunications Department, who are
aware of the knowledge management. Based on Cochran's formula, the sample size was 200 people. To
collect the data, a questionnaire designed by Prof. Seok Woo Sung with the reliability coefficient of 0.93
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 579
was used. The questionnaire consists of 8 general questions and 21 specialized questions. Each question
was encoded based on the 5-point Likert scale.
Table 1: Cronbach's alpha test for each of variables
Row Variable Cronbach's alpha values
1 Task variety 0.7008
2 Task analyzability 0.7342
3 Task interdependency 0.8391
4 Solidarity 0.7118
5 Autonomy 0.7237
6 information technology supports 0.9573
Data Analysis
In this study, to extract the logical rules to check the level of knowledge processing of Khuzestan
Telecommunications Department employees, the Rough set theory (RST) was used. Since 21 items
measure the factors affecting the knowledge processing and valuation is based on the 5-point Likert scale,
the minimum score for a respondent is 21 and the maximum one is 105.
On this basis:
If the respondent score is between 21 and 49, the knowledge processing is at a low level. It means:
21 ≤ X ≤48
If the respondent score is between 50 and 78, the knowledge processing is at an intermediate level. It
means: 49 ≤ X ≤76
If the respondent score is between 79 and 105, the knowledge processing is at a high level. It means:
77 ≤ X ≤105
On the other hand, these six aspects influencing the knowledge processing, regarding the number of
questions of each component, have the minimum and maximum scores as the following table:
Table 2: The score of organizational factors influencing the knowledge processing of decision table
Row
Components of
decision table
Organizational factors and
aspects
Number of
items
The
minimum
score
The
maximum
score
1 a1 Task variety 3 3 15
2 a2 Task analyzability 3 3 15
3 a3 Task interdependency 3 3 15
4 a4 Solidarity 3 3 15
5 a5 Autonomy 4 4 20
6 a6 information technology 5 5 25
According to Table (3), the range of each organizational factor affecting knowledge processing can be
stated as follows:
V (a1) = {3, 4, 5, …, 14, 15}
V (a2) = {3, 4, 5, … , 14, 15}
V (a3) = {3, 4, 5,… , 14, 15 }
V (a4) = {3, 4, 5, …, 14, 15}
V (a5) = {4, 5, 6, …, 19, 20}
V (a6) = {5, 6, 7, …, 24, 25}
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 580
In other words, the component of task variety can have a score between 3 and 15, the component of task
analyzability can have a score between 3 and 15, the component of task interdependency can have a score
between 3 and 15, the component of solidarity can have a score between 3 and 15, the component of
autonomy can have a score between 4 and 20 and the component of information technology can have a
score between 5 and 25.
In the next step, in the columns a1, a2, a3, a4, a5 and a6 (position features) in column d (decision
features), the listed numbers are replaced by the items codes. In other words, they are standardized. Thus,
in Table (3), the codes number 1, 2, and 3 indicate the low level, the intermediate level and the high
respectively for each variable, respectively.
Table 3: Standardization of organizational factors influencing the knowledge processing
Feature Name of organizational factor
and knowledge processing
The value of
each dimension
Maximum and
minimum
Standards
Code
X≤6≥3 1
a1 Task variety X≤15≥3 X≤10≥7 2
X≤15≥11 3
X≤6≥3 1
a2 Task analyzability X≤15≥3 X≤10≥7 2
X≤15≥11 3
X≤6≥3 1
a3 Task interdependency X≤15≥3 X≤10≥7 2
X≤15≥11 3
X≤6≥3 1
a4 Solidarity X≤15≥3 X≤10≥7 2
X≤15≥11 3
a5 Autonomy X≤20≥4
X≤9≥4 1
X≤15≥10 2
X≤20≥16 3
a6 information technology X≤25≥5
X≤11≥5 1
X≤17≥12 2
X≤25≥18 3
X≤49≥21 1
d knowledge processing X≤105≥21 X≤78≥50 2
X≤105≥79 3
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 581
At this stage, the decision table is rewritten and standardized according to the table (3).
Table 4: Standardized decision table N
Frequency
d =
knowledge
processing
a6 =
information
technology
a5 =
Autonomy
a4=
Solidarity
a3= Task
interdependency
a2= Task
analyzability
a1=
Task
variety
u
6 1 1 1 1 1 1 1 u1
12 2 2 2 2 2 2 2 u2
5 1 2 1 2 1 2 1 u3
6 1 1 1 1 1 1 1 u4
9 1 2 1 2 1 1 1 u5
12 2 1 2 1 2 2 1 u6
6 1 2 2 2 2 1 1 u7
12 3 1 1 1 1 1 2 u8
10 2 2 1 2 1 2 2 u9
12 1 2 1 2 1 1 2 u10
9 3 3 3 3 3 3 3 u11
11 2 1 1 1 1 2 1 u12
9 2 2 2 2 2 1 2 u13
11 3 3 3 3 3 2 3 u14
7 1 1 1 1 1 1 2 u15
12 1 1 2 1 2 2 1 u16
8 1 1 2 1 2 1 1 u17
12 3 2 3 2 3 2 3 u18
3 1 2 1 2 1 2 2 u19
10 2 2 1 2 1 2 2 u20
12 2 2 1 2 1 2 1 u21
6 3 3 3 3 3 3 2 u22
In the next step, the compatible and incompatible tables are created according to Table 4
Table 5: Incompatible components (similar components) in the decision table
u a1= Task
variety
a2= Task
analyzability
a3= Task
interdependency
a4=
Solidarity
a5=
Autonomy
a6= information
technology
d= knowledge
processing
u3 1 2 1 2 1 2 1
u21 1 2 1 2 1 2 2
u6 1 2 2 1 2 1 2
u16 1 2 2 1 2 1 1
u9 2 2 1 2 1 2 2
u19 2 2 1 2 1 2 1
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 582
Table 6: Compatible components in the decision table
u a1= Task
variety
a2= Task
analyzability
a3= Task
interdependency
a4=
Solidarity
a5=
Autonomy
a6=
information
technology
d= knowledge
processing
u1 1 1 1 1 1 1 1
u2 2 2 2 2 2 2 2
u4 1 1 1 1 1 1 1
u5 1 1 1 2 1 2 1
u7 1 1 2 2 2 2 1
u8 2 1 1 3 1 3 1
u10 2 1 1 2 1 2 1
u11 3 3 3 3 3 3 3
u12 2 2 2 2 2 2 2
u13 2 1 2 2 2 2 2
u14 3 3 3 2 3 2 3
u15 2 1 1 1 1 1 1
u17 1 1 2 1 2 1 1
u18 3 2 3 2 3 2 3
u20 2 2 1 2 1 2 2
u22 2 3 3 3 3 3 3
Table 7: The arranged compatible table
u a1 a2 a3 a4 a5 a6 d
u1 1 1 1 1 1 1 1
u4 1 1 1 1 1 1 1
u5 1 1 1 2 1 2 1
u7 1 1 2 2 2 2 1
u8 2 1 1 3 1 3 1
u10 2 1 1 2 1 2 1
u15 2 1 1 1 1 1 1
u17 1 1 2 1 2 1 1
u2 2 2 2 2 2 2 2
u12 2 2 2 2 2 2 2
u13 2 1 2 2 2 2 2
u20 2 2 1 2 1 2 2
u11 3 3 3 3 3 3 3
u14 3 3 3 2 3 2 3
u18 3 2 3 2 3 2 3
u22 2 3 3 3 3 3 3
Minimal Set of Features
Since the decision variable (d) has three statuses (low, medium and high), therefore, according to Table
(7), respondents who have the score of 1, 2 and 3 are placed in three different groups. These three groups
are called the equivalence classes of decision or the conceptual sets:
17,15,10,8,7,5,4,111 uuuuuuuudUxX
20,13,12,222 uuuudUxX
22,18,14,1133 uuuudUxX
Based on three sets of X1, X2, X3, the lower and upper approximations are calculated for each of the
three sets. It should be noted that A is defined as the following set:
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 583
654321 ,,,,, aaaaaaA
Table 8: Approximation of three sets of X1, X2, and X3
11 XxUxXAA
17,15,10,8,7,5,11 uuuuuuuXA
22 XxUxXAA
20,13,22 uuuXA
33 XxUxXAA
22,18,16,113 uuuuXA
11 XxUxXA A
17,15,10,8,7,5,4,11 uuuuuuuuXA 22 XxUxXA A
20,13,12,22 uuuuXA
33 XxUxXA A
22,18,16,113 uuuuXA
The precision of Rough set can be determined with the following statement:
X1set X2set X3set
4,141 uuuu AA 12,2122 uuuu AA 1111 uu A
55 uu A AA uu 1313 1616 uu A
77 uu A 2020 uu A 1818 uu A
88 uu A 2222 uu A
1010 uu A
1515 uu A
1717 uu A
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 584
Table: ???????
u
u1
u4
u5
u7
u8
u1
0
u1
5
u1
7
u2
u1
2
u1
3
u2
0
u1
1
u1
4
u1
8
u2
2
u1
λ
a4,a
6
a3,a
4,a
5,a
6
a3,a
4,a
5,a
6
a1,a
4,a
6
a1
a4,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
3,a
4,a
5,a
6
a1,a
2,a
4,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
u4
λ
a4,a
6
a3,a
4,a
5,a
6
a1,a
4,a
6
a1,a
4,a
6
a1
a3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
3,a
4,a
5,a
6
a1,a
2,a
4,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
u5
a4,a
6
a4,a
6
a3,a
4,a
5,a
6
a1,a
4,a
6
a1
a1,a
4,a
6
a3,a
4,a
5,a
6
a3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
3,a
5
a1,a
2
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
u7
a3,a
4,a
5,a
6
a3,a
4,a
5,a
6
a3,a
5
a1,a
3,a
4,a
5,a
6
a1,a
3,a
5
a1,a
3,a
4,a
5,a
6
a4,a
6
a1,a
2
a1,
a2
a1
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
u8
a1,a
4,a
6
a1,a
4,a
6
a2
a1,a
4,a
6
a4,a
6
a4,a
6
a1,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a2,a
4,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a2,a
3,a
5
u10
a1,a
4,a
6
a1,a
4,a
6
a1
a1,a
3,a
5
a4,a
6
a4,a
6
a1,a
2,a
3,a
5
a2,a
3,a
5
a2,a
3,a
5
a3,a
5
a2
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a2,a
3,a
4,a
5,a
6
u15
a1
a1
a1,a
4,a
6
a1,a
3,a
4,a
5,a
6
a4,a
6
a4,a
6
a1,a
3,a
5
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a3,a
4,a
5,a
6
a2,a
4.a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
u1
7
a3,a
5
a3,a
5
a3,a
4,a
5,a
6
a4,a
6
a1,a
3,a
4,a
5,a
6
a1,a
3,a
4,a
5,a
6
a1,a
3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
4,a
6
a1,a
4,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
لودج
10
: کیکفت سیرتام
یریذپ
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 585
u2
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2
a2,a
3,a
4,a
5,a
6
a2,a
3,a
5
a2,a
3,a
4,a
5,a
6
a1,a
2,a
4,a
6
λ
a2
a3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
3,a
5
a2,a
3,a
4,a
5,a
6
u1
2
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2
a2,a
3,a
4,a
5,a
6
a2,a
3,a
5
a2,a
3,a
4,a
5,a
6
a1,a
2,a
4,a
6
a1
a2
a3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
3,a
5
a2,a
3,a
4,a
5,a
6
u1
3
a1,a
3,a
4,a
5,a
6
a1,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a1,a
3,a
5
a3,a
4,a
5,a
6
a3,a
5
a3,a
4,a
5,a
6
a1,a
4,a
6
a2
a2
a2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a2,a
3,a
4,a
5,a
6
u2
0
a1,a
2,a
4,a
6
a1,a
2,a
4,a
6
a1,a
2
a1,a
2,a
4,a
6
a2
a2
a2,a
4,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1
a3
a2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
3,a
5
a2,a
3,a
4,a
5,a
6
u1
1
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a4,a
6
a2,a
4,a
6
a1
u14
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,2
,a3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a4,a
6
a2
a1,a
4,a
6
u18
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
5
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
3,a
5
a1,a
3,a
5
a1,a
2,a
3,a
5
a1,a
3,a
5
a2,a
4,a
6
a2
a1,a
2,a
4,a
6
u2
2
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a2,a
3,a
5
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a1,a
2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a2,a
3,a
4,a
5,a
6
a1
a1,a
4,a
6
a1,a
2,a
4,a
6
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 586
Table 10: Table of features frequency compared to decision feature
N2 N1 d A :Conditional features
u a6 a5 a4 a3 a2 a1
- - 12 1 1 1 1 1 1 1 u1
- - 12 2 2 2 2 2 2 2 u2
- - 6 1 2 2 2 2 1 1 u3
- - 9 1 2 1 2 1 1 1 u4
- - 8 1 1 2 1 2 1 1 u5
7 2 5 1,2 2 1 2 1 2 1 u6
- - 12 1,2 1 2 1 2 2 1 u7
- - 11 2 1 1 1 1 2 1 u8
- - 12 1 2 1 2 1 1 2 u9
- - 9 2 2 2 2 2 1 2 u10
17 2 3 1,2 2 1 2 1 2 2 u11
5 3 7 1,3 1 1 1 1 1 2 u12
- - 6 3 3 3 3 3 3 2 u13
- - 12 3 2 3 2 3 2 3 u14
- - 11 3 3 3 3 3 2 3 u15
- - 9 3 3 3 3 3 3 3 u16
Where:
yaxaAaAIND yx,
yINDxUyydxd &
Now suppose: V is a non-empty set.
Definition 1: function (1) is a Sugeno measure function if the following conditions are true:
1) 01 vg 12 vg
2) VVV 21 , 2121 vgvgVV
3) If a sequence of ascending or a descending sequence is a subset of V, then:
3)
iiii vgvg limlim
Obviously, if a finite ascending or descending sequence is a subset of V, then (3) is as follows:
For ascending sequence:
3’)
i
n
ii
n
i
vgvg11
For descending sequences:
3’’)
i
n
ii
n
i
vgvg11
Definition 2: The belief function (Bel): a Sugeno function which is true in the conditions (4) is a belief
function:
4) For every finite sequence of subsets of V, the following equation is satisfied:
k
kji
kji
k
i
i
k
i
i vvBelvvBelVBelVBel ...1... 1
1
1
11
Definition 3: The exponential function (Pl): a Sugeno function which is true in the conditions (4’) is a
power-like function.
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 587
k
kji
kji
k
i
i
k
i
i vvPlvvPlVPlvPl ...1... 1
1
1
11
The Sugeno measure function is defined as follows on 3,2,12 SubvSubv :
1,2,3 2,3 1,3 1,2 3 2 1 iV
0 0 173
7
173
20
173
43
173
56
173
47 0 ivm
Obviously, the exponential and belief functions can be easily calculated by this function especially for
incompatible rules.
Definition 5: The basic probability assignment function (BPAF):
The function of 1,0: VSubm is a basic probability assignment function if it is true in the following
conditions:
1) 10: xmvx
2)
1 xm
vx
Note that:
ymxBel
xy
ymxPl
xy
As can be seen, using data/ decision table No. 5, the agreement and conditional probability tables can be
obtained as follows:
Table 11: The agreement table of decision and feature values
sum 3 2 1 d
a4 sum 3 2 1
d
a1
74 12 23 39 1 87 0 35 52 1
100 12 53 35 2 81 18 41 22 2
26 26 0 0 3 32 32 0 0 3
200 50 76 74 sum 200 50 76 74 sum
sum 3 2 1 d
a5 sum 3 2 1
d
a2
103 12 43 48 1 75 12 9 54 1
59 0 33 26 2 110 23 67 20 2
38 38 0 0 3 15 15 0 0 3
200 50 76 74 sum 200 50 76 74 sum
sum 3 2 1 d
a6 sum 3 2 1
d
a3
74 12 23 39 1 103 12 43 48 1
100 12 53 35 2 59 0 33 26 2
26 26 0 0 3 38 38 0 0 3
200 50 76 74 sum 200 50 76 74 sum
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 588
Using the agreement table of decision and feature values, the probability distributions of features
(assuming independency of the features) and late conditional probability for each value of the decision
variable (d) (the condition of having known amounts of Features) can be calculated:
In terms of late conditional probability, there is jdd and rj 1 when dd vCardvr :
kk vavava ...2211
It is formulated in a general form as follows:
kkr
ikkrir
kkirvavavap
ddvavavapddpvavavaddp
...
......
2211
2211
2211
jvjarpk
j
iddjvjarpk
j
k
j
k
j
ir ddp
1
1
1
1
In terms of research question, using the agreement tables, probability distributions of features and the
conditional probability of these features can be calculated if there is a number of specific decisions:
Table 12: Probability distributions of features and the conditional probability of these features if d
is known
a1,a2,…,a6 1 2 3 Sum
1apr 0.435 0.405 0.16
1
2apr 0.35 0.55 0.75
3apr 0.515 0.295 0.19
4apr 0.37 0.50 0.13
5apr 0.55 0.295 0.19
6apr 0.37 0.50 0.13
11 dapr 0.703 0.297 0
12 dapr 0.73 0.27 0
13 dapr 0.649 0.351 0
14 dapr 0.527 0.473 0
15 dapr 0.649 0.351 0
16 dapr 0.527 0.473 0
21 dapr 0.461 0.539 0
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 589
22 dapr 0.118 0.882 0
23 dapr 0.566 0.434 0
24 dapr 0.303 0.697 0
25 dapr 0.566 0.434 0
26 dapr 0.303 0.697 0
31 dapr 0 0.36 0.64
32 dapr 0.24 0.46 0.30
33 dapr 0.24 0 0.76
34 dapr 0.24 0.24 0.52
35 dapr 0.24 0 0.76
36 dapr 0.24 0.24 0.52
dpr 0.37 0.38 0.25 1
In Table (12), dj icon is used to display the item (d = j) for j = 1, 2, 3.
For example; jdapdap irjjr , i=1,2,3,4,5,6, shows the conditional distribution of ai if the
decision variable d is equal to j. In addition,
3,2,1 ii a
For example, for the following decision rule:
2222212 654321 daaaaaa
Late conditional probability of event:
222212
2222222221222
654321
654321
apapapapapap
dapdapdapdapdapdapdp
rrrrrr
rrrrrrr
71712.0380030839484.0
510022115633.0
50.0295.035.0405.0
697.0434.0697.0434.0118.0539.038.0
RESULTS AND DISCUSSION
1. Given the set of 1XA , it can be concluded that the speakers of this set are sure that the knowledge
processing and the organizational factors influencing the knowledge processing of their organization are
at a low level. Given the set of 1XA , it can be stated that some of the speakers of this set expressed that the
knowledge processing may be at a low levels in their organization and the organizational factors
influencing the knowledge processing of their organization is at a low or intermediate level.
2222122 654321 aaaaaadpr
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 590
2. Given the set of 2XA , it can be stated that the speakers of this set are sure that the knowledge
processing and the organizational factors influencing the knowledge processing of their organization are
at an intermediate level. On the other hand, given the set of 2XA , it can be stated that some of the
speakers of this set expressed that the knowledge processing may be at an intermediate levels in their
organization and the organizational factors influencing the knowledge processing of their organization is
at an intermediate level.
3. Given the set of 3XA , it can be concluded that the speakers of this set are sure that the knowledge
processing and the organizational factors influencing the knowledge processing of their organization are
at a high level. Given the set of 3XA , it can be stated that some of the speakers of this set expressed that
the knowledge processing may be at a high levels in their organization and the organizational factors
influencing the knowledge processing of their organization is at a high level.
4. According to the rules if-then we can conclude that:
Table 13: Decision Rule
IF a1=1,a2=1,a3=1,a4=1,a5=1,a6=1 THEN Result=1
IF a1=1,a2=1,a3=1,a4=1,a5=1,a6=1 THEN Result=1
IF a1=1,a2=1,a3=1,a4=2,a5=1,a6=2 THEN Result=1
IF a1=1,a2=1,a3=2,a4=2,a5=2,a6=2 THEN Result=1
IF a1=2,a2=1,a3=1,a4=3,a5=1,a6=3 THEN Result=1
IF a1=2,a2=1,a3=1,a4=2,a5=1,a6=2 THEN Result=1
IF a1=2,a2=1,a3=1,a4=1,a5=1,a6=1 THEN Result=1
IF a1=1,a2=1,a3=2,a4=1,a5=2,a6=1 THEN Result=1
IF a1=2,a2=2,a3=2,a4=2,a5=2,a6=2 THEN Result=2
IF a1=2,a2=2,a3=2,a4=2,a5=2,a6=2 THEN Result=2
IF a1=2,a2=1,a3=2,a4=2,a5=2,a6=2 THEN Result=2
IF a1=2,a2=2,a3=1,a4=2,a5=1,a6=2 THEN Result=2
IF a1=3,a2=3,a3=3,a4=3,a5=3,a6=3 THEN Result=3
IF a1=3,a2=3,a3=3,a4=2,a5=3,a6=2 THEN Result=3
IF a1=3,a2=2,a3=3,a4=2,a5=3,a6=2 THEN Result=3
IF a1=2,a2=3,a3=3,a4=3,a5=3,a6=3 THEN Result=3
5. According to data reduction as well as reduction table, we can have a description of d = 1 constraint by
a2 = 1 which is called the value reducer.
IF a2=1 THEN Result=1
So, if the organizational factors affecting the knowledge processing are at a low level, then the knowledge
processing will be at a low level. Using the same argument, the above sixteen rules can be summarized as
follows:
IF a1=2, a4=2, a6=2 THEN Result=2
IF a3=3, a5=3 THEN Result=3
ACKNWLEDGEMENT
We are grateful to Islamic Azad University, Kerman branch authorities, for their useful collaboration.
Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online)
An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2014/04/jls.htm
2014 Vol. 4 (S4), pp. 574-591/Kiani et al.
Research Article
© Copyright 2014 | Centre for Info Bio Technology (CIBTech) 591
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