FDP-ISM_new

8/8/2019 FDP-ISM_new

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Interpretive Structural Modeling

Dr. G. P. Sahu

(Assistant Professor Information Systems)

School of Management Studies

Motilal Nehru National Institute of Technology, Allahabad.

July 25, 2008


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Interpretive Structural Modeling is used for

identifying and summarizing relationship

among specific variables, which define aproblem or an issues.

It is an interactive learning process.


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Objective of ISM

To identify and rank the variables.

To establish the interrelationship among the

variables.

To discuss the managerial implication of the

research.


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Example of Interpretive Structural

Modeling


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Variables affecting Information and

Communication Technology adoption in SME.

Sl.No.

Variables Supporting Studies

1 Relative Advantage Lee and Runge (2001). Khazanchi

(2005); Seyal and Rahman (2003).

2 Social Expectation Lee and Runge (2001). Khazanchi(2005); Seyal and Rahman (2003).

3 Firms Innovativeness Lee and Runge (2001); Winston and

Dologite (1999); Khazanchi (2005);

Seyal and Rahman (2003).

4 Management Attributes Seyal and Rahman, (2003); Jeon

et.al.(2006); Chahal and Kohali

(2006).


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Sl.No.


5 Organisational Attributes Seyal and Rahman (2003);

Levenburg and Klein (2006).

6 Adoption Attributes Seyal and Rahman (2003); Jeonet.al. (2006),

7 End User experience Winston and Dologite(1999).

8 Owner knowledge Winston and Dologite (1999);

Ihlstrom and Nilsson (2003);

Seyal and Rahman (2003);

Wymer and Regan (2005).


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Sl.No.


9 Extra organizational

situation

Winston and Dologite(1999);

Khazanchi (2005).

10 Government Support Jeon et.al. (2006); Wymer andRegan (2005); Jeon et.al. (2006);

Wymer and Regan (2005).

11 Financial Resource Levenburg and Klein (2006);

Khazanchi (2005)


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Relative Advantage

Firms Innovativeness

Management Attributes

Organisational Attributes

Adoption Attributes

End User experience

Owners knowledge

Extra organizational situation

Government Support

Financial Resource

Social Expectation

Usage of Information

and Communication

Technology


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Personal interview is conducted of the two experts, one is

academician and the other entrepreneurship consultant. It is

asked them to establish the relationship between the various

factors as follows: A, If i is predictor of j.

B, If j is predictor of i.

C, If i and j predict each other.

D, If no predict each other.


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Structural Self Interaction Matrix

(SSIM)

ISM methodology suggest the use of expert

opinions based on the various management

technique in developing the contextual

relationship among the variables.


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Elements 11 10 9 8 7 6 5 4 3 2

1 Relative Advantage A A A D D B A A A A

2 Social Expectation A A A A D A A A D

3 Firms Innovativeness D D D D D D A D

4 Management Attributes AB

D A D A A5 Organizational Attributes A D A A D A

6 Adoption Attributes B D D A D

7 End User experience B A A A

8 Owner knowledge A D D

9 Extra Org. situation B D

10 Government Support D

11 Financial Resource

Structural Self-Interaction Matrix (SSIM)


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Elements 1 2 3 4 5 6 7 8 9 10 11

1 Relative Advantage 1 1 1 1 1 0 0 0 1 1 1

2 Social Expectation 0 1 0 1 1 1 0 1 1 1 1

3 Firms Innovativeness 0 0 1 0 1 0 0 0 0 0 0

4 Management Attributes 0 0 0 1 1 1 0 1 0 0 1

5 Organizational Attributes 0 0 0 0 1 1 0 1 1 0 1

6 Adoption Attributes 1 0 0 0 0 1 0 1 0 0 0

7 End User experience 0 0 0 0 0 0 1 1 1 1 0

8 Owner knowledge 0 0 0 0 0 0 0 1 0 0 1

9 Extra Org. situation 0 0 0 0 0 0 0 0 1 0 0

10 Government Support 0 0 0 1 0 1 0 0 0 1 0

11 Financial Resource 0 0 0 0 0 0 1 0 1 0 1

Reachability Matrix


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Variable Reachability Set

1 1,2,3,4,5,9,10,11

2 2,4,5,6,8,9,10,11

3 3,5

4 4,5,6,8,11

5 5,6,8,9,11

6 1,6,8,

7 7,8,9,10

8 8,11

9 9

10 4,6,10

11 7,9,11

Reachability Set


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Variable Antecend Set

1 1,6

2 1,2

3 1,3

4 1,2,4,10

5 1,2,3,4,5

6 2,4,5,6,10

7 7,11

8 2,4,5,6,7,89 1,2,5,7,9,11

10 1,2,7,10

11 1,2,4,5,8,11

Antecend Set


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Level ofVariables

Level of variables are determined on the

basis of intersection of Reachability Set

and Intersection Set


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Variable ReachabilitySet

Antecend

Set

Intersect

ion Set

Level

1 1,2,3,4,5,9,10,1

1

1,6 1

2 2,4,5,6,8,9,10,1

1

1,2 2

3 3,5 1,3 3

4 4,5,6,8,11 1,2,4,10 4

5 5,6,8,9,11 1,2,3,4,5 5

6 1,6,8, 2,4,5,6,10 6

7 7,8,9,10 7,11 78 8,11 2,4,5,6,7,8 8

9 9 1,2,5,7,9,11 9 I

10 4,6,10 1,2,7,10 10

117,

9,11

1,2,4,5,8,

11

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Level ofVariables


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Antecend

Set

Intersect

ion Set

Level

1 1,2,3,4,5,10,11 1,6 1

2 2,4,5,6,8,10,11 1,2 2

3 3,5 1,3 3 II

4 4,5,6,8,11 1,2,4,10 4

5 5,6,8,11 1,2,3,4,5 5

6 1,6,8, 2,4,5,6,10 6

7 7,8,10 7,11 7

8 8,11 2,4,5,6,7,8 8 II

9 9 1,2,5,7,9,11 9 I

10 4,6,10 1,2,7,10 10

11 7,11 1,2,4,5,8,11 11 II

Level ofVariables


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Antecend

Set

Intersect

ion Set

Level

1 1,2,3,4,5,9,10,1

1

1,6 1 VII

2 2,4,5,6,8,9,10,1

1

1,2 2 VI

3 3,5 1,3 3 II

4 4,5,6,8,11 1,2,4,10 4 IV

5 5,6,8,9,11 1,2,3,4,5 5 III

6 1,6,8, 2,4,5,6,10 6 III

7 7,8,9,10 7,11 7 III8 8,11 2,4,5,6,7,8 8 II

9 9 1,2,5,7,9,11 9 I

10 4,6,10 1,2,7,10 10 V

11

7,9

,11

1

,2,4,5,8,11

11

II

Level ofVariables


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Sample paper


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FDP-ISM_new