Interpretive structural modeling

1. 1
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

2. 2
Interpretive Structural Modeling
Interpretive Structural Modeling is used for
identifying and summarizing relationship
among specific variables, which define a
problem or an issues.
It is an interactive learning process.

3. 3
Objective of ISM
•To identify and rank the variables.
•To establish the interrelationship among the
variables.
•To discuss the managerial implication of the
research.

4. 4
Steps of ISM Methodology
1. Variables affecting the system under consideration
are listed.
2. The Structural Self Interaction Matrix (SSIM) is
developed for the variables.
3. Reachability Matrix is developed from the SSIM.
4. Reachability Matrix obtained in step 3 is partitioned
into different level.
5. Finally the hierarchies of the variables are formed.

5. 5
Example of Interpretive Structural
Modeling

6. 6
Variables affecting Information and
Communication Technology adoption in SME.
Sl.
No.
Variables Supporting Studies
1Relative Advantage Lee and Runge (2001). Khazanchi
(2005); Seyal and Rahman (2003).
2Social Expectation Lee and Runge (2001). Khazanchi
(2005); Seyal and Rahman (2003).
3Firm’s InnovativenessLee and Runge (2001); Winston and
Dologite (1999); Khazanchi (2005);
Seyal and Rahman (2003).
4Management AttributesSeyal and Rahman, (2003); Jeon
et.al.(2006); Chahal and Kohali
(2006).

7. 7
Variables affecting Information and
Communication Technology adoption in SME.
Sl.
No.
Variables Supporting Studies
5Organisational AttributesSeyal and Rahman (2003);
Levenburg and Klein (2006).
6Adoption Attributes Seyal and Rahman (2003); Jeon
et.al. (2006),
7End User experience Winston and Dologite(1999).
8Owner knowledge Winston and Dologite (1999);
Ihlstrom and Nilsson (2003);
Seyal and Rahman (2003);
Wymer and Regan (2005).

8. 8
Variables affecting Information and
Communication Technology adoption in SME.
Sl.
No.
Variables Supporting Studies
9Extra organizational
situation
Winston and Dologite(1999);
Khazanchi (2005).
10Government Support Jeon et.al. (2006); Wymer and
Regan (2005); Jeon et.al. (2006);
Wymer and Regan (2005).
11Financial ResourceLevenburg and Klein (2006);
Khazanchi (2005)

9. 9
Relative Advantage
Firm’s Innovativeness
Management Attributes
Organisational Attributes
Adoption Attributes
End User experience
Owner’s knowledge
Extra organizational situation
Government Support
Financial Resource
Social Expectation
Usage of Information
and Communication
Technology

10. 10
Interpretive Structural Modeling
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.

11. 11
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.

12. 12
Elements
111098765432
1 Relative Advantage AAADDBAAAA
2 Social Expectation AAAADAAAD
3 Firm’s Innovativeness DDDDDDAD
4 Management Attributes ABDADAA
5Organizational Attributes ADAADA
6 Adoption Attributes BDDAD
7 End User experience BAAA
8 Owner knowledge ADD
9 Extra Org. situationBD
10 Government Support D
11 Financial Resource
Structural Self-Interaction Matrix (SSIM)

13. 13
Reachability Matrix
•A, If ‘i’ is predictor of ‘j’, then (i,j) is 1 and (j,i)
is 0
•B, If ‘j’ is predictor of ‘i’ then (j,i) is 1 and (i,j)
is 0
•C, If ‘i’ and ‘j’ predict each other then (i,j) is 1
and (j,i) is 1
•D, If no predict each other then (i,j) is 0 and
(j,i) is 0

14. 14
Elements
1234567891011
1 Relative Advantage 11111000111
2 Social Expectation 01011101111
3 Firm’s Innovativeness 00101000000
4 Management Attributes 00011101001
5Organizational Attributes 00001101101
6 Adoption Attributes 10000101000
7 End User experience 00000011110
8 Owner knowledge 00000001001
9 Extra Org. situation00000000100
10 Government Support 00010100010
11 Financial Resource 00000010101
Reachability Matrix

15. 15
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

16. 16
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 2,4,5,6,7,8
9 1,2,5,7,9,11
10 1,2,7,10
11 1,2,4,5,8,11
Antecend Set

17. 17
Level of Variables
Level of variables are determined on the
basis of intersection of Reachability Set
and Intersection Set

18. 18
Variable Reachability
Set
Antecend
Set
Intersection Set Level
1 1,2,3,4,5,9,10,11 1,6 1 VII
2 2,4,5,6,8,9,10,11 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 III
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 V
11 7,9,11 1,2,4,5,8,11 11 II
Level of Variables

19. 19
Variable Hierarchy
Extra Organizational
Situation (9)
Firm’s Innovativeness (3)Owner knowledge (8)Financial Resource (11)
Organizational Attributes (5)Adoption Attributes (6)End User experience (7)
Management Attributes (4)
Government Support (10)
Social Expectation (2)
Relative Advantage (1)