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An extension of interpretive structural modeling using linguistic term sets for business decision-making

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Abstract

This paper presents a new interpretive structural modeling (ISM) technique based on linguistic term sets. In the proposed approach, the linguistic terms will replace binary numbers 0 and 1, representing one attribute's influence on another. The main objective is to introduce the concept of linguistic term sets to the ISM and develop a linguistic interpretive structural modeling (LISM), where the decision-makers (DM) would use linguistic terms such as very high (VH), high (H), low (L), very low (VL) and, no influence (N) to measure the strength of the impact of an attribute on other attributes. Since the linguistic terms are closer to the human cognitive process, it is more convenient and realistic for the decision-makers to use linguistic terms instead of binary numbers to express the pairwise relationship between different attributes. The integration of fuzzy linguistic terms and the ISM would enhance the consistency level and reduce the uncertainty inherent in the decision-maker's choice. The proposed LISM has been demonstrated by identifying the inter-relationships among the key attributes of business analytics methodology (BAM) acceptance in the industry settings.

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The dataset for this work is present within the manuscript.

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Funding

The authors would like to thank the funding agencies for financial aid from grant nos. (F./2015-17/RGNF-2015-17-TAM-83 of UGC, India and SR/FST/ETI-349/2013 DST, India).

Author information

Authors and Affiliations

  1. Department of General Studies, Higher College of Technology, Fujairah, United Arab Emirates

    Sanjay Kumar Tyagi

  2. Indian Institute of Management, Tiruchirapplli, Tamil Nadu, 620024, India

    Sujeet Kumar Sharma

  3. Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India

    R. Krishankumar

  4. Rajiv Gandhi National Institute of Youth Development, Sriperumbudur, Tamil Nadu, India

    K. S. Ravichandran

  5. SASTRA University, Thanjavur, Tamil Nadu, 613401, India

    R. Krishankumar

Authors
  1. Sanjay Kumar Tyagi
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  2. Sujeet Kumar Sharma
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  3. R. Krishankumar
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  4. K. S. Ravichandran
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Contributions

The contributions and responsibilities of the authors were as follows. First Author has contributed in conceptualization, formal analysis, literature analysis, coding, validation, and writing. The second Author has contributed in conceptualization, formal analysis, literature analysis, validation, writing. Third and Fourth Authors have contributed to overall administration and curation, resources acquisition, conceptualization, formal analysis, reviewing, and editing.

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Correspondence to R. Krishankumar.

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Appendix

Appendix

1.1 List of notations

Notations

Meanings

V

Indicates that ith attribute is influencing jth attribute

A

Indicates that ith attribute is influenced by jth attribute

O

Indicates that there is no relationship between the ith and jth attributes

X

Indicates that both the attributes ith attribute and jth attribute are influencing each other

\(S\)

Set of linguistic terms

\(s_{\alpha }\)

A possible linguistic term for a linguistic variable

\(s_{0}\)

The lower limit of possible linguistic terms

\(s_{n}\)

The upper limit of possible linguistic terms

\(d(s_{\alpha } , s_{\beta } )\)

Deviation degree between any two linguistic terms \(s_{\alpha }\) and \(s_{\beta }\)

\(\rho \left( {s_{\alpha } , s_{\beta } } \right)\)

Similarity degree between any two linguistic terms \(s_{\alpha }\) and \(s_{\beta }\)

\(a_{i} \left( {i = 1, 2, \ldots , m} \right)\)

Any non-negative number

\(B^{p,q} \left( {a_{1} , a_{2} , \ldots , a_{n} } \right)\)

Bonferroni mean of non-negative numbers \(a_{1} , a_{2} , \ldots , a_{n}\)

p, q

Non-negative parameters

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Tyagi, S.K., Sharma, S.K., Krishankumar, R. et al. An extension of interpretive structural modeling using linguistic term sets for business decision-making. OPSEARCH 59, 1158–1177 (2022). https://doi.org/10.1007/s12597-021-00565-x

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