Simultaneous interpretive structural modelling and weighting (SISMW)

• Authors: NASROLLAHI Mahdi , RAMEZANI Javaneh , SADRAEI Mahmoud , FATHI Mohammad Reza
• Languages of publication: EN

Abstracts

EN

Multi-criteria decision-making (MCDM) methods have been implemented in many fields. In the meantime, several methods have been proposed to obtain the weight of the criteria determined by various methods in different ways. In this paper, a new approach, called simultaneous interpretive structural modelling and weighting (SISMW), is proposed to solve a multi-criterion decision-making (MCDM) problem. Using SISMW, the weight of the criteria and the relationship between them could be determined simultaneously. In this approach, like the ISM method, pair comparison between criteria was made by the decision-maker to determine the relationships among the different criteria. With the help of this data, the weight of the criteria, as well as the causal (cause and effect) relationships between them, were determined in 12 steps. The main advantage of this method is that only one stage of data collection is required for obtaining weights and modelling, and so the research process may be faster. This may increase the reliability of the collected data because, in a one-step survey, the impact of time is minimized. This process can be useful for conceptualizing and developing theories to help decisionmakers understand the problem better.

Keywords

EN

SISMW; MCDM; criteria; modelling; weighting

• Publisher: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
• Journal: Operations Research and Decisions
• Year: 2022
• Volume: 32
• Issue: 1
• Pages: 111-126

Contributors

author

NASROLLAHI Mahdi

• Faculty of Social Sciences, Imam Khomeini International University (IKIU), Qazvin 34149-16818, Iran

author

RAMEZANI Javaneh

• Faculty of Sciences and Technology, Campus da Caparica, NOVA University of Lisbon

author

SADRAEI Mahmoud

• OPTUS, Macquarie Park, NSW, Sydney, Australia

author

FATHI Mohammad Reza

• Department of Management and Accounting, College of Farabi, University of Tehran, P.O. Box 3718117469, Qom, Iran

References

• AGHAEE A., AGHAEE M., FATHI M.R., SHOA’BIN S., SOBHANI S.M., A novel fuzzy hybrid multi-criteria decision-making approach for evaluating maintenance strategies in petrochemical industry, J. Qual. Maint. Eng., 2021, 27 (2), 351–365.
• CHEN P.T., CHEN J.H., Implementing cloud-based medical systems in hospitals and strategic implications, Technol. Anal. Strat. Manage., 2015, 27 (2), 198–218.
• DIAKOULAKI D., MAVROTAS G., PAPAYANNAKIS L., Determining objective weights in multiple criteria problems: The critic method, Comp. Oper. Res., 1995, 22 (7), 763–770.
• GIRUBHA J., VINODH S., KEK V., Application of interpretative structural modelling integrated multi criteria decision making methods for sustainable supplier selection, J. Model. Manage., 2016, 11 (2), 358–388.
• GUIAŞU S., Weighted entropy, Rep. Math. Phys., 1971, 2 (3), 165–179.
• JAIN V., AJMERA P., Modelling the factors affecting Indian medical tourism sector using interpretive structural modelling, Bench. Int. J., 2018, 25 (5), 1461–1479.
• JAIN V., SONI V.K., Modelling and analysis of FMS performance variables by fuzzy TISM, J. Model. Manage., 2019, 14 (1), 2–30.
• MOUSAVIZADE F., SHAKIBAZAD M., Identifying and ranking CSFs for KM implementation in urban water and sewage companies using ISM-DEMATEL technique, J. Knowl. Manage., 2019, 23 (1), 200–218.
• NASROLLAHI M., FATHI M.R., SOBHANI S.M., KHOSRAVI A., NOORBAKHSH A., Modelling resilient supplier selection criteria in desalination supply chain based on fuzzy DEMATEL and ISM, Int. J. Manage. Sci. Eng. Manage., 2021, 16 (4), 264–278.
• NASROLLAHI M., RAMEZANI J., A model to evaluate the organizational readiness for big data adoption, Int. J. Comput. Comm. Cont., 2020, 15 (3), 3874.
• NASROLLAHI M., RAMEZANI J., SADRAEI M., A FBWM-PROMETHEE approach for industrial robot selection, Heliyon, 2020, 6 (5), e03859.
• NASROLLAHI M., SADRAEI M., Modelling evaluation criteria for resilient IT project supplier selection, Int. Conf. Data Sci. Mach. Lear. Stat., 2019 (DMS-2019), Turkey.
• PANDEY P., AGRAWAL N., SAHARAN T., RAUT R.D., Impact of human resource management practices on TQM: An ISM-DEMATEL approach, The TQM J., 2021, 34 (1), 199–228.
• PRIYA S.S., PRIYA M.S., JAIN V., DIXIT S.K., An assessment of government measures in combatting COVID-19 using ISM and DEMATEL modelling, Bench. Int. J., 2021, DOI: 10.1108/BIJ-05-2021-0244.
• RAMEZANI J., SADRAEI M., NASROLLAHI M., Identification and ranking of effective criteria in evaluating resilient IT project contractors, 2019 Int. Young Eng. Forum (YEF-ECE), IEEE, 2019, 205–212.
• SAATY T.L., What is the analytic hierarchy process? Mathematical models for decision support, Springer, Berlin 1988, 109–121.
• SAATY T.L., Decision making – the analytic hierarchy and network processes (AHP/ANP, J. Syst. Sci. Syst. Eng., 2004, 13 (1), 1–35.
• SONI V., SINGH S.P.AND BANWET D.K., Precise decisions in Indian energy sector by imprecise evaluation, Int. J. En. Sect. Manage., 2016, 10 (1), 118–142.
• SUSHIL S., Interpreting the interpretive structural model, Glob. J. Flex. Syst. Manage., 2012, 13 (2), 87–106.
• SUSHIL S., How to check correctness of total interpretive structural models?, Ann. Oper. Res., 2018, 270 (1–2), 473–487.
• TALANKAR A., VERMA P., SETH N., Modelling the clusters of critical success factors of six sigma for non-formal service sectors using interpretive structural modelling, Int. J. Six Sigma Comp. Adv., 2015, 9 (2–4), 222–240.
• TALIB F., RAHMAN Z., QURESHI M.N., Analysis of interaction among the barriers to total quality management implementation using interpretive structural modelling approach, Benchm. Int. J., 2011, 18 (4), 563–587.
• VISHNU C.R., SRIDHARAN R., RAM KUMAR P.N., REGI KUMAR V., Analysis of the operational risk factors in public hospitals in an Indian state: A hybrid DEMATEL–ISM–PROMETHEE approach, Int. J. Health Care Qual. Assur., 2020, 33 (1), 67–88.
• WALLER R.J., Contextual relations and mathematical relations in interpretive structural modelling, IEEE Trans. Syst., Man Cyber., 1980, 10 (3), 143–145.
• WARFIED J.N., The mathematics of structure, AJAR Publishing Company, 2003.
• WARFIELD J.N., CARDENAS A.R., A Handbook of Interactive Management, Iowa State University Press, Ames 1994, 338.
• WARFILED J.N., Interpretive Structural Modelling (ISM) Group Planning & Problem Solving Methods in Engineering, Wiley, New York 1982.
• ZHOU F., LIM M.K., HE Y., LIN Y., CHEN S., End-of-life vehicle (ELV) recycling management: Improving performance using an ISM approach, J. Clean. Prod., 2019, 228, 231–243.

Identifiers

DOI

10.37190/ord220106