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Integrating Fuzzy Kano and Fuzzy TOPSIS for Classification of Functional Requirements in National Standardization System

  • Research Article - Systems Engineering
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Abstract

Standardization of information is regarded as one of the three main approaches of supply chains and one of the effective strategies in integrating of their components. One of the most effective standardization systems is utilizing product coding at the national level which creates an appropriate framework for the integrated management of information in the chains. The identification and fulfillment of the customers’ needs (CNs) with the functional requirements (FRs) of this system would satisfy the customers. However, considering the limitation of resources, an appropriate ranking and selection of FRs is of vital importance. In this paper, a new procedure is presented by utilizing fuzzy TOPSIS and fuzzy KANO techniques aiming at two issues: (i) identifying and classifying CNs, and (ii) ranking and categorizing the FRs. By giving priority to the FRs that increases the beneficiaries’ satisfaction, investment will be more efficient. In order to validate and verify the credibility of the proposed procedure, a case in the commodity and service standardization system of Iran, known as “Iran Code” was employed. The outcomes include ranking and categorizing the present FRs of the system according to the satisfaction, extent and having the more favorable accuracy compared to the existing methods.

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References

  1. Chopra S., Meindal P.: Suppy Chain Management—Strategy, Planning & Operation. Pearson Prentice Hall, Englewood Cliffs (2009)

    Google Scholar 

  2. Agrawal A., Shankar R., Tiwari M.K.: Modeling the metrics of lean, agile and leagile supply chain: an ANP-based approach. Eur. J. Oper. Res. 173(1), 211–225 (2006)

    Article  Google Scholar 

  3. Christopher M.: Logistics and Supply Chain Management: Strategies for Reducing Cost & Improving Service. 2nd edn. Financial Times Publishing, London (1998)

    Google Scholar 

  4. Gansler, J.S.; Luby, R.E.; Kornberg, B.: Supply chain management in government and business. In: Transfering Government Supply Chain Management. Rowman & Littlefield, Maryland (2004)

  5. Kocoglu I., Imamoglu S.Z., Ince H., Keskin H.: The effect of supply chain integration sharinh: enhancing the supply chain performance. Produc. Soc. Behav. Sci. 24, 1610–1649 (2011)

    Google Scholar 

  6. Swafford P.M., Ghosh S., Murthy N.: Achieving supply chain agility through IT integration and flexibility. Int. J. Produc. Econ. 116, 288–297 (2008)

    Article  Google Scholar 

  7. Azhdari, B.; EkhtiarZadeh, A.: Iran Code from Concept to Operation. Jahad Daneshgahi Sanati, Tehran (2012)

  8. Alimi, H.: Stock Management and Operation Related with Stock Systems. Sazman Modiriate Sanati, Tehran (2008)

  9. Gharehgozli A.H., Tavakkoli-Moghaddam R., Zaerpour N.: A fuzzy-mixed-integer goal programming model for a parallel-machine scheduling problem with sequence-dependent setup times and release dates. Robot. Comput.-Integr. Manuf. 25(4–5), 853–859 (2009)

    Article  Google Scholar 

  10. Büyüközkan G., Feyzioğlu O., Nebol E.: Selection of the strategic alliance partner in logistics value chain. Int. J. Produc. Econ. 113(1), 148–158 (2007)

    Article  Google Scholar 

  11. Krohling R.A., Campanharo V.C.: Fuzzy TOPSIS for group decision making: a case study for accidents with oil spill in the sea. Expert Syst. Appl. 38, 4190–4197 (2011)

    Article  Google Scholar 

  12. Kano N., Seraku N., Takahashi F., Takahashi F.: Attractive quality and must-be quality. Hinshitsu (Qual. J. Japanese Soc. Qual. Control) 14, 39–48 (1984)

    Google Scholar 

  13. Schvaneveldt S.J., Enkawa T., Miyakawa M.: Customer evaluation perspectives of service quality: evaluation factors and two-way model of quality. Total Qual. Manag. 2(2), 149–161 (1991)

    Article  Google Scholar 

  14. Fynes B., De Bu’rca S.: The effects of design quality on quality performance. Int. J. Produc. Econ. 96(1), 1–14 (2005)

    Article  Google Scholar 

  15. Matzler K., Sauerwein E.: The factor structure of customer satisfaction: an empirical test of the importance grid and the penalty-reward-contrast analysis. Int. J. Serv. Ind. Manag. 13(4), 314–332 (2002)

    Article  Google Scholar 

  16. Anderson E.W., Mittal V.: Strengthening the satisfaction-profit chain. J. Serv. Res. 3(2), 107–120 (2000)

    Article  Google Scholar 

  17. Ting S.C., Chen C.N.: The asymmetrical and non-linear effects of store quality attributes on customer satisfaction. Total Qual. Manag. 13(4), 547–569 (2002)

    Article  Google Scholar 

  18. Brandt D.R.: How service marketers can identify value-enhancing service element. J. Serv. Market. 2(3), 35–41 (1988)

    Article  Google Scholar 

  19. Deng W.J.: Using a revised importance–performance analysis approach: the case of Taiwanese hot springs tourism. Tour. Manag. 28(5), 1274–1284 (2007)

    Article  Google Scholar 

  20. Matzler K., Bailom F., Hinterhuber H.H., Renzl B., Pichler J.: The asymmetric relationship between attribute-level performance and overall customer satisfaction: a reconsideration of the importance-performance analysis. Ind. Market. Manag. 33, 271–277 (2004)

    Article  Google Scholar 

  21. Vavra, T.G.: Improving Your Measurement of Customer Satisfaction: A Guide to Creating, Conducting, Analyzing, and Reporting Customer Satisfaction Measurement Program. ASQ Quality Press, Milwaukee (1997)

  22. Matzler K., Hinterhuber H.H.: How to make product development projects more successful by integrating Kano’s model of customer satisfaction into quality function deployment. Technovation 18(1), 25–38 (1998)

    Article  Google Scholar 

  23. Lee Y.C., Huang S.H.: A new fuzzy concept approach for Kano’s model. Expert Syst. Appl. 36, 4479–4484 (2009)

    Article  Google Scholar 

  24. Wu, B.; Sun, C.M.: Fuzzy statistical analysis for human thought with fuzzy data. In: International Workshop on Fuzzy Systems and Innovational Computing, pp. 389–397 (2004)

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Shafia, M.A., Abdollahzadeh, S. Integrating Fuzzy Kano and Fuzzy TOPSIS for Classification of Functional Requirements in National Standardization System. Arab J Sci Eng 39, 6555–6565 (2014). https://doi.org/10.1007/s13369-014-1251-z

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  • DOI: https://doi.org/10.1007/s13369-014-1251-z

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