Skip to main content
SpringerLink
Log in

A Fuzzy AHP–TOPSIS-Based Group Decision-Making Approach to IT Personnel Selection

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

Global competition and the rapid development of information technologies force organizations to continuously change their ways. Nowadays, organizations need personnel who make a difference through innovative ideas and who keep up with the rapid changes. In this paper, the personnel selection process in a Turkish dairy company’s information technology (IT) department is discussed as a group multi-criteria decision-making problem. The main purpose of the paper is to select the best employee candidate for an IT department by integrating fuzzy analytic hierarchy process (fuzzy AHP) with Chang’s (Eur J Oper Res 95(3):649–655, 1996) extent analysis and fuzzy The Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS). Decision makers’ (DMs) verbal evaluations are included in the process using intuitionistic fuzzy numbers. In fuzzy AHP–TOPSIS calculations, during the group decision-making process, hierarchical level weights, reflecting the importance of DMs’ verbal evaluations, are utilized. First, with fuzzy AHP, the importance weights of thirty sub-criteria are determined, and then, with fuzzy TOPSIS five IT personnel alternatives are ranked utilizing the weights obtained with fuzzy AHP.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Ayhan, M.B.: A Fuzzy AHP Approach for supplier selection problem: a case study in a gear motor company. Int. J. Manag. Value Supply Chains 4(3), 11 (2013)

    Article  Google Scholar 

  2. Alguliyev, R.M., Aliguliyev, R.M., Mahmudova, R.S.: Multicriteria personnel selection by the modified fuzzy VIKOR method. Sci. World J. Article ID 612767, 1–16 (2015)

  3. Amiri, M.P.: Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods. Expert Syst. Appl. 37(9), 6218–6224 (2010)

    Article  Google Scholar 

  4. Avikala, S., Mishraa, P., Jain, R.: A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems. Int. J. Prod. Res. 52(5), 1306–1317 (2014)

    Article  Google Scholar 

  5. Balezentis, A., Balezentis, T., Brauers, W.K.: Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Syst. Appl. 39(9), 7961–7967 (2012)

    Article  MATH  Google Scholar 

  6. Boran, F.E., Genc, S., Akay, D.: Personnel selection based on intuitionistic fuzzy sets. Hum. Factors Ergonomics Manuf. Serv. Ind. 21(5), 493–503 (2011)

    Article  Google Scholar 

  7. Bozbura, F.T., Beskese, A.: Prioritization of organizational capital measurement indicators using fuzzy AHP. Int. J. Approx. Reason. 44(2), 124–147 (2007)

    Article  Google Scholar 

  8. Büyüközkan, G., Çifçi, G.: A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry. Expert Syst. Appl. 39(3), 2341–2354 (2012)

    Article  Google Scholar 

  9. Büyüközkan, G., Çifçi, G., Güleryüz, S.: Strategic analysis of healthcare service quality using fuzzy AHP methodology. Expert Syst. Appl. 38(8), 9407–9424 (2011)

    Article  Google Scholar 

  10. Chang, D.-Y.: Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res. 95(3), 649–655 (1996)

    Article  MATH  Google Scholar 

  11. Cheng, C.-H.: Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. Eur. J. Oper. Res. 96(2), 343–350 (1997)

    Article  MATH  Google Scholar 

  12. Chen, C.-T.: Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst. 114(1), 1–9 (2000)

    Article  MATH  Google Scholar 

  13. Dagdeviren, M.: A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems. J. Intell. Manuf. 21(4), 451–460 (2010)

    Article  Google Scholar 

  14. Dursun, M., Karsak, E.E.: A fuzzy MCDM approach for personnel selection. Expert Syst. Appl. 37(6), 4324–4330 (2010)

    Article  Google Scholar 

  15. Ertugrul, I., Karakasoglu, N.: Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Syst. Appl. 36(1), 702–715 (2009)

    Article  Google Scholar 

  16. Güngör, Z., Serhadlıoğlu, G., Kesen, S.E.: A fuzzy AHP approach to personnel selection problem. Appl. Soft Comput. 9(2), 641–646 (2009)

    Article  Google Scholar 

  17. Heo, E., Kim, J., Boo, K.-J.: Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renew. Sustain. Energy Rev. 14(8), 2214–2220 (2010)

    Article  Google Scholar 

  18. Hwang, C.L., Lai, Y.J., Liu, T.Y.: A new approach for multiple objective decision making. Comput. Oper. Res. 20, 889–899 (1993)

    Article  MATH  Google Scholar 

  19. Hwang, C.L., Yoon, K.: Multiple Attribute Decision Making: Methods and Applications. Springer, New York (1981)

    Book  MATH  Google Scholar 

  20. Kahraman, C., Cebeci, U., Ulukan, Z.: Multi-criteria supplier selection using fuzzy AHP. Logist. Inf. Manag. 16(6), 382–394 (2003)

    Article  Google Scholar 

  21. Kaya, T., Kahraman, C.: Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology. Expert Syst. Appl. 38(6), 6577–6585 (2011)

    Article  Google Scholar 

  22. Kumar, P., Singh, R.K.: A fuzzy AHP and TOPSIS methodology to evaluate 3PL in a supply chain. J. Modell. Manag. 7(3), 287–303 (2012)

    Article  MathSciNet  Google Scholar 

  23. Kuo, R.J., Chi, S.C., Kao, S.S.: A decision support system for locating convenience store through fuzzy AHP. Comput. Ind. Eng. 37(1–2), 323–326 (1999)

    Article  Google Scholar 

  24. Kutlu, A.C., Ekmekçioglu, M.: Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Syst. Appl. 39(1), 61–67 (2012)

    Article  Google Scholar 

  25. Kwong, C.K., Bai, H.: Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach. IIE Trans. 35(7), 619–626 (2003)

    Article  Google Scholar 

  26. Lee, A.H.I., Chen, W.-C., Chang, C.-J.: A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Syst. Appl. 34(1), 96–107 (2008)

    Article  Google Scholar 

  27. Lee, S.-H.: Using fuzzy AHP to develop intellectual capital evaluation model for assessing their performance contribution in a university. Expert Syst. Appl. 37(7), 4941–4947 (2010)

    Article  Google Scholar 

  28. Liao, C.-N., Kao, H.-P.: An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Syst. Appl. 38(9), 10803–10811 (2011)

    Article  Google Scholar 

  29. Lin, H.-T.: Personnel selection using analytic network process and fuzzy data envelopment analysis approaches. Comput. Ind. Eng. 59(4), 937–944 (2010)

    Article  Google Scholar 

  30. Lootsma, F.A.: Fuzzy Logic for Planning and Decision Making. Kluwer Academic Publisher, Dordrecht (1997)

    Book  MATH  Google Scholar 

  31. Matin, H.Z., Fathi, M.R., Zarchi, M.K., Azizollahi, S.: The application of fuzzy TOPSIS approach to personnel selection for Padir Company, Iran. J. Manag. Res. 3(2), 1–14 (2011)

    Google Scholar 

  32. Mon, D.-L., Cheng, C.-H., Lin, J.-C.: Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight. Fuzzy Sets Syst. 62(2), 127–134 (1994)

    Article  Google Scholar 

  33. Nazam, M., Xu, J., Tao, Z., Ahmad, J., Hashim, M.: A fuzzy AHP–TOPSIS framework for the risk assessment of green supply chain implementation in the textile industry. Int. J. Supply Oper. Manag. 2(1), 548–568 (2015)

    Google Scholar 

  34. Rouyendegh, B.D., Erkan, T.E.: Selection of academic staff using the fuzzy analytic hierarchy process (FAHP): a pilot study. Tehnički vjesnik 19(4), 923–929 (2012)

    Google Scholar 

  35. Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York (1981)

    MATH  Google Scholar 

  36. Samvedi, A., Jain, V., Chan, F.T.S.: Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS. Int. J. Prod. Res. 51(8), 2433–2442 (2013)

    Article  Google Scholar 

  37. Singh, R., Benyoucef, L.: A fuzzy TOPSIS based approach for e-sourcing. Eng. Appl. Artif. Intell. 24(3), 437–448 (2011)

    Article  Google Scholar 

  38. Sun, C.-C.: A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert Syst. Appl. 37(12), 7745–7754 (2010)

    Article  Google Scholar 

  39. Torlak, G., Sevkli, M., Sanal, M., Zaim, S.: Analyzing business competition by using fuzzy TOPSIS method: an example of Turkish domestic airline industry. Expert Syst. Appl. 38(4), 3396–3406 (2011)

    Article  Google Scholar 

  40. Vatansever, K., Oncel, M.: An implementation of integrated multi-criteria decision making techniques for academic staff recruitment. J. Manag. Mark. Logist. 1(2), 111–126 (2014)

    Google Scholar 

  41. Wang, T.-C., Chang, T.-H.: Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Syst. Appl. 33(4), 870–880 (2007)

    Article  Google Scholar 

  42. Wang, Y.-M., Elhag, T.M.: Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Syst. Appl. 31(2), 309–319 (2006)

    Article  Google Scholar 

  43. Yong, D.: Plant location selection based on fuzzy TOPSIS. Int. J. Adv. Manuf. Technol. 28(7), 839–844 (2006)

    Article  Google Scholar 

  44. Yoon, K.: A reconciliation among discrete compromise situations. J. Oper. Res. Soc. 38, 277–286 (1987)

    Article  MATH  Google Scholar 

  45. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MATH  Google Scholar 

  46. Zadeh, L.A.: Fuzzy logic, neural network, and soft computing. Commun. ACM 37(3), 77–84 (1994)

    Article  Google Scholar 

  47. Zhang, S.-F., Liu, S.-Y.: A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Syst. Appl. 38(9), 11401–11405 (2011)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Kadir Has University, Cibali, 34083, Istanbul, Turkey

    Funda Samanlioglu, Yunus Emre Taskaya, Utku Can Gulen & Ogulcan Cokcan

Authors
  1. Funda Samanlioglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yunus Emre Taskaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Utku Can Gulen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ogulcan Cokcan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Funda Samanlioglu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Samanlioglu, F., Taskaya, Y.E., Gulen, U.C. et al. A Fuzzy AHP–TOPSIS-Based Group Decision-Making Approach to IT Personnel Selection. Int. J. Fuzzy Syst. 20, 1576–1591 (2018). https://doi.org/10.1007/s40815-018-0474-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-018-0474-7

Keywords

Search

Navigation