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The new combination with CRITIC and WASPAS methods for the time and attendance software selection problem

  • Ayşegül TuşEmail author
  • Esra Aytaç Adalı
Application Article
  • 24 Downloads

Abstract

Keeping track of employees’ time and attendance is difficult and time-consuming task for the companies. Today many companies are performing the digital time and attendance systems that automatically track and process the data to improve their operations and save money. There are many alternatives for the time and attendance systems in the market and appropriate selection among them is not easy in the presence of multiple, usually conflicting, criteria. So this selection may be considered as a Multi Criteria Decision Making (MCDM) problem. In this paper, the new combined decision making approach based on Criteria Importance Through Inter criteria Correlation (CRITIC) and Weighted Aggregated Sum Product Assessment (WASPAS) methods is used for the time and attendance software selection problem of the private hospital. The weights of the criteria are determined by CRITIC method and the alternatives are ranked by WASPAS method for finding the most suitable alternative. The novelty of this paper to the literature is to combine CRITIC and WASPAS methods for the first time.

Keywords

MCDM CRITIC WASPAS Time and attendance software selection 

Notes

References

  1. 1.
    Muhtahir, O., Adeyinka, A., Kayode, A.: Fingerprint biometric authentication for enhancing staff attendance system. Int. J. Appl. Inf. Syst. 5(3), 19–24 (2013)Google Scholar
  2. 2.
    Madic, M., Radovanović, M.: Ranking of some most commonly used nontraditional machining processes using ROV and CRITIC methods. U.P.B. Sci. Bull. Ser. D 77(2), 193–204 (2015)Google Scholar
  3. 3.
    Diakoulaki, D., Mavrotas, G., Papayannakis, L.: Determining objective weights in multiple criteria problems: the CRITIC method. Comput. Oper. Res. 22(7), 763–770 (1995)CrossRefGoogle Scholar
  4. 4.
    Yılmaz, B., Harmancıoğlu, N.B.: Multi-criteria decision making for water resource management: a case study of the Gediz River Basin, Turkey. Water SA 36(5), 563–576 (2010)Google Scholar
  5. 5.
    Aznar Bellver, J., Cervelló, R.R., García, G.F.: Spanish savings banks and their future transformation into private capital banks. Determining their value by a multicriteria valuation methodology. Eur. J. Econ. Finance Admin. Sci. 35, 155–164 (2011)Google Scholar
  6. 6.
    Milić, M.R., Goran, Z.Z.: Objektivni pristup određivanju težına krıterıjuma (An objective approach to determining criteria weights). Vojnotehnıčkı glasnık/mılıtary technıcal courıer, LX 1, 39–56 (2012)Google Scholar
  7. 7.
    Guo, C., Wang, Y., Jiang, W.: An empirical study of evaluation index system and measure method on city’s soft power: 17 cities in Shandong Province. Cross-Cultural Commun. 9(6), 27–31 (2013)Google Scholar
  8. 8.
    Çakır, S., Perçin, S.: Çok Kriterli Karar Verme Teknikleriyle Lojistik Firmalarında Performans Ölçümü. Ege Akademik Bakış 13(4), 449–459 (2013)Google Scholar
  9. 9.
    Liu, D., Zhao, X.: Method and application for dynamic comprehensive evaluation with subjective and objective information. PLoS ONE 8(12), 1–5 (2013)Google Scholar
  10. 10.
    Kazan, H., Ozdemir, O.: Financial performance assessment of large scale conglomerates via TOPSIS and CRITIC methods. Int. J. Manag. Sustain. 3(4), 203–224 (2014)Google Scholar
  11. 11.
    Alemiardakani, M.: Enhancing impact characterization and multi-criteria design optimization of glass fiber reinforced polypropylene laminates. Doctor of Philosophy, The University Of British Columbia (2014)Google Scholar
  12. 12.
    Luo, S. M.: Evaluation of sustainability index for urban water management system in Macau [Outstanding Academic Papers by Students (OAPS)]. Retrieved from University of Macau, Outstanding Academic Papers by Students Repository (2014)Google Scholar
  13. 13.
    Kim, J., Yu, K.: Areal feature matching based on similarity using CRITIC method. In: Joint International Geoinformation Conference 2015, 28–30 October, Kuala Lumpur, Malaysia, pp. 75–78 (2015)Google Scholar
  14. 14.
    Lu, C., Li, L., Wu, D.: Application of combination weighting method to weight calculation in performance evaluation of ICT. In: 15th International Conference on Advanced Learning Technologies, pp. 258–259 (2015)Google Scholar
  15. 15.
    Zavadskas, E.K., Turskis, Z., Antucheviciene, J., Zakarevicius, A.: Optimization of weighted aggregated sum product assessment. Elektron. Elektrotech. 122(6), 3–6 (2012)Google Scholar
  16. 16.
    Zavadskas, E.K., Baušys, R., Lazauskas, M.: Sustainable assessment of alternative sites for the construction of a waste incineration plant by applying WASPAS method with single-valued neutrosophic set. Sustainability 7, 15923–15936 (2015)CrossRefGoogle Scholar
  17. 17.
    Turskis, Z., Zavadskas, E.K., Antucheviciene, J., Kosareva, N.: A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. Int. J. Comput. Commun. Control 10(6), 873–888 (2015)CrossRefGoogle Scholar
  18. 18.
    Lashgari, S., Antuchevičienė, J., Delavari, A., Kheirkhah, O.: Using QSPM and WASPAS methods for determining outsourcing strategies. J. Bus. Econ. Manag. 15(4), 729–743 (2014)CrossRefGoogle Scholar
  19. 19.
    Zolfani, S.H., Aghdaie, M.H., Derakhti, A., Zavadskas, E.K., Varzandeh, M.H.M.: Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating. Expert Syst. Appl. 40, 7111–7121 (2013)CrossRefGoogle Scholar
  20. 20.
    Zavadskas, E.K., Antucheviciene, J., Šaparauskas, J., Zenonas Turskis, Z.: Multi-criteria assessment of facades’ alternatives: peculiarities of ranking methodology. Procedia Eng. 57, 107–112 (2013)CrossRefGoogle Scholar
  21. 21.
    Madić, M., Gecevska, V., Radovanović, M., Petković, D.: Multi-criteria economic analysis of machining processes using the WASPAS method. J. Prod. Eng. 17(2), 79–82 (2014)Google Scholar
  22. 22.
    Chakraborty, S., Zavadskas, E.K.: Applications of WASPAS method in manufacturing decision making. Informatica 25(1), 1–20 (2014)CrossRefGoogle Scholar
  23. 23.
    Chakraborty, S., Bhattacharyya, O., Zavadskas, E.K., Antucheviciene, J.: Application of WASPAS method as an optimization tool in non-traditional machining processes. Inf. Technol. Control 44(1), 77–88 (2015)Google Scholar
  24. 24.
    Aytaç Adalı, E., Tuş Işık, A.: Critic and Maut methods for the contract manufacturer selection problem. Eur. J. Multidiscip. Stud. 5(1), 93–101 (2017)CrossRefGoogle Scholar
  25. 25.
    Aytaç Adalı, E.,Tuş Işık, A.: A multi-criteria analysis based on critic and EDAS methods for hospital site selection. In: International Congress on Afro-Eurasian Research IV, April 27–29, pp. 734–743 (2018)Google Scholar
  26. 26.
    Tuş, A., Aytaç Adalı, E.: Personnel assessment with CODAS and PSI methods. Alphanumeric J. 6(2), 243–256 (2018)Google Scholar

Copyright information

© Operational Research Society of India 2019

Authors and Affiliations

  1. 1.Department of Business AdministrationPamukkale UniversityDenizliTurkey

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