Research Article
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Personnel Performance Assessment using Entropy based MABAC Method: An Application in the Food Sector

Year 2022, , 89 - 106, 21.03.2022

Rabia Nur Kalem , Muhammet Enes Akpınar

https://doi.org/10.48064/equinox.1063776
Cited By: 2
An Erratum to this article was published on March 21, 2022. https://dergipark.org.tr/en/pub/equinox/issue/68986/1091558

Abstract

Personnel selection is one of the decisions of strategic importance in terms of ensuring sustainability of companies. This decision is referred to as a multi-criteria decision-making problem in the literature in terms of the many criteria it contains and the determination of the candidate who meets these criteria at the most appropriate level. The use of these methods in order to decide on the most suitable candidate accelerates the nomination process for the enterprise, while at the same time preventing the loss of time that may occur. In this study, an evaluation was made among the personnel who applied for a food company. In the evaluation, some of the criteria determined by the company manager and found in the literature were taken into consideration. Entropy method was used for criterion weights in the solution of the problem. Afterwards, the weights obtained from this method were integrated with the MABAC method, and it was aimed to rank the most suitable candidates. Finally, the ranking results obtained were interpreted and the most suitable candidate was decided.

Keywords

Multi-criteria decision making Personnel selection MABAC method Entropy method , MABAC method

References

  • Akshya Kaveri, B., Gireesha, O., Somu, N., Gauthama Raman, M. R., & Shankar Sriram, V. S. (2017). E-FPROMETHEE: an entropy based fuzzy multi criteria decision making service ranking approach for cloud service selection. In International Conference on Intelligent Information Technologies, 224-238.
  • Alao, M. A., Ayodele, T. R., Ogunjuyigbe, A. S. O., & Popoola, O. M. (2020). Multi-criteria decision based waste to energy technology selection using entropy-weighted TOPSIS technique: The case study of Lagos, Nigeria. Energy, 201, 117675.
  • Arguea M., Cushing J., & Woodrow W., (1997) “Neural Network Analysis of the Employee Classification Problem for Tax Purposes”, Documentos de Trabajo del Instituto Complutense de Análisis Económico 01.
  • Baležentis, A., Baležentis, T., & Brauers, W. K. M. (2012). Personnel Selection Based On Computing With Words And Fuzzy MULTIMOORA. Expert Systems with Applications, 39(9).
  • Bhowmik, C., Gangwar, S., Bhowmik, S., & Ray, A. (2018). Selection of energy-efficient material: an entropy–TOPSIS approach. In Soft Computing: Theories and Applications,31-39.
  • Borman, W. C., Hanson, M. A., & Hedge, J. W. (1997). Personnel Selection. Annual review of psychology, 48(1), 299-337.
  • Bozanic, D., Tešić, D., & Kočić, J. (2019). Multi-criteria FUCOM–Fuzzy MABAC model for the selection of location for construction of single-span bailey bridge. Decision making: applications in management and engineering, 2(1), 132-146.
  • Biswas, S., Bandyopadhyay, G., Guha, B., & Bhattacharjee, M. (2019). An ensemble approach for portfolio selection in a multi-criteria decision making framework. Decision Making: Applications in Management and Engineering, 2(2), 138-158.
  • Chen, C. H. (2019). A new multi-criteria assessment model combining GRA techniques with intuitionistic fuzzy entropy-based TOPSIS method for sustainable building materials supplier selection. Sustainability, 11(8), 2265.
  • Chen, C. H. (2020). A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy, 22(2), 259.
  • Çakır, S. & Perçin, S., (2013). AB ülkeleri’nde bütünleşik entropi ağırlık-topsis yöntemiyle ar-ge performansının ölçülmesi. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 32(1), 77-95.
  • Çınar, Y. (2004). Çok nitelikli karar verme ve bankaların mali performanslarının değerlendirilmesi örneği. Yayınlanmamış yüksek lisans tezi, Ankara Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı, Ankara.
  • Dang, W. V. (2019). Multi-criteria decision-making in the evaluation of environmental quality of OECD countries: the entropy weight and VIKOR methods. International Journal of Ethics and Systems.
  • Dursun, M., & Karsak, E. E. (2010). A Fuzzy MCDM Approach For Personnel Selection. Expert Systems With Applications, 37(6), 4324—4330.
  • Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2009). A Fuzzy AHP Approach To Personnel Selection Problem. Applied Soft Computing, 9(2), 641—646.
  • He, L., Shao, F., & Ren, L. (2021). Sustainability appraisal of desired contaminated groundwater remediation strategies: an information-entropy-based stochastic multi-criteria preference model. Environment, development and sustainability, 23(2), 1759-1779.
  • Heidary Dahooie, J., Beheshti Jazan Abadi, E., Vanaki, A. S., & Firoozfar, H. R. (2018). Competency Based IT Personnel Selection Using A Hybrid SWARA And ARASG Methodology. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(1), 5—16.
  • Işık, A. T. (2017). The decision-making approach based on the combination of entropy and ROV methods for the apple selection problem. European Journal of Interdisciplinary Studies, 3(3), 80-86.
  • Jones, M., & Obermesik, J (1992), “Effects Of Worker Classification And Employment Relatedness On Student Employee Job Satisfaction”, Journal of College Student Development, 33(1), 34—38.
  • Jokić, Ž., Božanić, D., & Pamučar, D. (2021). Selection of fire position of mortar units using LBWA and Fuzzy MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 4(1), 115-135.
  • Kilic, H. S., Demirci, A. E., & Delen, D. (2020). An Integrated Decision Analysis Methodology Based On IF-DEMATEL and IF-ELECTRE for personnel selection. Decision Support Systems, 113360.
  • Karami, A. and Johansson, R. (2014). Utilization of multi attribute decision making techniques to integrate automatic and manual ranking of options. Journal Of Information Science and Engineering, 30, 519-534.
  • Krishankumar, R., Premaladha, J., Ravichandran, K. S., Sekar, K. R., Manikandan, R., & Gao, X. Z. (2020). A Novel Extension to VIKOR Method Under Intuitionistic Fuzzy Context For Solving Personnel Selection Problem. Soft Computing, 24(2), 1063—1081.
  • Kuruoğlu M., (2006), “İnşaat Sektöründe Fiziksel Güce Dayalı İşlerin Sınıflandırılması ve Bu İşlerde Çalışanların Aktivite Düzeyinin Belirlenmesi”, Marmara Üniversitesi Tez Koleksiyonu 35691.
  • Lı, X., Wang, K., Lıu, L. X., Jing, Y., H., & Gao, C. (2011). application of the entropy weight and topsıs method in safety evaluation of coal mines. Procedia Engineering, 26, 2085-2091.
  • Liang, X., Teng, F., & Sun, Y. (2020). Multiple group decision making for selecting emergency alternatives: a novel method based on the LDWPA operator and LD-MABAC. International Journal of Environmental Research and Public Health, 17(8), 2945.
  • Lin, H. T. (2010). Personnel Selection Using Analytic Network Process And Fuzzy Data Envelopment Analysis Approaches. Computers & Industrial Engineering, 59(4), 937—944.
  • Mishra, A. R., Chandel, A., & Motwani, D. (2020). Extended MABAC method based on divergence measures for multi-criteria assessment of programming language with interval-valued intuitionistic fuzzy sets. Granular Computing, 5(1), 97-117.
  • Nabeeh, N. A, Smarandache, F., Abdel-Basset, M., El-Ghareeb, HA & Aboelfetouh, A. (2019). An Integrated Neutrosophic-TOPSIS Approach and Its Application to Personnel Selection: A New Trend in Brain Processing and Analysis. IEEE, 7, 29734—29744.
  • Oswald, F. L., Hough, L. M., & Zuo, C. (2019). Personnel Selection And Vocational Interests: Recent Research and Future Directions. Vocational Interests in the Workplace, 129-141.
  • Pamučar, D., Petrović, I. & Ćirović, G. (2018). Modification of the Best–Worst and MABAC methods: A Novel Approach Based on Interval-Valued Fuzzy-Rough Numbers. Expert systems with applications, 91, 89—106.
  • Pamucar, D., Chatterjee, K., & Zavadskas, E. K. (2019). Assessment of third-party logistics provider using multi-criteria decision-making approach based on interval rough numbers. Computers & Industrial Engineering, 127, 383-407.
  • Peng, J. J., Tian, C., Zhang, W. Y., Zhang, S., & Wang, J. Q. (2020). An integrated multi-criteria decision-making framework for sustainable supplier selection under picture fuzzy environment. Technological and Economic Development of Economy, 26(3), 573-598.
  • Raj Mishra, A., Sisodia, G., Raj Pardasani, K., & Sharma, K. (2020). Multi-Criteria IT Personnel Selection on Intuitionistic Fuzzy Information Measures and ARAS Methodology. Iranian Journal of Fuzzy Systems, 17(4), 55—68.
  • Robertson, I. T., & Smith, M. (2001). Personnel Selection. Journal of occupational and Organizational psychology, 74(4), 441-472.
  • Samanlioglu, F., Taskaya, Y. E., Gulen, U. C., & Cokcan, O. (2018). A fuzzy AHP–TOPSIS-Based Group Decision-Making Approach to IT Personnel Selection. International Journal of Fuzzy Systems, 20(5), 1576—1591. Sang, X., Liu, X., & Qin, J. (2015). An Analytical Solution to Fuzzy TOPSIS And Its Application in Personnel Selection for Knowledge-Intensive Enterprise. Applied Soft Computing, 30, 190-204.
  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3), 379-423.
  • Sonar, H. C., & Kulkarni, S. D. (2021). An integrated ahp-mabac approach for electric vehicle selection. Research in Transportation Business & Management, 41, 100665.
  • Şenyiğit, E., & Demirel, B. (2018). The selection of material in dental implant with entropy based simple additive weighting and analytic hierarchy process methods. Sigma Journal of Engineering and Natural Sciences, 36(3), 731-740.
  • Vaid, S. K., Vaid, G., Kaur, S., Kumar, R., & Sidhu, M. S. (2022). Application of multi-criteria decision-making theory with VIKOR-WASPAS-Entropy methods: A case study of silent Genset. Materials Today: Proceedings, 50, 2416-2423.
  • VanDenHaute K., Prescott W., Altieri M., & Tietz R., (2017). Worker Classification Issues in Professional Practices. 24-43.
  • Zhang, S., & Liu, S. (2011). A GRA-based Intuitionistic Fuzzy Multi-Criteria Group Decision Making Method for Personnel Selection. Expert Systems with Applications, 38(9), 11401-11405.
  • Zhang, H., Wei, G., & Chen, X. (2021). CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection. Journal of Intelligent & Fuzzy Systems, 1-11.
  • Wang, T. C., & Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert systems with applications, 36(5), 8980-8985.
  • Wei, G., He, Y., Lei, F., Wu, J., Wei, C., & Guo, Y. (2020). Green supplier selection with an uncertain probabilistic linguistic MABAC method. Journal of Intelligent & Fuzzy Systems, 39(3), 3125-3136.
  • Wu, Y., Deng, Z., Tao, Y., Wang, L., Liu, F., & Zhou, J. (2021). Site selection decision framework for photovoltaic hydrogen production project using BWM-CRITIC-MABAC: A case study in Zhangjiakou. Journal of Cleaner Production, 324, 129233.

Year 2022, , 89 - 106, 21.03.2022

Rabia Nur Kalem , Muhammet Enes Akpınar

https://doi.org/10.48064/equinox.1063776
Cited By: 2
An Erratum to this article was published on March 21, 2022. https://dergipark.org.tr/en/pub/equinox/issue/68986/1091558

Abstract

References

  • Akshya Kaveri, B., Gireesha, O., Somu, N., Gauthama Raman, M. R., & Shankar Sriram, V. S. (2017). E-FPROMETHEE: an entropy based fuzzy multi criteria decision making service ranking approach for cloud service selection. In International Conference on Intelligent Information Technologies, 224-238.
  • Alao, M. A., Ayodele, T. R., Ogunjuyigbe, A. S. O., & Popoola, O. M. (2020). Multi-criteria decision based waste to energy technology selection using entropy-weighted TOPSIS technique: The case study of Lagos, Nigeria. Energy, 201, 117675.
  • Arguea M., Cushing J., & Woodrow W., (1997) “Neural Network Analysis of the Employee Classification Problem for Tax Purposes”, Documentos de Trabajo del Instituto Complutense de Análisis Económico 01.
  • Baležentis, A., Baležentis, T., & Brauers, W. K. M. (2012). Personnel Selection Based On Computing With Words And Fuzzy MULTIMOORA. Expert Systems with Applications, 39(9).
  • Bhowmik, C., Gangwar, S., Bhowmik, S., & Ray, A. (2018). Selection of energy-efficient material: an entropy–TOPSIS approach. In Soft Computing: Theories and Applications,31-39.
  • Borman, W. C., Hanson, M. A., & Hedge, J. W. (1997). Personnel Selection. Annual review of psychology, 48(1), 299-337.
  • Bozanic, D., Tešić, D., & Kočić, J. (2019). Multi-criteria FUCOM–Fuzzy MABAC model for the selection of location for construction of single-span bailey bridge. Decision making: applications in management and engineering, 2(1), 132-146.
  • Biswas, S., Bandyopadhyay, G., Guha, B., & Bhattacharjee, M. (2019). An ensemble approach for portfolio selection in a multi-criteria decision making framework. Decision Making: Applications in Management and Engineering, 2(2), 138-158.
  • Chen, C. H. (2019). A new multi-criteria assessment model combining GRA techniques with intuitionistic fuzzy entropy-based TOPSIS method for sustainable building materials supplier selection. Sustainability, 11(8), 2265.
  • Chen, C. H. (2020). A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy, 22(2), 259.
  • Çakır, S. & Perçin, S., (2013). AB ülkeleri’nde bütünleşik entropi ağırlık-topsis yöntemiyle ar-ge performansının ölçülmesi. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 32(1), 77-95.
  • Çınar, Y. (2004). Çok nitelikli karar verme ve bankaların mali performanslarının değerlendirilmesi örneği. Yayınlanmamış yüksek lisans tezi, Ankara Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı, Ankara.
  • Dang, W. V. (2019). Multi-criteria decision-making in the evaluation of environmental quality of OECD countries: the entropy weight and VIKOR methods. International Journal of Ethics and Systems.
  • Dursun, M., & Karsak, E. E. (2010). A Fuzzy MCDM Approach For Personnel Selection. Expert Systems With Applications, 37(6), 4324—4330.
  • Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2009). A Fuzzy AHP Approach To Personnel Selection Problem. Applied Soft Computing, 9(2), 641—646.
  • He, L., Shao, F., & Ren, L. (2021). Sustainability appraisal of desired contaminated groundwater remediation strategies: an information-entropy-based stochastic multi-criteria preference model. Environment, development and sustainability, 23(2), 1759-1779.
  • Heidary Dahooie, J., Beheshti Jazan Abadi, E., Vanaki, A. S., & Firoozfar, H. R. (2018). Competency Based IT Personnel Selection Using A Hybrid SWARA And ARASG Methodology. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(1), 5—16.
  • Işık, A. T. (2017). The decision-making approach based on the combination of entropy and ROV methods for the apple selection problem. European Journal of Interdisciplinary Studies, 3(3), 80-86.
  • Jones, M., & Obermesik, J (1992), “Effects Of Worker Classification And Employment Relatedness On Student Employee Job Satisfaction”, Journal of College Student Development, 33(1), 34—38.
  • Jokić, Ž., Božanić, D., & Pamučar, D. (2021). Selection of fire position of mortar units using LBWA and Fuzzy MABAC model. Operational Research in Engineering Sciences: Theory and Applications, 4(1), 115-135.
  • Kilic, H. S., Demirci, A. E., & Delen, D. (2020). An Integrated Decision Analysis Methodology Based On IF-DEMATEL and IF-ELECTRE for personnel selection. Decision Support Systems, 113360.
  • Karami, A. and Johansson, R. (2014). Utilization of multi attribute decision making techniques to integrate automatic and manual ranking of options. Journal Of Information Science and Engineering, 30, 519-534.
  • Krishankumar, R., Premaladha, J., Ravichandran, K. S., Sekar, K. R., Manikandan, R., & Gao, X. Z. (2020). A Novel Extension to VIKOR Method Under Intuitionistic Fuzzy Context For Solving Personnel Selection Problem. Soft Computing, 24(2), 1063—1081.
  • Kuruoğlu M., (2006), “İnşaat Sektöründe Fiziksel Güce Dayalı İşlerin Sınıflandırılması ve Bu İşlerde Çalışanların Aktivite Düzeyinin Belirlenmesi”, Marmara Üniversitesi Tez Koleksiyonu 35691.
  • Lı, X., Wang, K., Lıu, L. X., Jing, Y., H., & Gao, C. (2011). application of the entropy weight and topsıs method in safety evaluation of coal mines. Procedia Engineering, 26, 2085-2091.
  • Liang, X., Teng, F., & Sun, Y. (2020). Multiple group decision making for selecting emergency alternatives: a novel method based on the LDWPA operator and LD-MABAC. International Journal of Environmental Research and Public Health, 17(8), 2945.
  • Lin, H. T. (2010). Personnel Selection Using Analytic Network Process And Fuzzy Data Envelopment Analysis Approaches. Computers & Industrial Engineering, 59(4), 937—944.
  • Mishra, A. R., Chandel, A., & Motwani, D. (2020). Extended MABAC method based on divergence measures for multi-criteria assessment of programming language with interval-valued intuitionistic fuzzy sets. Granular Computing, 5(1), 97-117.
  • Nabeeh, N. A, Smarandache, F., Abdel-Basset, M., El-Ghareeb, HA & Aboelfetouh, A. (2019). An Integrated Neutrosophic-TOPSIS Approach and Its Application to Personnel Selection: A New Trend in Brain Processing and Analysis. IEEE, 7, 29734—29744.
  • Oswald, F. L., Hough, L. M., & Zuo, C. (2019). Personnel Selection And Vocational Interests: Recent Research and Future Directions. Vocational Interests in the Workplace, 129-141.
  • Pamučar, D., Petrović, I. & Ćirović, G. (2018). Modification of the Best–Worst and MABAC methods: A Novel Approach Based on Interval-Valued Fuzzy-Rough Numbers. Expert systems with applications, 91, 89—106.
  • Pamucar, D., Chatterjee, K., & Zavadskas, E. K. (2019). Assessment of third-party logistics provider using multi-criteria decision-making approach based on interval rough numbers. Computers & Industrial Engineering, 127, 383-407.
  • Peng, J. J., Tian, C., Zhang, W. Y., Zhang, S., & Wang, J. Q. (2020). An integrated multi-criteria decision-making framework for sustainable supplier selection under picture fuzzy environment. Technological and Economic Development of Economy, 26(3), 573-598.
  • Raj Mishra, A., Sisodia, G., Raj Pardasani, K., & Sharma, K. (2020). Multi-Criteria IT Personnel Selection on Intuitionistic Fuzzy Information Measures and ARAS Methodology. Iranian Journal of Fuzzy Systems, 17(4), 55—68.
  • Robertson, I. T., & Smith, M. (2001). Personnel Selection. Journal of occupational and Organizational psychology, 74(4), 441-472.
  • Samanlioglu, F., Taskaya, Y. E., Gulen, U. C., & Cokcan, O. (2018). A fuzzy AHP–TOPSIS-Based Group Decision-Making Approach to IT Personnel Selection. International Journal of Fuzzy Systems, 20(5), 1576—1591. Sang, X., Liu, X., & Qin, J. (2015). An Analytical Solution to Fuzzy TOPSIS And Its Application in Personnel Selection for Knowledge-Intensive Enterprise. Applied Soft Computing, 30, 190-204.
  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3), 379-423.
  • Sonar, H. C., & Kulkarni, S. D. (2021). An integrated ahp-mabac approach for electric vehicle selection. Research in Transportation Business & Management, 41, 100665.
  • Şenyiğit, E., & Demirel, B. (2018). The selection of material in dental implant with entropy based simple additive weighting and analytic hierarchy process methods. Sigma Journal of Engineering and Natural Sciences, 36(3), 731-740.
  • Vaid, S. K., Vaid, G., Kaur, S., Kumar, R., & Sidhu, M. S. (2022). Application of multi-criteria decision-making theory with VIKOR-WASPAS-Entropy methods: A case study of silent Genset. Materials Today: Proceedings, 50, 2416-2423.
  • VanDenHaute K., Prescott W., Altieri M., & Tietz R., (2017). Worker Classification Issues in Professional Practices. 24-43.
  • Zhang, S., & Liu, S. (2011). A GRA-based Intuitionistic Fuzzy Multi-Criteria Group Decision Making Method for Personnel Selection. Expert Systems with Applications, 38(9), 11401-11405.
  • Zhang, H., Wei, G., & Chen, X. (2021). CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection. Journal of Intelligent & Fuzzy Systems, 1-11.
  • Wang, T. C., & Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert systems with applications, 36(5), 8980-8985.
  • Wei, G., He, Y., Lei, F., Wu, J., Wei, C., & Guo, Y. (2020). Green supplier selection with an uncertain probabilistic linguistic MABAC method. Journal of Intelligent & Fuzzy Systems, 39(3), 3125-3136.
  • Wu, Y., Deng, Z., Tao, Y., Wang, L., Liu, F., & Zhou, J. (2021). Site selection decision framework for photovoltaic hydrogen production project using BWM-CRITIC-MABAC: A case study in Zhangjiakou. Journal of Cleaner Production, 324, 129233.
There are 46 citations in total.

Details

Primary Language English
Subjects Business Administration
Journal Section Research Article
Authors

Rabia Nur Kalem 0000-0002-8986-4934

Muhammet Enes Akpınar 0000-0003-0328-6107

Publication Date March 21, 2022
Acceptance Date March 18, 2022
Published in Issue Year 2022

Cite

APA Kalem, R. N., & Akpınar, M. E. (2022). Personnel Performance Assessment using Entropy based MABAC Method: An Application in the Food Sector. Ekinoks Ekonomi İşletme Ve Siyasal Çalışmalar Dergisi, 9(1), 89-106. https://doi.org/10.48064/equinox.1063776

Cited By

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https://doi.org/10.21076/vizyoner.1314956
ENTROPİ DESTEKLİ MABAC YÖNTEMİ İLE AB ÜLKELERİ DİJİTAL DÖNÜŞÜM PERFORMANSI ANALİZİ
Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi
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