Abstract
Measuring employee performance is critical to improving production and service processes in enterprises. However, as with all other abstract concepts, performance measurement has a complex process. Different approaches are used in the literature for performance measurement. One of these methods is Multi-Criteria Decision Making (MCDM). The MCDM aims to select the best alternatives by simultaneously evaluating the criteria. In addition, one or more decision-makers in the MCDM may be involved in the decision-making process at the same time. For these reasons, a Fuzzy-MCDM method is proposed for the performance evaluation of project groups operating in the software sector. The application part of the study aimed to determine the best-performing team among four software project groups working in an insurance company, combining the Fuzzy-Analytic Hierarchy Process (F-AHP) and Elimination and Choice Translating Reality (ELECTRE) methods. Each group comprises five software engineers who are experts in their field. In the first stage, the main criteria and sub-criteria that impact performance most were determined. Then, the weights of the criteria were determined by the F-AHP method. Finally, with the ELECTRE method, the performance ranking of the software groups was made.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Eraslan, E., Algün, O.: İdeal performans değerlendirme formu tasarımında analitik hiyerarşi yöntemi yaklaşımı (2005)
Saaty, T.L., Sodenkamp, M.: The Analytic Hierarchy and Analytic Network Measurement Processes: The Measurement of Intangibles, vol. 1, pp. 91–166 (2010). https://doi.org/10.1007/978-3-540-92828-7_4
Özder, E.H., Özcan, E., Eren, T.: Staff task-based shift scheduling solution with an ANP and goal programming method in a natural gas combined cycle power plant. Mathematics 7 (2019). https://doi.org/10.3390/math7020192
Farrell, M.J.: The measurement of productive efficiency. J. R. Stat. Soc. Ser. A. (1957). https://doi.org/10.2307/2343100
Lynch, R., Cross, K.: Measure Up - the essential guide to measuring business performance. In: IEEE International Conference on Robotics and Automation (1991)
Kaplan, R.S., Norton, D.: The balanced score card measures that drive performance. Harv. Bus. Rev. 70, 71–79 (1992). https://doi.org/10.1017/CBO9781107415324.004
Kaplan, R.S., Norton, D.P.: Linking the balanced scorecard to strategy. Calif. Manage. Rev. (1996). https://doi.org/10.2307/41165876
Hronec, S.M.: Vital signs: using quality, time, and cost performance measurements to chart your company’s future. Amacom American Management Association (1993)
Neely, A., Adams, C., Crowe, P.: The performance prism in practice. Meas. Bus. Excell. (2001). https://doi.org/10.1108/13683040110385142
Neely, A., Adams, C., Kennerley, M.: The performance prism: the scorecard for measuring and managing business success. Cranf. Sch. Manag. (2002). https://doi.org/10.1108/eb016623
Wu, H.Y., Tzeng, G.H., Chen, Y.H.: A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert Syst. Appl. (2009). https://doi.org/10.1016/j.eswa.2009.01.005
Wu, H.Y., Lin, Y.K., Chang, C.H.: Performance evaluation of extension education centers in universities based on the balanced scorecard. Eval. Program Plann. (2011). https://doi.org/10.1016/j.evalprogplan.2010.06.001
Gürbüz, T., Albayrak, Y.E.: An engineering approach to human resources performance evaluation: hybrid MCDM application with interactions. Appl. Soft Comput. J. (2014). https://doi.org/10.1016/j.asoc.2014.03.025
Ozdemir, Y.S., Oktay, T.: Evaluating service quality of an airline maintenance company by applying fuzzy-AHP. In: Calisir, F., Cevikcan, E., Camgoz Akdag, H. (eds.) Industrial Engineering in the Big Data Era. LNMIE, pp. 189–200. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-03317-0_16
Haseli, G., Sheikh, R., Sana, S.S.: Base-criterion on multi-criteria decision-making method and its applications. Int. J. Manag. Sci. Eng. Manag. 15, 79–88 (2020). https://doi.org/10.1080/17509653.2019.1633964
Rahmati, S., Mahdavi, M.H., Ghoushchi, S.J., Tomaskova, H., Haseli, G.: Assessment and prioritize risk factors of financial measurement of management control system for production companies using a hybrid Z-SWARA and Z-WASPAS with FMEA method: a meta-analysis. Mathematics. 10 (2022). https://doi.org/10.3390/math10020253
Goli, A., Mohammadi, H.: Developing a sustainable operational management system using hybrid Shapley value and Multimoora method: case study petrochemical supply chain. Environ. Dev. Sustain. 1–30 (2021). https://doi.org/10.1007/s10668-021-01844-9
Saaty, T.L.: The analytic hierarchy process. Education 1–11 (1980). https://doi.org/10.3414/ME10-01-0028
Piya, S., Shamsuzzoha, A., Azizuddin, M., Al-Hinai, N., Erdebilli, B.: Integrated fuzzy AHP-TOPSIS method to analyze green management practice in hospitality industry in the sultanate of Oman. Sustain. 14 (2022). https://doi.org/10.3390/su14031118
Ayyildiz, E., Taskin Gumus, A.: Pythagorean fuzzy AHP based risk assessment methodology for hazardous material transportation: an application in Istanbul. Environ. Sci. Pollut. Res. 28(27), 35798–35810 (2021). https://doi.org/10.1007/s11356-021-13223-y
Soner, S., Önüt, S.: Multi-criteria supplier selection: an Electre-Ahp application. J. Eng. Nat. Sci. Sigma. (2006)
Chan, F.T.S.: Performance measurement in a supply chain. Int. J. Adv. Manuf. Technol. (2003). https://doi.org/10.1007/s001700300063
Shaik, M., Abdul-Kader, W.: Performance measurement of reverse logistics enterprise: a comprehensive and integrated approach. Meas. Bus. Excell. (2012). https://doi.org/10.1108/13683041211230294
Fernandes, J.M., Rodrigues, S.P., Costa, L.A.: Comparing AHP and ELECTRE i for prioritizing software requirements. In: 2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2015 - Proceedings (2015)
Benayoun, R.B., Sussman, N.: Manual de Reference du Programme Electre. Note Synth. Format. (1966)
Daneshvar Rouyendegh, B., Erol, S.: Selecting the best project using the fuzzy ELECTRE method. Math. Probl. Eng. (2012). https://doi.org/10.1155/2012/790142
Kahraman, C., Cebeci, U., Ulukan, Z.: Multi-criteria supplier selection using fuzzy AHP. Logist. Inf. Manag. (2003). https://doi.org/10.1108/09576050310503367
Göleç, A., Taşkin, H.: Novel methodologies and a comparative study for manufacturing systems performance evaluations. Inf. Sci. (Ny). (2007). https://doi.org/10.1016/j.ins.2007.06.024
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, 96–107 (2008). https://doi.org/10.1016/j.eswa.2006.08.022
Sun, Q., Zhang, W.M., Li, P.Z.: A comprehensive evaluation approach for machining operation based on fuzzy AHP. In: Applied Mechanics and Materials (2014)
Zadeh, L.A.: Fuzzy sets. Inf. Control. 8, 338–353 (1965). https://doi.org/10.1109/2.53
Buckley, J.J.: Fuzzy hierarchical analysis. Fuzzy Sets Syst. 17, 233–247 (1985). https://doi.org/10.1016/0165-0114(85)90090-9
Saaty, T.L.: Decision making with the analytic hierarchy process. Int. J. Serv. Sci. (2008). https://doi.org/10.1504/IJSSCI.2008.017590
Beccali, M., Cellura, M., Mistretta, M.: Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology. Renew. Energy. (2003). https://doi.org/10.1016/S0960-1481(03)00102-2
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ansen, E., Özdemir, Y.S. (2023). Performance Measurement of Insurance Company Software Groups by Using Fuzzy-AHP and ELECTRE Method. In: Mirzazadeh, A., Erdebilli, B., Babaee Tirkolaee, E., Weber, GW., Kar, A.K. (eds) Science, Engineering Management and Information Technology. SEMIT 2022. Communications in Computer and Information Science, vol 1808. Springer, Cham. https://doi.org/10.1007/978-3-031-40395-8_25
Download citation
DOI: https://doi.org/10.1007/978-3-031-40395-8_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-40394-1
Online ISBN: 978-3-031-40395-8
eBook Packages: Computer ScienceComputer Science (R0)