SÜREÇ YÖNETİMİNİN ETKİSİNİ ARTIRAN KRİTİK BAŞARI FAKTÖRLERİNİN ÖNCELİKLENDİRİLMESİ

Yıl 2022, Cilt: 33 Sayı: 1, 212 - 228, 30.04.2022

Aylin Adem , Metin Dağdeviren

https://doi.org/10.46465/endustrimuhendisligi.1020664

Öz

İşletmelerde verimlilik ölçümü ve izlenebilirliğinin sağlanması açısından oldukça kritik bir öneme sahip olan süreç yönetimi çalışmalarının nihai hedeflerine ulaşmasındaki başarısını etkileyen çok sayıda kriter bulunmaktadır. Bu makalede başarılı bir süreç yönetimi sürdürebilmek için dikkat edilmesi gerek Kritik Başarı Faktörleri (KBF)’nin belirlenmesi ve bu faktörlerin çok kriterli analizine yönelik bir çalışma yapılmıştır. KBF’lerin belirlenmesi sırasında derin literatür araştırmasının yanı sıra vaka incelemeleri yapılmıştır. Elde edilen KBF’lerin analizinde ise karar vericilerin tereddütlerine odaklanan Küresel bulanık sayılarla bütünleştirilmiş edilmiş Analitik Hiyerarşi Prosesi yöntemi kullanılmıştır. Çalışmada elde edilen sonuçlara göre süreç yönetiminde insan faktörü en önemli KBF olarak belirlenirken, süreç yönetimi çalışmalarını sürdürecek ekibin uygun bir şekilde belirlenmesi en önemli alt KBF olarak belirlenmiştir. Bu çalışmada yer alan teorik ve çok kriterli analizin neticesinde sunulan pratik bilgiler, süreç yönetimi çalışmalarını başarılı bir biçimde yürütmek isteyen işletmeler ve profesyoneller için bir rehber niteliğinde olacağı öngörülmektedir.

Anahtar Kelimeler

süreç yönetimi, kritik başarı faktörleri, çok kriterli karar verme, bulanık mantık, küresel bulanık sayılar

PRIORITIZING THE CRITICAL SUCCESS FACTORS THAT INCREASE THE IMPACT OF PROCESS MANAGEMENT

Öz

There are plenty of criteria that affect the success of process management studies, which are of critical importance in terms of ensuring general efficiency measurement and traceability in enterprises, in reaching their final aims. In this article, a study was conducted to determine the Critical Success Factors (CSFs) that need attention in order to maintain successful process management and to analyze these factors with multiple criteria. During the identification of CSFs, case studies were conducted as well as in-depth literature research. In the analysis of the determined CSFs, the Analytical Hierarchy Process (AHP) technique, which is integrated with the spherical fuzzy numbers because it focuses on the hesitancy degree of decision-makers, was employed. According to the results, the human-factor in process management was determined as the most important CSFs, while the appropriate determination of the team was the most important sub-CSFs. It is foreseen that the practical and theoretical information presented as a result of multi-criteria analysis in this study is a guide for companies and professionals who want to carry out their process management studies successfully.

Anahtar Kelimeler

process management, critical success factors, multi-criteria decision making, fuzzy logic, spherical fuzzy numbers

Kaynakça

• Adem, A., Çakıt, E., & Dağdeviren, M. (2021). A fuzzy decision-making approach to analyze the design principles for green ergonomics. Neural Computing and Applications, 1-12.
• Adem, A., Çolak, A., & Dağdeviren, M. (2018). An integrated model using SWOT analysis and Hesitant fuzzy linguistic term set for evaluation occupational safety risks in life cycle of wind turbine. Safety science, 106, 184-190.
• Ashraf, S., & Abdullah, S. (2020). Emergency decision support modeling for COVID‐19 based on spherical fuzzy information. International Journal of Intelligent Systems, 35(11), 1601-1645.
• Ayyildiz, E., & Gumus, A. T. (2020). A novel spherical fuzzy AHP-integrated spherical WASPAS methodology for petrol station location selection problem: a real case study for İstanbul. Environmental Science and Pollution Research, 27(29), 36109-36120.
• Balzarova, M. A., Bamber, C. J., McCambridge, S., & Sharp, J. M. (2004). Key success factors in implementation of process‐based management: A UK housing association experience. Business Process Management Journal. 10 (4), 387-399.
• Buran, B., & Erçek, M. (2021, August). Public Transportation Business Model Assessment with Spherical Fuzzy AHP. In International Conference on Intelligent and Fuzzy Systems (pp. 741-748). Springer, Cham.
• Çolak, A., Adem, A., & Dağdeviren, M. (2019, July). Fuzzy Prioritization of Factors Affecting Employer Branding for Employees. International Conference on Intelligent and Fuzzy Systems (pp. 852-858). Springer, Cham.
• Dağdeviren, M., Eraslan, E., & Çelebi, F. V. (2011). An alternative work measurement method and its application to a manufacturing industry. Journal of Loss Prevention in the Process Industries, 24(5), 563-567.
• Dağdeviren, M., Yavuz, S., & Kılınç, N. (2009). Weapon selection using the AHP and TOPSIS methods under fuzzy environment. Expert systems with Applications, 36(4), 8143-8151.
• Demir, E., & Turan, H. (2021). An integrated spherical fuzzy AHP multi-criteria method for Covid-19 crisis management in regarding lean six sigma. International Journal of Lean Six Sigma, 12(4), 859-885
• Dogan, O. (2021). Process mining technology selection with spherical fuzzy AHP and sensitivity analysis. Expert Systems with Applications, 178, 114999.
• Gul, M. (2020), Application of Pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: the case of a gun and rifle barrel external surface oxidation and colouring unit. International journal of occupational safety and ergonomics.26(4), 705-718.
• Ittner, C., D. Larcher. (1997). The Performance Effects of Process Management Techniques. Management Science, 43(4), 522-534, 1997.
• Jaller, M., & Otay, I. (2020, July). Evaluating Sustainable Vehicle Technologies for Freight Transportation Using Spherical Fuzzy AHP and TOPSIS. In International Conference on Intelligent and Fuzzy Systems (pp. 118-126). Springer, Cham.
• Juran, J.M., B. Godfery, “Juran’s quality handbook”, Fifth Edition, McGraw- Hill, NY, 2000.
• Kieu, P. T., Nguyen, V. T., Nguyen, V. T., & Ho, T. P. (2021). A Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm in Distribution Center Location Selection: A Case Study in Agricultural Supply Chain. Axioms, 10(2), 53.
• Kurt, M., ve Dağdeviren M., (2003). İş Etüdü, Gazi Kitabevi, Ankara.
• Kutlu Gündoğdu, F. & Kahraman, C. (2019, July). Spherical fuzzy analytic hierarchy process (AHP) and its application to industrial robot selection. In International Conference on Intelligent and Fuzzy Systems (pp. 988-996). Springer, Cham.
• Kutlu Gündoğdu, F. K., & Kahraman, C. (2020). A novel spherical fuzzy analytic hierarchy process and its renewable energy application. Soft Computing, 24(6), 4607-4621.
• Mathew, M., Chakrabortty, R. K., & Ryan, M. J. (2020). A novel approach integrating AHP and TOPSIS under spherical fuzzy sets for advanced manufacturing system selection. Engineering Applications of Artificial Intelligence, 96, 103988. McNeese,W. and Marks, C. (2001), “The Power of Process Management ”, Annual Quality Congress, Charlotte , NC , Vol. 55 No.0, pp. 300- 309.
• Oktal, H., & Onrat, A. (2020). Analytic Hierarchy Process–Based Selection Method for Airline Pilot Candidates. The International Journal of Aerospace Psychology, 30(3-4), 268-281.
• Onar, S. C., & Ibil, E. H. (2021, August). A Decision Support System Proposition for Type-2 Diabetes Mellitus Treatment Using Spherical Fuzzy AHP Method. In International Conference on Intelligent and Fuzzy Systems (pp. 749-756). Springer, Cham. Oztaysi, B., Onar, S. C., & Kahraman, C. (2020). A dynamic pricing model for location based systems by using spherical fuzzy AHP scoring. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-10.
• Rezaiea, K., Ostadib, B., Tadayoun, S., & Aghdasi, M. (2009, October). Critical success factors (CSFs) for process management projects. In 2009 16th International Conference on Industrial Engineering and Engineering Management (pp. 100-103). IEEE.
• Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
• Şenol, M. B., Adem, A., & Dağdeviren, M. (2019). A Fuzzy MCDM Approach to Determine the Most Influential Logistic Factors. Politeknik Dergisi, 22(3), 793-800.
• Sharaf, I. M. (2021). Global Supplier Selection with Spherical Fuzzy Analytic Hierarchy Process. Decision Making with Spherical Fuzzy Sets (pp. 323-348). Springer, Cham.
• Singer, H., & Özşahin, Ş. (2021). Prioritization of laminate flooring selection criteria from experts’ perspectives: a spherical fuzzy AHP-based model. Architectural Engineering and Design Management, 1-16.
• Unal, Y., & Temur, G. T. (2020, July). Using Spherical Fuzzy AHP Based Approach for Prioritization of Criteria Affecting Sustainable Supplier Selection. In International Conference on Intelligent and Fuzzy Systems (pp. 160-168). Springer, Cham.
• Yucesan, M., & Gul, M. (2020). Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Computing, 24(5), 3237-3255.
• Zavareh, S. (2021). Key success factors in implementing process management and providing a framework for assessing organizational readiness, International Journal of Advanced Academic Studies 3(1): 362-368.