Clustering of Required Competences of the Employees Working in the Finance-Related Fields of Companies in the Era of Digitalization

Yıl 2021, Cilt: 16 Sayı: 62, 945 - 959, 30.04.2021

Mehmet Hakan Özdemir , Tolga Tuzcuoğlu

https://doi.org/10.19168/jyasar.814013

Cited By: 2

Öz

This study aims to provide a framework for the clustering of the required competences of the professionals that are working in the finance-related fields of business enterprises. Collecting data from 9 commercial departments of the Turkish subsidiary of an international company operating in a knowledge- and technology-intense sector, this paper employs cluster analysis to group the required employee competences that are sought in the data-driven business era. The findings suggest that out of the 27 diverse competences analyzed, the average silhouette width is the highest when the competences are divided into 11 different clusters leading to the conclusion that networking, future focus, coping, overview, assuming responsibility, customer oriented innovation, openness, result focus, establishing focus, managing performance and conceptual thinking are the most required skills that are sought in the finance-related areas of business firms.

Anahtar Kelimeler

Employee competence, digitalization, cluster analysis, silhouette width

Dijitalleşme Çağında Firmaların Finansla İlgili Alanlarında Çalışan Çalışanlarının Gerekli Yetkinliklerinin Kümelenmesi

Öz

Bu çalışma, ticari işletmelerin finans ilişkili alanlarında çalışan profesyonellerinin gerekli yetkinliklerinin kümelenmesi için bir çerçeve sağlamayı amaçlamaktadır. Veri odaklı işletmeler çağında aranan gerekli çalışan yetkinliklerini gruplandırmak amacıyla, bilgi ve teknoloji yoğun bir sektörde faaliyet gösteren uluslararası bir şirketin Türkiye’deki iştirakinin 9 ticari departmanından veri elde edilerek kümeleme analizi uygulanmıştır. Bulgular, analiz edilen 27 farklı yetkinliğin 11 farklı kümeye bölündüğünde ortalama silüet genişliğinin en yüksek olduğunu göstermektedir. Buna göre, ağ kurma, geleceğe odaklanma, başa çıkma, genel bakış, sorumluluk üstlenme, müşteri odaklı yenilikçilik, açıklık, sonuca odaklanma, odak oluşturma, performans yönetme ve kavramsal düşünmenin firmaların finansla ilgili iş alanlarında aranan en gerekli beceriler olduğu sonucu ortaya çıkmaktadır.

Anahtar Kelimeler

Çalışan yetkinliği, dijitalleşme, kümeleme analizi, silüet genişliği

Kaynakça

• Alias, Rosima, Mohd Hanapiah Ismail, and Nurhanis Sahiddan. 2015. “A Measurement Model for Leadership Skills Using Confirmatory Factor Analysis (CFA).” Contemporary Issues in Management and Social Science Research. 172 (January): 717–24.
• Alpar, Reha. 2013. Uygulamalı Çok Değişkenli İstatiksel Yöntemler, Detay Yayıncılık.
• Bohlouli, Mahdi, Nikolaos Mittas, George Kakarontzas, Theodosios Theodosiou, Lefteris Angelis, and Madjid Fathi. 2017. “Competence Assessment as an Expert System for Human Resource Management: A Mathematical Approach.” Expert Systems with Applications 70 (March): 83–102.
• Bratchell, Nicholas. 1989. Cluster analysis. Chemometrics and Intelligent Laboratory Systems 6(2):105–25.
• Cheng, and Chen. 2019. “An Exploration of Medical Education in Central and Southern China: Measuring the Professional Competence of Clinical Undergraduates.” International Journal of Environmental Research and Public Health 16 (October): 4119.
• Chursin, Alexander, and Andrey Tyulin. 2018. Competence Management and Competitive Product Development. Springer International Publishing AG.
• Cimiano, Philipp. 2006. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications, Springer.
• Cowan, David T., Dame Jenifer Wilson-Barnett, Ian J. Norman, and Trevor Murrells. 2008. “Measuring Nursing Competence: Development of a Self-Assessment Tool for General Nurses across Europe.” International Journal of Nursing Studies 45(6): 902–13.
• Doğan, Nuri, and T. Oğuz Başokçu. 2010. “İstatistik Tutum Ölçeği için uygulanan faktör analizi ve aşamalı kümeleme analizi sonuçlarının karşılaştırılması.” Eğitim ve Psikolojide Ölçme ve Değerlendirme Dergisi 1(2):65-71.
• Everitt, Brian S., Sabine Landau, Morven Leese, and Daniel Stahl. 2011. Cluster analysis 5th Edition, Wiley.
• Karnouskos, Stamatis. 2017. “Massive Open Online Courses (MOOCs) as an Enabler for Competent Employees and Innovation in Industry.” Computers in Industry 91 (October): 1–10.
• Kassambara, Alboukadel. 2017. Practical guide to cluster analysis in R: Unsupervised machine learning (Edition 1). Sthda.
• Ko, Wen-Hwa. 2015. “Constructing a Professional Competence Scale for Foodservice Research & Development Employees from an Industry Viewpoint.” International Journal of Hospitality Management 49 (August): 66–72.
• Lee, Youngjin, and GyeongAe Seomun. 2016. “Development and Validation of an Instrument to Measure Nurses’ Compassion Competence.” Applied Nursing Research 30 (May): 76–82.
• Legner, Christine, Torsten Eymann, Thomas Hess, Christian Matt, Tilo Böhmann, Paul Drews, Alexander Maedche, Nils Urbach, and Frederik Ahlemann. 2017. “Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community.” Business & Information Systems Engineering 59 (July): 301–8.
• Lin, Chi-Chang, and Chia-Hsun Chang. 2018. “Evaluating Skill Requirement for Logistics Operation Practitioners: Based on the Perceptions of Logistics Service Providers and Academics in Taiwan.” The Asian Journal of Shipping and Logistics 34(4): 328–36.
• Moldovan, Liviu. 2020. “A Tool for Continuous Evaluation of Competences and Approaches to Employment Support.” 13th International Conference Interdisciplinarity in Engineering, INTER-ENG 2019, 3–4 October 2019, Targu Mures, Romania 46 (January): 263–70.
• Romesburg, H. Charles. 1984. Cluster Analysis for Researchers. Lifetime Learning Publications.
• Tryfos, Peter. 1998. “Chapter 15: Cluster Analysis” in Methods for Business Analysis and Forecasting: Text & Cases, Wiley. Accessed September 23, 2020, http://www.yorku.ca/ptryfos/methods.htm
• Velldal, Erik. 2012. “INF4820, Algorithms for AI and NLP: Hierarchical Clustering.” Accessed September 8, 2020. https://www.uio.no/studier/emner/matnat/ifi/nedlagte-emner/INF4820/h12/undervisningsmateriale/06_clustering.pdf
• Urbach, Nils, and Maximilian Röglinger, eds. 2019. Digitalization Cases, Management for Professionals. Springer International Publishing AG.
• Ward Jr, Joe H. 1963. “Hierarchical grouping to optimize an objective function.” Journal of the American Statistical Association 58(301):236-44.
• Wierzchoń, Sławomir T., and Mieczysław A. Kłopotek. 2018. Modern Algorithms of Cluster Analysis. Springer International Publishing AG.
• Yim, Odilia, and Kylee T. Ramdeen. 2015. “Hierarchical cluster analysis: comparison of three linkage measures and application to psychological data.” The quantitative methods for psychology 11(1):8-21.