Demir-Çelik Üretim Şirketlerinin İnsan Kaynakları Departmanlarına Endüstri 4.0’ın Etkisinin İncelenmesi için Bir Karar Modeli

Yıl 2022, , 1127 - 1142, 30.12.2022

Tuğba Öz Yusuf Kuvvetli

https://doi.org/10.21605/cukurovaumfd.1230960

Öz

Bu çalışmanın temel amacı, demir-çelik sektöründeki insan kaynakları süreçlerinin Endüstri 4.0’a geçişten nasıl etkileneceğinin belirlenmesi için bir karar modelinin ortaya konulmasıdır. Buna göre, bir anket çalışması ile veriler elde edilmiş ve hipotezler için ki-kare testi ile analiz gerçekleştirmiştir. Sonrasında, Shannon'ın Entropi yöntemi ile geçiş sürecindeki en kritik problemler ağırlıklandırılmış ve geçiş problemleri için en uygun çözümler TOPSIS yöntemi ile sıralanmıştır. En ağırlıklı geçiş sorunları olarak, artan işçilik maliyetleri ve sürekli değişen teknolojiler ortaya çıkarken, çalışanların yeni teknolojilere uyum sağlamaları ve gerekli becerileri kazanmaları için eğitimlerle desteklenmeleri Endüstri 4.0’a geçiş sorunları için en önemli çözümler olarak değerlendirilmiştir. Böylece, karar vericilere geçiş süreci için bir yol haritası sunulmuştur.

Anahtar Kelimeler

Endüstri 4.0, İnsan kaynakları yönetimi, Demir çelik üretimi, Entropi yöntemi, TOPSIS yöntemi

A Decision Model for Examining the Impact of Industry 4.0 on the Human Resources Departments of Iron-Steel Production Companies

Öz

The main aim of this study is to present a decision model to determine how the human resources processes in the iron-steel industry will be affected by the transition to Industry 4.0. Accordingly, data were obtained through a survey and analysis was carried out with the chi-square test for the hypotheses. Then, the most critical problems in the transition process are weighted with Shannon's Entropy method and the most suitable solutions for the transition problems are listed with the TOPSIS method. While increasing labor costs and constantly changing technologies are emerging as the weightiest transition problems, supporting the employees with trainings to adapt to new technologies and gain the necessary skills has been evaluated as the most important solutions for the problems of transition to Industry 4.0. Thus, a roadmap for the transition process was presented to decision makers.

Anahtar Kelimeler

Transition to industry 4.0, Human resources management, Iron and steel production, Entropy method; TOPSIS method.

Kaynakça

• ⦁ Allen, R.C., 2009. The British Industrial Revolution in Global Perspective. Cambridge University Press, Cambridge, 331.
• ⦁ Mokyr, J., Strotz, R.H., 1998. The Second Industrial Revolution, 1870-1914. Storia Dell'ekonomia Mondiale, 1-16.
• ⦁ Kinghorn, J.R., Nye, J.V., 1996. The Scale of Production in Western Economic Development: A Comparison of Official Industry Statistics in the United States, Britain, France, and Germany, 1905–1913, The Journal of Economic History, 56(1), 90-112.
• ⦁ Scranton, P., 2000. Endless Novelty: Specialty Production and American Industrialization, 1865-1925. Princeton University Press, Princeton.
• ⦁ Rifkin, J., 2012. The Third Industrial Revolution: How the Internet, Green Electricity, and 3-D Printing are Ushering in a Sustainable Era of Distributed Capitalism. World Financial Review, 1(1), 4052-4057.
• ⦁ Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., Harnisch, M., 2015. Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries. Boston Consulting Group, 9(1), 54-89.
• ⦁ Collings, D.G., Wood, G.T., Szamosi L.T., 2018. Human Resource Management: A Critical Approach, in Human Resource Management. Routledge, New York, 1-23.
• ⦁ Schramm, J., 2006. HR Technology Competencies. SHRM Research Quarterly, 1, 1-11.
• ⦁ Cerika, A., Maksumic S., 2017. The Effects of New Emerging Technologies on Human Resources: Emergence of Industry 4.0, a Necessary Evil?. Yüksek Lisans Tezi, University of Agder, Kristiansand.
• ⦁ Ermolaeva, A., 2017. Industry 4.0 and HR in Logistics. Yüksek Lisans Tezi, University Of Economics In Prague, International Business – Central European Business Realities, Prag.
• ⦁ Pessl, E., Sorko, S.R., Mayer, B., 2017. Roadmap Industry 4.0–Implementation Guideline for Enterprises, International Journal of Science, Technology and Society, 5(6), 193-202.
• ⦁ Bonekamp, L., Sure, M., 2015. Consequences of Industry 4.0 on Human Labour and Work Organisation, Journal of Business and Media Psychology, 6(1), 33-40.
• ⦁ Hecklau, F., Galeitzke, M., Flachs, S., Kohl, H., 2016. Holistic Approach for Human Resource Management in Industry 4.0, Procedia Cirp, 54(1), 1-6.
• ⦁ Benešová, A., Tupa, J., 2017. Requirements for Rducation and Qualification of People in Industry 4.0, Procedia Manufacturing, 11, 2195-2202.
• ⦁ Mamoudou, S., Joshi, G., 2014. Impact of Information Technology in Human Resources Management, Global Journal of Business Management and Information Technology, 4(1), 33-41.
• ⦁ Yusoff, Y.M., Ramayah, T., Ibrahim, H., 2010. E-HRM: A Proposed Model Based on Technology Acceptance Model, African Journal of Business Management, 4(14), 3039.
• ⦁ Sivathanu, B., Pillai, R., 2018. Smart HR 4.0– How Industry 4.0 is Disrupting HR, Human Resource Management International Digest, 26(4), 7-11.
• ⦁ Sevinc, A., Gür, Ş., Eren, T., 2018. Analysis of the Difficulties of SMEs in Industry 4.0 Applications by Analytical Hierarchy Process and Analytical Network Process, Processes, 6(12), 264.
• ⦁ Moktadir, M.A., Ali, S.M., Kusi-Sarpong, S., Shaikh, M.A.A., 2018. Assessing Challenges for Implementing Industry 4.0: Implications for Process Safety and Environmental Protection. Process Safety and Environmental Protection, 117, 730-741.
• ⦁ Huang, C.J., Talla Chicoma E.D., Huang Y.H., 2019. Evaluating the Factors that are Affecting the Implementation of Industry 4.0 Technologies in Manufacturing MSMEs, the Case of Peru, Processes, 7(3), 161.
• ⦁ Erdogan, M., Ozkan, B., Karasan, A., Kaya, I., 2018. Selecting the Best Strategy for Industry 4.0 Applications with a Case Study. Industrial Engineering in the Industry 4.0 Era. Springer, 109-119.
• ⦁ Shaverdi, M., Heshmati, M.R., Ramezani, I., 2014. Application of Fuzzy AHP Approach for Financial Performance Evaluation of Iranian Petrochemical Sector. Procedia Computer Science, 31, 995-1004.
• ⦁ Kusumawardani, R.P., Agintiara M., 2015. Application of Fuzzy AHP-TOPSIS Method for Decision Making in Human Resource Manager Selection Process. Procedia Computer Science, 72, 638-646.
• ⦁ Türkiye Çelik Üreticileri Derneği, Demir Çelik Sektörü, http://celik.org.tr/category/teknik- konular/. Erişim Tarihi: 01.07.2019.
• ⦁ Lotfi, F.H., Fallahnejad, R., 2010. Imprecise Shannon’s Entropy and Multi Attribute Decision Making. Entropy, 12(1), 53-62.
• ⦁ Triantaphyllou, E., 2000. Multi-criteria Decision Making Methods. Multi-criteria Decision Making Methods: A Comparative Study, Springer, 5-21.
• ⦁ Madsen, E.S., Bilberg, A., Hansen, D.G., 2016. Industry 4.0 and Digitalization Call for Vocational Skills, Applied Industrial Engineering, and Less for Pure Academics. 5th P&OM World Conference, Production and Operations Management, P&OM. 2-10.
• ⦁ Tsaramirsis, G., Kantaros, A., Al-Darraji, I., Piromalis, D., Apostolopoulos, C., Pavlopoulou, A., Alrammal, M., Ismail, Z., Buhari, S.M., Stojmenovic, M., Tamimi, H., Randhawa, P., Patel, A., Khan, F.Q., 2022. A Modern Approach Towards an Industry 4.0 Model: From Driving Technologies to Management. Journal of Sensors, 5023011, 1-18.
• ⦁ Ghobakhloo, M., Iranmanesh, M., 2021. Digital Transformation Success Under Industry 4.0: A Strategic Guideline for Manufacturing SMEs. Journal of Manufacturing Technology Management, 32(8), 1533-1556.