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KOBİ YÖNETİCİLERİNİN ENDÜSTRİ 4.0 SÜRECİNE YÖNELİK BAKIŞ AÇILARINDAKİ DEĞİŞİMİNİN VE DİJİTAL DÖNÜŞÜMDEKİ FIRSATLARIN SWARA YÖNTEMİYLE DEĞERLENDİRİLMESİ

Year 2024, Issue: 67, 45 - 53, 30.04.2024

Damla Çevik Aka

https://doi.org/10.18070/erciyesiibd.1276967

Abstract

Çalışmanın amacı, Türkiye’deki KOBİ’lerin Endüstri 4.0 ile gelen dijital dönüşüme yönelik bakış açılarının tespit edilmesi ve sahip oldukları bilgilerin potansiyel gelişiminin ve yöneliminin belirlenmesidir. Çalışma beş yıl önce yarı yapılandırılmış mülakat ile otuz iki KOBİ yöneticisine yöneltilen soruların tekrar aynı bireylere yöneltilmesi yoluyla gerçekleşmiştir. Bu uygulama sonuçlarına göre yöneticilerin 2017 yılındaki verdikleri cevaplara nazaran endüstri 4.0 sürecine daha fazla hakim oldukları ve ilgili teknolojiler hakkında daha fazla bilgi sahibi oldukları görülürken, bu alandaki etkinliklerde de daha fazla yer almaya başlamıştır. Beş yıllık dönem içinde yöneticilerin en fazla endişe duyduğu alan siber güvenlik ve bütçe planlaması olarak belirlenmiştir. Diğer taraftan çalışmanın ikinci uygulamasında; Endüstri 4.0 dönüşüm sürecinin KOBİ’ler üzerinde sebep olacağı öngörülen bir takım fırsatların uzmanlar tarafından önem düzeylerinin belirlenmesi de amaçlanmıştır. Bu amacı gerçekleştirmek üzere beş uzmanla SWARA uygulaması yapılmış olup, en yüksek önem seviyesine sahip ilk üç fırsat düşük maliyetli üretim, rekabet gücü ve üretim hatalarında iyileştirme olarak belirlenmiştir.

Keywords

Dijital Dönüşüm KOBİ’lerde Endüstri 4.0 Avantajları KOBİ’lerde Endüstri 4.0 Fırsatlar SWARA

References

  • Ancillo, A. D., Gavrilla, S. G., Diez, J. R. F. D., & Beseler, J. C. (2021). LATAM and Spanish SME barriers to Industry 4.0. Academia Revista Latinoamericana de Administración. 35(2), 204-222.
  • Asif, M., Searcy, C., & Castka, P. (2022). Exploring the role of industry 4.0 in enhancing supplier audit authenticity, efficacy, and cost effectiveness. Journal of Cleaner Production, 331, 129939.
  • Bouraima, M. B., Qiu, Y., Stević, Ž., & Simić, V. (2023). Assessment of alternative railway systems for sustainable transportation using an integrated IRN SWARA and IRN CoCoSo model. Socio-Economic Planning Sciences, 86, 101475.
  • Cevik, D. (2018). Üç boyutlu yazıcı teknolojisinin seri ve kesikli üretim sistemleri üzerine etkisi. Yüksek Lisans Tezi, Sakarya Üniversitesi İşletme Enstitüsü, Sakarya, 502650. Cevik, D. (2019). KOBİ’lerde Sanayi 4.0’ın uygulanabilirliği ve yönetici bakış açılarının değerlendirilmesi. Uluslararası Bilimsel Araştırmalar Dergisi, 4(2), 277-291.
  • Cheng, F. T., Lee, C. Y., Hung, M. H., Mönch, L., Morrison, J. R., & Liu, K. (2022). Special issue on automation analytics beyond Industry 4.0: From hybrid strategy to zero-defect manufacturing. IEEE Transactions on Automation Science and Engineering, 19(3), 1472-1476.
  • Colotla, I., Fæste A., Heidmann, A., Winther, A., Høngaard Andersen, P., Duvold, T., & Hansen, M. (2016). Winning the Industry 4.0 race—How ready are danish manufacturers? BCG & Innovationsfonden.
  • Cui, Y., Liu, W., Rani, P., & Alrasheedi, M. (2021). Internet of Things (IoT) adoption barriers for the circular economy using Pythagorean Fuzzy SWARA-CoCoSo decision-making approach in the manufacturing sector. Technological Forecasting and Social Change, 171, 120951.
  • Dorst, W., Glohr, C., Hahn, T., Knafla, F., Loewen, U., Rosen, R., & Winterhalter, C. (2015). Umsetzungsstrategie Industrie 4.0–Ergebnisbericht der plattform Industrie 4.0. BITKOM eV, VDMA eV, ZVEI eV Berlin, Frankfurt.
  • Erdogan, H., Tutcu, B., Talas, H., & Terzioglu, M. (2022). Performance analysis in renewable energy companies: Application of SWARA and WASPAS methods. Journal of Sustainable Finance & Investment, 1-22.
  • Erol, S., Jaeger, A., Hold, P., Ott, K., & Sihn, W. (2016). Tangible Industry 4.0: A scenario-based approach to learning for the future of production. Procedia Cirp 54, 13–18. https://doi.org/10.1016/j.procir.2016.03.162.
  • Gezmisoglu, G., Unlu, A., & Cagil, G. (2023). Supplier evaluation with factor analysis based hybrid SWARA-VIKOR methods. Journal of the Faculty og Engineering and Architecture of Gazi University, 38(4), 2231-2239.
  • Ghasemi, P., Mehdiabadi, A., Spulbar, C., & Birau, R. (2021). Ranking of sustainable medical tourism destinations in Iran: An integrated approach using Fuzzy SWARA-PROMETHEE. Sustainability, 13(2), 683.
  • Ghorshi Nezhad, M. R., Zolfani, S. H., Moztarzadeh, F., Zavadskas, E. K., & Bahrami, M. (2015). Planning the priority of high tech industries based on SWARA-WASPAS methodology: The case of the nanotechnology industry in Iran. Ekonomska istraživanja, 28(1), 1111-1137.
  • Ghoushchi, S. J., Gharibi, K., Osgooei, E., Ab Rahman, M. N., & Khazaeili, M. (2021). Risk prioritization in failure mode and effects analysis with extended SWARA and MOORA methods based on Z-numbers theory. Informatica, 32(1), 41-67.
  • Ghoushchi, S. J., Bonab, S.R., Ghiaci, A. M., Haseli, G., Tomaskova, H., & Hajiaghaei-Keshteli, M. (2022). Landfill site selection for medical waste using an integrated SWARA-WASPAS framework based on spherical fuzzy set. Sustainability, 13 (24).
  • Guler, E., Avci, S., & Aladag, Z. (2023). Earthquake risk prioritization via two-step cluster analysis and SWARA-ELECTRE methods. Sigma, 41(2), 356-372.
  • Han, H., & Trimi, S. (2022). Towards a data science platform for improving SME collaboration through Industry 4.0 technologies. Technological Forecasting & Social Change, 174.
  • Hashemkhani Zolfani, S., Gorcun, O. F., & Kucukonder, H. (2021). Evaluating logistics villages in Turkey using hybrid Improved Fuzzy SWARA (IMF SWARA) and Fuzzy MABAC techniques. Technological and Economic Development of Economy, 27(6).
  • Herrero, A. C., Sanguesa, J. A., Martinez, F. J., Garrido, P., & Calafate, C. T. (2021). Mitigating electromagnetic noise when using low-cost devices in Industry 4.0. IEEE Access, 9, 63267-63282.
  • Hu, Y., Al-Barakati, A., & Rani, P. (2022). Investigating the internet-of-things (IOT) risks for supply chain management using q-rung orthopair fuzzy-SWARA-ARAS framework. Technological and Economic Development of Economy, 1-26.
  • Jepsen, S. C., Worm, T., Johansen, A., Lazarova-Molnar, S., Kjærgaard, M. B., Kang, E. Y., ... & Schwee, J. H. (2021, September). A research setup demonstrating flexible Industry 4.0 production. In 2021 International Symposium ELMAR (pp. 143-150). IEEE.
  • Johnson, V. C., Bali, J. S., Kolanur, C. B., & Tanwashi, S. (2022). Industry 4.0: Intelligent quality control and surface defect detection. 3c Empresa: investigación y Pensamiento Crítico, 11(2), 214-220.
  • Koca, G., Egilmez, O., Demir, E., Karamasa, Ç., & Gokcan, H. (2022). Analysis of drivers and challenges in circular economy with SWARA and BWM methods in clothing sector. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, 9(2).
  • Karamollaoglu, H., Yucedag, I., & Dogru, I. A. (2022). Risk assessment for electricity generation management process with SWARA based Fuzzy TOPSIS Method. Journal of Polytechnoc, ISSN: 2147-9429.
  • Kazantsez, N., Pishchulov Grzgory., Mehandjiev, N., Sampaio, P., & Zolkiewski, J. (2022). Investigating barriers to demand-driven SME collaboration in low-volume high-variability manufacturing. Supply Chain Management-An International Journal. 27(2), 265-282.
  • Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new Step-Wise Weight Assessment Ratio Analysis (SWARA). Journal of Business Economics and Management, 11(2), 243– 258.
  • Khalili, J., & Alinezhad, A. (2021). Performance evaluation in aggregate production planning using integrated RED-SWARA method under uncertain condition. Scientia Iranica, 28(2), 912-926.
  • Koren Y. (2010). The global manufacturing revolution: Product-process-business integration and reconfigurable systems, John Wiley & Sons, New York, USA, ISBN 0470583770.
  • Korucuk, S., Aytekin, A., Ecer, F., Karamasa, Ç., & Zavadskas, E. K. (2022). Assessing green approaches and digital marketing strategies for twin transition via fermatean Fuzzy SWARA-COPRAS. Axioms, 11(12), 709.
  • Kurnaz, S., Özdağoğlu, A., & Keleş, M. K. (2023). Method of evaluation of military helicopter pilot selection criteria: A novel Grey SWARA approach. Aviation, 27(1), 27-35.
  • Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. business and information systems engineering. Business & Information Systems Engineering, 6(4), 239-242.
  • May, G., & Kiritsis, D. (2019). Zero defect manufacturing strategies and platform for smart factories of Industry 4.0. In Proceedings of the 4th International Conference on the Industry 4.0 Model for Advanced Manufacturing: AMP 2019 4 (pp. 142-152). Springer International Publishing.
  • Mahdiraji, H. A., Zavadskas, E. K., Arab, A., Turskis, Z., & Sahebi, I. G. (2021). Formulation of manufacturing strategies based on an extended SWARA method with intuitionisic fuzzy numbers: An automotive industry application. Transformations in Business and Economics, 20(2).
  • Milošević, I., Arsić, S., Glogovac, M., Rakić, A., & Ruso, J. (2022). Industry 4.0: Limitation or benefit for success?. Serbian Journal of Management, 17(1), 85-98.
  • Mittal, S., Ahman Khan, M., Romero, D., & Wuest,T. (2018). A critical review of smart manufacturing & Industry 4.0 maturity models: Implications for Small and Medium-Sized Enterprises (SMEs). Journal of Manufacturing Systems. 49, pp.194-214.
  • Müller, J. M., Buliga, O., & Voigt, K. (2018). Fortune favors the prepared: how SMEs approach business model innovations in Industry 4.0. Technol. Forecast. Soc. Chang. 132, 2–17.
  • Moeuf, A., Pellerin, R., Lamouri, S., Tamayo-giraldo, S., & Barbaray, R. (2017). The industrial management of SMEs in the era of Industry 4.0. Int. J. Prod. Res. 56, 1118–1136.
  • Oliff, H., & Liu, Y. (2017). Towards Industry 4.0 utilizing data-mining techniques: a case study on quality improvement. Paper presented at the CIRP Conference on Manufacturing Systems. Elsevier B.V.167–172.
  • Posada, J., Toro, C., Barandiaran, I., Oyarzun, D., Stricker, D., de Amicis, R.,& Vallarino, I. (2015). Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE Computer Graphics and Applications, 35(2), 26-40.
  • Puška, A., Štilić, A., & Stević, Ž. (2023). A comprehensive decision framework for selecting distribution center locations: A hybrid improved fuzzy SWARA and fuzzy CRADIS approach. Computation, 11(4), 73.
  • Rauch, E., Dallasega, P., & Matt, D. T. (2017). Critical factors for introducing lean product development to small and medium sized enterprises in Italy. Procedia CIRP, 60, 362–367.
  • Rehman, S., Rehman, N., Naz, M., Mumtaz, A., & Jianglin, Z. (2021). Application of grey-based SWARA and COPRAS techniques in disease mortality risk assessment. Journal of Healthcare Engineering.
  • Ruzgys, A., Volvačiovas, R., Ignatavičius, Č., & Turskis, Z. (2014). Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method. Journal of Civil Engineering and Management, 20(1), 103-110.
  • Safar, L., Sopko, J., Bednar, S., & Poklemba, R. (2018). Concept of SME business model for Industry 4.0 environment. TEM Journal, 7(3), 626-637.
  • Sanders, A., Elangeswaran, C., & Wulfsberg, J. (2016). Industry 4.0 implies lean manufacturing: Research activities in Industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management, 9(3), 811-833.
  • Schröder, C. (2017). The Challenges of Industry 4.0 for small and medium-sized enterprises; Friedrich-Ebert-Stiftung: Bonn, Germany.
  • Sharma, H., Sohani, N., & Yadav, A. (2023). A fuzzy SWARA-WASPAS based approach for determining the role of lean practices in enabling the supply chain agility. International Journal of System Assurance Engineering and Management, 14(Suppl 1), 492-511.
  • Sitton, I., & Rodríguez, S. (2017). Pattern extraction for the design of predictive models in Industry 4.0. International Conference on Practical Applications of Agents and Multi-Agent Systems, 258–261.
  • Sivageerthi, T., Bathrinath, S., Uthayakumar, M., & Bhalaji, R. K. A. (2022). A SWARA method to analyze the risks in coal supply chain management. Materials Today-Proceedings, 5, 935-940.
  • Stanujkic, D., Karabasevic, D., & Zavadskas, E. K. (2015). A framework for the selection of a packaging design based on the SWARA method. Engineering Economics, 26(2), 181-187.
  • Stentoft ,J., Wickstrøm, K. A., Philipsen, K., & Haug, A. (2021). Drivers and barriers for Industry 4.0 readiness and practice: empirical evidence from small and medium-sized manufacturers. Production Planning & Control, 32(109), 811-828, doi: 10.1080/09537287.2020.1768318.
  • Soltysova, Z., & Bednar, S. (2015). Complexity management in terms of mass customized manufacturing. Polish Journal of Management Studies, 12(2), 139-149.
  • Somohano-Rodríguez, F. M., & Madrid-Guijarro, A. (2022). Do Industry 4.0 technologies improve Cantabrian manufacturing SMEs performance? The role played by industry competition. Technology in Society, 70, 102019.
  • Tas, M. A., Cakir, E., & Ulukan, Z. (2021). Spherical fuzzy SWARA-MARCOS approach for green supplier selection. 3C Tecnología, Technology as an enabler in business, management, environmental, and social science, Edición Especial, 115-133. https://doi.org/10.17993/3ctecno.2021.specialissue7.115-133
  • Tortorella, L. G., & Fettermann, D. (2018). Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. Int. J. Prod. Res. 56, 2975–2987.
  • Turkes, M. C., Oncioiu, I., Aslam, H. D., Marin-Pantelescu, A., Topor, D. I., & Căpusneanu, S. (2019). Drivers and barriers in using Industry 4.0: A perspective of SMEs in Romania. Processes, 7(3), 153. doi:10.3390/pr7030153.
  • Tus A., & Adali, E.A. (2022). Green supplier selection based on the combination of Fuzzy SWARA (SWARA-F) and Fuzzy MARCOS (MARCOS-F) Methods. Gazi University Journal of Science, 35(4), 1535-1554.
  • Tvaronaviciene, M., & Burinskas, A. (2020). Industry 4.0 significance to competition and the EU competition policy: a literature review. Economics & Sociology, 13(3), 244-258.
  • Ulutas, A., Meidute-Kavaliauskiene, I., Topal, A., & Demir, E. (2022). Assessment of collaboration-based and non-collaboration-based logistics risks with plithogenic SWARA Method. Logistic, 5(4), 82.
  • Valdeza, A. C., Braunera, P., Schaara, A. K., Holzingerb, A., & Zieflea, M. (2015). Reducing complexity with simplicity-usability methods for Industry 4.0. Paper presented at Proceedings 19th Triennial Congress of the IEA, 9(14).
  • Vuković, M., Jorg, O., Hosseinifard, M., & Fantoni, G. (2022). Low-Cost digitalization solution through scalable IIoT prototypes. Applied Sciences, 12(17), 8571.
  • Yalcin, M.F. (2018). Industry 4.0, Turning point in the global competition in terms of Turkey. Sosyoekonomi Journal, 26 (36).

EVALUATION OF THE CHANGE IN PERSPECTIVES OF SME EXECUTIVES TOWARDS THE INDUSTRY 4.0 PROCESS AND OPPORTUNITIES IN DIGITAL TRANSFORMATION WITH THE SWARA METHOD

Year 2024, Issue: 67, 45 - 53, 30.04.2024

Damla Çevik Aka

https://doi.org/10.18070/erciyesiibd.1276967

Abstract

The aim of this study is to determine the perspectives of small and medium-sized enterprises (SMEs) in Turkey towards the digital transformation that comes with Industry 4.0 and to determine the potential development and orientation of the information they had. In this study, the questions asked to thirty-two SME executives five years ago with a semi-structured interview were again directed to the same individuals. According to the results, it’s been seen that the executives have more knowledge of the Industry 4.0 process and have more information about the relevant technologies compared to the answers in 2017. In addition, executives have started to take more part in activities in this field. During the five-year period, the most concerned issue of executives was identified as cyber security and budget planning. In the second application of the study, it’s also aimed to determine the importance levels of some opportunities that are predicted to be caused by the Industry 4.0 transformation process on SMEs. In order to realize this aim, Step-Wise Weight Assessment Ratio Analysis (SWARA) application was made with five experts, and the first three opportunities with the highest level of importance were determined as low-cost production, competitiveness and improvement in production defects.

Keywords

Digital Transformation Industry 4.0 advantages in SMEs Industry 4.0 in SMEs Opportunities SWARA

References

  • Ancillo, A. D., Gavrilla, S. G., Diez, J. R. F. D., & Beseler, J. C. (2021). LATAM and Spanish SME barriers to Industry 4.0. Academia Revista Latinoamericana de Administración. 35(2), 204-222.
  • Asif, M., Searcy, C., & Castka, P. (2022). Exploring the role of industry 4.0 in enhancing supplier audit authenticity, efficacy, and cost effectiveness. Journal of Cleaner Production, 331, 129939.
  • Bouraima, M. B., Qiu, Y., Stević, Ž., & Simić, V. (2023). Assessment of alternative railway systems for sustainable transportation using an integrated IRN SWARA and IRN CoCoSo model. Socio-Economic Planning Sciences, 86, 101475.
  • Cevik, D. (2018). Üç boyutlu yazıcı teknolojisinin seri ve kesikli üretim sistemleri üzerine etkisi. Yüksek Lisans Tezi, Sakarya Üniversitesi İşletme Enstitüsü, Sakarya, 502650. Cevik, D. (2019). KOBİ’lerde Sanayi 4.0’ın uygulanabilirliği ve yönetici bakış açılarının değerlendirilmesi. Uluslararası Bilimsel Araştırmalar Dergisi, 4(2), 277-291.
  • Cheng, F. T., Lee, C. Y., Hung, M. H., Mönch, L., Morrison, J. R., & Liu, K. (2022). Special issue on automation analytics beyond Industry 4.0: From hybrid strategy to zero-defect manufacturing. IEEE Transactions on Automation Science and Engineering, 19(3), 1472-1476.
  • Colotla, I., Fæste A., Heidmann, A., Winther, A., Høngaard Andersen, P., Duvold, T., & Hansen, M. (2016). Winning the Industry 4.0 race—How ready are danish manufacturers? BCG & Innovationsfonden.
  • Cui, Y., Liu, W., Rani, P., & Alrasheedi, M. (2021). Internet of Things (IoT) adoption barriers for the circular economy using Pythagorean Fuzzy SWARA-CoCoSo decision-making approach in the manufacturing sector. Technological Forecasting and Social Change, 171, 120951.
  • Dorst, W., Glohr, C., Hahn, T., Knafla, F., Loewen, U., Rosen, R., & Winterhalter, C. (2015). Umsetzungsstrategie Industrie 4.0–Ergebnisbericht der plattform Industrie 4.0. BITKOM eV, VDMA eV, ZVEI eV Berlin, Frankfurt.
  • Erdogan, H., Tutcu, B., Talas, H., & Terzioglu, M. (2022). Performance analysis in renewable energy companies: Application of SWARA and WASPAS methods. Journal of Sustainable Finance & Investment, 1-22.
  • Erol, S., Jaeger, A., Hold, P., Ott, K., & Sihn, W. (2016). Tangible Industry 4.0: A scenario-based approach to learning for the future of production. Procedia Cirp 54, 13–18. https://doi.org/10.1016/j.procir.2016.03.162.
  • Gezmisoglu, G., Unlu, A., & Cagil, G. (2023). Supplier evaluation with factor analysis based hybrid SWARA-VIKOR methods. Journal of the Faculty og Engineering and Architecture of Gazi University, 38(4), 2231-2239.
  • Ghasemi, P., Mehdiabadi, A., Spulbar, C., & Birau, R. (2021). Ranking of sustainable medical tourism destinations in Iran: An integrated approach using Fuzzy SWARA-PROMETHEE. Sustainability, 13(2), 683.
  • Ghorshi Nezhad, M. R., Zolfani, S. H., Moztarzadeh, F., Zavadskas, E. K., & Bahrami, M. (2015). Planning the priority of high tech industries based on SWARA-WASPAS methodology: The case of the nanotechnology industry in Iran. Ekonomska istraživanja, 28(1), 1111-1137.
  • Ghoushchi, S. J., Gharibi, K., Osgooei, E., Ab Rahman, M. N., & Khazaeili, M. (2021). Risk prioritization in failure mode and effects analysis with extended SWARA and MOORA methods based on Z-numbers theory. Informatica, 32(1), 41-67.
  • Ghoushchi, S. J., Bonab, S.R., Ghiaci, A. M., Haseli, G., Tomaskova, H., & Hajiaghaei-Keshteli, M. (2022). Landfill site selection for medical waste using an integrated SWARA-WASPAS framework based on spherical fuzzy set. Sustainability, 13 (24).
  • Guler, E., Avci, S., & Aladag, Z. (2023). Earthquake risk prioritization via two-step cluster analysis and SWARA-ELECTRE methods. Sigma, 41(2), 356-372.
  • Han, H., & Trimi, S. (2022). Towards a data science platform for improving SME collaboration through Industry 4.0 technologies. Technological Forecasting & Social Change, 174.
  • Hashemkhani Zolfani, S., Gorcun, O. F., & Kucukonder, H. (2021). Evaluating logistics villages in Turkey using hybrid Improved Fuzzy SWARA (IMF SWARA) and Fuzzy MABAC techniques. Technological and Economic Development of Economy, 27(6).
  • Herrero, A. C., Sanguesa, J. A., Martinez, F. J., Garrido, P., & Calafate, C. T. (2021). Mitigating electromagnetic noise when using low-cost devices in Industry 4.0. IEEE Access, 9, 63267-63282.
  • Hu, Y., Al-Barakati, A., & Rani, P. (2022). Investigating the internet-of-things (IOT) risks for supply chain management using q-rung orthopair fuzzy-SWARA-ARAS framework. Technological and Economic Development of Economy, 1-26.
  • Jepsen, S. C., Worm, T., Johansen, A., Lazarova-Molnar, S., Kjærgaard, M. B., Kang, E. Y., ... & Schwee, J. H. (2021, September). A research setup demonstrating flexible Industry 4.0 production. In 2021 International Symposium ELMAR (pp. 143-150). IEEE.
  • Johnson, V. C., Bali, J. S., Kolanur, C. B., & Tanwashi, S. (2022). Industry 4.0: Intelligent quality control and surface defect detection. 3c Empresa: investigación y Pensamiento Crítico, 11(2), 214-220.
  • Koca, G., Egilmez, O., Demir, E., Karamasa, Ç., & Gokcan, H. (2022). Analysis of drivers and challenges in circular economy with SWARA and BWM methods in clothing sector. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, 9(2).
  • Karamollaoglu, H., Yucedag, I., & Dogru, I. A. (2022). Risk assessment for electricity generation management process with SWARA based Fuzzy TOPSIS Method. Journal of Polytechnoc, ISSN: 2147-9429.
  • Kazantsez, N., Pishchulov Grzgory., Mehandjiev, N., Sampaio, P., & Zolkiewski, J. (2022). Investigating barriers to demand-driven SME collaboration in low-volume high-variability manufacturing. Supply Chain Management-An International Journal. 27(2), 265-282.
  • Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new Step-Wise Weight Assessment Ratio Analysis (SWARA). Journal of Business Economics and Management, 11(2), 243– 258.
  • Khalili, J., & Alinezhad, A. (2021). Performance evaluation in aggregate production planning using integrated RED-SWARA method under uncertain condition. Scientia Iranica, 28(2), 912-926.
  • Koren Y. (2010). The global manufacturing revolution: Product-process-business integration and reconfigurable systems, John Wiley & Sons, New York, USA, ISBN 0470583770.
  • Korucuk, S., Aytekin, A., Ecer, F., Karamasa, Ç., & Zavadskas, E. K. (2022). Assessing green approaches and digital marketing strategies for twin transition via fermatean Fuzzy SWARA-COPRAS. Axioms, 11(12), 709.
  • Kurnaz, S., Özdağoğlu, A., & Keleş, M. K. (2023). Method of evaluation of military helicopter pilot selection criteria: A novel Grey SWARA approach. Aviation, 27(1), 27-35.
  • Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. business and information systems engineering. Business & Information Systems Engineering, 6(4), 239-242.
  • May, G., & Kiritsis, D. (2019). Zero defect manufacturing strategies and platform for smart factories of Industry 4.0. In Proceedings of the 4th International Conference on the Industry 4.0 Model for Advanced Manufacturing: AMP 2019 4 (pp. 142-152). Springer International Publishing.
  • Mahdiraji, H. A., Zavadskas, E. K., Arab, A., Turskis, Z., & Sahebi, I. G. (2021). Formulation of manufacturing strategies based on an extended SWARA method with intuitionisic fuzzy numbers: An automotive industry application. Transformations in Business and Economics, 20(2).
  • Milošević, I., Arsić, S., Glogovac, M., Rakić, A., & Ruso, J. (2022). Industry 4.0: Limitation or benefit for success?. Serbian Journal of Management, 17(1), 85-98.
  • Mittal, S., Ahman Khan, M., Romero, D., & Wuest,T. (2018). A critical review of smart manufacturing & Industry 4.0 maturity models: Implications for Small and Medium-Sized Enterprises (SMEs). Journal of Manufacturing Systems. 49, pp.194-214.
  • Müller, J. M., Buliga, O., & Voigt, K. (2018). Fortune favors the prepared: how SMEs approach business model innovations in Industry 4.0. Technol. Forecast. Soc. Chang. 132, 2–17.
  • Moeuf, A., Pellerin, R., Lamouri, S., Tamayo-giraldo, S., & Barbaray, R. (2017). The industrial management of SMEs in the era of Industry 4.0. Int. J. Prod. Res. 56, 1118–1136.
  • Oliff, H., & Liu, Y. (2017). Towards Industry 4.0 utilizing data-mining techniques: a case study on quality improvement. Paper presented at the CIRP Conference on Manufacturing Systems. Elsevier B.V.167–172.
  • Posada, J., Toro, C., Barandiaran, I., Oyarzun, D., Stricker, D., de Amicis, R.,& Vallarino, I. (2015). Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE Computer Graphics and Applications, 35(2), 26-40.
  • Puška, A., Štilić, A., & Stević, Ž. (2023). A comprehensive decision framework for selecting distribution center locations: A hybrid improved fuzzy SWARA and fuzzy CRADIS approach. Computation, 11(4), 73.
  • Rauch, E., Dallasega, P., & Matt, D. T. (2017). Critical factors for introducing lean product development to small and medium sized enterprises in Italy. Procedia CIRP, 60, 362–367.
  • Rehman, S., Rehman, N., Naz, M., Mumtaz, A., & Jianglin, Z. (2021). Application of grey-based SWARA and COPRAS techniques in disease mortality risk assessment. Journal of Healthcare Engineering.
  • Ruzgys, A., Volvačiovas, R., Ignatavičius, Č., & Turskis, Z. (2014). Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method. Journal of Civil Engineering and Management, 20(1), 103-110.
  • Safar, L., Sopko, J., Bednar, S., & Poklemba, R. (2018). Concept of SME business model for Industry 4.0 environment. TEM Journal, 7(3), 626-637.
  • Sanders, A., Elangeswaran, C., & Wulfsberg, J. (2016). Industry 4.0 implies lean manufacturing: Research activities in Industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management, 9(3), 811-833.
  • Schröder, C. (2017). The Challenges of Industry 4.0 for small and medium-sized enterprises; Friedrich-Ebert-Stiftung: Bonn, Germany.
  • Sharma, H., Sohani, N., & Yadav, A. (2023). A fuzzy SWARA-WASPAS based approach for determining the role of lean practices in enabling the supply chain agility. International Journal of System Assurance Engineering and Management, 14(Suppl 1), 492-511.
  • Sitton, I., & Rodríguez, S. (2017). Pattern extraction for the design of predictive models in Industry 4.0. International Conference on Practical Applications of Agents and Multi-Agent Systems, 258–261.
  • Sivageerthi, T., Bathrinath, S., Uthayakumar, M., & Bhalaji, R. K. A. (2022). A SWARA method to analyze the risks in coal supply chain management. Materials Today-Proceedings, 5, 935-940.
  • Stanujkic, D., Karabasevic, D., & Zavadskas, E. K. (2015). A framework for the selection of a packaging design based on the SWARA method. Engineering Economics, 26(2), 181-187.
  • Stentoft ,J., Wickstrøm, K. A., Philipsen, K., & Haug, A. (2021). Drivers and barriers for Industry 4.0 readiness and practice: empirical evidence from small and medium-sized manufacturers. Production Planning & Control, 32(109), 811-828, doi: 10.1080/09537287.2020.1768318.
  • Soltysova, Z., & Bednar, S. (2015). Complexity management in terms of mass customized manufacturing. Polish Journal of Management Studies, 12(2), 139-149.
  • Somohano-Rodríguez, F. M., & Madrid-Guijarro, A. (2022). Do Industry 4.0 technologies improve Cantabrian manufacturing SMEs performance? The role played by industry competition. Technology in Society, 70, 102019.
  • Tas, M. A., Cakir, E., & Ulukan, Z. (2021). Spherical fuzzy SWARA-MARCOS approach for green supplier selection. 3C Tecnología, Technology as an enabler in business, management, environmental, and social science, Edición Especial, 115-133. https://doi.org/10.17993/3ctecno.2021.specialissue7.115-133
  • Tortorella, L. G., & Fettermann, D. (2018). Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. Int. J. Prod. Res. 56, 2975–2987.
  • Turkes, M. C., Oncioiu, I., Aslam, H. D., Marin-Pantelescu, A., Topor, D. I., & Căpusneanu, S. (2019). Drivers and barriers in using Industry 4.0: A perspective of SMEs in Romania. Processes, 7(3), 153. doi:10.3390/pr7030153.
  • Tus A., & Adali, E.A. (2022). Green supplier selection based on the combination of Fuzzy SWARA (SWARA-F) and Fuzzy MARCOS (MARCOS-F) Methods. Gazi University Journal of Science, 35(4), 1535-1554.
  • Tvaronaviciene, M., & Burinskas, A. (2020). Industry 4.0 significance to competition and the EU competition policy: a literature review. Economics & Sociology, 13(3), 244-258.
  • Ulutas, A., Meidute-Kavaliauskiene, I., Topal, A., & Demir, E. (2022). Assessment of collaboration-based and non-collaboration-based logistics risks with plithogenic SWARA Method. Logistic, 5(4), 82.
  • Valdeza, A. C., Braunera, P., Schaara, A. K., Holzingerb, A., & Zieflea, M. (2015). Reducing complexity with simplicity-usability methods for Industry 4.0. Paper presented at Proceedings 19th Triennial Congress of the IEA, 9(14).
  • Vuković, M., Jorg, O., Hosseinifard, M., & Fantoni, G. (2022). Low-Cost digitalization solution through scalable IIoT prototypes. Applied Sciences, 12(17), 8571.
  • Yalcin, M.F. (2018). Industry 4.0, Turning point in the global competition in terms of Turkey. Sosyoekonomi Journal, 26 (36).
There are 62 citations in total.

Details

Primary Language English
Journal Section Makaleler
Authors

Damla Çevik Aka 0000-0001-9622-273X

Early Pub Date April 28, 2024
Publication Date April 30, 2024
Acceptance Date October 16, 2023
Published in Issue Year 2024 Issue: 67

Cite

APA Çevik Aka, D. (2024). EVALUATION OF THE CHANGE IN PERSPECTIVES OF SME EXECUTIVES TOWARDS THE INDUSTRY 4.0 PROCESS AND OPPORTUNITIES IN DIGITAL TRANSFORMATION WITH THE SWARA METHOD. Erciyes Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi(67), 45-53. https://doi.org/10.18070/erciyesiibd.1276967
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