• ISSN: 2148-2225 (online)

Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

A Quantitative Analysis for Prioritizing Success Elements in Agile Logistics Applications: The Case of Giresun and Ordu

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Çağlar Karamaşa, Ph.D.

Selçuk Korucuk, Ph.D.

Ezgi Demir, Ph.D.

Salih Memiş, Ph.D.


Abstract

In today's competitive market conditions, it is not enough to produce high-quality products at the cheapest price. Businesses are expected to deliver the product to the end user round the clock and around the world. One effective way to achieve this is through effective logistics management (Büyükçetin, 2003). Recently, agility has become a frequently discussed topic when it comes to creating an effective logistics management system. The word agility has become synonymous with a strategic response to the survival of businesses in today's competitive environment. However, it should be noted that every business has its unique philosophy and operates under the influence of different environmental factors. Therefore, there is no single agility concept that is suitable for all businesses or every situation (İlhan, 2007). Creating an agile logistics strategy can be achieved not only by minor changes but also by completely differentiating the methods of performing activities (Gunesakaran,1999). The creation of this differentiation depends on various success factors. The success factors of agile logistics considered in this study include: “Managing Change and Uncertainty”, “Flexibility and Responsiveness in Service”, “Increasing the Value Shown to the Customer”, “Information Technologies”, “Flexible Human Resources” and “Building Collaborations Among Service Providers”. These factors play a crucial role in the success of businesses and can increase their competitiveness. The absence of studies in the literature regarding the ranking of the success factors in agile logistics applications points to the important contribution of this study to the literature. To address this research gap, this study aims to rank the success factors of agile logistics practices in logistics firms in Giresun and Ordu provinces. The ranking will be done using the Spherical fuzzy sets based AHP. By prioritizing these success factors, businesses can identify the areas they need to focus on and improve, ultimately enhancing their competitiveness and success in the market.

Keywords: Agile Logistics, Agile Logistics Success Elements, Logistics, Spherical Fuzzy AHP, Spherical Fuzzy Sets

Jel Classification: C46

Suggested citation

Karamaşa, Ç., Korucuk, S., Demir, E. & Memiş, S. (). A Quantitative Analysis for Prioritizing Success Elements in Agile Logistics Applications: The Case of Giresun and Ordu. Alphanumeric Journal, 11(1), 63-84. https://doi.org/10.17093/alphanumeric.1136178

References

  • Arslan, A. (2011). The applicability of agile manufacturing management system on apparel: Regional Development Agency Level 2 TR72 (Kayseri, Sivas and Yozgat) example. Unpublished Master Thesis, Gazi University, Ankara.
  • Ashraf, S., & Abdullah, S. (2019). Spherical aggregation operators and their application in multiattribute group decision-making. Int J Intell Syst, 34(3),493–523. https://doi.org/10.1002/int.22062.
  • Atanacković, A. (2019). The Implementation of Agile Project Management in the Fast Fashion Industry. European Project Management Journal, 9(1), 42-51. https://doi.org/10.18485/epmj.2019.9.1.6
  • Baki, B. (2003). 21. Yüzyılın Üretim Paradigması: Çevik Üretim, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 17(1-2), 291-305.
  • Barahona, F., Ettl, M., Petrik, M., & Rimshnick, P. M. (2013). Agile Logistics Simulation and Optimization for Managing Disaster Responses. Proceedings of the 2013 Winter Simulation Conference (WSC), Washington, DC, USA (pp. 3341-3351). https://doi.org/ 10.1109/WSC.2013.6721698.
  • Büyükçetin, Y. (2003). Lojistik görüş. TÜGİAD Elegans Magazine, Sayı:59, Haber:30, Retreived from http://www.elegans.com.tr/arsiv/59/haber030.html. Accessing date: 22.03.2019.
  • Candan, G., & Cengiz Toklu, M. (2022). Sustainable industrialization performance evaluation of European Union countries: an integrated spherical fuzzy analytic hierarchy process and grey relational analysis approach. International Journal of Sustainable Development & World Ecology, 29(5), 387-400. https://doi.org/10.1080/13504509.2022.2027293.
  • Chege, S.M., Wang, D., & Suntu, S.L. (2020) Impact of information technology innovation on firm performance in Kenya. Information Technology for Development, 26(2), 316-345. https://doi.org/10.1080/02681102.2019.1573717.
  • Christopher, M., & Towill, D.R. (2000). Supply chain migration from lean and functional to agile and customised. Suppy Chain Management:An International Journal,5(4),206-213. https://doi.org/10.1108/13598540010347334
  • Çancı, M. & Erdal, M. (2003). Lojistik yönetimi. İstanbul:UTİKAD Yayınları.
  • Damen, J. (2001). Service-controlled agile logistics. Logistics Information Management, 14(3), 185-195. https://doi.org/10.1108/09576050110390211
  • Erdal, H. & Korucuk, S. (2016). Toplam Kalite Yönetimine Askeri Bakış Açısı: Toplam Kalite Liderliği. Karabük Üniversitesi Sosyal Bilimler Enstitüsü Dergisi , 6 (2) , 465-484.
  • Galankashi, M. R., Helmi, S. A., Rahim, A. R., & Rafiei, F. M. (2019). Agility assessment in manufacturing companies. Benchmarking: An International Journal, 26(7), 2081-2104. https://doi.org/10.1108/BIJ-10-2018-0328
  • Ghobakhloo, M., & Azar, A. (2018). Business excellence via advanced manufacturing technology and lean-agile manufacturing. Journal of Manufacturing Technology Management, 29(1), 2-24. https://doi.org/10.1108/JMTM-03-2017-0049
  • Gunasekaran, A. (1999). Agile manufacturing: A framework for research and development. International Journal of Production Economics, 62(1-2), 87-105. https://doi.org/10.1016/S0925-5273(98)00222-9
  • Haq, A. N., & Boddu, V. (2015). Analysis of agile supply chain enablers for Indian food processing industries using analytical hierarchy process. International Journal of Manufacturing Technology and Management, 29(1-2), 30-47. https://doi.org/10.1504/IJMTM.2015.066780
  • İlhan, Ö.Ö. (2007). Agile manufacturing, the effects of environmental factors on agile manufacturing and the point of view of Turkish companies about agile manufacturing. Unpublished Master Thesis, Gebze Technical University, Kocaeli.
  • Kahraman, C., & Kaya, İ. (2010). Supplier Selection in Agile Manufacturing Using Fuzzy Analytic Hierarchy Process. In: L. Wang, S. L. Koh (eds), Enterprise Networks and Logistics for Agile Manufacturing (pp. 155-190). Springer, London. https://doi.org/10.1007/978-1-84996-244-5_8
  • Kalkan, M. B., & Aydın, K. (2020). The role of 4PL provider as a mediation and supply chain agility. Modern Supply Chain Research and Applications, 2(2), 99-111. https://doi.org/10.1108/MSCRA-09-2019-0019
  • Kasap, G. C., & Peker, D. (2009). Çevik Üretim: Otomotiv Ana Sanayinde Faaliyet Gösteren Bir İşletmenin Çevikliğinin Ortaya Konmasına Yönelik Bir Araştırma. Electronic Journal of Social Sciences, 8(27), 57-78.
  • Kisperska-Moroń, D. (2003). Potential for SMEs Partnership in Agile Supply Chains. DSI & APDSI (pp. 1-2). Shanghai:China.
  • Korucuk, S. (2018). Lojistik Strateji Seçenekleri, 3. Bölüm, Editör, Erdal, H. Lojistik Stratejiler (Yalın, Çevik ve İşbirlikli), Ekin Yayınları: Bursa.
  • Korucuk, S. (2019). Üretim işletmelerinde verimliliğin önündeki engellerin ve verim artırıcı tekniklerin bütünleşik ahp-topsıs ile sıralanması: Erzurum ili örneği , Verimlilik Dergisi, 1, 219-241.
  • Kutlu Gündoğdu, F. & Kahraman, C. (2019a) Spherical fuzzy sets and spherical fuzzy TOPSIS method. Journal of Intelligent & Fuzzy Systems, 36(1), 337-352. https://doi.org/ 10.3233/JIFS-181401
  • Kutlu Gündoğdu, F. & Kahraman, C. (2019b) Extension of WASPAS with spherical fuzzy sets. Informatica, 30(2), 269-292.
  • Kutlu Gündoğdu, F. & Kahraman, C. (2019c) A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection. Journal of Intelligent & Fuzzy Systems, 37(1),1197-1211. https://doi.org/ 10.3233/JIFS-182651
  • Kutlu Gündoğdu, F. & Kahraman, C. (2019d) A novel fuzzy TOPSIS method using emerging interval-valued spherical fuzzy sets. Engineering Applications of Artificial Intelligence,85, 307-323. https://doi.org/10.1016/j.engappai.2019.06.003
  • Kutlu Gündoğdu, F. & Kahraman, C. (2020a). A novel spherical fuzzy analytic hierarchy process and its renewable energy application. Soft Computing, 24, 4607-4621. https://doi.org/10.1007/s00500-019-04222-w
  • Kutlu Gündoğdu, F. & Kahraman, C. (2020b). Spherical Fuzzy Analytic Hierarchy Process (AHP) and Its Application to Industrial Robot Selection. In: C. Kahraman, S. Cebi, S. Cevik Onar, B. Oztaysi, A. Tolga, I. Sari (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029 (pp.988-996). Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_117
  • Lubinski, P., Doliwa, D., & Stachowiak, A. (2016). Agile Logistics Strategy as the Determinant of Supply Chain Management – the Textile Industry Case Study. 3rd International Conference on Social Science (ICSS 2016), (pp. 958-963).
  • Maskell, B. (2001). The age of agile manufacturing. Supply Chain Management, 6(1), 5-11. https://doi.org/10.1108/13598540110380868
  • Malakouti, M., Rezaei, S., & Shahijan, M. K. (2017). Agile supply chain management (ASCM): a management decision-making approach. Asia Pacific Journal of Marketing and Logistics, 29(1), 171-182. https://doi.org/10.1108/APJML-02-2016-0031
  • Mishra, N., Kumar, V., & Chan, F. (2010). A Multi-agent Framework for Agile Outsourced Supply Chains. In: L. Wang, & S. L. Koh (eds), Enterprise Networks and Logistics for Agile Manufacturing. (pp.207-226). Springer, London. https://doi.org/10.1007/978-1-84996-244-5_10
  • Olimov, S.S. & Mamurova, D.I. (2022). Information Technology in Education. Pioneer : Journal of Advanced Research and Scientific Progress, 1(1), 17–22. Retrieved from https://innosci.org/jarsp/article/view/11.
  • Özparlak, H.M.(2003). Differences between lean manufacturing-agile manufacturing and the management of transition to agile enterprise. Unpublished Master Thesis, İstanbul Techical University, İstanbul.
  • Pool, J. K., Jamkhaneh, H. B., Tabaeeian, R. A., & Shahin, A. (2018). The effect of business intelligence adoption on agile supply chain performance. International Journal of Productivity and Quality Management, 23(3), 289-306. https://doi.org/10.1504/IJPQM.2018.089802
  • Rahman, A. R., Ab. Rashid, S., & Hamid, N. R. (2018). Agility and Digitalization Competency in Logistics 4.0 in Military Setting: The Challenge, Risks and Opportunities. Asian Journal of Social Science Research, 1(2), 1-29.
  • Saaty, T.L. (1980). The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill, New York.
  • Saaty, T.L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1),83–98. https://doi.org/10.1504/IJSSci.2008.01759
  • Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping Agility through Digital Options: Reconceptualizing the Role of Information Technology in Contemporary Firms. MIS quarterly, 27(2), 237-263. https://doi.org/10.2307/30036530
  • Selvakumar, G., & Jayashree, L.S. (2020). Agile Supply Chain Management Enabled by the Internet of Things and Microservices. In: L. Kumar, L. Jayashree, R. Manimegalai (eds) Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications,AISGSC 2019 (pp. 449-456). Springer, Cham. https://doi.org/10.1007/978-3-030-24051-6_43
  • Shahriaria, M., & Pilevarib, N. (2017). Agile Supplier Selection in Sanitation Supply Chain Using Fuzzy VIKOR Method. Journal of Optimization in Industrial Engineering, 10(21), 19-28. https://doi.org/10.22094/JOIE.2016.257
  • Sharaf, I.M. (2021). Global Supplier Selection with Spherical Fuzzy Analytic Hierarchy Process. In: C. Kahraman, F. Kutlu Gündoğdu (eds) Decision Making with Spherical Fuzzy Sets. Studies in Fuzziness and Soft Computing, vol 392. Springer, Cham. https://doi.org/10.1007/978-3-030-45461-6_14
  • Sharifi, H., & Zhang, Z. (1999). A methodology for achieving agility in manufacturing organisations: An introduction. International Journal of Production Economics, 62(1-2), 7-22. https://doi.org/10.1016/S0925-5273(98)00217-5
  • Surkova, E.V., & Mazhaiskii, Y.A. (2022). Management of Business Processes. Russ. Engin. Res. 42, 292–294. https://doi.org/10.3103/S1068798X22030248
  • Swafford P.M., Ghosh S., & Murthy N. (2008). Achieving supply chain agility through IT integration and flexibility. International Journal of Production Economics,116(2),288-297. https://doi.org/10.1016/j.ijpe.2008.09.002
  • Şanal, M. (2020). Yönetimde Sinerji için Kuantum Bakış Açısı . Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi , 7 (1) , 42-50 .
  • Taghizadeh, H., Valyani, A., & Bazrkar, A. (2015). Analysis and Prioritization of Effective Strategies for Agile Supply Chain Case Study: Pharmaceutical Industry in Iran. Mediterranean Journal of Social Sciences, 6(6), 376-383. https://doi.org/10.5901/mjss.2015.v6n6s2p376
  • Tao, J., Li, Y., & Yao, M. (2009). Reconstruction Model of Agile Logistics Based on Decision-Making Method of Gray Relational Grade. International Conference on Artificial Intelligence and Computational Intelligence, Shanghai, China (pp. 518-522). https://doi.org/10.1109/AICI.2019.18
  • Wen, Z., Liao, H., Zavadskas., E. K., & Al-Barakati, A. (2019) Selection third-party logistics service providers in supply chain finance by a hesitant fuzzy linguistic combined compromise solution method, Economic Research-Ekonomska Istraživanja, 32(1), 4033-4058. https://doi.org/10.1080/1331677X.2019.1678502
  • Xu, H. (2010). Agile Manufacturing in Complex Supply Networks. In: L. Wang, L. S. Koh (eds) Enterprise Networks and Logistics for Agile Manufacturing (pp. 39-65). Springer, London. https://doi.org/10.1007/978-1-84996-244-5_3
  • Xu, N.R., Liu, J.B., Li, D.X., & Wang, J. (2016). Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory. Mathematical Problems in Engineering, 4346580. https://doi.org/10.1155/2016/4346580
  • Xu,Z., Cao, J., Xu, Y., Sun, Y., & Zhang, X., (2022). Decision-Making Mechanism of Cooperative Innovation between Clients and Service Providers Based on Evolutionary Game Theory. Discrete Dynamics in Nature and Society, 8774462. https://doi.org/10.1155/2022/8774462
  • Xu, Z. & Liao, H. (2014). Intuitionistic Fuzzy Analytic Hierarchy Process. IEEE Transactions on Fuzzy Systems, 22(4),749–761. https://doi.org/10.1109/TFUZZ.2013.2272585
  • Yarmohammadi, Y., Maleki, R., Khanbabaie, K., Yasini, A., & Mafi, K. (2014). Identifying the Most Agile Supply Chain in Iran Auto Industry: ANP Approach. INTERNATIONAL JOURNAL of ACADEMIC RESEARCH, 6(5), 55-63. https://doi.org/10.7813/2075-4124.2014/6-5/A.9
  • Zerenler, M.(2007). Information Technology and Business Performance in Agile Manufacturing: An Empirical Study in Textile Industy. 4th International Conference on Information Technology (ITNG’07), Las Vegas, Nevada, USA (pp.543-549). https://doi.org/10.1109/ITNG.2007.111
  • Zhang, X., Liu, Y., & Dan, B. (2021). Cooperation strategy for an online travel platform with value-added service provision under demand uncertainty, International Transactions in Operational Research, 28(6),3416-3436. https://doi.org/10.1111/itor.12977.

Volume 11, Issue 1, 2023

2023.11.01.OR.01

alphanumeric journal

Volume 11, Issue 1, 2023

Pages 63-84

Received: July 4, 2022

Accepted: May 16, 2023

Published: July 12, 2023

Full Text [734.5 KB]

2023 Karamaşa, Ç., Korucuk, S., Demir, E., Memiş, S.

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