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LOJİSTİK OPERASYONUN DİJİTALİZASYONUNUN GEÇMİŞİ, BUGÜNÜ VE GELECEĞİ: BİBLİYOMETRİK BİR ANALİZ

Year 2022, Volume: 4 Issue: 2, 175 - 192, 28.12.2022
https://doi.org/10.55580/oguzhan.1140477

Abstract

Bu makale, bibliyometrik teknik kullanarak 1995'ten 2021'e kadar olan dijitalleşme-lojistik operasyonla ilgili literatürü analiz etmeyi amaçlamaktadır. Bu makale Web of Science veritabanından 266 makaleyi analiz etmektedir ve veritabanı hakemli dergi makaleleri, incelemeler ve erken erişim makalelerinden oluşmaktadır. Bunun yanı sıra, bibliyografik materyali haritalamak için Bibliometrix R-Package yazılımı kullanılmaktadır. Araştırma şunu ortaya koymuştur: 2017'den sonra yayın sayısı istikrarlı bir şekilde artmış ve Mühendislik, İşletme ve Ekonomi en verimli araştırma alanlarıdır. Toplam yayın ve toplam atıf bazında Çin, ABD ve Almanya en üretken ülkelerdir. Nitekim, ülkeler arasındaki akademik işbirliği ilişkileri analiz edildiğinde, Çin uluslararası işbirliğinin merkezidir ve çoğunlukla Birleşik Krallık ve ABD ile çalışmaktadır. Ayrıca dergiler arasında “Sustainability” en verimli dergi, “International Journal of Production Research” en yüksek etki faktörüne sahip dergi ve “Annals of Operations Research” dergiler arasında en yüksek toplam atıf sayısına sahip dergidir. Bunun yanı sıra, Jinan Üniversitesi toplam yayınlara göre en verimli kurumdur ve yazar performans analizi, Ivanov D. araştırma alanında akademik olarak en etkili yazarlardan biridir. Anahtar kelime analizine göre “lojistik”, “yönetim” ve “performans” anahtar kelimeleri yazarlar tarafından sıklıkla kullanılmaktadır.

References

  • Accenture (2016). Türkiye Dijitalleşme Endeksi. Erişim 3 Şubat 2022, http://tbv.org.tr/accenture-turkiye-dijitallesme-endeksi.
  • Ahmad, R. W., Hasan, H., Jayaraman, R., Salah, K. & Omar, M. (2021). Blockchain applications and architectures for port operations and logistics management. Research in Transportation Business & Management, 41 (1), 1-17.
  • Aria, M. & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11 (4), 959-975.
  • Armağan, İ. Ü., Özdağoğlu, A., & Keleş, M. K. (2021). Covıd-19 Salgınının Banka Performanslarına Etkisinin Seca Yöntemiyle Değerlendirilmesi. Oğuzhan Sosyal Bilimler Dergisi, 3(2), 114-124.
  • Asdecker, B. & Felch, V. (2018). Development of an Industry 4.0 maturity model for the delivery process in supply chains. Journal of Modelling in Management, 13 (4), 840-883.
  • Balakrishnan, A. S. & Ramanathan, U. (2021). The role of digital technologies in supply chain resilience for emerging markets’ automotive sector. Supply Chain Management, 26 (6), 654-671.
  • Broadus, R. N. (1987). Toward a definition of “bibliometrics”. Scientometrics, 12 (5), 373-379.
  • Büyüközkan, G. & Göçer, F. (2018). An extension of ARAS methodology under interval valued intuitionistic fuzzy environment for digital supply chain. Applied Soft Computing, 69 (1), 634-654.
  • Cagle, M. (2020). A Mappıng Analysis of Blockchain Applications within the Field of Auditing. Muhasebe Bilim Dünyası Dergisi, 22 (4), 695-724.
  • Cagle, M. (2021). Denetimde Blokzincir Teknolojisinin Uygulanması ve Denetim Mesleğinin Geleceği. Detay Yayıncılık.
  • Cagle, M. N., Yılmaz, K. & Doğru, H. (2020). Digitalization of business functions under Industry 4.0. Umit Hacioglu, U. (Eds.), Digital Business Strategies in Blockchain Ecosystems (105-132). Springer.
  • Candell, O., Karim, R. & Söderholm, P. (2009). eMaintenance—Information logistics for maintenance support. Robotics and Computer-Integrated Manufacturing, 25 (6), 937-944.
  • Chen, H., Yang, Y., Yang, Y., Jiang, W. & Zhou, J. (2014). A bibliometric investigation of life cycle assessment research in the web of science databases. The International Journal of Life Cycle Assessment, 19 (10), 1674-1685.
  • Choi, T. M., Wen, X., Sun, X. & Chung, S. H. (2019). The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era. Transportation Research Part E: Logistics and Transportation Review, 127 (1), 178-191.
  • DMCC (2021). Future of Trade 2021 Report. Erişim 4 Şubat 2022, https://www.futureoftrade.com/.
  • Evans, P. C. & Annunziata, M. (2012). Industrial Internet: Pushing the Boundaries of Minds and Machines.Erişim 2 Şubat 2022, http://energyoutlook2013.naseo.org/presentations/Evans.pdf.
  • Ferreira, M. P., Santos, J. C., de Almeida, M. I. R. & Reis, N. R. (2014). Mergers & acquisitions research: A bibliometric study of top strategy and international business journals, 1980–2010. Journal of Business Research, 67 (12), 2550-2558.
  • Frazzon, E. M., Rodriguez, C. M. T., Pereira, M. M., Pires, M. C. & Uhlmann, I. (2019). Towards supply chain management 4.0. Brazilian Journal of Operations & Production Management, 16 (2), 180-191.
  • Fujitsu (2017). Global Digital Transformation Survey Report. Erişim 1 Şubat 2022, https://www.fujitsu.com/downloads/GLOBAL/vision/2017/download-center/FTSV2017_Survey_EN-1.pdf.
  • Fujitsu (2021). Global Digital Transformation Survey Report. Erişim 3 Şubat 2022, https://www.fujitsu.com/downloads/GLOBAL/vision/2021/download-center/FTSV2021_Survey_EN.pdf.
  • Giuffrida, M., Mangiaracina, R. & Burki, U. (2021). Cloud-Based Booking Platforms in Warehouse Operations. Sustainability, 13 (20), 1-16.
  • Grover, P., Kar, A. K. & Dwivedi, Y. K. (2020). Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions. Annals of Operations Research, 308, 1-37.
  • Herold, D. M., Ćwiklicki, M., Pilch, K. & Mikl, J. (2021). The emergence and adoption of digitalization in the logistics and supply chain industry: an institutional perspective. Journal of Enterprise Information Management, 34 (6), 1917-1938.
  • Holmström, J., & Partanen, J. (2014). Digital manufacturing-driven transformations of service supply chains for complex products. Supply Chain Management: An International Journal, 19 (4), 421-430.
  • Hsu, C. & Wallace, W. A. (2007). An industrial network flow information integration model for supply chain management and intelligent transportation. Enterprise Information Systems, 1 (3), 327-351.
  • Ivanov, D., Sethi, S., Dolgui, A. & Sokolov, B. (2018). A survey on control theory applications to operational systems, supply chain management, and Industry 4.0. Annual Reviews in Control, 46 (1), 134-147.
  • Kache, F. & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International journal of operations & production management, 37 (1), 10-36.
  • Kaewunruen, S. & Lian, Q. (2019). Digital twin aided sustainability-based lifecycle management for railway turnout systems. Journal of Cleaner Production, 228, 1537-1551.
  • Kagermann, H. (2015). Management of Permanent Change. Springer.
  • Kagermann, H., Helbig, J., Hellinger, A. & Wahlster, W. (2013). Securing the future of German manufacturing industry. Erişim 26 Şubat 2022, https://www.din.de/blob/76902/e8cac883f42bf28536e7e8165993f1fd/recommendations-for-implementing-industry-4-0-data.pdf/.
  • Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, H.B. & Noh, S. D. (2016). Smart manufacturing: Past research, present findings, and future directions. International journal of precision engineering and manufacturing-green technology, 3 (1), 111-128.
  • Law, M. K., Bermak, A. & Luong, H. C. (2010). A Sub-µW Embedded CMOS Temperature Sensor for RFID Food Monitoring Application. IEEE journal of solid-state circuits, 45 (6), 1246-1255.
  • Leung, K. H., Choy, K. L., Siu, P. K., Ho, G. T., Lam, H. Y., & Lee, C. K. (2018). A B2C e-commerce intelligent system for re-engineering the e-order fulfilment process. Expert Systems with Applications, 91, 386-401.
  • Liu, S. X. (2016). Innovation design: made in China 2025. Design Management Review, 27 (1), 52-58.
  • Lopes de Sousa Jabbour, A. B., Jabbour, C. J. C., Godinho Filho, M. & Roubaud, D. (2018). Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Annals of Operations Research, 270 (1), 273-286.
  • Meudt, T., Metternich, J. & Abele, E. (2017). Value stream mapping 4.0: Holistic examination of value stream and information logistics in production. CIRP Annals, 66 (1), 413-416.
  • Mishra, N. & Singh, A. (2018). Use of twitter data for waste minimisation in beef supply chain. Annals of Operations Research, 270 (1), 337-359.
  • Moral Muñoz, J. A., Herrera Viedma, E., Santisteban Espejo, A. & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El profesional de la información, 29 (1), 1-20.
  • Müller, F., Jaeger, D. & Hanewinkel, M. (2019). Digitization in wood supply–A review on how Industry 4.0 will change the forest value chain. Computers and Electronics in Agriculture, 162, 206-218.
  • Nerur, S. P., Rasheed, A. A. & Natarajan, V. (2008). The intellectual structure of the strategic management field: An author co‐citation analysis. Strategic Management Journal, 29 (3), 319-336.
  • Nikolakis, N., Alexopoulos, K., Xanthakis, E. & Chryssolouris, G. (2019). The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor. International Journal of Computer Integrated Manufacturing, 32 (1), 1-12.
  • Özdağoğlu, A., Ulutaş, A., & Keleş, M. K. (2022). Lojistik Değerlendirme Ölçütlerine Göre Ülke Sıralamaları: Farklı Yöntemlerin Sıralama Üzerindeki Etkisi. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 512-541.
  • Perboli, G., Musso, S. & Rosano, M. (2018). Blockchain in logistics and supply chain: A lean approach for designing real-world use cases. IEEE Access, 6, 62018-62028.
  • Pourkhani, A., Abdipour, K. H., Baher, B. & Moslehpour, M. (2019). The impact of social media in business growth and performance: A scientometrics analysis. International Journal of Data and Network Science, 3 (3), 223-244.
  • Qu, Y. J., Ming, X. G., Liu, Z. W., Zhang, X. Y. & Hou, Z. T. (2019). Smart manufacturing systems: state of the art and future trends. The International Journal of Advanced Manufacturing Technology, 103 (9), 3751-3768.
  • Queiroz, M. M., Ivanov, D., Dolgui, A. & Fosso Wamba, S. (2020). Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of operations research, 289, 1-38.
  • Rajkumar, R., Lee, I., Sha, L. & Stankovic, J. (2010). CPS: the next computing revolution. In Design Automation Conference, IEEE, 731-736.
  • Schroeder, A., Ziaee Bigdeli, A., Galera Zarco, C. & Baines, T. (2019). Capturing the benefits of industry 4.0: a business network perspective. Production Planning & Control, 30 (16), 1305-1321.
  • Shafique, M. (2013). Thinking inside the box? Intellectual structure of the knowledge base of innovation research (1988–2008). Strategic Management Journal, 34 (1), 62-93.
  • Skute, I. (2019). Opening the black box of academic entrepreneurship: a bibliometric analysis. Scientometrics, 120 (1), 237-265.
  • Stock, T. & Seliger, G. (2016). Opportunities of Sustainable Manufacturing in Industry 4.0. Procedia CIRP, 40, 536-541.
  • Tang, S., Shelden, D. R., Eastman, C. M., Pishdad-Bozorgi, P. & Gao, X. (2019). A review of building information modeling (BIM) and the internet of things (IoT) devices integration: Present status and future trends. Automation in Construction, 101, 127-139.
  • Tian, G., Ren, Y. & Zhou, M. (2016). Dual-objective scheduling of rescue vehicles to distinguish forest fires via differential evolution and particle swarm optimization combined algorithm. IEEE Transactions on intelligent transportation systems, 17 (11), 3009-3021.
  • Van Leeuwen, T. (2006). The application of bibliometric analyses in the evaluation of social science research. Who benefits from it, and why it is still feasible. Scientometrics, 66 (1), 133-154.
  • Vanderroost, M., Ragaert, P., Verwaeren, J., De Meulenaer, B., De Baets, B. & Devlieghere, F. (2017). The digitization of a food package’s life cycle: Existing and emerging computer systems in the logistics and post-logistics phase. Computers in Industry, 87, 15-30.
  • Vinkler, P. (2010). The evaluation of research by scientometric indicators. Elsevier.
  • Wallin, J. A. (2005). Bibliometric methods: pitfalls and possibilities. Basic & clinical pharmacology & toxicology, 97 (5), 261-275.
  • Zemigala, M. (2019). Tendencies in research on sustainable development in management sciences. Journal of cleaner production, 218, 796-809.
  • Zhang, X., Estoque, R. C., Xie, H., Murayama, Y. & Ranagalage, M. (2019). Bibliometric analysis of highly cited articles on ecosystem services. PloS one, 14 (2), 1-16.

PAST, PRESENT AND FUTURE OF DIGITALIZATION OF LOGISTIC OPERATION: A BIBLIOMETRIC ANALYSIS

Year 2022, Volume: 4 Issue: 2, 175 - 192, 28.12.2022
https://doi.org/10.55580/oguzhan.1140477

Abstract

This paper aims to analyze the digitalization-logistic operation-related literature from 1995 to 2021 using the bibliometric technique. This article analyses 266 papers from the Web of Science database and the database consisted of peer-reviewed journal articles, reviews, and early accesses articles. Moreover, Bibliometrix R-Package software is used to map the bibliographic material. The research revealed that: the number of publications steadily increased after 2017 and Engineering and Business and Economies are the most productive research areas. China, the USA and Germany are the most productive country based on the total publications and total citations. Indeed, when analyzing the academic collaborative relationships among countries, China is the center of international collaboration and mostly works with the UK and the USA. Furthermore, “Sustainability” is the most productive journal, “International Journal of Production Research” has the highest impact factor and “Annals of Operations Research” has the highest total citation. Besides, Jinan University is the most productive institution and Ivanov D. is one of the most academically influential author in the research area. According to keyword analysis, “logistics”, “management” and “performance” keywords are frequently used by authors.

References

  • Accenture (2016). Türkiye Dijitalleşme Endeksi. Erişim 3 Şubat 2022, http://tbv.org.tr/accenture-turkiye-dijitallesme-endeksi.
  • Ahmad, R. W., Hasan, H., Jayaraman, R., Salah, K. & Omar, M. (2021). Blockchain applications and architectures for port operations and logistics management. Research in Transportation Business & Management, 41 (1), 1-17.
  • Aria, M. & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11 (4), 959-975.
  • Armağan, İ. Ü., Özdağoğlu, A., & Keleş, M. K. (2021). Covıd-19 Salgınının Banka Performanslarına Etkisinin Seca Yöntemiyle Değerlendirilmesi. Oğuzhan Sosyal Bilimler Dergisi, 3(2), 114-124.
  • Asdecker, B. & Felch, V. (2018). Development of an Industry 4.0 maturity model for the delivery process in supply chains. Journal of Modelling in Management, 13 (4), 840-883.
  • Balakrishnan, A. S. & Ramanathan, U. (2021). The role of digital technologies in supply chain resilience for emerging markets’ automotive sector. Supply Chain Management, 26 (6), 654-671.
  • Broadus, R. N. (1987). Toward a definition of “bibliometrics”. Scientometrics, 12 (5), 373-379.
  • Büyüközkan, G. & Göçer, F. (2018). An extension of ARAS methodology under interval valued intuitionistic fuzzy environment for digital supply chain. Applied Soft Computing, 69 (1), 634-654.
  • Cagle, M. (2020). A Mappıng Analysis of Blockchain Applications within the Field of Auditing. Muhasebe Bilim Dünyası Dergisi, 22 (4), 695-724.
  • Cagle, M. (2021). Denetimde Blokzincir Teknolojisinin Uygulanması ve Denetim Mesleğinin Geleceği. Detay Yayıncılık.
  • Cagle, M. N., Yılmaz, K. & Doğru, H. (2020). Digitalization of business functions under Industry 4.0. Umit Hacioglu, U. (Eds.), Digital Business Strategies in Blockchain Ecosystems (105-132). Springer.
  • Candell, O., Karim, R. & Söderholm, P. (2009). eMaintenance—Information logistics for maintenance support. Robotics and Computer-Integrated Manufacturing, 25 (6), 937-944.
  • Chen, H., Yang, Y., Yang, Y., Jiang, W. & Zhou, J. (2014). A bibliometric investigation of life cycle assessment research in the web of science databases. The International Journal of Life Cycle Assessment, 19 (10), 1674-1685.
  • Choi, T. M., Wen, X., Sun, X. & Chung, S. H. (2019). The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era. Transportation Research Part E: Logistics and Transportation Review, 127 (1), 178-191.
  • DMCC (2021). Future of Trade 2021 Report. Erişim 4 Şubat 2022, https://www.futureoftrade.com/.
  • Evans, P. C. & Annunziata, M. (2012). Industrial Internet: Pushing the Boundaries of Minds and Machines.Erişim 2 Şubat 2022, http://energyoutlook2013.naseo.org/presentations/Evans.pdf.
  • Ferreira, M. P., Santos, J. C., de Almeida, M. I. R. & Reis, N. R. (2014). Mergers & acquisitions research: A bibliometric study of top strategy and international business journals, 1980–2010. Journal of Business Research, 67 (12), 2550-2558.
  • Frazzon, E. M., Rodriguez, C. M. T., Pereira, M. M., Pires, M. C. & Uhlmann, I. (2019). Towards supply chain management 4.0. Brazilian Journal of Operations & Production Management, 16 (2), 180-191.
  • Fujitsu (2017). Global Digital Transformation Survey Report. Erişim 1 Şubat 2022, https://www.fujitsu.com/downloads/GLOBAL/vision/2017/download-center/FTSV2017_Survey_EN-1.pdf.
  • Fujitsu (2021). Global Digital Transformation Survey Report. Erişim 3 Şubat 2022, https://www.fujitsu.com/downloads/GLOBAL/vision/2021/download-center/FTSV2021_Survey_EN.pdf.
  • Giuffrida, M., Mangiaracina, R. & Burki, U. (2021). Cloud-Based Booking Platforms in Warehouse Operations. Sustainability, 13 (20), 1-16.
  • Grover, P., Kar, A. K. & Dwivedi, Y. K. (2020). Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions. Annals of Operations Research, 308, 1-37.
  • Herold, D. M., Ćwiklicki, M., Pilch, K. & Mikl, J. (2021). The emergence and adoption of digitalization in the logistics and supply chain industry: an institutional perspective. Journal of Enterprise Information Management, 34 (6), 1917-1938.
  • Holmström, J., & Partanen, J. (2014). Digital manufacturing-driven transformations of service supply chains for complex products. Supply Chain Management: An International Journal, 19 (4), 421-430.
  • Hsu, C. & Wallace, W. A. (2007). An industrial network flow information integration model for supply chain management and intelligent transportation. Enterprise Information Systems, 1 (3), 327-351.
  • Ivanov, D., Sethi, S., Dolgui, A. & Sokolov, B. (2018). A survey on control theory applications to operational systems, supply chain management, and Industry 4.0. Annual Reviews in Control, 46 (1), 134-147.
  • Kache, F. & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International journal of operations & production management, 37 (1), 10-36.
  • Kaewunruen, S. & Lian, Q. (2019). Digital twin aided sustainability-based lifecycle management for railway turnout systems. Journal of Cleaner Production, 228, 1537-1551.
  • Kagermann, H. (2015). Management of Permanent Change. Springer.
  • Kagermann, H., Helbig, J., Hellinger, A. & Wahlster, W. (2013). Securing the future of German manufacturing industry. Erişim 26 Şubat 2022, https://www.din.de/blob/76902/e8cac883f42bf28536e7e8165993f1fd/recommendations-for-implementing-industry-4-0-data.pdf/.
  • Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, H.B. & Noh, S. D. (2016). Smart manufacturing: Past research, present findings, and future directions. International journal of precision engineering and manufacturing-green technology, 3 (1), 111-128.
  • Law, M. K., Bermak, A. & Luong, H. C. (2010). A Sub-µW Embedded CMOS Temperature Sensor for RFID Food Monitoring Application. IEEE journal of solid-state circuits, 45 (6), 1246-1255.
  • Leung, K. H., Choy, K. L., Siu, P. K., Ho, G. T., Lam, H. Y., & Lee, C. K. (2018). A B2C e-commerce intelligent system for re-engineering the e-order fulfilment process. Expert Systems with Applications, 91, 386-401.
  • Liu, S. X. (2016). Innovation design: made in China 2025. Design Management Review, 27 (1), 52-58.
  • Lopes de Sousa Jabbour, A. B., Jabbour, C. J. C., Godinho Filho, M. & Roubaud, D. (2018). Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations. Annals of Operations Research, 270 (1), 273-286.
  • Meudt, T., Metternich, J. & Abele, E. (2017). Value stream mapping 4.0: Holistic examination of value stream and information logistics in production. CIRP Annals, 66 (1), 413-416.
  • Mishra, N. & Singh, A. (2018). Use of twitter data for waste minimisation in beef supply chain. Annals of Operations Research, 270 (1), 337-359.
  • Moral Muñoz, J. A., Herrera Viedma, E., Santisteban Espejo, A. & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El profesional de la información, 29 (1), 1-20.
  • Müller, F., Jaeger, D. & Hanewinkel, M. (2019). Digitization in wood supply–A review on how Industry 4.0 will change the forest value chain. Computers and Electronics in Agriculture, 162, 206-218.
  • Nerur, S. P., Rasheed, A. A. & Natarajan, V. (2008). The intellectual structure of the strategic management field: An author co‐citation analysis. Strategic Management Journal, 29 (3), 319-336.
  • Nikolakis, N., Alexopoulos, K., Xanthakis, E. & Chryssolouris, G. (2019). The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor. International Journal of Computer Integrated Manufacturing, 32 (1), 1-12.
  • Özdağoğlu, A., Ulutaş, A., & Keleş, M. K. (2022). Lojistik Değerlendirme Ölçütlerine Göre Ülke Sıralamaları: Farklı Yöntemlerin Sıralama Üzerindeki Etkisi. Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 512-541.
  • Perboli, G., Musso, S. & Rosano, M. (2018). Blockchain in logistics and supply chain: A lean approach for designing real-world use cases. IEEE Access, 6, 62018-62028.
  • Pourkhani, A., Abdipour, K. H., Baher, B. & Moslehpour, M. (2019). The impact of social media in business growth and performance: A scientometrics analysis. International Journal of Data and Network Science, 3 (3), 223-244.
  • Qu, Y. J., Ming, X. G., Liu, Z. W., Zhang, X. Y. & Hou, Z. T. (2019). Smart manufacturing systems: state of the art and future trends. The International Journal of Advanced Manufacturing Technology, 103 (9), 3751-3768.
  • Queiroz, M. M., Ivanov, D., Dolgui, A. & Fosso Wamba, S. (2020). Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of operations research, 289, 1-38.
  • Rajkumar, R., Lee, I., Sha, L. & Stankovic, J. (2010). CPS: the next computing revolution. In Design Automation Conference, IEEE, 731-736.
  • Schroeder, A., Ziaee Bigdeli, A., Galera Zarco, C. & Baines, T. (2019). Capturing the benefits of industry 4.0: a business network perspective. Production Planning & Control, 30 (16), 1305-1321.
  • Shafique, M. (2013). Thinking inside the box? Intellectual structure of the knowledge base of innovation research (1988–2008). Strategic Management Journal, 34 (1), 62-93.
  • Skute, I. (2019). Opening the black box of academic entrepreneurship: a bibliometric analysis. Scientometrics, 120 (1), 237-265.
  • Stock, T. & Seliger, G. (2016). Opportunities of Sustainable Manufacturing in Industry 4.0. Procedia CIRP, 40, 536-541.
  • Tang, S., Shelden, D. R., Eastman, C. M., Pishdad-Bozorgi, P. & Gao, X. (2019). A review of building information modeling (BIM) and the internet of things (IoT) devices integration: Present status and future trends. Automation in Construction, 101, 127-139.
  • Tian, G., Ren, Y. & Zhou, M. (2016). Dual-objective scheduling of rescue vehicles to distinguish forest fires via differential evolution and particle swarm optimization combined algorithm. IEEE Transactions on intelligent transportation systems, 17 (11), 3009-3021.
  • Van Leeuwen, T. (2006). The application of bibliometric analyses in the evaluation of social science research. Who benefits from it, and why it is still feasible. Scientometrics, 66 (1), 133-154.
  • Vanderroost, M., Ragaert, P., Verwaeren, J., De Meulenaer, B., De Baets, B. & Devlieghere, F. (2017). The digitization of a food package’s life cycle: Existing and emerging computer systems in the logistics and post-logistics phase. Computers in Industry, 87, 15-30.
  • Vinkler, P. (2010). The evaluation of research by scientometric indicators. Elsevier.
  • Wallin, J. A. (2005). Bibliometric methods: pitfalls and possibilities. Basic & clinical pharmacology & toxicology, 97 (5), 261-275.
  • Zemigala, M. (2019). Tendencies in research on sustainable development in management sciences. Journal of cleaner production, 218, 796-809.
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There are 59 citations in total.

Details

Primary Language English
Journal Section Review Articles
Authors

Kevser Yılmaz 0000-0003-0415-8844

Aşkın Özdağoğlu 0000-0001-5299-0622

Publication Date December 28, 2022
Published in Issue Year 2022 Volume: 4 Issue: 2

Cite

APA Yılmaz, K., & Özdağoğlu, A. (2022). PAST, PRESENT AND FUTURE OF DIGITALIZATION OF LOGISTIC OPERATION: A BIBLIOMETRIC ANALYSIS. Oğuzhan Sosyal Bilimler Dergisi, 4(2), 175-192. https://doi.org/10.55580/oguzhan.1140477

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