Authors :
Özden Özkanlısoy
Volume/Issue :
Volume 9 - 2024, Issue 8 - August
Google Scholar :
https://tinyurl.com/2ehmr4aj
Scribd :
https://tinyurl.com/3k3psyb7
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24AUG502_
Abstract :
Supply chain performance measurement is an
integral part of supply chain management that reveals
the efficiency, health and success of the supply chain and
offers areas for improvement in this regard. Nowadays,
new ways maintain to be sought to realise the highest
possible potential of supply chains. The Fourth
Industrial Revolution enabled limitless benefits to supply
chains and created a transformation that alters the
entire supply chain and business models. This study aims
to reveal the contributions of this industrial revolution’s
technologies to supply chain performance and to ensure
superior performance is achieved thanks to these
technologies. In this study, the fourth industrial
revolution was examined in light of the stages of
industrial revolutions and the concept of supply chain
performance was explained by considering the historical
development of performance management. Afterwards,
the dimensions of supply chain performance in the
literature and the SCOR model version 13.0 attributes
and their metrics, which are considered as dimensions of
supply chain performance in this study, are elaborated.
The contributions of these technologies to supply chain
performance were investigated. The study ended with
the evaluation of the findings.
References :
- Abdelmajied, F.E.Y. (2022). Industry 4.0 and its implications: Concept, opportunities, and future directions. In T. Bányai, Á. Bányai, & I. Kaczmar (Eds.), Supply chain - Recent Advances and new perspectives in the industry 4.0 era (pp. 1-24). IntechOpen. doi: 10.5772/intechopen.102520
- Agarwal, A., & Shankar, R. (2002). Analyzing alternatives for improvement in supply chain performance. Work Study, 51(1), 32-37. https:// doi.org/10.1108/00438020210415497
- Agiwal, M., Saxena, N., & Roy, A. (2019). Towards connected living: 5G enabled internet of things (IoT). IETE Technical Review, 36(2), 190-202. https:// doi.org/10.1080/02564602.2018.1444516
- Ahi, P., & Searcy, C. (2015) An analysis of metrics used to measure performance in green and sustainable supply chains. Journal of Cleaner Production, 86(January 2015), 360–377. https:// doi.org/10.1016/j.jclepro.2014.08.005
- Al-Khatib, A. W., & Ramayah, T. (2023). Big data analytics capabilities and supply chain performance: Testing a moderated mediation model using partial least squares approach. Business Process Management Journal, 29(2), 393-412. https://doi.org/ 10.1108/BPMJ-04-2022-0179
- Alkış, G., Piritini, S., & Ertemel, A. V. (2020). Lojistik sektöründe Endüstri 4.0 uygulamalarinin operasyonel verimliliğe etkisi. Business & Management Studies: An International Journal, 8(1), 371-395. https://doi.org/10.15295/bmij.v8i1.1341
- Altay, N., A. Gunasekaran, R. Dubey, S., & J. Childe. (2018). Agility and resilience as antecedents of supply chain performance under moderating effects of organizational culture within the humanitarian setting: A dynamic capability view. Production Planning & Control, 29(14), 1158–1174. https://doi.org/10.1080/09537287.2018.1542174
- Ambe, I. M. (2014). Key indicators for optimising supply chain performance: The case of light vehicle manufacturers in South Africa. Journal of Applied Business Research, 30(1), 277–289. https://doi.org/ 10.19030/jabr.v30i1.8301
- Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22(6–7), 493–520. https://doi.org/10.1002/smj.187
- Anand, N. & Grover, N. (2015). Measuring retail supply chain performance: Theoretical model using key performance indicators (KPIs). Benchmarking: An International Journal, 22 (1), 135-166. https:// doi.org/10.1108/BIJ-05-2012-0034
- APICS, (2022). Supply Chain Operations Reference Model (SCOR) version 12.0 quick reference guide. http://www.apics.org/docs/default-source/scor-p-toolkits/apics-scc-scor-quick-reference-guide.pdf
- ASCM. (2020). Supply Chain Operations Reference Model SCOR digital standard. pp. 19-50. https:// www.ascm.org/globalassets/ascm_website_assets/docs/intro-and-front-matter-scor-digital-standard.pdf
- ASCM, (2023). Introduction to process. https:// scor.ascm.org/processes/introduction.
- Avelar-Sosa, L., García-Alcaraz, J. L., & Maldonado-Macías, A. A. (2019). Evaluation of supply chain performance: a manufacturing industry approach. Springer. https://doi.org/10.1007/978-3-319-93876-9
- Aylak, B., Oral, O., & Yazıcı, K. (2021). Using artificial intelligence and machine learning applications in logistics. El-Cezeri Journal of Science and Engineering, 8(1), 79–88. https://doi.org/ 10.31202/ecjse.776314
- Baskarada, S., Gao, J., & Koronios, A. (2005, May 31-Jun 2). Agile maturity model approach to assessing and enhancing the quality of asset information in engineering asset management information systems. 9th International Conference on Business Information Systems in cooperation with ACM SIGMIS. Klagenfurt, Austria.
- Bauernhansl, T. (2014). Die vierte industrielle revolution – der weg in ein wertschaffendes produktionsparadigma. In T. Bauernhansl, M. ten Hompel & B. Vogel-Heuser (Eds.), Industrie 4.0 in produktion, automatisierung und logistik (pp. 5–35). Springer. https://doi.org/10.1007/978-3-662-53254-6_1
- Beamon, B.M. (1999). Measuring supply chain performance. International Journal of Operations & Production Management, 19(3), 275–292. https:// doi.org/10.1108/01443579910249714
- Belhadi, A., Kamble, S. S., Gunasekaran, A., Zkik, K., & Touriki, F. E. (2023). A Big data analytics-driven lean six sigma framework for enhanced green performance: A case study of chemical company. Production Planning & Control, 34(9), 767-790. https://doi.org/10.1080/09537287.2021.1964868
- Bi, Z., & Cochran, D. (2014). Big data analytics with applications. Journal of Management Analytics, 1(4), 249–265. https://doi.org/10.1080/23270012.2014. 992985
- Blome, C., Paulraj, A., & Schuetz, K. (2014). Supply chain collaboration and sustainability: A profile deviation analysis. International Journal of Operations & Production Management, 34(5), 639–663. doi:10.1108/IJOPM-11-2012-0515.
- Bolstorff, P., & Rosenbaum, R. (2012). Supply Chain Excellence: A Handbook for Dramatic Improvement Using the SCOR Model (3rd ed.). Amacom. pp. 9–12.
- Bonilla, S. H., Silva, H. R. O., da Silva, M. T., Gonçalves, R. F., & Sacomano, J. B. (2018). Industry 4.0 and sustainability implications: A scenario-based analysis of the impacts and challenges. Sustainability, 10(10), 1–24. doi:10.3390u10103740
- Bourne, M., Mills, J., Wilcox, M., Neely, A. & Platts, K. (2000). Designing, implementing and updating performance measurement systems. International Journal of Operations & Production Management, 20(7), 754–771. https://doi.org/10.1108/ 01443570010330739
- Brettel, M., Friederichsen, N., Keller, M., & Rosenberg, M. (2014). How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 perspective. International Journal of Information and Communication Engineering, 8(1), 37–44.
- Bruque Cámara, S., Moyano Fuentes, J., & Maqueira Marín, J.M. (2015). Cloud computing, Web 2.0, and operational performance: The mediating role of supply chain integration. The International Journal of Logistics Management, 26(3), 426-458. https:// doi.org/10.1108/IJLM-07-2013-0085
- Brynjolfsson, E., & McAfee, A. (2014). The second machine age-work, progress, and prosperity in a time of brilliant technologies. Norton & Company.
- Bugmann, G., Siegel, M., & Burcin, R. (2011, September 13-15). A role for robotics in sustainable development? IEEE Africon’11, Victoria Falls, Zambia. IEEE. doi:10.1109/AFRCON.2011.6072154
- Burns, L.R., Goldsmith, J.C., & Sen, A. (2014). Horizontal and vertical integration of physicians: A tale of two tails. In L. Friedman, J. Goes & G.T. Savage (Eds.), Annual review of health care management: Revisiting the evolution of health systems organization (advances in health care management, vol. 15) (pp. 39-117). Emerald Group Publishing. https://doi.org/10.1108/S1474-8231 (2013)0000015009
- Büyüközkan, G., & Güler, M. (2019). Lojistik 4.0 teknolojilerinin analizi için metodolojik yaklaşım. Journal of Entrepreneurship and Innovation Management, 8(1), 21–47.
- Cavalli, L., Lizzi, G., Guerrieri, L., Querci, A., De Bari, F., Barbieri, G., ... & Lattuca, D. (2021). Addressing efficiency and sustainability in the port of the future with 5G: The experience of the Livorno Port. a methodological insight to measure innovation technologies’ benefits on port operations. Sustainability, 13(21), 1-21. https://doi.org/ 10.3390/su132112146
- Chae, B.K. (2009). Developing key performance indicators for supply chain: An industry perspective. Supply Chain Management: An International Journal, 14(6), 422–428. https://doi.org/ 10.1108/13598540910995192
- Chan, F.T.S. (2003). Performance measurement in a supply chain. The International Journal of Advanced Manufacturing Technology, 21(7), 534–548. https://doi.org/10.1007/s001700300063
- Chan, F.T.S. & Qi, H.J. (2003). An innovative performance measurement method for supply chain management. Supply Chain Management: An International Journal, 8(3), 209–223. https://doi.org/ 10.1108/13598540310484618
- Charan, P., Shankar, R., & Baisya, R.K. (2008). Analysis of interactions among the variables of supply chain performance measurement system implementation. Business Process Management Journal, 14(4), 512–529. https://doi.org/ 10.1108/ 14637150810888055
- Chen, K., Hu, Y., & Hsieh, Y. (2015). Predicting customer churn from valuable B2B customers in the logistics industry: A case study. Information Systems and E-Business Management, 13, 475-494. https://doi.org/10.1007/s10257-014-0264-1
- Chen, X., Li, C., Tang, Y., & Xiao, Q. (2018). An Internet of Things based energy efficiency monitoring and management system for machining workshop. Journal of cleaner production, 199, 957-968. https://doi.org/10.1016/j.jclepro.2018.07.211
- Choi, S., Jung, K., & Nog, S. D. (2015). Virtual reality applications in manufacturing industries: Past research, present findings, and future directions. Concurrent Engineering, Research and Applications, 21(1), 565–572. doi:10.1177/1063293X14568814
- Chopra, S., Meindl, P., & Kalra, D. V. (2016). Supply chain management: Strategy, planning and operation (6th ed.). Pearson Education.
- Choudhury, A., Behl, A., Sheorey, P.A., & Pal, A. (2021). Digital supply chain to unlock new agility: A TISM approach. Benchmarking: An International Journal, 28(6), 2075-2109. https://doi.org/10.1108/ BIJ-08-2020-0461
- Christopher, M. (2023). Logistics & supply chain management (6th ed.). Pearson. p. 305.
- Christopher, M. (2000). The agile supply chain: competing in volatile markets. Industrial Marketing Management, 29(1), 37–44, https://doi.org/10.1016/ S0019-8501(99)00110-8.
- Cirtita, H., & Glaser‐Segura, D.A. (2012). Measuring downstream supply chain performance. Journal of Manufacturing Technology Management, 23(3), 299-314. https://doi.org/10.1108/17410381211217380
- Cohen, S., & Roussel, J. (2013). Strategic supply chain management: the five disciplines for top performance (2nd ed.). McGraw-Hill. pp. 68–203.
- Correa Tavares, E., Meirelles, F. D. S., Tavares, E. C., Cunha, M. A., & Schunk, L. M. (2021). Blockchain in the Amazon: Creating public value and promoting sustainability. Information Technology for Development, 27(3), 579–598. doi:10.1080/ 02681102.2020.1848772
- Dallasega, P., Rauch, E., & Linder, C. (2018). Industry 4.0 as an enabler of proximity for construction supply chains: A systematic literature review. Computers in Industry, 99, 205-225. https:// doi.org/10.1016/j.compind.2018.03.039
- Dalmarco, G., & Barros, A. C. (2018). Adoption of Industry 4.0 technologies in supply chains. In A. C. Moreira, L. Miguel, D. F. Ferreira, & R. A. Zimmermann (Eds.), Innovation and supply chain management (pp. 303–319). Springer. doi:10.1007/ 978-3-319-74304-2_14
- Dauvergne, P. (2022). Is artificial intelligence greening global supply chains? Exposing the political economy of environmental costs. Review of International Political Economy, 29(3), 696-718. https://doi.org/10.1080/09692290.2020.1814381
- Davenport, T. H. (2006). Competing on analytics. Harvard Business Review, 84(1), 98–107.
- Davis, L. B., King, R. E., Hodgson, T. J., & Wei, W. (2011). Information sharing in capacity constrained supply chains under lost sales. International Journal of Production Research, 49 (24), 7469–7491. https://doi.org/10.1080/00207543.2010.535037
- De Toni, A., & Tonchia, S. (2001). Performance measurement systems, International Journal of Operations & Production Management, 21(1/2), 46-70. https://doi.org/10.1108/01443570110358459
- Delipinar, G. E., & Kocaoglu, B. (2016). Using SCOR model to gain competitive advantage: A literature review. Procedia - Social and Behavioral Sciences, 229, 398–406. https://doi.org/10.1016/ j.sbspro.2016.07.150
- Demirkol, Ö.F., & İkvan, A. (2020). Denetimin geleceği: Endüstri 4.0’ın etkisinde denetimin yeniden dizaynı. Muhasebe ve Finans Araştırmaları Dergisi, 2(1), 55-72.
- Dhaigude, A., & Kapoor, R. (2017). The mediation role of supply chain agility on supply chain orientation-supply chain performance link. Journal of Decision Systems, 26(3), 275-293. https://doi.org/ 10.1080/12460125.2017.1351862
- Dhamija, P., & Bag, S. (2020). Role of artificial intelligence in operations environment: A review and bibliometric analysis. The TQM Journal, 32(4), 869-896. https://doi.org/10.1108/TQM-10-2019-0243
- Dombrowski, U., & Wagner, T. (2014). Mental strain as field of action in the 4th industrial revolution. Procedia CIRP, 17, 100–105. https://doi.org/ 10.1016/j.procir.2014.01.077
- Druehl, C., Carrillo, J., & Hsuan, J. (2018). Technological innovations: Impacts on supply chains. In A.C. Moreira, L.M. D.F. Ferreira, & R.A. Zimmermann (Eds.), Innovation and supply chain management: Relationship, collaboration and strategies (pp. 259-281). Springer International Publishing. https://doi.org/10.1007/978-3-319-74304-2_12
- Dyer, J. H. (1997). Effective interfirm collaboration: How firms minimize transaction costs and maximize transaction value. Strategic Management Journal, 18(7), 535–556. https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<535::AID-SMJ885>3.0.CO;2-Z
- Elangovan, U. (2022). Industry 5.0: The future of the industrial economy (1st ed.). CRC Press. https:// doi.org/10.1201/9781003190677
- Ellinger, A.E. (2000). Improving marketing/logistics cross functional collaboration in the supply chain. Industrial Marketing Management, 29(1), 85-96. https://doi.org/10.1016/S0019-8501(99)00114-5
- Elrod, C., Murray, S., & Bande, S. (2013). A review of performance metrics for supply chain management. Engineering Management Journal, 25(3), 39–50. http://dx.doi.org/10.1080/10429247. 2013.11431981
- Emelogu, A., Marufuzzaman, M., Thompson, S. M., Shamsaei, N., & Bian, L. (2016). Additive manufacturing of biomedical implants: A feasibility assessment via supply chain cost analysis. Additive Manufacturing, 11, 97-113. https://doi.org/10.1016/ j.addma.2016.04.006
- Erboz, G., Yumurtacı Hüseyinoğlu, I.Ö., & Szegedi, Z. (2022). The partial mediating role of supply chain integration between Industry 4.0 and supply chain performance. Supply Chain Management, 27(4), 538-559. https://doi.org/10.1108/SCM-09-2020-0485
- Eslami, M. H., Jafari, H., Achtenhagen, L., Carlbäck, J., & Wong, A. (2021). Financial performance and supply chain dynamic capabilities: The Moderating Role of Industry 4.0 technologies. International Journal of Production Research, Ahead-of-print, 1-18. https://doi.org/10.1080/00207543.2021.1966850
- Fatorachian, H., & Kazemi, H. (2021). Impact of Industry 4.0 on supply chain performance. Production Planning & Control, 32(1), 63-81. https://doi.org/10.1080/09537287.2020.1712487
- Fawcett, S., Ellram, L., & Ogden, J. (2007). Supply chain management: From vision to implementation. Pearson Prentice Hall.
- Fawcett, S. E., & Waller, M. A. (2014). Supply chain game changers—mega, nano, and virtual trends—and forces that impede supply chain design (i.e, building a winning team). Journal of Business Logistics, 35(3), 157-164. https://doi.org/10.1111/jbl.12058
- Forslund, H., & Jonsson, P. (2007). The impact of forecast information quality on supply chain performance. International Journal of Operations & Production Management, 27(1), 90–107. doi:10.1108/01443570710714556
- Frank, A., Dalenogare, L., & Ayala, N. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210(April 2019), 15–26. https://doi.org/10.1016/j.ijpe.2019.01.004
- Frederico, G. F. (2021). Project management for supply chains 4.0: A conceptual framework proposal based on PMBOK methodology. Operations Management Research, 14, 434–450. https://doi.org/ 10.1007/s12063-021-00204-0
- Gammelgaard, B., & Nowicka, K. (2023). Next generation supply chain management: The impact of cloud computing. Journal of Enterprise Information Management, ahead-of-print, 1-21. https://doi.org/ 10.1108/JEIM-09-2022-0317
- Gashti, S. G., Seyedhosseini, S. M., & Noorossana, R. (2012). Developing a framework for supply chain value measurement based on value index system: Real case study of manufacturing company. African Journal of Business Management, 6(44), 11023–11034. https://doi.org/10.5897/AJBM12.651
- Geigl, F., Moik, C., Hintereggerz, S., & Goller, M. (2017, May 1). Using machine learning and RFID localization for advanced logistic applications. In 2017 IEEE International Conference on RFID, 73-74. https://www2.spsc.tugraz.at/www-archive/downloads/GeiglRFID2017.pdf
- Ghadge, A., Er Kara, M., Moradlou, H., & Goswami, M. (2020). The impact of Industry 4.0 implementation on supply chains. Journal of Manufacturing Technology Management, 31(4), 669-686. https://doi.org/10.1108/JMTM-10-2019-0368.
- Giannakis, M., Spanaki, K., & Dubey, R. (2019). A cloud-based supply chain management system: effects on supply chain responsiveness. Journal of Enterprise Information Management, 32(4), 585-607. https://doi.org/10.1108/JEIM-05-2018-0106
- Gilchrist, A. (2016). Industry 4.0: The industrial internet of things. Nonthaburi, Thailand: Apress. doi:10.1007/978-1-4842-2047-4
- Glockner, H., Jannek, K., Mahn, J., & Theis, B. (2014). Augmented reality in logistics: Changing the way we see logistics: A DHL perspective. DHL Customer Solutions & Innovation. https://www. dhl.com/discover/content/dam/dhl/downloads/interim/full/dhl-csi-augmented-reality-report.pdf
- Goel, R. K., Saunoris, J. W., & Goel, S. S. (2020). Supply chain reliability and international economic growth: Impacts of disruptions like COVID-19. CESifo Working Paper, 8294, 1-22. http://dx.doi.org/ 10.2139/ssrn.3603829
- Gowda, A.B., & Subramanya, K.N. (2016). A sensitivity analysis of the cloud characteristics in supply chain network using AHP. IUP Journal of Supply Chain Management, 13(1), 55-69.
- Görçün, Ö.F. (2022). Autonomous robots and utilization in logistics process. In I. Iyigün, & Ö.F. Görçün (Eds.), Logistics 4.0 and future of supply chains (pp. 83–93). Springer. https://doi.org/10.1007/ 978-981-16-5644-6
- Guarraia, P., Gerstenhaber, G., Athanassiou, M., & Boutot, P. H. (2015). The intangible benefits of a digital supply chain. Bain & Company. https://www. bain.com/insights/the-intangible-benefits-of-a-digital -supply-chain/
- Guersola, M., Lima, E. P. D., & Steiner, M. T. A. (2018). Supply chain performance measurement: a systematic literature review. International Journal of Logistics Systems and Management. 31(1), 109-131. https://doi.org/10.1504/IJLSM.2018.094193
- Guler, H., Akad, M., & Ergun, M. (2004, May 22-27). Railway asset management system in Turkey: A GIS application. FIG Working Week 2004. Athens, Greece. https://www.fig.net/resources/proceedings/ fig_proceedings/athens/papers/ts20/TS20_3_Guler_et_al.pdf
- Gunal, M. (2019). Simulation for the better: The future in Industry 4.0. In M. Gunal (Ed.), Simulation for Industry 4.0 (pp. 275–283). Springer. doi:10. 1007/978-3-030-04137-3_16
- Gunasekaran, A., & Kobu, B. (2007). Performance measures and metrics in logistics and supply chain management: A review of recent literature (1995–2004) for research and applications. International Journal of Production Research, 45(12), 2819–2840. https://doi.org/10.1080/00207540600806513
- Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87, 333–347. http://dx.doi.org/10.1016/ j.ijpe.2003.08.003
- Gunasekaran, A., Subramanian, N., & Rahman, S. (2017). Improving supply chain performance through management capabilities. Production Planning & Control, 28(6-8), 473–477. https://doi.org/10.1080/ 09537287.2017.1309680.
- Hamada, M., & Jarrell, G. (2009, January 26-29). Achieving world-class reliability in general aviation's supply chain. 2009 Annual Reliability and Maintainability Symposium. Fort Worth, TX, USA. DOI: 10.1109/RAMS.2009.4914684
- Handfield, R. (2016). Preparing for the era of the digitally transparent supply chain: A call to research in a new kind of journal. Logistics, 1(1), 1-15. https://doi.org/10.3390/logistics1010002
- Helo, P., & Hao, Y. (2017). Cloud manufacturing system for sheet metal processing. Production Planning and Control, 28(6–8), 524–537. doi:10.1080/09537287.2017.1309714
- Heng, S. (2020). Industry 4.0 creating buzz in the western hemisphere: But watch out for China pulling into the fast lane. In C. Machado & P. Davim (Eds.), Industry 4.0: Challenges, Trends, and Solutions in Management and Engineering (pp. 43-76). CRC Press. http://dx.doi.org/10.2139/ssrn.3617996
- Hieber, R. (2002). Supply chain management: A collaborative performance measurement approach. vdf Hochschulverlag AG an der ETH Zurich.
- Hofmann, E., & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics, Computers in Industry, 89(August 2017), 23–34. https://doi.org/10.1016/j.compind.2017.04. 002
- Hofmann, T., & Wenzel, D. (2021). How to minimize cycle times of robot manufacturing systems. Optimization and Engineering, 22, 895-912. https://doi.org/10.1007/s11081-020-09531-w
- Höchtl, J., Parycek, P., & Schöllhammer, R. (2016). Big data in the policy cycle: Policy decision making in the digital era. Journal of Organizational Computing and Electronic Commerce, 26(1-2), 147–169. doi:10.1080/10919392.2015.1125187
- Huang, S.H., Sheoran, S.K., & Wang, G. (2004). A review and analysis of supply chain operations reference (SCOR) model. Supply Chain Management: An International Journal, 9(1), 23–29. https://doi.org/10.1108/13598540410517557
- Hwang, Y., Lin, Y., & Lyu Jr, J. (2008). The performance evalutation of SCOR sourcing process—The case study of Taiwans TFT-LCD industry. International Journal of Production Economics, 115, 411–423. https://doi.org/10.1016/j.ijpe.2007.09.014
- Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI: How machine intelligence changes the rules of business. Harvard Business Review, 98(1), 60-67.
- IBM, (2018). Watson visual recognition: Maintenance with AI-driven visual inspection. https://www.ibm.com/topics/computer-vision
- Ilkka, S. (2015). Empirical study of measuring supply chain performance. Benchmarking: An International Journal, 22(2), 290–308. https://doi. org/10.1108/BIJ-01-2013-0009
- Immerman, G. (2017). Why Industry 4.0 important? https://www.machinemetrics.com/blog/why-industry-4-0-is-important
- Ivanov, D., Dolgui, A., Das, A., & Sokolov, B. (2019c). Digital supply chain twins: Managing the ripple effect, resilience, and disruption risks by data driven optimization, simulation, and visibility. In D. Ivanov, A. Dolgui, & B. Sokolov (Eds.), Handbook of ripple effects in the supply chain (pp. 309-332). Springer. https://doi.org/10.1007/978-3-030-14302-2_15
- Jalali Naini, S.G., Aliahmadi, A.R., & Jafari-Eskandari, M. (2011). Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: a case study of an auto industry supply chain. Resources, Conservation and Recycling, 55(6), 593–603. https://doi.org/ 10.1016/j.resconrec.2010.10.008
- Janvier-James, A. (2012). A new introduction to supply chains and supply chain management: Definitions and theories perspective. International Business Research, 5(1), 194-207. http://dx.doi.org/ 10.5539/ibr.v5n1p194
- Jasperneite, J., Sauter, T., & Wollschlaeger, M. (2020). Why we need automation models: handling complexity in industry 4.0 and the internet of things. IEEE Industrial Electronics Magazine, 14(1), 29-40. doi: 10.1109/MIE.2019.2947119.
- Jeble, S., Kumari, S., & Patil, Y. (2018). Role of big data in decision making. Operations and Supply Chain Management: An International Journal, 11(1), 36-44. DOI: http://doi.org/10.31387/oscm0300198
- Jum’a, L. (2023). The role of blockchain-enabled supply chain applications in improving supply chain performance: The case of Jordanian manufacturing sector. Management Research Review, 46(10), 1315-1333. https://doi.org/10.1108/MRR-04-2022-0298
- 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. doi:10.1108/IJOPM-02-2015-0078
- Kagermann, H., Lukas, W.D., & Wahlster, W. (2011). Industrie 4.0: Mit dem internet der dinge auf dem weg zur 4. industriellen revolution. https://www. ingenieur.de/technik/fachbereiche/produktion/industrie-40-mit-internet-dinge-weg-4-industriellen-revolution /
- Kagermann, H., Wahlster, W., & Helbig, J. (2013). Umsetzungsempfehlungen für das zukunftsprojekt Industry 4.0. Abschlussbericht des arbeitskreises industry 4.0. deutschlands zukunft als produktionsstandort sichern. promotorengruppe kommunikation der. Forschungsunion Wirtschaft.
- Kamble, S. S., & Gunasekaran, A. (2019). Big data-driven supply chain performance measurement system: A review and framework for implementation. International Journal of Production Research, 58(1), 65-86. https://doi.org/10.1080/00207543.2019. 1630770
- Kamble, S.S., Gunasekaran, A., Ghadge, A., & Raut, R. (2020). A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs-A review and empirical investigation. International Journal of Production Economics, 229, 1-15. https://doi.org/10.1016/j.ijpe.2020.107853
- Katicic, L., & Susnjar, I. (2011, June 30- July 1). Facility and asset management. 5th International Scientific Conference. Maritime University of Szczecin, Poland.
- Kayikci, Y., Subramanian, N., Dora, M., & Bhatia, M. S. (2020). Food supply chain in the era of Industry 4.0: Blockchain technology implementation opportunities and impediments from the perspective of people, process, performance, and technology. Production Planning & Control, 33(2-3), 301-321. https://doi.org/10.1080/09537287.2020.1810757
- Kayikci, Y., Durak Usar, D., & Aylak, B. L. (2022). Using blockchain technology to drive operational excellence in perishable food supply chains during outbreaks. The International Journal of Logistics Management, 33(3), 836-876. https://doi.org/ 10.1108/IJLM-01-2021-0027
- Kennerley, M., & Neely, A. (2003). Measuring performance in a changing business environment. International Journal of Operations & Production Management. 23(2), 213–229. https://doi.org/10. 1108/01443570310458465
- Khan, M. M., Bashar, I., Minhaj, G. M., Wasi, A. I., & Hossain, N. U. I. (2023). Resilient and sustainable supplier selection: an integration of SCOR 4.0 and machine learning approach. Sustainable and Resilient Infrastructure, 1-17. https://doi.org/10.1080/ 23789689.2023.2165782
- Klötzer, C. (2018). Bridging two worlds: How cyber-physical systems advance supply chain management. E. Sucky, R. Kolke, N. Biethahn, J. Werner & M. Volgelsang (Eds.). Mobility in a globalised world 2018 (pp. 86-109). University of Bamberg Press.
- Koh, L., Orzes, G., & Jia, F. (2019). The fourth industrial revolution (Industry 4.0): Technologies’ disruption on operations and supply chain management. International Journal of Operations & Production Management, 39, 817–828. https:// doi.org/10.1108/IJOPM-08-2019-788
- Kolberg, D., & Zühlke, D. (2015). Lean automation enabled by industry 4.0 technologies. IFAC-PapersOnLine, 48(3), 1870-1875. https://doi.org/ 10.1016/j.ifacol.2015.06.359
- Korepin, V., Dzenzeliuk, N., Seryshev, R., & Rogulin, R. (2021). Improving supply chain reliability with blockchain technology. Maritime Economics and Logistics, 4, 1-16. https://doi.org/ 10.1057/s41278-021-00197-4
- Korpela, K., Hallikas, J., & Dahlberg, T. (2017, January 4-7). Digital supply chain transformation toward blockchain integration. Proceedings of the 50th Hawaii International Conference on System Sciences. Hawaii, USA. doi:10.24251/HICSS.2017. 506
- Kumar, A., & Nayyar, A. (2020). si3- Industry: A sustainable, intelligent, innovative, internet-of-things industry. In A. Kumar, & A. Nayyar (Eds.), A roadmap to Industry 4.0: Smart production, sharp business and sustainable development (pp. 1-21). Springer. https://doi.org/10.1007/978-3-030-14544-6_1
- Kumar, D., Singh, R. K., Mishra, R., & Wamba, S. F. (2022). Applications of the internet of things for optimizing warehousing and logistics operations: A systematic literature review and future research directions. Computers & Industrial Engineering, 171, 1-17. https://doi.org/10.1016/j.cie.2022.108455
- Kumar, V., Ramachandran, D., & Kumar, B. (2021). Influence of new-age technologies on marketing: A research agenda. Journal of Business Research, 125, 864-877. https:// doi.org/10.1016/j.jbusres.2020.01. 007
- Kurien, G.P., & Qureshi, M.N. (2011). Study of performance measurement practices in supply chain management. International Journal of Business, Management and Social Sciences, 2(4), 19–34.
- Kusiak, A. (2023). Smart manufacturing. In S.Y. Nof (Ed.) Springer handbook of automation (pp. 973-985). Springer. https://doi.org/10.1007/978-3-030-96729-1_45
- Lai, K. H., Ngai, E. W., & Cheng, T. C. E. (2002). Measures for evaluating supply chain performance in transport logistics. Transportation Research Part E: Logistics and Transportation Review, 38(6), 439-456. https://doi.org/10.1016/S1366-5545(02)00019-4
- Lam, W. S., Lam, W. H., & Lee, P. F. (2023). A bibliometric analysis of digital twin in the supply chain. Mathematics, 11(15). https://doi.org/10.3390/ math11153350
- Lamba, K., & Singh, S. P. (2017). Big data in operations and supply chain management: Current trends and future perspectives. Production Planning & Control, 28(11-12), 877-890. https://doi.org/ 10.1080/09537287.2017.1336787
- Lambert, D., & Cooper, M. (2000). Issues in supply chain management. Industrial Marketing Management, 29(1), 65–83. https://doi.org/10.1016/ S0019-8501(99)00113-3
- Lehyani, F., Zouari, A., Ghorbel, A., & Tollenaere, M. (2021). Defining and measuring supply chain performance: a systematic literature review. Engineering Management Journal, 33(4), 283-313. https://doi.org/10.1080/10429247.2020.1834309
- Leng, J., Zhou M., Xiao Y., Zhang H., Liu Q., Shen W., Su Q., & Li L., (2021). Digital twins based remote semi-physical commissioning of flow-type smart manufacturing systems. Journal of Cleaner Production, 306, 1-15. https://doi.org/10.1016/ j.jclepro.2021.127278
- Li, M., Li, Z., Huang, X., & Qu, T. (2021). Blockchain-Based Digital Twin Sharing Platform for Reconfigurable Socialized Manufacturing Resource Integration. International Journal of Production Economics, 240, 1-14. https://doi.org/10.1016/ j.ijpe.2021.108223
- Lin, M., Lin, C., & Chang, Y.-S. (2021). The impact of using a cloud supply chain on organizational performance. Journal of Business and Industrial Marketing. 36(1), 97-110. https://doi.org/10.1108/ JBIM-04-2019-0154
- Lockamy, A., & McCormack, K. (2004). Linking the SCOR planning practices to supply chain performance. International Journal of Operations & Production Management, 24(12), 1192–1218. https://doi.org/10.1108/01443570410569010
- Lohtia, R., Xie, F.T., & Subramaniam, R. (2004). Efficient consumer response in Japan: industry concerns, current status, benefits, and barriers to implementation. Journal of Business Research, 57(3), 306–311. https://doi.org/10.1016/S0148-2963 (01)00326-5
- Luthra, S., & Mangla, S. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168–179. https:// doi.org/10.1016/j.psep.2018.04.018
- Maestrini, V., Luzzinii, D., Maccarrone, P., & Caniato, F. (2007). Supply chain performance measurement systems: A systematic review and research agenda. International Journal of Production Economics, 183, 299–315. https://doi.org/10.1016/ j.ijpe.2016.11.005
- Mahroof, K. (2019). A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse. International Journal of Information Management, 45, 176-190. https://doi.org/10.1016/j.ijinfomgt. 2018.11.008
- Majumdar, D., Banerji, P. K. & Chakrabarti, S. (2018). Disruptive technology and disruptive innovation: ignore at your peril! Technology Analysis & Strategic Management, 30(11), 1247-1255. https:// doi.org/10.1080/09537325.2018.1523384
- Manners-Bell, J., & Lyon, K. (2019). The logistics and supply chain innovation handbook: Disruptive technologies and new business models. Kogan Page Publishers.
- Mashaly, M. (2021). Connecting the twins: A review on digital twin technology & its networking requirements. Procedia Computer Science, 184, 299-305.
- Masood, T., & Sonntag, P. (2020). Industry 4.0: Adoption challenges and benefits for SMEs. Computers in Industry, 121, 1-12. https://doi.org/ 10.1016/j.compind.2020.103261
- Mattioli, J., Perico, P., & Robic, P. O. (2020, June 2-4). Artificial intelligence-based asset management. 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE). Budapest, Hungary. IEEE. DOI: 10.1109/SoSE50414.2020.9130505
- Menon, D., Anand, B., & Chowdhary, C. L. (2023). Digital twin: Exploring the intersection of virtual and physical worlds. IEEE Access, 11(June), 75152–75172. https://doi.org/10.1109/ACCESS.2023. 3294985
- Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D., & Zacharia, Z.G. (2001). Defining supply chain management. Journal of Business Logistics, 22, 1–25. https://doi.org/ 10.1002/j.2158-1592.2001.tb00001.x
- Millet, P.A., Trilling, L., Moyaux, T., & Sakka, O. (2013). Ontology of SCOR for the strategic alignment of organizations and information systems. In V. Botta-Genoulaz, J.P. Campagne, D. Llerena., & C. Pellegrin (Eds.), Supply chain performance: Collaboration, alignment and coordination (pp. 171-210). John Wiley & Sons. https://doi.org/10.1002/ 9781118558065.ch5
- Mishra, R., Tiwari, A. K., Mishra, Y., Kumar, A., & Prajapati, A. (2023). Augmented reality in supply chains of Indian micro and small enterprises. Rivista Italiana di Filosofia Analitica Junior, 14(1), 93-104.
- Mohsen, B. M. (2023). Developments of digital technologies related to supply chain management. Procedia Computer Science, 220, 788-795. https://doi.org/10.1016/j.procs.2023.03.105
- Mohseni, M. (2003, September 7-12). What does asset management mean to you? 2003 IEEE PES Transmission and Distribution Conference and Exposition. Dallas, TX, USA IEEE. DOI: 10.1109/ TDC.2003.1335069
- Moeuf, A., Pellerin, R., Lamouri, S., Tamayo-Giraldo, S., & Barbaray, R. (2017). The industrial management of SMEs in the era of Industry 4.0. International Journal of Production Research, 56(3), 118-1136. doi: 10.1080/00207543.2017.1372647
- Mrugalska, B., & Wyrwicka, M.K. (2017). Towards lean production in Industry 4.0. Procedia Engineering, 182, 466–473. https://doi.org/10.1016/ j.proeng.2017.03.135
- Mujber, T. S., Szecsi, T., & Hashmi, M. S. J. (2004). Virtual reality applications in manufacturing process simulation. Journal of Materials Processing Technology, 155-156, 1834–1838. doi: 10.1016/ j.jmatprotec.2004.04.401
- Nan, J., Erlin, T., Fattaneh, D.M., & Alireza, B. (2020). A new model for investigating the impact of urban knowledge, urban intelligent transportation systems and IT infrastructures on the success of supply chain management systems in the distributed organizations. Kybernetes, 49(11), 2799-2818. https://doi.org/10.1108/K-04-2019-0288
- Naslund, D., & Williamson, S. (2010). What is management in supply chain management? A critical review of definitions, frameworks and terminology. Journal of Management Policy and Practice, 11(4), 11-28.
- Neely, A. (1999). The performance measurement revolution: Why now and what next? International Journal of Operations & Production Management, 19(2), 205–228. https://doi.org/10.1108/ 01443579910247437
- Neely, A. (2005). The evolution of performance measurement research: developments in the last decade and a research agenda for the next. International Journal of Operations & Production Management, 25(12), 1264–1277. https://doi.org/ 10.1108/01443570510633648
- Nnaji, C., & Karakhan, A. A. (2020). Technologies for safety and health management in construction: Current use, implementation benefits and limitations, and adoption barriers. Journal of Building Engineering, 29, 1-11. https://doi.org/10.1016/ j.jobe.2020.101212
- Ntabe, E. N., LeBel, L., Munson, A. D., & Santa-Eulalia, L. A. (2015). A systematic literature review of the supply chain operations reference (SCOR) model application with special attention to environmental issues. International Journal of Production Economics, 169, 310-332. https://doi.org/ 10.13140/RG.2.1.3618.7606
- OECD, (2016). Enabling the next production revolution: The Future of manufacturing and services. Interim report. https://www.oecd.org/mcm/ documents/Enabling-the-next-production-revolution-the-future-of-manufacturing-and-services-interim-report.pdf
- Oh, J., & Jeong, B. (2019). Tactical supply planning in smart manufacturing supply chain. Robotics and Computer-Integrated Manufacturing, 55, 217-233. https://doi.org/10.1016/j.rcim.2018.04.003
- Özcan, E., & Akkaya, B. (2020). The effect of Industry 4.0 on accounting in terms of business management. In B. Akkaya (Ed.), Agile business leadership methods for Industry 4.0. Emerald Publishing. https://doi.org/10.1108/978-1-80043-380-920201009
- Özkanlısoy, Ö., & Bulutlar, F. (2023). Measuring supply chain performance as SCOR v13. 0-based in disruptive technology era: Scale development and validation. Logistics, 7(3), 1-35. https://doi.org/ 10.3390/logistics7030065
- Pagano, A. M., & Liotine, M. (2020). Technology in supply chain management and logistics: Current practice and future applications. Elsevier.
- Park, J. H., Lee, J. K., & Yoo, J. S. (2005). A framework for designing the balanced supply chain scorecard. European Journal of Information Systems, 14(4), 335-346. https://doi.org/10.1057/ palgrave.ejis.3000544
- Park, M., & Singh, N. P. (2023). Predicting supply chain risks through big data analytics: Role of risk alert tool in mitigating business disruption. Benchmarking: An International Journal, 30(5), 1457-1484. https://doi.org/10.1108/BIJ-03-2022-0169
- Pellicelli, M. (2023). The digital transformation of supply chain management. Cambridge, US: Elsevier. https://doi.org/10.1016/B978-0-323-85532-7.00004-9
- Perussi, J. B., Gressler, F., & Seleme, R. (2019). Supply chain 4.0: Autonomous vehicles and equipment to meet demand. International Journal of Supply Chain Management, 8(4), 33–41.
- Phung, H. G., & Pham, D. B. (2018). Effects of integrated shrimp farming in Vietnam. Journal of the World Aquaculture Society, 49(4), 664–675. doi:10.1111/jwas.12465
- Pietras, B. (2015). New frontiers in driverless vehicles. Engineering & Technology, 10(3), 64–67. doi:10.1049/et.2015.0326
- Piyathanavong, V., Huynh, V. N., Karnjana, J., & Olapiriyakul, S. (2022). Role of project management on sustainable supply chain development through industry 4.0 technologies and circular economy during the COVID-19 pandemic: A multiple case study of Thai metals industry. Operations Management Research, 1-25. doi:10.1007/s12063-022-00283-7
- Premus, R., & Sanders, N. R. (2008). Information sharing in global supply chain alliances. Journal of Asia-Pacific Business, 9(2), 174–192. https://doi.org/ 10.1080/10599230801981928
- Pretorius, C., Ruthven, G. A., & Von Leipzig, K. (2013). An empirical supply chain measurement model for a national egg producer based on the supply chain operations reference model. Journal of Transport and Supply Chain Management, 7(1), 1–13. https://doi.org/10.4102/jtscm.v7i1.97
- Qader, G., Junaid, M., Abbas, Q., & Mubarik, M. S. (2022). Industry 4.0 enables supply chain resilience and supply chain performance. Technological Forecasting and Social Change, 185, 1-12. https://doi.org/10.1016/j.techfore.2022.122026
- Ramezankhani, M.J., Torabi, S.A., & Vahidi, F. (2018). Supply chain performance measurement and evaluation: A mixed sustainability and resilience approach. Computers & Industrial Engineering, 126, 531–548. https://doi.org/10.1016/j.cie.2018.09.054
- Rana, K., & Sharma, S. (2019). Supply chain performance measurement: A scale development. IUP Journal of Business Strategy, 16(1), 88-111.
- Raji, I.O., Shevtshenko, E., Rossi, T., & Strozzi, F. (2021). Industry 4.0 technologies as enablers of lean and agile supply chain strategies: an exploratory investigation. The International Journal of Logistics Management, 32(4) 1150-1189. https://doi.org/ 10.1108/IJLM-04-2020-0157
- Rajkumar, R., Lee, I., Sha, L., & Stankovic, J. (2010, June). Cyber-physical systems: The next computing revolution. In Proceedings of the Design Automation Conference (pp. 731-736), IEEE. 10.1145/1837274. 1837461
- Ren, L., Zhang, L., Wang, L., Tao, F., & Chai, X. (2017). Cloud manufacturing: Key characteristics and applications. International Journal of Computer Integrated Manufacturing, 30(6), 501–515. https://doi.org/10.1080/0951192X.2014.902105
- Riahi, Y., Saikouk, T., Gunasekaran, A., & Badraoui, I. (2021). Artificial intelligence applications in supply chain: A descriptive bibliometric analysis and future research directions. Expert Systems with Applications, 173, 1-19. https://doi.org/10.1016/ j.eswa.2021.114702
- Rodríguez-Espíndola, O., Chowdhury, S., Beltagui, A., & Albores, P. (2020). The potential of emergent disruptive technologies for humanitarian supply chains: the integration of blockchain, Artificial Intelligence and 3D printing. International Journal of Production Research, 58(15), 4610-4630. https:// doi.org/10.1080/00207543.2020.1761565
- Roe, M., Xu, W., & Song, D. (2015). Optimizing supply chain performance: Information sharing and coordinated management. Palgrave Macmillan: p.14. DOI: 10.1057/9781137501158
- Romagnoli, S., Tarabu’, C., Maleki Vishkaei, B., & De Giovanni, P. (2023). The impact of digital technologies and sustainable practices on circular supply chain management. Logistics, 7, 1–17. https://doi.org/10.3390/logistics7010001.
- 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.
- Saad, M., & Patel, B. (2006). An investigation of supply chain performance measurement in the Indian automotive sector. Benchmarking: An International Journal, 13(1/2), 36-53. https://doi.org/10.1108/ 14635770610644565
- Sabet, S., & Farooq, B. (2023). Energy-smart transportation systems: Role of connectivity, automation, big data, and machine learning. in M. Fathi, E. Zio, & P. M. Pardalos (Eds.), Handbook of smart energy systems (pp. 2003-2023). Springer. https://doi.org/10.1007/978-3-030-72322-4
- Sabri, Ö. Z., Onursal, F.B., & Uca, N. C. (2020). Dijital gelecekte mesleklerin ve sektörlerin dönüşümü. Hiperlink Yayıncılık.
- Saleheen, F., & Habib, M. M. (2023). Embedding attributes towards the supply chain performance measurement. Cleaner Logistics and Supply Chain, 6, 1-12. Saucedo Martínez, J., Pérez Lara, M., Marmolejo Saucedo, J., Salais Fierro, T., & Vasant, P. (2018). Industry 4.0 framework for management and operations: A review. Journal of Ambient Intelligence and Humanized Computing, 9(3), 789–801. doi:10.100712652-017-0533-1
- Schroeder, R.G., John, C.A, & Scudder, G.D., (1986). White collar productivity measurement. Management Decision, 24(5), 3–7. https://doi.org/ 10.1108/eb001411
- Schwab, K. (2017). The fourth industrial revolution. New York: World Economic Forum.
- Shafiq, S., Sanin, C., Szczerbicki, E., & Toro, C. (2015). Virtual engineering object/virtual engineering process: A specialized form of cyber physical system for Industrie 4.0. Procedia Computer Science, 60, 1146–1155. https://doi.org/10.1016/j.procs.2015.08. 166
- Shahidehpour, M., & Ferrero, R. (2005). Time management for assets: chronological strategies for power system asset management. IEEE Power and Energy Magazine, 3(3), 32-38. doi: 10.1109/MPAE. 2005.1436498
- Shapiro, C., & Varian, R. H. (1998). Information rules: A Strategic guide for the network economy. Harvard Business School Press.
- Shnaiderman, M., & Ouardighi, F. E. (2014). The impact of partial information sharing in a two-echelon supply chain. Operations Research Letters, 42(3), 234–237. https://doi.org/10.1016/j.orl.2014.03. 006
- Shepherd, C., & Günter, H. (2006). Measuring supply chain performance: Current research and future directions. International Journal of Productivity and Performance Management, 55(3/4), 242–258. https://doi.org/10.1108/174104006106532 19
- Shoman, W., Yeh, S., Sprei, F., Köhler, J., Plötz, P., Todorov, Y., ... & Speth, D. (2023). A review of big data in road freight transport modeling: gaps and potentials. Data Science for Transportation, 5(1), 1-16. https://doi.org/10.1007/s42421-023-00065-y
- Silvestre, B. S. (2015). Sustainable supply chain management in emerging economies: Environmental turbulence, institutional voids and sustainability trajectories. International Journal of Production Economics, 167(September 2015), 156-169. https://doi.org/10.1016/j.ijpe.2015.05.025
- Singh, R.K. (2015). Modelling of critical factors for responsiveness in supply chain. Journal of Manufacturing Technology Management, 26(6), 868-888. https://doi.org/10.1108/JMTM-04-2014-0042
- Sinha, A., Bernardes, E., Calderon, R., & Wuest, T. (2020). Digital supply networks: Transform your supply chain and gain competitive advantage with disruptive technology and reimagined processes (kindle ed.) McGraw-Hill Education.
- Smith, M. J., & Carayon, P. (1995). New technology, automation, and work organization: stress problems and improved technology implementation strategies. International Journal of Human Factors in Manufacturing, 5(1), 99-116. https://doi.org/10.1002/ hfm.4530050107
- Soni, G., Kumar, S., Mahto, R.V., Mangla, S.K., Mittal, M.L., & Lim, W.M. (2022). A decision-making framework for Industry 4.0 technology implementation: The case of FinTech and sustainable supply chain finance for SMEs. Technological Forecasting and Social Change, 180, 1–12. https://doi.org/10.1016/j.techfore.2022.121686
- Srivastava, R. K., Shervani, T. A., & Fahey, L. (1998). Market-based assets and shareholder value: A framework for analysis. Journal of Marketing, 62(1), 2-18. https://doi.org/10.1177/0022242998062001
- Stearns, P.N. (2021). The industrial revolution in world history (5th ed.). Routledge.
- Stephens, S. (2001). Supply chain operations reference model version 5.0: A new tool to improve supply chain efficiency and achieve best practice. Information Systems Frontiers, 3, 471–476. https://doi.org/10.1023/A:1012881006783
- Stewart, G. (1995). Supply chain performance benchmarking study reveals keys to supply chain excellence. Logistics Information Management, 8(2), 38-44. https://doi.org/10.1108/09576059510085000
- Sukati, I., Hamid, A. B. A., Baharun, R., Alifiah, M. N., & Anuar, M. A. (2012). Competitive advantage through supply chain responsiveness and supply chain integration. International Journal of Business and Commerce, 1(7), 1-11.
- Surana, A., Kumara, S., Greaves, M., & Raghavan, U.N. (2005). Supply-chain networks: A complex adaptive systems perspective. International Journal of Production Research, 43, 4235–4265. https://doi.org/10.1080/00207540500142274.
- Sürie, C., & Reuter, B. (2014). Supply chain analysis. In H. Stadtler, C. Kilger, & H. Meyr (Eds.), Supply chain management and advanced planning: Concepts, models, software, and case studies (pp. 29-54). Springer. https://doi.org/10.1007/978-3-642-55309-7_2
- Taboada, I., & Shee, H. (2020). Understanding 5G technology for future supply chain management. International Journal of Logistics Research and Applications, 24(4), 392-406. https://doi.org/10.1080/ 13675567.2020.1762850
- Tan, K. H., Ji, G., Lim, C.P., & Tseng, M.L. (2017). Using big data to make better decisions in the digital economy. International Journal of Production Research, 55(17), 4998–5000. doi:10.1080/ 00207543.2017.1331051
- Tang, C. S., & Veelenturf, L. P. (2019). The strategic role of logistics in the Industry 4.0 era. Transportation Research Part E: Logistics and Transportation Review, 129, 1-11. https://doi.org/ 10.1016/j.tre.2019.06.004
- Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal of Manufacturing Systems Part C, 48, 157–169. https://doi.org/10.1016/j.jmsy.2018.01.006
- Tao, X. (2009, December). Performance evaluation of supply chain based on fuzzy matter-element theory. In 2009 International Conference on Information Management, Innovation Management and Industrial Engineering (Vol. 1, ppç 549-552). IEEE.
- Tekin, M., Zerenler, M., & Bilge, A. (2005). Bilişim teknolojileri kullanımının işletme performansına etkileri: Lojistik sektöründe bir uygulama. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 4(8), 115-129.
- Teoh, Y.K., Gill, S.S., & Parlikad, A.K. (2021). IoT and fog computing based predictive maintenance model for effective asset management in Industry 4.0 using machine learning. IEEE Internet of Things Journal, 10(3), 1-8. doi: 10.1109/JIOT.2021. 3050441.
- Thames, L., & Schaefer, D. (2017). Industry 4.0: An overview of key benefits, technologies, and challenges. In L. Thames, & D. Schaefer (Eds.), Cybersecurity for Industry 4.0 (pp. 1-33). Springer. https://doi.org/10.1007/978-3-319-50660-9_1
- Tjahjono, B., Esplugues, C., Ares, E., & Pelaez, G. (2017). What does Industry 4.0 mean to supply chain? Procedia Manufacturing, 13, 1175-1182. https://doi.org/10.1016/j.promfg.2017.09.191
- Tieman, M., & Darun, M. R. (2017). Leveraging blockchain technology for halal supply chains. ICR Journal, 8(4), 547–550. doi: 10.52282/icr.v8i4.167
- Tushman, M. L., & Anderson, P. (2018). Technological discontinuities and organizational environments. In G. Hage (Ed.), Organizational innovation (pp. 345-372). Routledge. https://doi.org/ 10.4324/9780429449482
- Üstündağ, A., & Tanyaş, M. (2009). Radyo frekanslı tanıma (RFID) teknolojisinin tedarik zinciri üzerindeki etkileri. İTÜDERGİSİ/d, 8(4), 83-94.
- van Hoek, R. I. (1998). Measuring the unmeasurable – measuring and improving performance in the supply chain. Supply Chain Management, 3(4), 187–192. http://dx.doi.org/10.1108/13598549810244232
- Vazquez-Martinez, G. A., Gonzalez-Compean, J. L., Sosa-Sosa, V. J., Morales-Sandoval, M., & Perez, J. C. (2018). Cloud Chain: A novel distribution model for digital products based on supply chain principles. International Journal of Information Management, 39, 90-103. https://doi.org/10.1016/j.ijinfomgt. 2017.12.006
- Wamba, S.F., Akter, S., Coltman, T., & WT Ngai, E. (2015). Guest editorial: information technology-enabled supply chain management. Production Planning & Control, 26(12), 933-944. https://doi.org/ 10.1080/09537287.2014.1002025
- Wamba, S.F., Queiroz, M.M., & Trinchera, L. (2020). Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation. International Journal of Production Economics, 229, 1-15.
- Wang, L., Deng, T., Shen, Z. J. M., Hu, H., & Qi, Y. (2022). Digital twin-driven smart supply chain. Frontiers of Engineering Management, 9(1), 56–70. https://doi.org/10.1007/s42524-021-0186-9
- Wang, Y., Han, J. H., & Beynon-Davies, P. (2019). Understanding blockchain technology for future supply chains: A systematic literature review and research agenda. Supply Chain Management: An International Journal, 24(1), 62-84. https://doi.org/ 10.1108/scm-03-2018-0148
- Warner, K. S. R., & M. Wäger. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/ j.lrp.2018.12.001
- Wenzel, H., Smit, D., & Sardesai, S. (2019). A literature review on machine learning in supply chain management. In W. Kersten, T. Blecker, & C.M. Ringle (Eds.) Artificial intelligence and digital transformation in supply chain management: Innovative approaches for supply chains (1st ed.) (pp. 413-441). epubli GmbH.
- Wiengarten, F., & Longoni, A. (2015). A nuanced view on supply chain integration: a coordinative and collaborative approach to operational and sustainability performance improvement. Supply Chain Management, 20(2), 139-150. https://doi.org/ 10.1108/SCM-04-2014-0120
- Williamson, O. E. (1980). Organizational innovation: The transaction cost approach. University of Pennsylvania, Center for the Study of Organizational Innovation. pp. 101–134.
- Witkowski, K. (2017). Internet of things, big data, industry 4.0–innovative solutions in logistics and supply chains management. Procedia Engineering, 182, 763-769. https://doi.org/10.1016/j.proeng.2017. 03.197
- Wu, L., Yue, X., Jin, A., & Yen, D. C. (2016). Smart supply chain management: A review and implications for future research. The International Journal of Logistics Management, 27(2), 395–417. doi:10.1108/IJLM-02-2014-0035
- Xie, Y., Yin, Y., Xue, W., Shi, H., & Chong, D. (2020). Intelligent supply chain performance measurement in Industry 4.0. Systems Research and Behavioral Science, 37(4), 711–718. https://doi.org/ 10.1002/sres.2712
- Xu, J., Pero, M., & Fabbri, M. (2023). Unfolding the link between big data analytics and supply chain planning. Technological Forecasting and Social Change, 196, 1-13. https://doi.org/10.1016/ j.techfore.2023.122805
- Ye, F., & Wang, Z. (2013). Effects of information technology alignment and information sharing on supply chain operational performance. Computers & Industrial Engineering, 65(3), 370-377. https:// doi.org/10.1016/j.cie.2013.03.012
- Yu, S., Mishra, A. N., Gopal, A., Slaughter, S., & Mukhopadhyay, T. (2015). E-procurement infusion and operational process impacts in MRO procurement: Complementary or substitutive effects? Production and Operations Management, 24(7), 1054–1107. doi: 10.1111/poms.12362
- Zekhnini, K., Cherrafi, A., Bouhaddou, I., Benabdellah, A. C., & Raut, R. (2021). A holonic architecture for the supply chain performance in industry 4.0 context. International Journal of Logistics Research and Applications, 1-28. https://doi.org/10.1080/13675567.2021.1999912
- Zhu, Q., & Kouhizadeh, M. (2019). Blockchain technology, supply chain information, and strategic product deletion management. IEEE Engineering Management Review, 47(1), 36-44. doi: 10.1109/EMR.2019.2898178
Supply chain performance measurement is an
integral part of supply chain management that reveals
the efficiency, health and success of the supply chain and
offers areas for improvement in this regard. Nowadays,
new ways maintain to be sought to realise the highest
possible potential of supply chains. The Fourth
Industrial Revolution enabled limitless benefits to supply
chains and created a transformation that alters the
entire supply chain and business models. This study aims
to reveal the contributions of this industrial revolution’s
technologies to supply chain performance and to ensure
superior performance is achieved thanks to these
technologies. In this study, the fourth industrial
revolution was examined in light of the stages of
industrial revolutions and the concept of supply chain
performance was explained by considering the historical
development of performance management. Afterwards,
the dimensions of supply chain performance in the
literature and the SCOR model version 13.0 attributes
and their metrics, which are considered as dimensions of
supply chain performance in this study, are elaborated.
The contributions of these technologies to supply chain
performance were investigated. The study ended with
the evaluation of the findings.