- Agdas, D., and R. D. Ellis. (2010). The Potential of XML Technology as an Answer to the Data Interchange Problems of the Construction Industry. Construction Management and Economics 28 (7): 737–746.
- Alex, V. B. (2006). A Parametric Analysis of Heuristics for the Vehicle Routing Problem with Side-Constraints. European Journal of Operational Research 137 (2): 348–370.
- Angreani, L.S, Annas Vijaya, A. Wicaksono, H, (2020). Systematic Literature Review of Industry 4.0 Maturity Model for Manufacturing and Logistics Sectors, Procedia Manufacturing 52:337–343.
- Arrais-Castro, A., R. Maria Leonilde, G. D. Varela, R. A. Putnik, J. M. Ribeiro, and L. Ferreira. (2018). Collaborative Framework for Virtual Organisation Synthesis Based on a Dynamic Multi-Criteria Decision Model. International Journal of Computer Integrated Manufacturing 31 (9): 857–868.
- Bag, S., Gupta, S., & Kumar, S. (2021). Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development. International Journal of Production Economics, 231, 107844.
- Bag, S., Yadav, G., Wood, L.C, Dhamija P, Joshi, S. (2020). Industry 4.0 and the circular economy: Resource melioration in logistics. Resources Policy 68, 101776.
- Ballou, R.H. (2007). The evolution and future of logistics and supply chain management, European Business Review, 19 (4): 332-348.
- Barrera, M. M., Mario, and O. Cruz-Mejia. (2014). Reverse Logistics of Recovery and Recycling of Non-Returnable Beverage Containers in the Brewery Industry: A Profitable Visit Algorithm. International Journal of Physical Distribution & Logistics Management 44 (7): 577–596.
- Barreto, L., Amaral, A., Pereira, T. (2017). Industry 4.0 implications in logistics: an overview. Procedia Manuf. 13: 1245–1252.
- Battista C, Fumi A, Schiraldi M.M. (2012), The Logistics Maturity Model: guidelines for logistic processes continuous improvement, Proceedings of the XXIII World POMS Conference, 20-23 April; Chicago (USA. confpapers/025/025-1329.pdf
- Battista, C, Schirald, M. M. (2013). The Logistic Maturity Model: Application to a Fashion Company. International Journal of Engineering Business Management, 5, 29-38.
- Becker, J., Knackstedt, R., P¨oppelbuß, J. (2009). Developing maturity models for IT management. Inf. Syst. Eng. 1: 213–222.
- Bloss, R. (2011). Automation Meets Logistics at the Promat Show and Demonstrates Faster Packing and Order Filling. Assembly Automation, 31 (4): 315–318.
- Bogataj, D., M. Bogataj, and D. Hudoklin. (2017). Mitigating Risks of Perishable Products in the Cyber-Physical Systems Based on the Extended MRP Model. International Journal of Production Economics, 193: 51–62.
- Boysen, N., S. Schwerdfeger, and F. Weidinger. (2018). Scheduling Last-Mile Deliveries with Truck-Based Autonomous Robots. European Journal of Operational Research, 271 (3): 1085–1099.
- Caiado, R.G. Scavarda L.F, Gavi˜ao, L.C, Ivson P, Nascimento D.L, Garza-Reyes. J.A. (2021). A fuzzy rule-based industry 4.0 maturity model for operations and supply chain management, J. Production Economics, 231, 1-21.
- Carvalho, J, Rocha A, Abreu, A. (2016). Maturity Models of Healthcare Information Systems and Technologies: a Literature Review, Review of Managerial Science, 5(2):9
- Choy, K. (2002). An Intelligent Supplier Management Tool for Benchmarking Suppliers in Outsource Manufacturing. Expert Systems with Applications, 22 (3): 213–224.
- Domingues, P. Sampaio, P. Arezes, P, M. (2016). Integrated management systems assessment: a maturity model proposal, Journal of Cleaner Production, 124 (2016) 164-174.
- Essaadi, I, Grabot, B, Fénies, P. (2016). Location of logistics hubs at national and subnational level with consideration of the structure of the location choice, IFAC-PapersOnLine, 49-31: 155–160.
- Fawcett, S. E., and M. A. Waller. (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.
- Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869
- Giusti, R., Manerba, D., Bruno, G., Tadei, R. (2019b). Synchro-modal logistics: an overview of critical success factors, enabling technologies, and open research issues. Transportation Research Part E: Logistics and Transportation Review, 129, 92–110.
- Glistau E., Machado N. I. C. (2018). Logistics 4.0 and the Revalidation of Logistics Concepts and Strategies, Available at: htILs: //www.researchgate.net/publication/ 327417565, (Accessed 25 February 2019).
- Hallikainen, H., Savimäki, E., & Laukkanen, T. (2020). Fostering B2B sales with customer big data analytics. Industrial Marketing Management, 86, 90-98.
- Hercko, J., Botka, M., (2017). Intelligent logistic management, in Next Generation Logistics: Technologies and Applications. In: Drašković, V. (Ed.). SPH – The Scientific Publishing, Velje, Denmark, pp. 1–18.
- Home-Ortiza, J M., Pourakbari-Kasmaei, M, Lehtonen, M, (2019). Optimal location-allocation of storage devices and renewable-based DG in distribution systems. Electric Power Systems Research 172, 11–21. DOI: 1016/j.epsr.2019.02.013
- Hou, J.-L., W. Nathan, and W. Yu-Jen. (2009). A Job Assignment Model for Conveyor-Aided Picking System. Computers & Industrial Engineering 56 (4): 1254–1264.
- Jahn, C., Kersten, W. and Ringle, C. M. (2018), Logistics 4.0 and sustainable supply chain management: innovative solutions for logistics and sustainable supply chain management in the context of industry 4.0. In: Hamburg International Conference of Logistics (HICL).
- Javanmard, H, (2017), Logistics and supply chain management. Arak Branch, Iran. Publication of Islamic azad university. (In Persian)
- Javanmard, H. (2008). Using Degree of Adaptive (DOA) Model for Partner Selection in Supply Chain. International Journal of Mechanical, Industrial and Aerospace Sciences. 1.0 (4).
- Junge, A. L., Verhoeven, P., Reipert, J. and M. Mansfeld. (2019). Pathway of Digital Transformation in Logistics: Best Practice Concepts and Future Developments.” Edited by Frank Straube. In Scientific Series Logistics at the Berlin Institute of Technology. Special Edition Berlin: Universitätsverlag der TU Berlin. https://depositonce.tu-berlin.de/handle/11303/9446.
- Kersten, W., M. Seiter, V. S. Birgit, N. Hackius, and T. Maurer. (2017). Trends and Strategies in Logistics and Supply Chain Management: Digital Transformation Opportunities. Journal of Logistics Research and Applications 13 (1): 13–39.
- Kiil, K., Dreyer, H. C., Hvolby H.-H., and Chabada, L. (2018). Sustainable Food Supply Chains: The Impact of Automatic Replenishment in Grocery Stores. Production Planning & Control 29 (2): 106–116.
- Kim, B. I., Graves R. J., Heragu, S. S., Onge, A. S. (2009). Intelligent Agent Modeling of an Industrial Warehousing Problem.” IIE Transactions 34 (7): 601–612.
- Kochak, A., Sharma, S. (2015). Demand Forecasting Using Neural Network for Supply Chain Management. International Journal of Mechanical Engineering and Robotics Research 4 (1): 96–104.
- Kostrzewski, M, Filina-Dawidowicz, L, Walusiak, M, (2021). Modern technologies development in logistics centers: the case study of Poland, Transportation Research Procedia 55, P- 268–275
- Li, R, Chen, H, 2022, Research on Automation Control of University Logistics Management System Based on Wireless Communication Network, Wireless Communications and Mobile Computing, Article ID 1939434, 8.
- Lin, B. Liua, S. Linb, R. Wang, J. Sun, M. Wang, X, Liu, C, Wu, J. Xiao, J, (2019), The location-allocation model for multi-classification-yard location problem, Transportation Research Part E 122, 283–308.
- Lindstrom, V, Winroth, M, (2010), Aligning manufacturing strategy and levels of automation: A case study, Journal of Engineering Technology Management. 27 148–159.
- Liu, W, Wang, S, Lin, Y, Xie, D, Zhang, J, (2020), Effect of intelligent logistics policy on shareholder value: Evidence from Chinese logistics companies, Transportation Research Part E, 137, 101928.
- Lizarralde D. R., Ganzarain, E. López C. Serrano L.I. (2020), An Industry 4.0 maturity model for machine tool companies, Technological Forecasting & Social Change 159, P. 1-13.
- Marchet, G., Melacini, M. Perotti, S. Tappia, E. (2013). Development of a Framework for the Design of Autonomous Vehicle Storage and Retrieval Systems. International Journal of Production Research 51 (14): 4365–4387.
- Mittal, S. Muztoba, A.K Romero, D. Wuest, T. (2018). Critical review of smart manufacturing & Industry 4.0 maturity models: Implications for small and medium-sized enterprises (SMEs). Journal of Manufacturing Systems. 49, October, P. 194-214.
- Mori, J., Kajikawa, Y. Kashima, H. Sakata. I. (2012). Machine Learning Approach for Finding Business Partners and Building Reciprocal Relationships. Expert Systems with Applications 39 (12): 10402–10407.
- Myers, M. B., Daugherty, P. J. Autry, C.W. (2000). The Effectiveness of Automatic Inventory Replenishment in Supply Chain Operations: Antecedents and Outcomes. Journal of Retailing 76 (4): 455–481.
- Nikolopoulos, K. I., Zied Babai, M. Bozos. K. (2016). Forecasting Supply Chain Sporadic Demand with Nearest Neighbor Approaches. International Journal of Production Economics 177: 139–148.
- Nitsche, B. (2021). Exploring the Potentials of Automation in Logistics and Supply Chain Management: Paving the Way for Autonomous Supply Chains, journal of Logistics,5(3), 51-63.
- Oleśków-Szłapka, J. Wojciechowski, H., Domański, R. (2019). Logistics 4.0 Maturity Levels Assessed Based on GDM (Grey Decision Model) and Artificial Intelligence in Logistics 4.0 -Trends and Future Perspective, Procedia Manufacturing 39 1734–1742.
- Proença, D, Borbinha, J. (2016). Maturity Models for Information Systems - A State of the Art, Procedia Computer Science 100, 1042 – 1049.
- Phuong Vu, T, Grant, D.B, Menachof, D.A, (2021). Exploring logistics service quality in Hai Phong, Vietnam, The Asian Journal of Shipping and Logistics, 36, 54–64.
- Ramos, L.F.P., Louresa E. F. R., Deschamps F. (2021). An Analysis of Maturity Models and Current State Assessment of Organizations for Industry 4.0 Implementation, Procedia Manufacturing 51, P.1098–1105.
- Ranjbar, R, Mohammadi, A, Hamidi, N. (2018). Increasing the level of invincibility and reducing the cost of supply chain based on radio frequency identification technology, Journal of strategic management in industrial systems, 13 (46). P.14-29(in persian)
- Rashidi torbati, SH. Rdfar, R, Pilevari, N. (2021). Supply Chain Intelligence with IoT Approach (Case study: Companies active in the field of information and communication technology in Tehran province), Journal of strategic management in industrial systems, 16 (58). P.14-29(in persian).
- Reay, J. H., Colaianni, A. J., Harleston, E. F., Maletic, A., Marcus, J. G. (2006). Logistics maturity evaluator (Report No. IR509R1). LMI Research Institute. Retrieved from http://www.dtic.mil/dtic/tr/fulltext/u2/a457193.pdf.
- Richards, G. Grinsted, S. (2013). The Logistics and Supply Chain Toolkit: Over 90 Tools for Transport, Warehousing and Inventory Management, USA, Kogan Page Publishers.
- Sakai, T, Beziat, A, Heitz, A, (2020). Location factors for logistics facilities: Location choice modeling considering activity categories. Journal of Transport Geography85:102710.
- Sanae, Y., Faycal, F. Ahmed M., (2019). A Supply Chain Maturity Model for automotive SMEs: a case study, International Federation of Accountants. 52-13, P. 2044–2049.
- Van der Laan, E.A. Brito, M.P. Vermaesen, S.C. (2007). Logistics Information and Knowledge Management Issues in Humanitarian Aid Organizations ERIM Report Series Reference No. ERS-2007-026-LIS, Available at SSRN: https://ssrn.com/abstract=985724
- Villegas, M. A., Pedregal, D. J. (2019). Automatic Selection of Unobserved Components Models for Supply Chain Forecasting. International Journal of Forecasting 35 (1): 157–169.
- Wen, J., Li, H. Zhu. F. (2018). Swarm Robotics Control and Communications: Imminent Challenges for Next Generation Smart Logistics. IEEE Communications Magazine 56 (7): 102–107.
- Werner-Levandoska, K, Kosacka-Olejnik, M. (2018). Lgistics Maturity Model for Service Company- Theorical Background. Procedia Manufacturing 17, P. 791-802.
- Werner-Lewandowska, M, Olejnik K, (2019), Logistics 4.0 Maturity in Service Industry: Empirical Research Results. Procedia Manufacturing 38, Pages 1058-1065.
- Werner-Lewandowska, M, Olejnik K, (2020), How to improve logistics maturity? – A roadmap proposal for the service industry, Procedia Manufacturing 51, 1650–1656.
- Williams, J. A. S. (2007). A Review of Research Towards Computer Integrated De-manufacturing for Materials Recovery. International Journal of Computer Integrated Manufacturing 20 (8): 773–780.
- Willner, O, Gosling, J, Schönsleben, P. (2016). Establishing a maturity model for design automation in sales-delivery, processes of ETO products, Computers in Industry 82, 57–68.
- Woschank M, Dallasega, P. (2021). The Impact of Logistics 4.0 on Performance in Manufacturing Companies: A Pilot Study, Procedia Manufacturing 55, 487–491.
- Yadas, G., Luthra, S., Jakhar, S. K., Mangla, S. K., & Rai, D. P. (2020). A framework to overcome sustainable supply chain challenges through solution measures of industry 4.0 and circular economy: An automotive case. Journal of Cleaner Production, 254-267.
- Yavas, V. Ozkan-Ozenb, Y.D (2020), Logistics centers in the new industrial era: A proposed framework for logistics center 4.0, Transportation Research Part B. 101864, P 1-18.
- Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). Research commentary—the new organizing logic of digital innovation: an agenda for information systems research. Information systems research, 21(4), 724-735.
|