Disruptive and Conventional Technologies for the Support of Logistics Processes: A Literature Review

The supply chain has become a key element of increasing the productivity and competitiveness of companies. To achieve this, it is essential to implement a strategy based on the use of technologies, which depends on knowledge of the scope and impact of logistics technologies. Therefore, this article aims to identify the main technologies supporting logistics management and supply chain processes to establish their functionality, scope, and impacts. For this, conventional technologies and technologies framed by the concept of Industry 4.0 that allow the implementation of Logistics 4.0 in companies are analyzed. As a result of searching databases such as Scopus, Web of Science, and Science Direct, we provide an analysis of 18 technologies focusing on their definition, scope, and the logistics processes involved. This study concludes that technologies in logistics management allow for a reduction in total costs, improve collaboration with suppliers and customers, increase the visibility and traceability of products and information, and support decision-making for all agents in the supply chain, including the final consumer.

Industry 4.0; Logistics 4.0; Logistics; Supply chain management; Technologies

        Logistics management plays a vital role in supply chains, as it is responsible for the efficient and effective flow of goods, services, information, and finances within and between organizations to satisfy an end consumer. To achieve this, logistics management must support its business processes with technologies that efficiently record, store, process, and deliver information related to procurement, warehousing, production management, service management, transportation, distribution, customer service, final products disposal, and other operations covered by logistics management (Winkelhaus and Grosse, 2019). In this way, supply chains add value by processing information and providing timely support forstrategic, tactical, and operational decision-making (Tang and Veelenturf, 2019); achieving sustainability (Thöni and Tjoa, 2017); and providing better customer service through the visibility and traceability of orders and requests pertaining to the company performing these logistics operations (Barreto et al., 2017).

Likewise, technologies support the real-time decisions of logistics processes by transforming the data collected in the supply chain into effective and efficient supply chain decisions (Villalobos et al., 2019), in turn providing the technological infrastructure required by Industry 4.0 to support complex virtual and physical systems (da Silva et al., 2019). Other benefits of technologies in the logistics supply chain include decision-making support; the facilitation of information exchange and real-time management for supply chain execution (Perego et al., 2011); the provision of accurate and sufficient information at the right time in the right format to the right person (Wijewickrama et al., 2021); an increase in cross channel visibility and incentives; the analysis of tradeoffs; and complexity optimization, among others (Gunasekaran et al., 2017).

The rapid development of technologies increases the number and scope of the tools applicable to several logistics processes, while rising internet penetration in society and organizations generates a pressure to implement technologies to support logistics processes (Gunasekaran et al., 2017). Similarly, the development of the Internet of Things (IoT) and the massive volume of data generated, received, and stored in organizations demand the implementation of technologies supported by techniques such as Big Data analytics, cloud services, and artificial intelligence, among others, to obtain added value in business processes through predictive, prescriptive, and descriptive approaches (Tang and Veelenturf, 2019). This situation has caused an increase in the number of information and communication technologies (ICTs) that can be implemented in logistics processes, which impedes decision-making about which technology is more convenient to implement in these processes.

Several reviews related to technologies and logistics can be found in the literature. Some of them are focused on specific topics such as freight transportation (Perego et al., 2011); the contribution of information technology (IT) to competitive advantage within logistics and supply chains (Gunasekaran et al., 2017); technology development to support the real-time decisions of fresh food logistics (Villalobos et al., 2019); the potential, influence, and status of research on blockchain technology in logistics and supply chain management (Gurtu and Johny, 2019; Wang et al., 2019; Musigmann et al., 2020; Paliwal et al., 2020); technology transfer in the supply chain oriented to Industry 4.0 (da Silva et al., 2019); the relationships between information and digital technologies of Industry 4.0 and lean supply chain management (Núñez-Merino et al., 2020); information sharing in reverse logistics supply chains (Wijewickrama et al., 2021); trends toward new technologies in logistics (Lagorio et al., 2020); and IT adoption and its role in supply chain management (Sorooshian and Teck, 2020).

However, there is no study analyzing the main technologies (both conventional technologies and technologies framed by the concept of Industry 4.0) supporting logistics management and supply chain processes, and establishing these technologies’ functionality, impacts, and scope for logistics systems. Consequently, this article focuses on the following main research questions:

RQ1. What are the main technologies supporting logistics management and supply chain processes?

RQ2. What are the logistics systems addressed by the main technologies considered in the literature?

    Globalization, business competition, and the development of business technologies have induced industries to manufacture products at low cost, with better quality and availability for the market. This requires rapid technological adoption to make an important differentiation between productive organizations regarding logistics efficiency. This implies that companies must make significant investments in acquiring, updating, and maintaining technological infrastructure, considering the adoption of traditional technologies such as CPFR, EDI, E-Procurement, ERP, GPS and GPRS, Pick-to-Light and Pick-by-Voice, RFID, S&OP, TMS, and WMS with disruptive technologies of Logistics 4.0 including additive manufacturing, augmented reality, Big Data analytics, cloud services, wearable technology, and IoT. This situation generates challenges in complementing and updating technologies that have been appropriated in logistics processes to enable a transition toward Logistics 4.0 to increase efficiency and fulfil the requirements of customers and consumers. This approach allows logistics systems to respond quickly to costumers, increase the traceability and visibility of orders in real time, and facilitate collaborative decision-making with other agents in the supply chain.

Barreto, L., Amaral, A., Pereira, T., 2017. Industry 4.0 Implications in Logistics: An Overview. Procedia Manufacturing, Volume 13, pp.1245–1252

Baruffaldi, G., Accorsi, R., Manzini, R., 2019. Warehouse Management System Customization and Information Availability in 3pl Companies: A Decision-Support Tool. Industrial Management and Data Systems, Volume 119(2), pp. 251–273

Büyüközkan, G., Güler, M., Uztürk, D., 2016. Selection of Wearable Glasses in the Logistics Sector. In: International Logistics and Supply Chain Congress. Izmir, Turkey: Ege University, pp. 377–385

Cano, J.A., Ayala, C., 2019. Logistics Education for Business Management Students: A Learning- Doing and Service-Learning Approach. International Journal of Innovation, Creativity and Change, Volume 9(3), pp. 46–55

Cano, J.A., Baena, J.J., 2015a. Impact of Information and Communication Technologies in International Negotiation Performance. Review of Business Management, Volume 17(54), pp. 751–768

Cano, J.A. Baena, J.J., 2017. Limitations in the Use and Appropriation of ICT for International Negotiation in Colombian Companies. Observatorio, Volume 11(1), pp. 111–133

Cano, J.A., Baena, J.J., 2015b. Trends in the Use of Information and Communication Technologies for International Negotiation. Estudios Gerenciales, Volume 31(136), pp. 335–346

Cano, J.A., Salazar, F., Gómez-montoya, R.A., 2020. ICT Validation Methodologies for Logistics Management. International Journal of Supply Chain Management, Volume 9(5), pp. 1157–1163

Chuang, C-H., Lee, D-H., Chang, W-J., Weng, W-C., Shaikh, M.O., Huang, C-L., 2017. Real-Time Monitoring via Patch-Type Piezoelectric Force Sensors for Internet of Things Based Logistics. IEEE Sensors Journal, Volume 17(8), pp. 2498–2506

Correa, A.A., Gómez, R.A., Cano, J.A., 2010. Warehouse Management and Information and Communication Technology. Estudios Gerenciales, Volume 26(117), pp. 145–171

Demiray, A., Akay, D., Tekin, S., Boran, F.E., 2017. A Holistic and Structured CPFR Roadmap with an Application between Automotive Supplier and Its Aftermarket Customer. International Journal of Advanced Manufacturing Technology, Volume 91(5–8), pp. 1567–1586

Durach, C.F., Kurpjuweit, S., Wagner, S.M., 2017. The Impact of Additive Manufacturing on Supply Chains. International Journal of Physical Distribution and Logistics Management, 47(10), pp. 954–971

da Silva, F.A., 2018. Evaluation of Transportation Management System in logistic operations in a beverage company. Gestão da Produção, Operações e Sistemas, Volume 13(2), pp. 1–20

da Silva, V.L., Kovaleski, J.L., Pagani, R.N., 2019. Technology Transfer in the Supply Chain Oriented to Industry 4.0: A Literature Review. Technology Analysis and Strategic Management, Volume 31(5), pp. 546–562

de Vries, J., de Koster, R., Stam, D., 2015. Exploring the Role of Picker Personality in Predicting Picking Performance with Pick by Voice, Pick to Light and RF-Terminal Picking. International Journal of Production Research, Volume 7543, pp. 1–15

El Ouadaa, S., Bah, S., Berrado, A., 2017. New Classification Framework of ICT Deployments in Supply Chain. In: Proceedings of the International Conference on Industrial Engineering and Operations Management. IEOM Society, pp. 2228–2238

Frigo, M.A., Silva, E.C.C. da., Barbosa, G.F., 2016. Augmented Reality in Aerospace Manufacturing: A Review. Journal of Industrial and Intelligent Information, Volume January 2016

Gonzalez-R, P.L., Cancaa, D., Andrade-Pinedab, J.L., Calle, M., Leon-Blancoa, J.M., 2020. Truck-Drone Team Logistics: A Heuristic Approach to Multi-Drop Route Planning. Transportation Research Part C: Emerging Technologies, Volume 114, pp. 657–680

Gunasekaran, A., Subramanian, N., Papadopoulos, T., 2017. Information Technology for Competitive Advantage within Logistics and Supply Chains: A Review. Transportation Research Part E: Logistics and Transportation Review, Volume 99, pp. 14–33

Gurtu, A., Johny, J., 2019. Potential of Blockchain Technology in Supply Chain Management: A Literature Review. International Journal of Physical Distribution and Logistics Management, Volume 49(9), pp. 881–900

Hasan, M.M., Jiang, D., Ullah, A.M.M.S., Noor-E-Alam, Md., 2020. Resilient Supplier Selection in Logistics 4.0 with Heterogeneous Information. Expert Systems with Applications, Volume 139, 112799, https://doi.org/10.1016/j.eswa.2019.07.016

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, Volume 37(1), pp. 10–36

Karak, A., Abdelghany, K., 2019. The Hybrid Vehicle-Drone Routing Problem for Pick-Up and Delivery Services. Transportation Research Part C: Emerging Technologies, Volume 102, pp. 427–449

Kong, X.T.R., Luo, A., Huang, G.Q., Yang, X., 2018. Industrial Wearable System: The Human-Centric Empowering TechnologyiIn Industry 4.0. Journal of Intelligent Manufacturing, Volume 30, pp. 2853–2869

Kshetri, N., 2018. 1 Blockchain’s Roles in Meeting Key Supply Chain Management Objectives. International Journal of Information Management, Volume 39, pp. 80–89

Lagorio, A., Zenezini, G., Mangano, G., Pinto, R., 2020. A Systematic Literature Review of Innovative Technologies Adopted in Logistics Management. International Journal of Logistics Research and Applications,  https://doi.org/10.1080/13675567.2020.1850661, pp. 1–24

Lee, C.K.M., Lv, Y., Ho, W., Ng, K.K.H., Choy, K.L., 2018. Design and Application of Internet of Things-Based Warehouse Management System for Smart Logistics. International Journal of Production Research, Volume 56(8), pp. 2753–2768

Lee, C.K.M., Ho, W., Ho, G.T.S., Lau, H.C.W., 2011. Design and Development of Logistics Workflow Systems for Demand Management with RFID. Expert Systems with Applications, Volume 38(5), pp. 5428–5437

Lim, M.K., Bahr, W., Leung, S.C.H., 2013. RFID in the Warehouse: A Literature Analysis (1995-2010) of its Applications, Benefits, Challenges and Future Trends. International Journal of Production Economics, Volume 145(1), pp. 409–430

Lin, C.-C., Yang, J.-W., 2018. Cost-Efficient Deployment of Fog Computing Systems at Logistics Centers in Industry 4.0. IEEE Transactions on Industrial Informatics, Volume 14(10), pp. 4603–4611

Musigmann, B., Von Der Gracht, H., Hartmann, E., 2020. Blockchain Technology in Logistics and Supply Chain Management - A Bibliometric Literature Review from 2016 to January 2020. IEEE Transactions on Engineering Management, Volume 67(4), pp. 988–1007

Naumova, O.N., Ivanova, EA., Prischepa , A.S., Soshnev, A.N.,  Fedyukovsky, A.A., 2020. Analysis of the Influence of Information and Communication Technologies on the Development of Transport and Logistics Activities in the Regions of the Arctic Zone of the RF. In: IOP Conference Series: Earth and Environmental Science, Volume 434(1)

Noroozi, S., Wikner, J., 2017. Sales and Operations Planning in the Process Industry: A Literature Review. International Journal of Production Economics, Volume 188, pp. 139–155

Nunes, K.M., Júnior, J., Costa, L., Souza, M., Alencar, D., Sanches, A., 2019. Proposal for the Implementation of a Transport Management System in a Manaus Conveyor. Journal of Engineering and Technology for Industrial Applications, Volume 5(17), pp. 68–74

Núñez-Merino, M., Maqueira-Marin, J.M., Moyano-Fuentes, J., Martinez-Juardo, P.J., 2020. Information and Digital Technologies of Industry 4.0 and Lean supply Chain Management: A Systematic Literature Review. International Journal of Production Research, 58(16), pp. 5034–5061

Ouali, B.A., Kocaoglu, B., 2016. Criteria for Selecting ERP Systems: A Framework for Logistics Companies. In: International Logistics and Supply Chain Congress. Izmir, Turkey: Ege University, pp. 377–385

Özcan, E., Çimtay, M.A., 2016. Software Application in Supply Chain Management and Examining of Productivity Effects of use “ERP” in Enterprises. In: International Logistics and Supply Chain Congress. Izmir, Turkey: Ege University, pp. 402–408

Paliwal, V., Chandra, S.,  Sharma, S., 2020. Blockchain Technology for Sustainable Supply Chain Management: A Systematic Literature Review and a Classification Framework. Sustainability (Switzerland), Volume 12(18), pp. 1–39

Panahifar, F., Heavey, ., Byrne, P.J., Fazlollahtabar, H., 2015. A Framework for Collaborative Planning, Forecasting and Replenishment (CPFR): State of the Art.  Journal of Enterprise Information Management, Volume 28(6), pp. 838-871

Pedroso, C.B., da Silva, A.L., Tate, W.L., 2016. Sales and Operations Planning (S&OP): Insights from a Multi-case Study of Brazilian Organizations. International Journal of Production Economics, Volume 182, pp.213–229

Perego, A., Perotti, S., Mangiaracina, R., 2011. ICT for Logistics and Freight Transportation: A Literature Review and Research Agenda. International Journal of Physical Distribution and Logistics Management, Volume 41(5), pp. 457–483

Perera, S., Dawande, M., Janakiraman, G., Mookerjee, V., 2020. Retail Deliveries by Drones: How Will Logistics Networks Change? Production and Operations Management, Volume 29(9), pp. 2019–2034

Pour, M.A., Zanardini, M., Bacchetti, A., Zanoni, S., 2016. Additive Manufacturing Impacts on Productions and Logistics Systems. IFAC-PapersOnLine, Volume 49(12), pp. 1679–1684

Raj, A., Sah, B., 2019. Analyzing Critical Success Factors for Implementation of Drones in the Logistics Sector using Grey-DEMATEL Based Approach. Computers and Industrial Engineering, Volume 138, 106118, https://doi.org/10.1016/j.cie.2019.106118

Rashid, S., 2013. The Role of Quick Response for Demand Driven Globalized Apparel Supply Chain Management. In J. Xu, M. Yasinzai, & B. Lev, eds. Lecture Notes in Electrical Engineering. Springer-Verlag London, pp. 643–654

Sah, B., Gupta, R., Bani-Hani, D., 2020. Analysis of Barriers to Implement Drone Logistics. International Journal of Logistics Research and Applications, https://doi.org/10.1080/13675567.2020.1782862, pp.1–20

Simbolon, S., Muhammad, Z., Ilham, R.N., 2020. Investigating the Supply Chain Strategy for Enhancing Teacher Performance. International Journal of Innovation, Creativity and Change, Volume 13(3), pp. 531–541

Sorooshian, S., Teck, T.S., 2020. Information Technology for Supply Chain Management: Literature Review. International Journal of Advanced Trends in Computer Science and Engineering, Volume 9(1), pp. 80–86

Stoltz, M.H., Giannikas, A., McFarlane, D., Strachan, J., Um, J., Srinivasan, R., 2017. Augmented Reality in Warehouse Operations: Opportunities and Barriers. IFAC-PapersOnLine, Volume 50(1), pp. 12979–12984

Sun, J., 2012. Design and Implementation of IOT-based Logistics Management System. In: Proceedings - 2012 IEEE Symposium on Electrical and Electronics Engineering, EEESYM 2012, pp. 603–606

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, Volume 129, pp. 1–11

Thöni, A., Tjoa, A.M., 2017. Information Technology for Sustainable Supply Chain Management: A Literature Survey. Enterprise Information Systems, Volume 11(6), pp. 828–858

Thürer, M., Pan., Y.H., Qu, T., Luo, H., 2016. Internet of Things (Iot) Driven Kanban System for Reverse Logistics: Solid Waste Collection. Journal of Intelligent Manufacturing, Volume 30(4), pp. 1–10

Tiwari, S.T.S., Chan, S.W., Ahmad, M.F., Zaman, I., 2019. Application and Implementation of e-Procurement Technologies in Malaysian Manufacturing Firm. International Journal of Supply Chain Management, Volume 8(2), pp. 923–929

Tokta?-Palut, P., Baylava, E., Teoman, S., Altunbey, M., 2014. The Impact of Barriers and Benefits of e-Procurement on its Adoption Decision: An Empirical Analysis. International Journal of Production Economics, Volume 158, pp. 77–90

Villalobos, J.R., Soto-Silva, W.E., González-Araya, M.C., González–Ramirez, R.G., 2019. Research Directions in Technology Development to Support Real-Time Decisions of Fresh Produce Logistics: A Review and Research Agenda. Computers and Electronics in Agriculture, Volume 167, 105092, https://doi.org/10.1016/j.compag.2019.105092

Wang, G., Gunasekarana, A., Ngaib, E.W.T., Papadopoulos, T., 2016. Big Data Analytics in Logistics and Chain Management: Certain Investigations for Research and Applications. International Journal of Production Economics, 176, pp.98–110

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, Volume 24(1), pp. 62–84

Wijewickrama, M.K.C.S., Chileshe, N., Rameezdeen, R., Ochoa, J.O., 2021. Information Sharing in Reverse Logistics Supply Chain of Demolition Waste: A Systematic Literature Review. Journal of Cleaner Production, Volume 280(Part 1), 124359, https://doi.org/10.1016/j.jclepro.2020.124359

Winkelhaus, S., Grosse, E.H., 2019. Logistics 4.0: A Systematic Review Towards a New Logistics System. International Journal of Production Research, Volume 58(1), pp. 18–43

Xu, Z., He, J., Chen, Z., 2012. Design and Actualization of IoT-Based Intelligent Logistics System. In: IEEE International Conference on Industrial Engineering and Engineering Management, pp. 2245–2248

Zhong, R.Y., Huanga, G.Q., Lana, S., Dai, Q.Y., Xu, C., Zhang, T.,  2015. A Big Data Approach for Logistics Trajectory Discovery from RFID-Enabled Production Data. International Journal of Production Economics, Volume 165, pp. 260–272