A SYSTEMATIC REVIEW ON FLEXIBILITY ENABLERS IN LOGISTICS SURVIVABILITY
DOI:
https://doi.org/10.55197/qjssh.v3i6.200Keywords:
flexibility, technologies, adoption, logistics management, supply chain, logistics service providersAbstract
The demand uncertainty particularly during the outbreak of COVID-19 and the increasing competition of market have imposed pressures on the logistics industry to embrace the technology innovation. The pandemic caused a huge impact on world economies and communities and many companies were struggling to survive in this changing environment, thus leaving a question to the resilience of industry. In this situation, flexibility plays the key role for the logistics industry to recover from the supply chain crisis and get prepared for future uncertainties. This paper aims to provide a comprehensive insight on the technology innovations which enable the function of flexibility in logistics through a systematic literature analysis of papers from 2017 to 2022. Bibliometric analysis and content analysis are the methods used to analyse the multiple sources from different databases. The main research gaps in this paper is the flexibility enablers available in the logistics field, their implications on the logistics operations in terms of survivability performance are analysed and the challenges for the adoption of these flexibility enablers to the logistics service providers (LSPs) are identified. The identified flexibility enablers are blockchain, automated guided vehicle (AGV), drones, big data, radio frequency identification (RFID), cyber-physical system (CPS), sensors, cloud computing, augmented reality (AR), unmanned aerial vehicle (UAV), internet of things (IoT), digital twin, artificial Intelligence (AI) and information and communications technology (ICT). An implication model is set up to show the relationship of these flexibility with the logistics. The barriers to the LSPs to adopt the flexibility enablers are categorised into economic barriers, managerial barriers and operational barriers. Overall, these could provide some suggestions to the LSPs when they are considering the technological transformation and assist technology developers in identifying commercial opportunities.
References
Abideen, A.Z., Sundram, V.P.K., Pyeman, J., Othman, A.K., Sorooshian, S. (2021): Digital Twin Integrated Reinforced Learning in Supply Chain and Logistics. – Logistics 5(4): 22p.
Alalawneh, A.A.F., Alkhatib, S.F. (2020): The barriers to big data adoption in developing economies. – The Electronic Journal of Information Systems in Developing Countries 87(1): 16p.
Asokan, D., Sunny, J., Pillai, V.M., Nath, H.V. (2022): Blockchain technology: a troubleshooter for blood cold chains. – Journal of Global Operations and Strategic Sourcing 15(3): 316-344.
Chalmeta, R., Santos-deLeón, N.J. (2020): Sustainable Supply Chain in the Era of Industry 4.0 and Big Data: A Systematic Analysis of Literature and Research. – Sustainability 12(10): 24p.
Chen, C., Demir, E., Huang, Y., Qiu, R. (2021): The adoption of self-driving delivery robots in last mile logistics. – Transportation Research Part E: Logistics and Transportation Review 146: 17p.
Choi, T.M., Siqin, T. (2022): Blockchain in logistics and production from Blockchain 1.0 to Blockchain 5.0: An intra-inter-organizational framework. – Transportation Research Part E: Logistics and Transportation Review 160: 16p.
Chung, S.H. (2021): Applications of smart technologies in logistics and transport: A review. – Transportation Research Part E: Logistics and Transportation Review 153: 17p.
Cichosz, M., Wallenburg, C.M., Knemeyer, A.M. (2020): Digital transformation at logistics service providers: barriers, success factors and leading practices. – The International Journal of Logistics Management 31(2): 209-238.
Custodio, L., Machado, R. (2019): Flexible automated warehouse: a literature review and an innovative framework. – The International Journal of Advanced Manufacturing Technology 106(1-2): 533-558.
D’Amico, G., Szopik-Depczyńska, K., Dembińska, I., Ioppolo, G. (2021): Smart and sustainable logistics of Port cities: A framework for comprehending enabling factors, domains and goals. – Sustainable Cities and Society 69: 19p.
Dolgui, A., Ivanov, D. (2021): 5G in digital supply chain and operations management: fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. – International Journal of Production Research 60(2): 442-451.
Evangelista, P., Santoro, L., Thomas, A. (2018): Environmental sustainability in third-party logistics service providers: A systematic literature review from 2000-2016. – Sustainability 10(5): 34p
Giusti, R., Manerba, D., Bruno, G., Tadei, R. (2019): Synchromodal logistics: An overview of critical success factors, enabling technologies, and open research issues. – Transportation Research Part E: Logistics and Transportation Review 129: 92-110.
Gözaçan, N., Lafci, I. (2020): Evaluation of Key Performance Indicators of Logistics Firms. – Logistics & Sustainable Transport 11(1): 24-32.
Ivanov, D., Dolgui, A. (2020): Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. – International Journal of Production Research 58(10): 2904-2915.
Jamkhaneh, H.B., Shahin, R., Tortorella, G.L. (2022): Analysis of Logistics 4.0 service quality and its sustainability enabler scenarios in emerging economy. – Cleaner Logistics and Supply Chain 4: 13p.
Karia, N. (2018): Knowledge resources, technology resources and competitive advantage of logistics service providers. – Knowledge Management Research & Practice 16(4): 451-463.
Khatib, E.J., Barco, R. (2021): Optimization of 5G Networks for Smart Logistics. – Energies 14(6): 19p.
Kouhizadeh, M., Saberi, S., Sarkis, J. (2021): Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. – International Journal of Production Economics 231: 21p.
Kshetri, N. (2018): 1 Blockchain’s roles in meeting key supply chain management objectives. – International Journal of Information Management 39: 80-89.
Kumar, K.M. (2022): The influence of sustainable logistic practices and supplier support on logistics transport performance: An empirical review on Malaysian logistics service providers. – Journal of Entrepreneurship, Business and Economics 10(1): 141-176.
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 25(7): 1043-1066.
Lamba, K., Singh, S.P. (2018): Modeling big data enablers for operations and supply chain management. – The International Journal of Logistics Management 29(2): 629-658.
Li, G., Tu, Y., Duan, L., Zhang, J., Huang, L., Wu, W., Lv, Z. (2020): Survival Analysis of Logistics Service Providers: An Empirical Study of Chengdu, Area in China. – Open Journal of Statistics 10(06): 915-935.
Manders, J.H., Caniëls, M.C., Paul, W.T. (2017): Supply chain flexibility: A systematic literature review and identification of directions for future research. – The International Journal of Logistics Management 28(4): 964-1026.
Mogili, R., Ganji, K., Acharyulu, G.V.R.K. (2020): Survivability and Resilience of Supply Chain System Post-Pandemic in India. – Academy of Marketing Studies Journal 24(4): 1-11.
Panayides, P.M., So, M. (2005): Logistics service provider–client relationships. – Transportation Research Part E: Logistics and Transportation Review 41(3): 179-200.
Rey, A., Panetti, E., Maglio, R., Ferretti, M. (2021): Determinants in adopting the Internet of Things in the transport and logistics industry. – Journal of Business Research 131: 584-590.
Sellevold, E., May, T., Gangi, S., Kulakowski, J., McDonnell, I., Hill, D., Grabowski, M. (2020): Asset tracking, condition visibility and sustainability using unmanned aerial systems in global logistics. – Transportation Research Interdisciplinary Perspectives 8: 13p.
Sivarajah, U., Kamal, M.M., Irani, Z., Weerakkody, V. (2017): Critical analysis of Big Data challenges and analytical methods. – Journal of Business Research 70: 263-286.
Sohi, A.J., Bosch-Rekveldt, M., Hertogh, M. (2020): Does flexibility in project management in early project phases contribute positively to end-project performance? – International Journal of Managing Projects in Business 13(4): 665-694.
Sony, M., Naik, S.S. (2019): Ten lessons for managers while implementing Industry 4.0. – IEEE Engineering Management Review 47(2): 45-52.
Sreedevi, R., Saranga, H. (2017): Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation. – International Journal of Production Economics 193: 332-342.
Stączek, P., Pizoń, J., Danilczuk, W., Gola, A. (2021): A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR’s) Operating Environment-A Case Study. – Sensors 21(23): 16p.
Steclik, T., Cupek, R., Drewniak, M. (2022): Automatic grouping of production data in Industry 4.0: The use case of internal logistics systems based on Automated Guided Vehicles. – Journal of Computational Science 62: 13p.
Sun, X., Yu, H., Solvang, W.D., Wang, Y., Wang, K. (2022): The application of Industry 4.0 technologies in sustainable logistics: a systematic literature review (2012–2020) to explore future research opportunities. – Environmental Science and Pollution Research 29(7): 9560-9591.
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.
Testi, D. (2020): Sustainable logistics: Definition, approach and relevance. – Contship Italia Group Official Portal. Retrieved from:
https://www.cswindow.contshipitalia.com/en/sustainable-logistics
Tian, Z., Zhong, R.Y., Vatankhah Barenji, A., Wang, Y.T., Li, Z., Rong, Y. (2020): A blockchain-based evaluation approach for customer delivery satisfaction in sustainable urban logistics. – International Journal of Production Research 59(7): 2229-2249.
Wang, J.J., Chen, H., Rogers, D.S., Ellram, L.M., Grawe, S.J. (2017): A bibliometric analysis of reverse logistics research (1992-2015) and opportunities for future research. – International Journal of Physical Distribution & Logistics Management 47(8): 666-687.
Watson, H.J. (2019): Update Tutorial: Big Data Analytics: Concepts, Technology, and Applications. – Communications of the Association for Information Systems 44(1): 364-379.
Winkelhaus, S., Grosse, E.H. (2019): Logistics 4.0: a systematic review towards a new logistics system. – International Journal of Production Research 58(1): 18-43.
Zafarzadeh, M., Wiktorsson, M., Baalsrud Hauge, J. (2021): A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective. – Logistics 5(2): 32p.
