Developing an Internet of Things-based Intelligent Transportation Technology Roadmap in the Food Cold Supply Chain

Document Type : Research Paper

Authors

1 Associate Prof., Department of Management, Faculty of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran.

2 Prof., Department of Management, Faculty of Management, Tarbiat Modares University, Tehran, Iran.

3 Ph.D. Candidate, Department of Industrial Management, College of Farabi, University of Tehran, Qom, Iran.

4 Lecture, Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.

Abstract

Objective: The Fourth Industrial Revolution affected all industries and transformed the digital, cyber, and real worlds in the supply chains of corporations. Internet of Things (IoT) is one of the emerging technologies that mostly manifests the fourth industrial revolution. As the future of the food industry is tied to the design and management of supply chains enabled by technologies such as the IoT, this paper is to provide a model for developing an IoT-based intelligent transportation technology roadmap based on alternative IoT scenarios in the food-producing cold supply chain.
Methods: In this study, scenarios were developed using qualitative methods such as the PESTEL framework and content analysis, based on the critical uncertainty method or GBN, through open semi-structured interviews with experts in the food industry and IoT. After identifying the best IoT technology stock for each selected scenario, a roadmap was developed using the T-plan quick-start method during a tow-day-interactive workshop.
Results: Communication infrastructure and time horizon of technology development were recognized as the most important uncertainties for applying IoT technology in refrigerated transportation of food cold supply chain in producing companies. Finally, “Mutation Alone” and “Ascent Slow” scenarios were selected and technology roadmaps were developed for each scenario in three layers.
Conclusion: Food companies with cold supply chains can use one of the roadmaps presented in this paper as guidelines to equip their transport fleet with IoT technology based on their current situation and choose one of the two selected scenarios. This would enable them to plan, control, and manage the cold transportation chain process by digitally monitoring, tracing, and information sharing in an efficient and effective way.

Keywords

References

Abdel-Basset, M., Manogaran, G. & Mohamed, M. (2018). Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems. Future Generation Computer Systems, 86, 614-628.
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M. &Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE communications surveys & tutorials, 17(4), 2347-2376.
Amer, M., Daim, T.U., Jetter, A., 2016. Technology roadmap through fuzzy cognitive mapbased scenarios: the case of wind energy sector of a developing country. Technology Analysis and Strategic Management, 28 (2), 131–155.
Anvari, Z., Kamousi, Z. & Rafiey Mehr, B. (2012) Connected Vehicle Technology: An Overview of Concepts and Application. Journal of industrial technology development, 9(18), 73-82. (in Persian)
Atzori, L., Iera, A. & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787-2805.
Babbie, E. (2013). The basics of social research. Cengage learning. Stamford, CT.
Barreto, L., Amaral, A. & Pereira, T. (2017). Industry 4.0 implications in logistics: an overview. Procedia Manufacturing, 13, 1245-1252.
Bo, Y. & Danyu, L. (2009). Application of RFID in cold chain temperature monitoring system, Second ISECS International Colloquium on Computing, Communication, Control, and Management, CCCM, pp. 258-261.
Börjeson, L., Höjer, M., Dreborg, K. H., Ekvall, T. & Finnveden, G. (2006). Scenario types and techniques: towards a user’s guide. Futures, 38(7), 723-739.
Campos, Y. & Villa, J. L. (2018, November). Technologies applied in the monitoring and control of the temperature in the Cold Chain. IEEE 2nd Colombian Conference on Robotics and Automation (CCRA), pp. 1-6
Chunling, S. (2012). Application of RFID Technology for Logistics on Internet of Things, AASRI Procedia, 1, 106-111.
Crainic, T. G., Gendreau, M. & Potvin, J. Y. (2009). Intelligent freight-transportation systems: Assessment and the contribution of operations research. Transportation Research Part C: Emerging Technologies, 17(6), 541-557.
Danaeifard, H., Mozaffari, Z. (2009) Promoting Validity and Reliability in Qualitative Management Research: Reflections on Research Auditing Strategies, Management Research, 1(1), 131-162. (in Persian)
Dion, C., Bouaanani, N., Tremblay, R., Lamarche, C. P. & Leclerc, M. (2011). Real-time dynamic substructuring testing of viscous seismic protective devices for bridge structures. Engineering structures, 33(12), 3351-3363.
Engel, V. J. L. & Supangkat, S. H. (2014, September). Context-aware inference model for cold-chain logistics monitoring. International Conference on ICT for Smart Society (ICISS) (pp. 192-196).
Fanjun, L. & Zhaojiong, C. (2011). Brief analysis of application of RFID in pharmaceutical cold-chain temperature monitoring system, Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering, pp. 2418-2420.
Filina-Dawidowicz, L. & Stankiewicz, S. (2021). Organization and Implementation of Intermodal Transport of Perishable Goods: Contemporary Problems of Forwarders. In Sustainable Design and Manufacturing 2020 (pp. 543-553). Springer, Singapore.
Geum, Y., Lee, S. & Park, Y. (2014). Combining technology roadmap and system dynamics simulation to support scenario-planning: A case of car-sharing service. Computers & Industrial Engineering, 71, 37-49.
Ghadge, A., Kara, M. E., Moradlou, H. & Goswami, M. (2020). The impact of Industry 4.0 implementation on supply chains. Journal of Manufacturing Technology Management, 31(4), 669-686.
Ghasemi, R., Mohaghar, A., Safari, H. & Akbari Jokar, M.R (2016), prioritizing the applications of internet of things technology in the healthcare sector in Iran: a driver for sustainable development, journal of information technology management, 8(1), 155-176. (in Persian)
Giannopoulos, A. G. (2020, September). Quantifying the role of IT in the ITS sector. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) (pp. 1-6). IEEE.
Giannopoulos, G. A. (2009). Towards a European ITS for freight transport and logistics: results of current EU funded research and prospects for the future. European Transport Research Review, 1(4), 147-161.
Govindan, K. (2018). Sustainable consumption and production in the food supply chain: A conceptual framework. International Journal of Production Economics, 195, 419-431.
Heard, B. R., Taiebat, M., Xu, M. & Miller, S. A. (2018). Sustainability implications of connected and autonomous vehicles for the food supply chain. Resources, conservation and recycling, 128, 22-24.
Iran Telecommunication Research Center (2015), Road map of connected cars applications, Tehran, Iran. (in Persian)
Jideani, A. I., Mutshinyani, A. P., Maluleke, N. P., Mafukata, Z. P., Sithole, M. V., Lidovho, M. U., ... & Matshisevhe, M. M. (2020). Impact of Industrial Revolutions on Food Machinery-An Overview. Journal of Food Research, 9(5).
Jovane, F., Koren, Y., Boer, C., (2003). Present and future of flexible automation: towards new paradigms. CIRP Ann. Manuf. Technol. 52 (2), 543–560
Kajikawa, Y., Kikuchi, Y., Fukushima, Y. & Koyama, M. (2011, July). Utilizing risk analysis and scenario planning for technology roadmapping: A case in energy technologies. In 2011 Proceedings of PICMET’11: Technology Management in the Energy Smart World (PICMET), pp. 1-5.
Kumar, S. & Mukherjee, S. (2021). Monitoring Food Quality in Supply Chain Logistics. In Research in Intelligent and Computing in Engineering (pp. 781-786). Springer, Singapore.
Lakshmi, V. & Vijayakumar, S. (2012). Wireless sensor network based alert system for cold chain management, Procedia Engineering, 38, 537-543.
Lee, W. H., Tseng, S. S. & Shieh, W. Y. (2010). Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system. Information Sciences, 180(1), 62-70.
Li, Y. N., Peng, Y. L., Zhang, L., Wei, J. F. & Li, D. (2015). Quality monitoring traceability platform of agriculture products cold chain logistics based on the internet of things. Chemical Engineering Transactions, 46, 517-522.
Li, Y., Hou, M., Liu, H. & Liu, Y. (2012). Towards a theoretical framework of strategic decision, supporting capability and information sharing under the context of Internet of Things. Information Technology and Management, 13(4), 205-216.
Liu, L. & Jia, W. (2010, September). Business model for drug supply chain based on the internet of things. In 2010 2nd IEEE InternationalConference on Network Infrastructure and Digital Content, pp. 982-986.
Lizaso, F. & Reger, G. (2004). Linking roadmapping and scenarios as an approach for strategic technology planning. International Journal of Technology Intelligence and Planning, 1(1), 68-86.
Long, T. & Johnson, M. (2000). Rigour, reliability and validity in qualitative research. Clinical effectiveness in nursing, 4(1), 30-37.
Luo, H., Zhu, M., Ye, S., Hou, H., Chen, Y. & Bulysheva, L. (2016). An intelligent tracking system based on internet of things for the cold chain. Internet Research, 26(2), 435-445.
McQueen, B. & McQueen, J. (1999). Intelligent transportation systems architectures.
Minelli, S., Izadpanah, P. & Razavi, S. (2015). Evaluation of connected vehicle impact on mobility and mode choice. Journal of traffic and transportation engineering, 2(5), 301-312.
Mirzaie, M. (2016) Future business model design pattern in Iran software industry using scenario and roadmap merger. Phd thesis, University of Tehran, Tehran, Iran.
(in Persian)
Mohammadzadeh, A.K., Ghafoori, S., Mohammadian, A., Mohammadkazemi, R., Mahbanooei, B. & Ghasemi, R. (2018). A Fuzzy Analytic Network Process (FANP) approach for prioritizing internet of things challenges in Iran. Technology in Society, 53, 124-134.
Mulani, Tanjim T., & Subash V. Pingle. (2016). Internet of things. International Research Journal of Multidisciplinary Studies, 2(3).
Ng, I., Scharf, K., Pogrebna, G. &Maull, R. (2015). Contextual variety, Internet-of-Things and the choice of tailoring over platform: Mass tilizationn strategy in supply chain management. International Journal of Production Economics, 159, 76-87.
Pagani M. (2009). Roadmapping 3G mobile TV: strategic thinking and scenario planning through repeated cross-impact handling, Technological Forecasting and Social Change, 76 (3) 382–395.
Pang, Z., Chen, Q., Han, W. & Zheng, L. (2015). Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion. Information Systems Frontiers, 17(2), 289-319.
Phaal, R. & Muller, G. (2009). An architectural framework for roadmapping: Towards visual strategy. Technological forecasting and social change, 76(1), 39-49.
Phaal, R., Farrukh, C. & Probert, D. (2001). Technology Roadmapping: linking technology resources to business objectives. Centre for Technology Management, University of Cambridge, 1-18.
Porter, M., Heppelmann, J. (2018). How Smart, Connected Products Are Transforming Competition. Harvard Business Review. Disponível em: https://hbr.org/2014/11/ howsmart-connected-products-are-transforming-competition. Acessado em 15 fev.
Rani, P., Jain, V., Joshi, M., Khandelwal, M. & Rao, S. (2021). A Secured Supply Chain Network for Route Optimization and Product Traceability Using Blockchain in Internet of Things. In Data Analytics and Management (pp. 637-647). Springer, Singapore.
Robinson, D. K. & Propp, T. (2008). Multi-path mapping for alignment strategies in emerging science and technologies. Technological Forecasting and Social Change, 75(4), 517-538
Schiele, H., Bos-Nehles, A., Delke, V., Stegmaier, P. & Torn, R. J. (2021). Interpreting the industry 4.0 future: technology, business, society and people. Journal of Business Strategy.
Schwartz, P. (1991). The Art of Long View. New York: Bantam Doubleday Dell Publishing Group.
Son, C., Kim, J. & Kim, Y. (2020). Developing scenario-based technology roadmap in the big data era: an tilization of fuzzy cognitive map and text mining techniques. Technology Analysis & Strategic Management, 32(3), 272-291.
Strozzi, F., Colicchia, C., Creazza, A. & Noè, C. (2017). Literature review on the "Smart Factory" concept using bibliometric tools. International Journal of Production, 4, 512-514. https://doi.org/10.1080/00207543.2017.1326643
Suharto, Y. (2013). Study of multi-scenario based technology roadmapping: Bayesian causal maps approach. In 2013 Proceedings of PICMET’13: Technology Management in the IT-Driven Services (PICMET), pp. 2212-2218.
Talebzadeh Hosseini, S. (2015). Measuring Sustainability Performance of Supply Chain Management Practices Using Fuzzy Inference. Doctoral dissertation, Faculty of Graduate Studies and Research, University of Regina.
Tian, F. (2018). An information system for food safety monitoring in supply chains based on HACCP, blockchain and internet of things. Doctoral dissertation, WU Vienna University of Economics and Business.
Tsang, Y. P., Choy, K. L., Wu, C. H., Ho, G. T., Lam, C. H. & Koo, P. S. (2018). An Internet of Things (IoT)-based risk monitoring system for managing cold supply chain risks. Industrial Management & Data Systems, 118(7), 1432-1462.
Tu, M. (2018). An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management: A mixed research approach. The International Journal of Logistics Management, 29(1), 131-151.
Verdouw, C. N., Beulens, A. J., Reijers, H. A. & van der Vorst, J. G. (2015). A control model for object virtualization in supply chain management. Computers in industry, 68, 116-131.
Verdouw, C. N., Wolfert, J., Beulens, A. J. M. & Rialland, A. (2016). Virtualization of food supply chains with the internet of things. Journal of Food Engineering, 176, 128-136.
Vermesan, O. & Friess, P. (Eds.). (2014). Internet of Things-From Research and Innovation to Market Deployment. River Publishers.
Wortmann, F. & Flüchter, K. (2015). Internet of things. Business & Information Systems Engineering, 57(3), 221-224
Xiaorong, Z., Honghui, F., Hongjin, Z. &Hanyu, F. (2015). The design of the internet of things solution for food supply chain. In 5th International Conference on Education, Management, Information and Medicine, Shenyang, China, pp. 314-318.
Xu, L. D. (2020). The contribution of systems science to Industry 4.0. Systems Research and Behavioral Science, 37(4), 618-631.
Yvonna, S. L. (1985). Naturalistic inquiry (Vol. 75). Egon G. Guba (Ed.). Sage.
Zadtootaghaj, P., Mohammadian, A., Mahbanooei, B. & Ghasemi, R. (2019). Internet of Things: A Survey for the Individuals' E-Health Applications. Journal of Information Technology Management, 11(1), 102-129.
Zarei, M., Jamalian, A. & Ghasemi, R. (2017). Industrial guidelines for stimulating entrepreneurship with the internet of things. In The Internet of Things in the Modern Business Environment (pp. 147-166). IGI Global.
Zarei, M., Mohammadian, A. & Ghasemi, R. (2016). Internet of things in industries: A survey for sustainable development. International Journal of Innovation and Sustainable Development, 10(4), 419-442.
Zeng, X., Balke, K. N. & Songchitruksa, P. (2012). Potential connected vehicle applications to enhance mobility, safety, and environmental security (No. SWUTC/12/161103-1). Southwest Region University Transportation Center, Texas Transportation Institute, Texas A & M University System.
Zhang, Y. J. & Chen, E. X. (2014). Comprehensive monitoring system of fresh food cold chain logistics. In Applied Mechanics and Materials (Vol. 602, pp. 2340-2343). Trans Tech Publications Ltd.
Zhu, L., Yu, F. R., Wang, Y., Ning, B. & Tang, T. (2018). Big data analytics in intelligent transportation systems: A survey. IEEE Transactions on Intelligent Transportation Systems, 20(1), 383-398.
Zou, P. X., Zhang, G. & Wang, J. Y. (2006, January). Identifying key risks in construction projects: life cycle and stakeholder perspectives. In Pacific Rim Real Estate Society Conference.
Industrial Management Journal
Volume 14, Issue 2
2022
Pages 195-219

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