Internet of things and its challenges in supply chain management; a rough strength-relation analysis method

dc.contributor.authorPishdar, Mahsa
dc.contributor.authorGhasemzadeh, Fatemeh
dc.contributor.authorAntucheviciene, Jurgita
dc.contributor.authorSaparauskas, Jonas
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2018-06-28
dc.date.available2018-06-28
dc.date.issued2018-06-28
dc.description.abstractInternet of Things application (IOT) in supply chain management is becoming imperative and can shape a strategic competitive advantage. Albeit, different challenges appear through this application, most of the previous studies consider less about these challenges and focus on the advantages of IOT. To overcome this defect, different challenges that a supply chain may face as whole are determined based on systematic literature review and expert opinions. Then, a rough group decision-making and trial evaluation laboratory (DEMATEL) is applied. Advantages of the proposed model are that both internal strength and external influence of challenges and also vagueness and ambiguity of experts’ opinions are simultaneously noticed to completely show the importance of these challenges. The results show that challenges such as lack of strategy and scenario planning in IOT, storage issues, lack of security and lack of privacy are of great importance. So, these challenges should have a higher priority in attracting attention and resources. These results help managers to be equipped to face with main challenges in their path toward IOT in their supply chains. Accordingly some practical suggestions for managers are discussed in this paper, such as starting the journey toward IOT step by step, planning for a data storage system which is appropriate for big data, setting up a security policy to prevent out-coming problems caused by lack of security and privacy inherited by IOT, conducting a privacy or security risk assessment, minimizing the data collection and retain and testing the security measures before launching the products, and establishment of a legal framework to construct a problem-solving network in such a messed up and dynamic environment for processing such complicated huge data.en
dc.formattext
dc.format.extent15 strancs
dc.identifier.doi10.15240/tul/001/2018-2-014
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/26424
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.ispartofAddo-Tenkorang, R., & Helo, P. T. (2016). Big data applications in operations/supply-chain management: A literature review. Computers & Industrial Engineering, 101, 528-543. https://dx.doi.org/10.1016/j.cie.2016.09.023.cs
dc.relation.ispartofAtzori, L., Iera, A., & Morabito, G. (2017). Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Networks, 56, 122-140, https://dx.doi.org/10.1016/j.adhoc.2016.12.004.cs
dc.relation.ispartofBanafa, A. (2016). IOT Standardization and Implementation Challenges. IEEE. Retrieved April 2017 from http://IOT.ieee.org/newsletter/july-2016/IOT-standardization-and-implementation-challenges.html.cs
dc.relation.ispartofChen, Y., Lee, G. M., Shu, L., & Crespi, N. (2016). Industrial internet of things-based collaborative sensing intelligence: framework and research challenges. Sensors, 16(2), 215, https://dx.doi.org/10.3390/s16020215.cs
dc.relation.ispartofDebnath, A., Roy, J., Kar, S., Zavadskas, E. K., & Antucheviciene, J. (2017). A hybrid MCDM approach for strategic project portfolio selection of agro by-products. Sustainability, 9(8), 1302. https://dx.doi.org/10.3390/su9081302.cs
dc.relation.ispartofDutton, W. H. (2014). Putting things to work: social and policy challenges for the Internet of things. Info, 16(3), 1-21. https://dx.doi.org/10.1108/info-09-2013-0047.cs
dc.relation.ispartofEbrahimnejad, S., Naeini, M. A., Ebrahimnejad, & Mousavi, S. (2017). Selection of IT outsourcing services’ activities considering services cost and risks by designing an interval-valued hesitant fuzzy-decision approach. Journal of Intelligent & Fuzzy Systems, 32(6), 4081-4093. https://dx.doi.org/10.3233/JIFS-152520.cs
dc.relation.ispartofFarahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., & Mankodiya, K. (2017). Towards fog-driven IOT eHealth: Promises and challenges of IOT in medicine and healthcare. Future Generation Computer Systems, 78(2), 659-676. https://dx.doi.org/10.1016/j.future.2017.04.036.cs
dc.relation.ispartofFernandez-Gago, G., Moyano, F., & Lopez, J. (2017). Modelling Trust Dynamics in the Internet of Things. Information Sciences, 396, 72-82. https://dx.doi.org/10.1016/j.ins.2017.02.039.cs
dc.relation.ispartofForoozesh, N., Tavakkoli-Moghaddam, R., & Mousavi, S. M. (2017). Resilient Supplier Selection in a Supply Chain by a New Interval-Valued Fuzzy Group Decision Model Based on Possibilistic Statistical Concepts. Journal of Industrial and Systems Engineering, 10(2), 113-133.cs
dc.relation.ispartofGandhi, S., Mangla, S. K., Kumar, P., & Kumar, D. (2015). Evaluating factors in implementation of successful green supply chain management using DEMATEL: A case study. International Strategic Management Review, 3(1-2), 96-109. https://dx.doi.org/10.1016/j.ism.2015.05.001.cs
dc.relation.ispartofGill, A. Q., Phennel, N., Lane, D., & Phung, V. L. (2016). IOT-enabled Emergency Information Supply Chain Architecture for Elderly People: The Australian Context. Information Systems, 58, 75-86, https://dx.doi.org/10.1016/j.is.2016.02.004.cs
dc.relation.ispartofHsu, C. W., & Yeh, C. C. (2016). Understanding the factors affecting the adoption of the Internet of Things. Technology Analysis & Strategic Management, 29(9), 1089-1102, https://dx.doi.org/10.1080/09537325.2016.1269160.cs
dc.relation.ispartofIERC. (2015). Internet of Things- IOT Governance, Privacy and Security Issues. European Research Cluster on The Internet Of Things.cs
dc.relation.ispartofJian, L., Liu, S., & Lin, Y. (2011). Hybrid Rough Sets and Applications in Uncertain Decision-Making. Auerbach Publications.cs
dc.relation.ispartofKees, A., Oberländer, A., Röglinger, M., & Rosemann, M. (2015). Understanding the Internet of Things: A Conceptualisation of Business-To-Thing (B2T) Interactions. In The Proceedings of Twenty-Third European Conference on Information Systems (ECIS) (pp. 1-16). Münster, Germany.cs
dc.relation.ispartofKim, S., & Kim, S. (2016). A multi-criteria approach toward discovering killer IOT application in Korea. Technological Forecasting and Social Change, 102, 143-155, https://dx.doi.org/10.1016/j.techfore.2015.05.007.cs
dc.relation.ispartofKrotov, V. (2017). The Internet of Things and new business opportunities. Business Horizons, 60(6), 831-841. https://doi.org/10.1016/j.bushor.2017.07.009.cs
dc.relation.ispartofLee, H. (2017). Framework and development of fault detection classification using IOT device and cloud environment. Journal of Manufacturing Systems, 43(2), 257-270. https://dx.doi.org/10.1016/j.jmsy.2017.02.007.cs
dc.relation.ispartofLiou, J. J. H., Tamosaitiene, J., Zavadskas, E. K., Tzeng, G. H. (2016). New hybrid COPRAS-G MADM model for improving and selecting suppliers in green supply chain management. International Journal of Production Research, 54(1), 114-134. https://dx.doi.org/10.1080/00207543.2015.1010747.cs
dc.relation.ispartofLu, M. T., Lin, S. W., & Tzeng, G. H. (2013). Improving RFID adoption in Taiwan's healthcare industry based on a DEMATEL technique with a hybrid MCDM model. Decision Support Systems, 56, 259-269. https://dx.doi.org/10.1016/j.dss.2013.06.006.cs
dc.relation.ispartofMardani, A., Nilashi, M., Antucheviciene, J., Tavana, M., Bausys, R., & Ibrahim, O. (2017). Recent fuzzy generalisations of rough sets theory: a systematic review and methodological critique of the literature. Complexity, 2007. https://dx.doi.org/10.1155/2017/1608147.cs
dc.relation.ispartofMital, M., Choudhary, P., Chang, V., Papa, A., & Pani, A. K. (2017). Adoption of Internet of Things in India: A test of competing models using a structured equation modeling approach. Technological Forecasting & Social Change, In Press. https://dx.doi.org/10.1016/j.techfore.2017.03.001.cs
dc.relation.ispartofMeola, M. (2016). How IOT logistics will revolutionize supply chain management. Retrieved 10th August, 2017, from http://www.businessinsider.com/internet-of-things-logistics-supply-chain-management-2016-10.cs
dc.relation.ispartofPark, K. C., & Shin, D. H. (2017). Security assessment framework for IOT service. Telecommunication Systems, 64(1), 193-209. https://dx.doi.org/10.1007/s11235-016-0228-5.cs
dc.relation.ispartofPourahmad, A., Hosseini, A., Banaitis, A., Nasiri, H., Banaitienė, N., & Tzeng, G. H. (2015). Combination of fuzzy–AHP and DEMATEL–ANP with GIS in a new hybrid MCDM model used for the selection of the best space for leisure in a blighted urban site. Technological and Economic Development of Economy, 21(5), 773-796. https://dx.doi.org/10.3846/20294913.2015.1056279.cs
dc.relation.ispartofRajesh, R., & Ravi, R. (2015). Modeling enablers of supply chain risk mitigation in electronic supply chains: A Grey–DEMATEL approach. Computers & Industrial Engineering, 87, 126-139. https://dx.doi.org/10.1016/j.cie.2015.04.028.cs
dc.relation.ispartofRiahi Sfar, A., Natalizio, E., Challal, Y., & Chtourou, Z. (2017). A Roadmap for Security Challenges in Internet of Things. Digital Communications and Networks. In press. https://doi.org/10.1016/j.dcan.2017.04.003.cs
dc.relation.ispartofSaarikko, T., Westergren, U. H., & Blomquist, T. (2017). The Internet of Things: Are you ready for what’s coming? Business Horizons, 60(5), 667-676. https://dx.doi.org/10.1016/j.bushor.2017.05.010.cs
dc.relation.ispartofShankar, U. (2017). How the Internet of Things Impacts Supply Chains. In bound Logistics, white paper. Retrieved 10th April, 2017, from http://www.inboundlogistics.com/cms/article/how-the-internet-of-things-impacts-supply-chains/cs
dc.relation.ispartofSong, W., Ming, X., & Liu, H. C. (2017). Identifying critical risk factors of sustainable supply chain management: A rough strength-relation analysis method. Journal of Cleaner Production, 143, 100-115. https://dx.doi.org/10.1016/j.jclepro.2016.12.145.cs
dc.relation.ispartofSupeekit, T., Somboonwiwat, T., & Kritchanchai, D. (2016). DEMATEL-modified ANP to evaluate internal hospital supply chain performance. Computers & Industrial Engineering, 102, 318-330. https://dx.doi.org/10.1016/j.cie.2016.07.019.cs
dc.relation.ispartofTeixeira, F. A., Pereira, F. M. Q., Wong, H. C., Nogueira, J. M. S., & Oliveira, L. B. (2017). SIOT: Securing Internet of Things through distributed systems analysis. Future Generation Computer Systems. In Press. https://doi.org/10.1016/j.future.2017.08.010.cs
dc.relation.ispartofVerdouw, C. N., Beulens, A. J. M., & van der Vorst, J. G. A. J. (2013). Virtualisation of floricultural supply chains: A review from an Internet of Things perspective. Computers and Electronics in Agriculture, 99, 160-175. https://dx.doi.org/10.1016/j.compag.2013.09.006.cs
dc.relation.ispartofVerdouw, C. N., Wolfert, J., Beulens, A. J. M., & Rialland, A. (2015). Virtualization of food supply chains with the internet of things. Journal of Food Engineering, 176, 128-136, https://dx.doi.org/10.1016/j.jfoodeng.2015.11.009.cs
dc.relation.ispartofVinton, G. C., Ryan, P. S., Senges, M., & Whitt, R. S. (2016). IOT Safety and Security as Shared Responsibility. Journal of Business Informatics, 35(1), 7-19.cs
dc.relation.ispartofWeber, R. H. (2013). Internet of things – Governance quo vadis? Computer Law & Security Review, 29(4), 341-347. https://dx.doi.org/10.1016/j.clsr.2013.05.010.cs
dc.relation.ispartofWoodside, A. G., Megehee, C. M., & Sood, S. (2012). Conversations with (in) the collective unconscious by consumers, brands, and relevant others. Journal of Business Research, 65(5), 594-602. https://dx.doi.org/10.1016/j.jbusres.2011.02.016.cs
dc.relation.ispartofYupeng, L., Yifei, C., & Tzeng, G. H. (2017). Identification of key factors in consumers’ adoption behavior of intelligent medical terminals based on a hybrid modified MADM model for product improvement. International Journal of Medical Informatics, 105, 68-82, https://dx.doi.org/10.1016/j.ijmedinf.2017.05.017.cs
dc.relation.ispartofZarpelão, B. B., Miani, R. S., Kawakani, C. T., & Alvarenga, S. T. (2017). A survey of intrusion detection in Internet of Things. Journal of Network and Computer Applications, 84, 25-37. https://dx.doi.org/10.1016/j.jnca.2017.02.009.cs
dc.relation.ispartofZhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2009). Design concept evaluation in product development using rough sets and gray relation analysis. Expert Systems with Application, 36(3), 7072-7079. https://dx.doi.org/10.1016/j.eswa.2008.08.068.cs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectgroup decision makingen
dc.subjectgroup DEMATELen
dc.subjectinternet of things (IOT)en
dc.subjectrisk managementen
dc.subjectrough set theoryen
dc.subjectsupply chain managementen
dc.subject.classificationO33
dc.subject.classificationD81
dc.subject.classificationM15
dc.titleInternet of things and its challenges in supply chain management; a rough strength-relation analysis methoden
dc.typeArticleen
local.accessopen
local.citation.epage222
local.citation.spage208
local.facultyFaculty of Economics
local.filenameEM_2_2018_14
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue2
local.relation.volume21
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
EM_2_2018_14.pdf
Size:
1.47 MB
Format:
Adobe Portable Document Format
Description:
Článek
Collections