Evaluating the feasibility of blockchain in logistics operations: A decision framework

Abstract The main purpose of this study is to investigate the feasibility of blockchain technology in logistics industry using a quantitative approach. To this end, a decision framework is proposed based on a multi-criteria decision structure that incorporates AHP into VIKOR under Intuitionistic Fuzzy Theory. This integration presents different solutions and rankings based on different decision-making strategies and also captures uncertainty in the evaluation process. While Intuitionistic Fuzzy AHP calculates the importance weights of the proposed criteria indicated as scalability, privacy, interoperability, audit, latency, visibility, trust, and security, Fuzzy VIKOR ranks the logistics operations demonstrated as materials handling, warehousing, order processing, transportation, packaging, fleet management, labeling, vehicle routing and product returns management. The proposed decision framework was applied in a large-scale logistics company located in Turkey. The findings of this study suggest that while the most important criteria are security, visibility and audit, the most feasible logistics operations proved to be transportation, materials handling, warehousing, order processing and fleet management in a possible blockchain implementation. The decision framework in this study may enable decision makers to evaluate the feasibility of blockchain in logistics operations, which is one of the main research gaps in the current blockchain research. Furthermore, this is the first study that integrates AHP and VIKOR methods under Intuitionistic Fuzzy Theory in the context of blockchain.

[1]  R. Ballou Business Logistics Management , 1991 .

[2]  Serafim Opricovic,et al.  Fuzzy VIKOR with an application to water resources planning , 2011, Expert Syst. Appl..

[3]  Cheng-Fu Chou,et al.  Blockchain: The Evolutionary Next Step for ICT E-Agriculture , 2017 .

[4]  Shuai Wang,et al.  Blockchain-Enabled Smart Contracts: Architecture, Applications, and Future Trends , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[5]  Marijn Janssen,et al.  Boundary conditions for traceability in food supply chains using blockchain technology , 2020, Int. J. Inf. Manag..

[6]  Alexander E. Ellinger,et al.  Supplier transparency: scale development and validation , 2018, The International Journal of Logistics Management.

[7]  Zina Ben Miled,et al.  A Distributed Ledger for Supply Chain Physical Distribution Visibility , 2017, Inf..

[8]  E. Rodríguez‐Merchán,et al.  How blockchain technology can change medicine , 2018, Postgraduate medicine.

[9]  T. Choi,et al.  The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era , 2019, Transportation Research Part E: Logistics and Transportation Review.

[10]  Nir Kshetri,et al.  Will blockchain emerge as a tool to break the poverty chain in the Global South? , 2017 .

[11]  Gwo-Hshiung Tzeng,et al.  Comparison among three analytical methods for knowledge communities group-decision analysis , 2007, Expert Syst. Appl..

[12]  Remko I. van Hoek,et al.  Exploring blockchain implementation in the supply chain , 2019 .

[13]  Yingli Wang,et al.  Making sense of blockchain technology: How will it transform supply chains? , 2019, International Journal of Production Economics.

[14]  Zeshui Xu,et al.  Intuitionistic Fuzzy Analytic Hierarchy Process , 2014, IEEE Transactions on Fuzzy Systems.

[15]  P. Beynon-Davies,et al.  Understanding blockchain technology for future supply chains: a systematic literature review and research agenda , 2019, Supply Chain Management: An International Journal.

[16]  Chung-Shan Yang,et al.  Maritime shipping digitalization: Blockchain-based technology applications, future improvements, and intention to use , 2019, Transportation Research Part E: Logistics and Transportation Review.

[17]  Ismail Erol,et al.  Assessment of blockchain applications in travel and tourism industry , 2020, Quality & Quantity.

[18]  Luis Martínez-López,et al.  An attitude-driven web consensus support system for heterogeneous group decision making , 2013, Expert systems with applications.

[19]  Tsan-Ming Choi,et al.  Blockchain-technology-supported platforms for diamond authentication and certification in luxury supply chains , 2019, Transportation Research Part E: Logistics and Transportation Review.

[20]  Ender Özcan,et al.  Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey , 2015 .

[21]  Jiann-Min Yang,et al.  Bibliometrics-based evaluation of the Blockchain research trend: 2008 – March 2017 , 2018, Technol. Anal. Strateg. Manag..

[22]  Yogesh Kumar Dwivedi,et al.  Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda , 2019, Int. J. Inf. Manag..

[23]  Ayse Yildiz,et al.  Bulanik VIKOR Yontemine Dayali Personel Secim Sureci , 2013 .

[24]  Lazim Abdullah,et al.  Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia , 2016 .

[25]  Yang Lu,et al.  Blockchain and the related issues: a review of current research topics , 2018, Journal of Management Analytics.

[26]  Samuel Fosso Wamba,et al.  Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA , 2019, Int. J. Inf. Manag..

[27]  Elmar Fürst,et al.  Blockchain for and in Logistics: What to Adopt and Where to Start , 2018, Logistics.

[28]  Vasily Kupriyanovsky,et al.  Blockchain applications for transport industry , 2017 .

[29]  Tsan-Ming Choi,et al.  When blockchain meets social-media: Will the result benefit social media analytics for supply chain operations management? , 2020 .

[30]  Teodor Gabriel Crainic,et al.  Simulation of intermodal freight transportation systems: a taxonomy , 2017, Eur. J. Oper. Res..

[31]  T. L. Saaty A Scaling Method for Priorities in Hierarchical Structures , 1977 .

[32]  Sanjay K. Prasad,et al.  A TISM modeling of critical success factors of blockchain based cloud services , 2018, Journal of Advances in Management Research.

[33]  Gülçin Büyüközkan,et al.  A Fuzzy MCDM Approach to Evaluate Green Suppliers , 2011 .

[34]  Zeshui Xu,et al.  Intuitionistic Preference Modeling and Interactive Decision Making , 2013, Studies in Fuzziness and Soft Computing.

[35]  Zsolt Kemény,et al.  Efficiency and Security of Process Transparency in Production Networks—A View of Expectations, Obstacles and Potentials☆ , 2016 .

[36]  Walid Al-Saqaf,et al.  Blockchain technology for social impact: opportunities and challenges ahead , 2017 .

[37]  Sicheng Zhang,et al.  A blockchain-based service composition architecture in cloud manufacturing , 2020, Int. J. Comput. Integr. Manuf..

[38]  Urs Magnus Strewe,et al.  Conclusion—What Can We Learn from Blockchain-Driven Supply Chain Finance? , 2018 .

[39]  Angappa Gunasekaran,et al.  Modeling the blockchain enabled traceability in agriculture supply chain , 2020, Int. J. Inf. Manag..

[40]  Reza Zanjirani Farahani,et al.  Logistics Operations and Management : Concepts and Models , 2011 .

[41]  Francisco Herrera,et al.  Consensus under a fuzzy context: Taxonomy, analysis framework AFRYCA and experimental case of study , 2014, Inf. Fusion.

[42]  Joseph Sarkis,et al.  Blockchain technology and its relationships to sustainable supply chain management , 2018, Int. J. Prod. Res..

[43]  M. Christopher Logistics and supply chain management , 2011 .

[44]  J. Aitken,et al.  Blockchain technology: implications for operations and supply chain management , 2019, Supply Chain Management: An International Journal.

[45]  Justin D Macinante A Conceptual Model for Networking of Carbon Markets on Distributed Ledger Technology Architecture , 2017 .

[46]  Mahalingam Ramkumar,et al.  Executing large-scale processes in a blockchain , 2018, Journal of Capital Markets Studies.

[47]  Gwo-Hshiung Tzeng,et al.  Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..

[48]  Horst Treiblmaier,et al.  The Impact of the Blockchain on the Supply Chain: A Theory-Based Research Framework and a Call for Action , 2018, Supply Chain Management: An International Journal.

[49]  JaeShup Oh,et al.  A case study on business model innovations using Blockchain: focusing on financial institutions , 2017 .

[50]  Guiwu Wei,et al.  Some Induced Aggregating Operators with Fuzzy Number Intuitionistic Fuzzy Information and their Applications to Group Decision Making , 2010, Int. J. Comput. Intell. Syst..

[51]  Stephan M. Wagner,et al.  Blockchain in Additive Manufacturing and its Impact on Supply Chains , 2019, Journal of Business Logistics.

[52]  Philippa Ryan,et al.  What is the Blockchain , 2018 .

[53]  Yong Shi,et al.  Public blockchain evaluation using entropy and TOPSIS , 2019, Expert Syst. Appl..

[54]  Fei-Yue Wang,et al.  Blockchain and Cryptocurrencies: Model, Techniques, and Applications , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[55]  N. Tran,et al.  Application of Blockchain Technology in Sustainable Energy Systems: An Overview , 2018, Sustainability.

[56]  M. A. Engelhardt,et al.  Hitching Healthcare to the Chain: An Introduction to Blockchain Technology in the Healthcare Sector , 2017 .

[57]  Malin Song,et al.  Blockchain technology and enterprise operational capabilities: An empirical test , 2020, Int. J. Inf. Manag..

[58]  Nir Kshetri,et al.  1 Blockchain's roles in meeting key supply chain management objectives , 2018, Int. J. Inf. Manag..

[59]  Kim Sundtoft Hald,et al.  How the blockchain enables and constrains supply chain performance , 2019, International Journal of Physical Distribution & Logistics Management.

[60]  Andrei O. J. Kwok,et al.  Is blockchain technology a watershed for tourism development? , 2019 .

[61]  Juan M. Corchado,et al.  How blockchain improves the supply chain: case study alimentary supply chain , 2018, FNC/MobiSPC.

[62]  Tino T. Herden,et al.  Examples from Blockchain Implementations in Logistics and Supply Chain Management: Exploring the Mindful Use of a New Technology , 2018, Logistics.

[63]  T. Choi,et al.  Information disclosure structure in supply chains with rental service platforms in the blockchain technology era , 2020 .

[64]  Viswanath Venkatesh,et al.  Blockchain, adoption, and financial inclusion in India: Research opportunities , 2020, Int. J. Inf. Manag..

[65]  Kichan Nam,et al.  Blockchain technology for smart city and smart tourism: latest trends and challenges , 2019, Asia Pacific Journal of Tourism Research.

[66]  Angappa Gunasekaran,et al.  Understanding the Blockchain technology adoption in supply chains-Indian context , 2018, Int. J. Prod. Res..

[67]  Diyar Akay,et al.  A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method , 2009, Expert Syst. Appl..

[68]  Xuehong Wang,et al.  Applications of Blockchain Technology to Logistics Management in Integrated Casinos and Entertainment , 2018, Informatics.

[69]  Guido Perboli,et al.  Blockchain in Logistics and Supply Chain: A Lean Approach for Designing Real-World Use Cases , 2018, IEEE Access.

[70]  Manuel Díaz,et al.  On blockchain and its integration with IoT. Challenges and opportunities , 2018, Future Gener. Comput. Syst..

[71]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[72]  Volodymyr Babich,et al.  Distributed Ledgers and Operations: What Operations Management Researchers Should Know About Blockchain Technology , 2018 .

[73]  Wei Ni,et al.  Blockchain's adoption in IoT: The challenges, and a way forward , 2019, J. Netw. Comput. Appl..

[74]  ManMohan S. Sodhi,et al.  Blockchain for Supply Chain Traceability: Business Requirements and Critical Success Factors , 2020 .

[75]  T. Choi,et al.  Data quality challenges for sustainable fashion supply chain operations in emerging markets: Roles of blockchain, government sponsors and environment taxes , 2019, Transportation Research Part E: Logistics and Transportation Review.

[76]  Fran Casino,et al.  A systematic literature review of blockchain-based applications: Current status, classification and open issues , 2019, Telematics Informatics.

[77]  Hyeon-Eui Kim,et al.  Blockchain distributed ledger technologies for biomedical and health care applications , 2017, J. Am. Medical Informatics Assoc..

[78]  Na Liu,et al.  Optimal pricing in on-demand-service-platform-operations with hired agents and risk-sensitive customers in the blockchain era , 2020, Eur. J. Oper. Res..

[79]  G. Sakthivel,et al.  A decision support system to evaluate the optimum fuel blend in an IC engine to enhance the energy efficiency and energy management , 2017 .

[80]  Stefan Tönnissen,et al.  Analysing the impact of blockchain-technology for operations and supply chain management: An explanatory model drawn from multiple case studies , 2020, Int. J. Inf. Manag..