An analysis of blockchain versus relational databases for digitalising information flows in global supply chains using the analytic network process

Abstract

Global trade is plagued by slow and inefficient manual processes associated with physical documents. Firms are constantly looking for new ways to improve transparency and increase the resilience of their supply chains. This can be solved by the digitalisation of supply chains and the automation of document- and information-sharing processes. Blockchain is touted as a solution to these issues due to its unique combination of features, such as immutability, decentralisation and transparency. A lack of business cases that quantify the costs and benefits causes uncertainty regarding the truth of these claims. This paper explores how the costs and benefits of a blockchain-based solution for digitalising and automating documentation flows in cross-border supply chains compare to a conventional centralised relational database solution. The research described in this paper uses primary data collected through semi-structured interviews with industry experts, as well as secondary data from literature. Two models based on existing services were developed and the costs and benefits compared and then analysed using the Architecture Trade-off Analysis Method (ATAM) and the Analytic Network Process (ANP). Findings from the analysis show that a consortium blockchain solution like TradeLens is the favourable solution for digitalising and automating information flows in cross-border supply chains.

KEYWORDS:

• Blockchain
• relational database
• supply chain digitalisation
• Analytic Network Process
• cross-border trade
• SDG 9: industry, innovation and infrastructure

Disclosure statement

The authors report there are no competing interests to declare.

Data availability statement

The output data that support the findings of this study are available from the corresponding author, DEW, upon reasonable request. The participants of this study asked for raw data provided by them to not be made available to the public, so some supporting data is not available.

Additional information

Notes on contributors

Dieter E. Wolf

Dieter Wolf is a postgraduate student pursuing a joint master’s degree in industrial engineering at Stellenbosch University in South Africa and ESB Business School at Reutlingen University in Germany. His research focus area is the digitalisation and automation of cross-border supply chains.

Louis Louw

Louis Louw is an associate professor in the Department of Industrial Engineering, Stellenbosch University, South Africa. He has more than 16 years’ experience working with high-profile organisations across various industries. His current research focuses on digitalisation and ‘smart’ Industrie 4.0 enabled operations & supply chain management. Professor Louw has more than 40 publications in various international journals and conference proceedings and is a member of the International Association of Learning Factories. He also serves on the scientific committee for two international conferences.

Daniel Palm

Daniel Palm is a professor for Supply Chain Management and Logistics at the ESB Business School of Reutlingen University in Germany. Professor Palm has been a researcher and consultant at the Fraunhofer Institute in the field of Corporate Management and Corporate Logistics, he was the Division Director of Production and Logistics Management and Director Finance and Administration of the Fraunhofer Austria Research GmbH. He worked in more than 50 research and consultancy projects in the fields of Logistics Planning and Supply Structures, Supply Chain Management, Business Process Reengineering, Factory Planning, Organization and Production management. At ESB Business School Professor Palm leads the Education and Research Centre ‘Value Creation and Logistics Systems’, the Reutlinger Zentrum Industrie 4.0 and the Steinbeis Transferplattform Industrie 4.0.