Abstract
Blockchain technology (BT), which provides to record transactions among many computers as a distributed ledger, is commonly utilized by companies to develop and manage business processes. Since it is a multi-process and multi-agent complex system, the implementation process of BT contains many risk factors. Identifying and analyzing these risks in order to minimize their adverse effects during the implementation process is also completely critical for companies. Since evaluating these risks must be handled by considering many different perspectives, the evaluation of risk factors for BT can be considered as a multi-criteria decision-making (MCDM) problem. To cope with uncertainty in this process, the fuzzy set theory (FST) can be effectively utilized with MCDM methods to increase their ability to obtain more concrete and realistic results. Therefore, this paper proposes an MCDM methodology consisting of Decision-Making Trail and Evaluating Laboratory (DEMATEL) and cognitive mapping methods based on FST. These methods have been reconstructed with hesitant fuzzy Z-numbers that enable not only to state impreciseness of the assessments but also to consider indeterminacy and hesitancy of the experts to evaluate risk factors with respect to BT implementation. While the dependencies of risk factors have been determined via the hesitant fuzzy Z-DEMATEL method, their weights have been obtained through the hesitant fuzzy Z-cognitive mapping method. As a result, this study aims to prioritize risk factors related to the BT implementation process with a novel fuzzy decision-making methodology and provide a road map for companies. With this study, which is the first paper in the literature in terms of the subject of the study and the method adopted, an integrated, comprehensive fuzzy approach is introduced for the first time in evaluating BT risks. As a result of detailed research, risk factors that companies may encounter in BT use and the degrees of their importance have been determined. Through that, essential decision analysis has been put forward that companies can apply for their strategic decisions. A sensitivity analysis based on changes in the initial vector values has also been adapted to analyze the effects of the risk factors.
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