Assessment of barriers impeding the incorporation of blockchain technology in the service sector: a case of hotel and health care

IF 1.8 Q3 MANAGEMENT

Journal of Modelling in Management Pub Date : 2023-07-17 DOI:10.1108/jm2-06-2022-0159

Kunwar Saraf, Karthik Bajar, Aaditya Jain, A. Barve

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引用次数: 0

Abstract

Purpose This study aims to determine the barriers hindering the incorporation of blockchain technology (BCT) in two key service industries – hotel and health care – as well as to assess their readiness for implementing BCT after overcoming the barriers. Design/methodology/approach The barriers of this study are determined through two phases: a review of prior literature and obtaining expert opinions, which are then analyzed to identify specific barriers that are impeding the incorporation of BCT. Moreover, to generate a blockchain implementation reluctance index (BIRI), this study presents an interval-valued intuitionistic fuzzy set (IVIFS) that uses graph theory and matrix approach (GTMA). The permanent function in the GTMA approach is computed using the PERMAN algorithm. Finally, to compare the readiness of the hotel and health-care industries to adopt BCT, the BIRI values are plotted and evaluated. Findings The barriers identified by this study are listed under five major headings, namely, financial, operational, behavioral, technical and legal. This study revealed that the operational and technical barriers of BCT are critically hindering its widespread integration in hotel and health-care industries. Furthermore, on comparing the BIRI values of both industries, the result suggested that the hotel industry needs to work more on these barriers to effectively incorporate BCT. Besides the comparison, the BIRI values clearly indicate that both industries have to put a lot of effort into the mitigation of the barriers found by this study to successfully integrate BCT. Research limitations/implications The experts’ opinions are used to evaluate the identified barriers, which raises the chance that the opinions are prejudiced based on the experts’ perspectives and ideologies. The sensitivity of decision-maker loads toward preference outcomes is not analyzed in this manuscript. Therefore, any recent sensitivity analysis may be considered a prospective field for future research. This study applies a multicriteria decision-making (MCDM) approach, IVIFS–GTMA, which limits the evaluation of the influence caused by individual barriers on the integration of BCT in the hotel and health-care industries. Henceforth, in future investigations, alternative MCDM methods may be used to analyze individual barriers. Practical implications According to the findings, if the hotel or health-care industry aims to incorporate BCT in its supply chain operations, it is recommended to emphasize more on the operational barriers along with the technical and behavioral barriers. The barriers mentioned in this manuscript can be used as guidance for developers in their development activities, such as scalability concerns, establishment costs, the 51% attack and the inefficient nature of BCT. Furthermore, they may address the potential users’ negative perceptions about security, privacy, trust and risk avoidance through creatively developed blockchain solutions to promote BCT implementation. Originality/value To the best of the author’s knowledge, this is the first study that identifies barriers toward BCT incorporation in the major service industries, i.e. hotel and health care. Moreover, this is the first study that compares the preparedness of the hotel and health-care industries to determine the industry that requires more work to implement BCT.

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评估妨碍将区块链技术纳入服务部门的障碍:以酒店和保健为例

目的本研究旨在确定阻碍区块链技术(BCT)在两个主要服务行业-酒店和医疗保健-纳入的障碍，并评估他们在克服障碍后实施BCT的准备情况。设计/方法/方法本研究的障碍是通过两个阶段确定的:回顾先前的文献和获得专家意见，然后分析以确定阻碍纳入BCT的具体障碍。此外，为了生成区块链实现不情愿指数(BIRI)，本研究提出了一个区间值直觉模糊集(IVIFS)，该模糊集使用图论和矩阵方法(GTMA)。采用PERMAN算法计算GTMA方法中的永久函数。最后，为了比较酒店和医疗保健行业采用BCT的准备程度，绘制并评估了BIRI值。本研究确定的障碍分为五个主要标题，即财务、操作、行为、技术和法律。该研究表明，BCT的操作和技术壁垒严重阻碍了其在酒店和医疗保健行业的广泛整合。此外，通过比较两个行业的BIRI值，结果表明酒店业需要在这些障碍上做更多的工作，以有效地纳入BCT。除了比较之外，BIRI值清楚地表明，为了成功整合BCT，两个行业都必须付出大量努力来缓解本研究发现的障碍。研究局限/启示专家的意见被用来评估已识别的障碍，这增加了基于专家观点和意识形态的偏见意见的机会。本文没有分析决策者负载对偏好结果的敏感性。因此，任何近期的敏感性分析都可能被认为是未来研究的一个有前景的领域。本研究采用多标准决策(MCDM)方法，即IVIFS-GTMA，该方法限制了个体障碍对酒店和医疗保健行业BCT整合影响的评估。因此，在未来的研究中，可以使用替代的MCDM方法来分析单个障碍。根据研究结果，如果酒店或医疗保健行业的目标是将BCT纳入其供应链运营，建议更多地强调运营障碍以及技术和行为障碍。本文中提到的障碍可以作为开发人员开发活动的指导，例如可伸缩性问题、建立成本、51%攻击和BCT的低效性质。此外，他们可以通过创造性地开发区块链解决方案来解决潜在用户对安全、隐私、信任和风险规避的负面看法，以促进BCT的实施。原创性/价值据作者所知，这是第一个确定在主要服务行业(即酒店和医疗保健)引入BCT的障碍的研究。此外，这是第一个比较酒店和医疗保健行业的准备情况的研究，以确定需要更多工作来实施BCT的行业。

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来源期刊

Journal of Modelling in Management MANAGEMENT-

CiteScore

5.50

自引率

12.50%

发文量

期刊介绍： Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.