Assessing the factors for humanitarian logistics digital business ecosystem (HLDBE) using a novel integrated correlation coefficient and standard deviation - combined compromise solution (CCSD-CoCoSo) method

IF 1.4 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Decision Science Letters Pub Date : 2023-01-01 DOI:10.5267/j.dsl.2022.10.001
Benjamin Ohene Kwapong Baffoe, Wenping Luo, Qiao Pan, Shengwu Zhou, Mei Ju Wu, Louis Kofi Desire Atimu, P. Darko, Evans Opoku‐Mensah
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引用次数: 1

Abstract

This study updates Humanitarian Logistics Digital Business Ecosystem framework coupled with the development of a proposed integrated CCSD-CoCoSo MCDM method to rank factors used in assessing humanitarian and business logistics actor’s propensity to use, diffuse, and adopt a collaborative digital business ecosystem platform for their future operational use. Employing nine criteria derived from technology innovation theories and institutional theory, and 28 experts comprising our decision matrix. The findings report perceived relative advantage, perceived safety and security, and infrastructure and expertise as the top three vital criteria that experts believe when addressed in an ecosystem platform for humanitarian and business logistics actors it would encourage a collaboration for their sustainable future operations. With organisational culture and structure as the least prioritised criteria. The study concludes that the CCSD-CoCoSo obtained results are objective, validating, and that this model is useful and suitable for MCDM analysis and policy making.
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利用一种新的综合相关系数和标准差组合妥协解(CCSD-CoCoSo)方法评估人道主义物流数字商业生态系统(HLDBE)的因素
本研究更新了人道主义物流数字商业生态系统框架,并开发了拟议的集成CCSD-CoCoSo MCDM方法,对评估人道主义和商业物流参与者使用、扩散和采用协作式数字商业生态系统平台的倾向所使用的因素进行排名,以供其未来运营使用。采用从技术创新理论和制度理论推导出的9个标准,由28位专家组成决策矩阵。专家认为,在人道主义和商业物流参与者的生态系统平台中,感知相对优势、感知安全和保障、基础设施和专业知识是最重要的三个标准,这将鼓励他们在未来的可持续运营中进行合作。以组织文化和结构作为最不优先的标准。研究表明,CCSD-CoCoSo模型的结果是客观的、有效的,该模型适用于MCDM分析和决策。
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来源期刊
Decision Science Letters
Decision Science Letters Decision Sciences-Decision Sciences (all)
CiteScore
3.40
自引率
5.30%
发文量
49
审稿时长
20 weeks
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