Ranking the benefits of drone-based last-mile delivery due to adoption of its enablers

无人机 最后一英里(运输) 排名(信息检索) 业务 过程管理 持续性 利益相关者 服务交付框架 服务(商务) 营销 计算机科学 经济 英里 生态学 物理 遗传学 管理 天文 机器学习 生物
作者
Chandresh Kumbhani,Ravi Kant
出处
期刊:Journal of Advances in Management Research [Emerald (MCB UP)]
卷期号:21 (5): 805-836 被引量:1
标识
DOI:10.1108/jamr-03-2024-0103
摘要

Purpose Strategic integration of enablers and the realization of drone delivery benefits emerge as essential strategies for business organizations to enhance operational efficiency and stay competitive in last-mile logistics. This paper aims to explore the benefits of drone-based last-mile delivery in the Indian logistic sector by providing a framework for ranking drone delivery benefits (DDBs) due to the adoption of its enablers. Design/methodology/approach This study proposes a novel hybrid framework applied in the Indian logistic sector by integrating a sentence boundary extraction algorithm for extracting benefits from literature, a spherical fuzzy analytical hierarchy process (SF-AHP) for evaluating primary enablers, unsupervised fuzzy C-means clustering (FCM) for clustering benefits and a spherical combined compromised solution (SF-CoCoSo) for ranking benefits with respect to primary enablers. Findings The results reveal that technological and infrastructure enablers (TIE), government and legislation enablers (GLE) and operational and service quality enablers (OSE) are the most significant enablers for drone implementation in logistics. Top-ranked benefits increase the efficiency of last-mile delivery (DDB10), foster supply chain management and logistic sustainability (DDB16) and increase delivery access to rural area and vulnerable people (DDB17). Practical implications This research assists scholars, entrepreneurs and policymakers in the sustainable deployment of drone delivery in the logistics sector. This study facilitates the use of drones in delivery services and provides a foundation for all stakeholders in logistics. Originality/value The assessments involve considering judgment from a highly knowledgeable and experienced group in India, characterized by a large volume of inputs and a high level of expertise.
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