Logistics services outsourcing decision making: a literature review and research agenda

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
M. Akhtar
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引用次数: 3

Abstract

Logistics plays important role in any firm’s supply chain. Outsourcing allows firms to focus on core business. Logistics outsourcing to third party logistics or logistics service providers (LSP) helps the companies to reduce costs, improve performance, sustainability, customer satisfaction and profitability. Logistics assessment and selection of LSP is a complex and important aspect of outsourcing decision. The purpose of this paper is to provide a review of logistics outsourcing literature to provide an insight to the trend, opportunities, criteria and techniques adopted in logistics outsourcing decision-making. This paper is based on literature review of 62 research articles published related to LSP evaluation and selection during 2010-2020. The analysis includes publications in journals, year, selection criteria and evaluation methods. It has been found that 44 major selection criteria have been used by different authors but most commonly used are: price, on-time delivery, service quality, reliability, flexibility, equipment and technology, customer relationship, while environmental and social criteria are rarely adopted. It is also observed that multi criteria decision making (MCDM) methods have been adopted by majority of researchers wherein Analytic Hierarchy Process (AHP), Technique for order of preference by similarity to ideal solution (TOPSIS) and their fuzzy variant are highly applied. Conclusion, implications for researchers and practitioners, limitations, and direction for future research are provided.
物流服务外包决策:文献回顾与研究议程
物流在任何企业的供应链中都扮演着重要的角色。外包使公司能够专注于核心业务。物流外包给第三方物流或物流服务提供商(LSP)有助于公司降低成本,提高绩效、可持续性、客户满意度和盈利能力。LSP的物流评估和选择是外包决策的一个复杂而重要的方面。本文的目的是对物流外包文献进行回顾,以深入了解物流外包决策的趋势、机遇、标准和技术。本文基于对2010-2020年期间发表的62篇与LSP评估和选择相关的研究文章的文献综述。分析包括期刊上的出版物、年份、选择标准和评估方法。研究发现,不同的作者使用了44个主要的选择标准,但最常用的是:价格、准时交货、服务质量、可靠性、灵活性、设备和技术、客户关系,而很少采用环境和社会标准。多准则决策方法已被大多数研究者所采用,其中层次分析法(AHP)、理想解相似偏好排序技术(TOPSIS)及其模糊变量得到了高度应用。结论、对研究人员和从业者的启示、局限性以及未来研究的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
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