In-plant lean logistics management: Case study on Chinese automotive practices

Feng, Mengying; Suresh, Jayshree; As, Balakrishnan

doi:10.1504/ijlsm.2020.10028542

Cited by 3 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some of the benefits from applying CTM are the balanced load capacity usage, reduced travel time and diminished transport costs. Feng and Yuan (2007) and Chan and Zhang (2011) have confirmed that interaction among logistics parties improves physical distribution flexibility. Okdinawati et al (2017a) modeled the learning process of all CTM agents, showing that the maturity of the system grows in several areas, such as operational planning and execution.…”

Section: Literature Reviewmentioning

confidence: 78%

See 1 more Smart Citation

Intelligent algorithms applied to the prediction of air freight transportation delays

Mendonça,

Oliveira,

Lima Jr

et al. 2023

IJPDLM

View full text Add to dashboard Cite

PurposeThe objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.Design/methodology/approachThe research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).FindingsShipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.Originality/valueThese findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

show abstract

Section: Literature Reviewmentioning

confidence: 78%

Section: Literature Reviewmentioning

confidence: 78%

Intelligent algorithms applied to the prediction of air freight transportation delays

Mendonça,

Oliveira,

Lima Jr

et al. 2023

IJPDLM

View full text Add to dashboard Cite

show abstract

“…(1) Due to the physical integration of the Internet of ings and logistics, the application of the Internet of ings in logistics is self-evident [10,11]. With the rapid development of the Internet of ings and increasingly fierce market competition, traditional logistics can no longer meet the needs of customers or adapt to the market environment, requiring companies to use Internet of ings technology and methods to change business processes to adapt to today's society.…”

Section: Changes In the External Environment Of Logistics Companiesmentioning

confidence: 99%

Intelligent Logistics Enterprise Management Based on the Internet of Things

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

At this stage, many large domestic logistics companies have problems such as complex processes, low efficiency, and chaotic vehicle management. This usually leads to vehicle failure, material loss, or improper installation of the company’s factory, which affects the company’s interests and damages the company’s reputation. In response to the above problems, this article proposes, designs, and implements an intelligent logistics management system based on the Internet of Things technology through the research of the Internet of Things technology at home and abroad. The specific content is as follows: one is to study the origin and current situation of the Internet of Things technology at home and abroad, to understand related theories and cutting-edge technologies of the Internet of Things; the other is to imitate intelligent logistics companies, study the processes and existing problems of the logistics link, and integrate the management concepts of the Internet of Things. A model of intelligent logistics enterprise management is established with enterprise intelligent technology; the third is to conduct an experiment on the management of an intelligent logistics enterprise and do an experimental data analysis of the management of an intelligent logistics enterprise. Experimental research shows that the data of factors affecting logistics operations in smart logistics companies are low, and smart logistics companies are operating in good condition, and the established data model is suitable for smart logistics enterprise management. The Internet of Things and intelligent logistics management are both emerging concepts, while the intelligent logistics management based on the Internet of Things is still in its infancy, and relevant scholars have little research on the intelligent logistics management based on the Internet of Things. It plays a guiding role for the intelligent logistics management of enterprises and promotes the management of intelligent logistics enterprises.

show abstract

“…The implementation of CTM is aimed at developing collaborative relationships among shippers, carriers, and third-party logistics providers to improve transportation services and reduce costs along the supply chain (Esper and Williams, 2003). Feng and Yuan (2007) asserted that the CTM involves three constructs: relational integration, collaborative integration, and IT integration. Relational integration assesses the extent of cooperation, such as the scope of cooperation, goals, responsibilities, strategic information, and a long-term and trustworthy cooperative relationship.…”

Section: Collaborative Transportation Managementmentioning

confidence: 99%

“…The SCII construct was adapted from the work of Wong et al's (2011) work to compose the items on internal integration, supplier integration, and customer integration. The CTM construct was adapted from the literature (Stank et al, 2001;Feng and Yuan, 2007;Wen, 2012), and had three parts: relationship integration, collaborative planning and forecasting, and IT integration. Five items on logistics performance, namely, speed of delivery, reliability of delivery, flexibility of delivery, responsiveness, and order fill capacity were adapted from prior studies (Rodrigues et al, 2004;Green et al, 2008;Hotrawaisaya et al, 2014).…”

Section: Questionnaire Developmentmentioning

confidence: 99%

Evaluating the Guanxi and Supply Chain Collaborative Transportation Management in Manufacturing Industries

Yang¹,

Kao²,

Lai³

et al. 2022

IJSTL

View full text Add to dashboard Cite

Manufacturing firms can facilitate their shipping and logistics operations via cooperation by adopting collaborative supply chain transportation. Moreover, in Chinese culture, guanxi is considered crucial for fostering close partnerships. This study empirically examines the relationships between supply chain information integration (SCII), collaborative transportation management (CTM) through interaction and collaboration between trading partners and carriers (supply chain CTM), logistics performance, and guanxi in manufacturing industries. In total, 152 usable responses from the manufacturing industry were collected using a questionnaire. A structural equation model (SEM) was used to evaluate the hypotheses. The results indicate that SCII is significantly positively related to supply chain CTM and logistics performance. While supply chain CTM is significantly positively related to logistics performance for manufacturing firms, guanxi has a significant moderating effect between SCII and supply chain CTM. The moderating effect of guanxi on manufacturing firms' supply chain CTM and logistics performance was not found in this study.

show abstract

In-plant lean logistics management: Case study on Chinese automotive practices

Cited by 3 publications

References 0 publications

Intelligent algorithms applied to the prediction of air freight transportation delays

Intelligent algorithms applied to the prediction of air freight transportation delays

Intelligent Logistics Enterprise Management Based on the Internet of Things

Evaluating the Guanxi and Supply Chain Collaborative Transportation Management in Manufacturing Industries

Contact Info

Product

Resources

About