Improvement of the Containerized Logistics Performance Using the Unitary Traceability of Smart Logistics Units

Wattanakul, Siraprapa; Henry, Sébastien; Bentaha, Mohand Lounes; Reeveerakul, Napaporn; Ouzrout, Yacine

doi:10.1007/978-3-030-01614-2_38

Cited by 7 publications

(9 citation statements)

References 14 publications

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“…This was followed by visualizing the entire supply chain (mean = 4.13). This result was no surprise to us because enhancing supply chains’ visualization and traceability has seen a big leap after more smart technologies have been adopted within supply chains (Hermann et al , 2016; Verdouw et al , 2016; Wattanakul et al , 2018). The third and fourth potential impacts were providing better risk management (mean = 4.08) and more effective identification of abnormalities in the system (mean = 4.03).…”

Section: Analysis and Resultsmentioning

confidence: 94%

Digitalizing supply chains potential benefits and impact on lean operations

Haddud

Khare²

2020

IJLSS

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Purpose New technological trends continue to emerge, and businesses adopt them in different capacity in a pursuit of improving current ways of doing things and to gain competitive advantages over rivals. One of the key business functions that is impacted by the implementation of different disruptive technologies is the supply chain management. As a result, there is a continuous need to identify where digitalizing supply chains may provide businesses with benefits to capitalize such gains. This study aims to examine potential impacts of digitalizing supply chains on five selected lean operations practices through the identification of key areas and benefits under each of these practices. Design/methodology/approach Data were collected from 74 participants mainly from the academic community and who were university scholars through the use of an online survey. The used online survey consists of six main parts in total, but three were included in this paper and these were designed to gather data about participants’ general information, level of influence of seven technological trends on supply chain performance and management and potential impact of digitalizing supply chains on five lean operations practices. Findings The authors were able to confirm the significant impact of digitalizing supply chains on the five examined lean operations practices. Most of the examined potential impacts were found to improve certain areas that directly improve the practices of the explored five lean operations practices as well as the overall supply chain and business performance. They were also able to determine the level of influence of the seven examined enabling technologies on supply chain performance and management. Originality/value To the best of the authors’ knowledge, this study is the first of its kind. Although some literature explored different aspects related to the concept of Industry 4.0 and digitalizing supply chains, no study has specifically explored potential impacts of digitalizing supply chains on lean operations. The results from this study can be beneficial to academic scholars interested in the researched themes, business professionals specializing in supply chain management and lean operations, organizations within different industrial sectors particularly manufacturing where lean thinking is adopted and any other party interested in understanding more about the impact of digitalizing supply chain on lean operations and on an overall business performance.

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Section: Analysis and Resultsmentioning

confidence: 94%

Digitalizing supply chains potential benefits and impact on lean operations

Haddud

Khare²

2020

IJLSS

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“…d) Cloud Computing and Internet of Things(IOT): Cloud computing offers unlimited data storage space to collect the information provided by the IOT. The survey shows that few research use cloud computing technology and smart device (IoT) to track and collect data during container transport [8], [23], [34].…”

Section: A Scientific Methods and Solutionsmentioning

confidence: 99%

“…Güller et al [7] developed an Agent-based Simulation framework which comprises data management/data source; supply chain visualization and detection; simulation and prevention stages. More recently Wattanakul et al proposed a framework to identify in real time disruption and root cause of disruption during container shipment due to traceability data and route plane [34].…”

Section: A Scientific Methods and Solutionsmentioning

confidence: 99%

“…Research also shows the existence of solutions in terms of supply chain optimization and risk management based on artificial intelligence [47], big data [35], [36], simulation [7] and IOTs [48]. However just few of these methods integrate real-time data in their process [7], [34]. Thanks to various technological advances, commercial solutions ensuring container tracking have been proposed.…”

Section: Review and Recommendationmentioning

confidence: 99%

“…Communication throughout the supply chain is of foremost importance in order for decision-making to be truly responsive to events [17]. On this basis, Mr Güller et al [7] proposes a framework for the design of a simulationbased decision support system for the real-time management of disruptions and mitigation of risks in supply chains, in the same way Zou and al [48] introduce a new method, which uses field programmable gate array (FPGA) to design embedded device to execute related algorithms in parallel for underling data processing to reduce risks which caused by time-delay in supply chain network (SCN) and wattanakul et al [34] proposed a framework using historical and real-time data to improve the responsiveness to disturbances of the supply chain and to develop robust scheduling in container shipping. In addition Andziulis et al [49] design a real-time mobile cargo monitoring system integrate RFID and sensor in order to increase intermodal container transportation mobility, safety and overall effectiveness.…”

Section: Review and Recommendationmentioning

confidence: 99%

See 2 more Smart Citations

Traceability and Risk Management in Multi-modal Container Transport: A Small - Scale Review of methods and technologies

Ouedraogo¹,

Namakiaraghi²,

Rosemont³

et al. 2020

2020 5th International Conference on Logistics Operations Management (GOL)

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Increasing flexibility and responsiveness are the opportunities that smart logistics offers to companies. With the development of the supply chain network (SCN) and big data processing, a simple view at above two technologies separately has become unadvisable. This work deals with the traceability and supply chain risk management of containers during shipping expeditions using real-time Data. The main objective of this article is to analyse proposed solutions to improve the efficiency of the supply chain by acting on risk management in containers transport. A future approach to improve the real-time management of shipments by taking into account random events is mentioned.

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Food supply network disruption and mitigation: an integrated perspective of traceability technology and network structure

Wang

Feng

et al. 2022

Comput Math Organ Theory

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The 2019 coronavirus disease (COVID-19) epidemic has caused serious disruptions in food supply networks. Based on the case of the remerging epidemic in China, this paper aims to investigate food supply network disruption and its mitigation from technical and structural perspectives. To solve the optimal policy choice problem that how to improve mitigation capability of food supply networks by using traceability technology and adjusting network structure, the occurrence mechanism of food supply network disruptions is revealed through a case study of the remerging COVID-19 outbreak in Beijing’s Xinfadi market. Five typical traceability solutions are proposed to mitigate network disruptions and their technical attributes are analyzed to establish disruption mitigation models. The structure of food supply networks is also controlled to mitigate disruptions. The structural attributes of three fundamental networks are extracted to adjust the network connections pattern in disruption mitigation models. Next, simulation experiments involving the disruption mitigation models are carried out to explore the independent and joint effects of traceability technology and network structure on mitigation capability. The findings suggest that accuracy makes a more positive effect on the mitigation capability of food supply networks than timeliness due to the various technical compositions behind them; the difference between these effects determines the choice decision of supply networks on traceability solution types. Likewise, betweenness centralization makes a positive effect but degree centralization makes a negative effect on mitigation capability because intermediary firms and focal firms in food supply networks have different behavior characteristics; these effects are both regulated by supply network types and exhibit different sensitivities. As for the joint effect of technical and structural attributes on mitigation capability, the joint effect of accuracy and betweenness centralization is bigger than the independent effects but smaller than their sum; the joint effect of timeliness and betweenness centralization depends on networks type; while the positive effect of accuracy or timeliness on mitigation capability is greater than the negative effect of degree centralization; theses joint effects are caused by the complicated interactive effects between technical composition and behaviors of intermediary firms or focal firms. These findings contribute to disruption management and decision-making theories and practices.

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Improvement of the Containerized Logistics Performance Using the Unitary Traceability of Smart Logistics Units

Cited by 7 publications

References 14 publications

Digitalizing supply chains potential benefits and impact on lean operations

Digitalizing supply chains potential benefits and impact on lean operations

Traceability and Risk Management in Multi-modal Container Transport: A Small - Scale Review of methods and technologies

Food supply network disruption and mitigation: an integrated perspective of traceability technology and network structure

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