A Systematic Investigation of the Integration of Machine Learning into Supply Chain Risk Management

Schroeder, Meike; Lodemann, Sebastian

doi:10.3390/logistics5030062

Cited by 40 publications

(13 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The purchase of services, such as hotel stays, however, has been demonstrated to be more satisfactory for clients if they are served by human employees, as guaranteed service quality is a key element in the service industry (Pasca et al, 2021). However, the service sector and, more specifically, the health industry, must adapt their systems to attract or maintain their customers (Aamer et al, 2021; Bilan et al, 2022; Díez‐Sanmartín et al, 2021; Lin et al, 2018); the application of AI to supply chain management might form better company–customer relationships (Jamwal et al, 2021; Schroeder & Lodemann, 2021; Sharma et al, 2020; Tiwari et al, 2018; Younis et al, 2022).…”

Section: Findings and Discussionmentioning

confidence: 99%

Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda

Suraña‐Sánchez,

Aramendia‐Muneta

2024

Int J Consumer Studies

View full text Add to dashboard Cite

This study, through a bibliometric analysis, aims to provide increased knowledge of the evolution and effects of artificial intelligence over the last 30 years in customer engagement and advertising engagement. Articles were gathered from three databases by using combinations of keywords (artificial intelligence, customer engagement, advertising engagement, marketing, machine learning, etc.). A set of inclusion/exclusion criteria were then applied to obtain the final sample. The final sample was made up of 190 peer‐reviewed articles. Three separate analyses were performed to test the sample. A performance analysis identified the articles' years of publication, contributions per country and the performance/output of the relevant journals. A data analysis created 10 clusters; these are examined in depth, and provide explanations of the evolution of the relevant scientific production. The study's findings offer a wide perspective of research undertaken to date, and identify possible research gaps. This research contributes to the marketing field by bridging a gap, through undertaking a bibliometric analysis, in the research about the impact of artificial intelligence on customer and advertising engagement over the years 1991 through 2022. It offers scholars and researchers ideas for future research.

show abstract

Section: Findings and Discussionmentioning

confidence: 99%

Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda

Suraña‐Sánchez,

Aramendia‐Muneta

2024

Int J Consumer Studies

View full text Add to dashboard Cite

show abstract

“…Using IoTs, more rigorous temperature monitoring in real time and forecasting can be achieved, although the processing of the generated data is questionable. Various aspects of cold chain generate experimental and numerical data that can train deep and machine learning models to predict temperature control, although according to Schroeder et al, a reliable method to detect a break in the cold chain is yet to be validated [ 33 ].…”

Section: Recommendations For Best Practicementioning

confidence: 99%

Management of COVID-19 vaccines cold chain logistics: a scoping review

Fahrni

Ismail

Refi

et al. 2022

J of Pharm Policy and Pract

View full text Add to dashboard Cite

Background Successful mass vaccination programmes are public health achievements of the contemporary world. While pharmaceutical companies are actively developing new vaccines, and demonstrating results of effectiveness and safety profiles, concerns on COVID-19 vaccine management are under-reported. We aimed to synthesise the evidence for efficient cold chain management of COVID vaccines. Methods The scoping review’s conduct and reporting were based on the PRISMA–ScR 2018 checklist. We searched from April 2020 to January 2022 for publications in PubMed (LitCovid), Scopus and ScienceDirect. All review stages were pilot-tested to calibrate 2 reviewers. Articles on cold chain logistics and management were included, while publications solely describing COVID vaccines, their development and clinical aspects of the vaccine, were excluded. To capture relevant data, charting was conducted by one reviewer and verified by another. Results were analysed thematically and summarised descriptively in a table and in-text. Results and discussion We assessed 6984 potentially relevant citations. We included 14 publications originating from USA (n = 6), India (n = 2), Finland, Spain, Bangladesh, Netherlands, Switzerland and Ethiopia. They were reported as reviews (4), policy or guidance documents (3), experimental studies (2), case reports (2), expert commentary (1), phenomenological study (1), and decision-making trial and evaluation laboratory trial (1). The findings were presented in three themes: (i) regulatory requirements for cold-chain logistics, (ii) packaging and storage, and (iii) transportation and distribution. A conceptual framework emerged linking regulatory requirements, optimal logistics operation and formulation stability as the key to efficient cold chain management. Recommendations were made for improving formulation stability, end-product storage conditions, and incorporating monitoring technologies. Conclusion COVID-19 vaccines require special end-to-end supply cold chain requirements, from manufacture, and transportation to warehouses and healthcare facilities. To sustain production, minimise wastage, and for vaccines to reach target populations, an efficient and resilient vaccine supply chain which is assisted by temperature monitoring technologies is imperative.

show abstract

“…Thus, insurance companies can process the causes of the incident, the carrier involved, the type of cargo and the validity of the claims faster and easier. Also, ML can be used to model disruptive events and their impact on the supply chain to identify potential risks in a timely manner [91]. In maritime fleet risk management, the assessment of ship risks can be improved by: detection of anomalies in marine operations from data gathered on vessel movement; investigation of cargo loss in logistics systems employing datadriven analytics; and identification of how CC may become an enabler of dynamic and synchro modal container consolidation [40], [56].…”

Section: ) Risk Managementmentioning

confidence: 99%

Supply Chain Management, Game-Changing Technologies, and Physical Internet: A Systematic Meta-Review of Literature

2022

View full text Add to dashboard Cite

To improve the effectiveness and the sustainability of logistics, the Physical Internet paradigm proposes disruptive solutions. This implies developing an ecosystem of tech-based logistics solutions and supporting methodologies that enable all players in global trade to cooperate. The purpose of this paper is to investigate systematic literature review (SLR) studies to gain detailed insight into how innovative transport technologies, and digitalization initiatives around the Physical Internet development impact supply chains. This paper presents the results of a tertiary study that systematically identified more than twelve thousand articles and selects to review 74 secondary studies on the application of disruptive technologies and the Physical Internet initiative on supply chains from a management perspective. This is complementary to previous reviews, since no one provides a comprehensive and consolidated approach towards the relationship of these three fields. The five-stage systematic review process proposed by Denyer and Tranfield ( 2009) is followed. As a result, we identify the key activities, knowledge areas and strategies in the supply chain field where the Physical Internet and disruptive technologies interact and are game-changing. Also, we present a conceptual framework that summarises the relationships that exist between relevant disruptive technologies, the physical internet topics, and supply chain key activities. The framework is helpful for researchers and practitioners to find potential technologies to invest in, to assess the potential effects on companies of their implementation, and to support strategic decision-making. The paper concludes with an outlook on future research opportunities from operational, tactical, and strategic perspectives.

show abstract

A Systematic Investigation of the Integration of Machine Learning into Supply Chain Risk Management

Cited by 40 publications

References 85 publications

Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda

Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda

Management of COVID-19 vaccines cold chain logistics: a scoping review

Supply Chain Management, Game-Changing Technologies, and Physical Internet: A Systematic Meta-Review of Literature

Contact Info

Product

Resources

About