Special issue: Data-driven decision making in supply chains

Cedillo-Campos, Miguel Gastón; González-Ramírez, Rosa G.; Mejía-Argueta, Christopher; González-Feliu, Jesús

doi:10.1016/j.cie.2019.106022

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…Companies can achieve significant savings and sustainability by utilizing strategic and tactical supply chain models and underlie the focus on research in this area (Abdussalam et al, 2021;Sahebi, Nickel et Ashayeri, 2014). Previous research has proven that collaboration and integration are key strategies frequently used by different industrial and services sectors and might lead to significant cost savings (Cedillo-Campos et al, 2020;Er Kara, Oktay Fırat et Ghadge, 2020;Long, 2018). This can be achieved through horizontal and vertical integration resulting from a merger between two or more companies or through internal re-organization and transformation (add a reference here).…”

Section: Discussionmentioning

confidence: 99%

“…Previous research demonstrates that data-driven decision-making capabilities, collaboration, and integration are vital strategies used by different industrial and service sectors (manufacturing, retailers, etc.). It might lead to significant cost savings (Cedillo-Campos et al, 2020;Er Kara, Oktay Fırat et Ghadge, 2020;Long, 2018) This can be achieved through horizontal and vertical supply chain integration resulting from a merger between two or more companies or internal re-organization and transformation (Hsu, Wright et Zhu, 2017;Milliou et Petrakis, 2007). At the same time, there is evidence that less than 25% of all mergers achieve their stated goals (Marks et Mirvis, 2001).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tactical supply chain planning after mergers under uncertainty with an application in oil and gas

ALNAQBI

Trochu

Dweiri

et al. 2023

Computers & Industrial Engineering

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tactical supply chain planning after mergers under uncertainty with an application in oil and gas

ALNAQBI

Trochu

Dweiri

et al. 2023

Computers & Industrial Engineering

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“…Some studies of 4.0 industry have provided illustrations that offer economic examples which allow for the evaluation of productivity and technical efficiency of regional manufacturing industries, [7]. Results shown in research demonstrate that for both the standard model and the proposed factorial model, the economic theory is validated in terms of the importance of the inputs that form the manufacturing outputs, [7],…”

Section: Ahp Methods Of Choicementioning

confidence: 95%

“…[28]. The results show a data-driven model that predicts the optimal decisions with important accuracy, time efficiency, and flexibility to simultaneously handle several uncertainty sources disregarding their distributions, [7].…”

Section: Mixed Integer Linear Programming (Milp)mentioning

confidence: 99%

Risk Assessment of Computer Numerical Control (CNC) Machine Service Quality

Kevin¹

2021

AJMIE

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The background of this paper stems from the uncertainties related to machine down time can have a very high cost to modern manufacturing organizations in the form of, productivity losses, product lead times, and poor-quality low product yields. The objective of this research is to review applicable risk management systems and identify the most suitable system for CNC maintenance service. Recurrent CNC machine malfunctions can result in major economic losses, poor customer service, and loss of business reputation. Many examples of the occurrences of down time disruption due to machine failure and or maintenance issues are prolific throughout modern organizations. These instances cause process volatility, disruptions to productivity, digital incidents throughout the Industrial Internet of things (known as IIoT) process, which are all contributors to CNC machine down time risk. While "just-in-time" and lean concepts may benefit the organization in general, these concepts may contribute to risk during process stoppages. The identification, assessment and management of risk is the focus of this article. A combination of modern methods and techniques are presented for comparison to identify the most relevant method to use in this research. The method identified in this case is the Analytical Hierarchical Process (AHP) which is then used as the as the method of choice for this research to successfully address and manage the consequences of risks associated with CNC machine down time. The results of this research utilize the selected risk management system of AHP analysis and priority matrix methods. This is then simulated in the model of potential occurrences of variable risks. The estimation of prospective risk factor effects is identified and analyzed for the CNC production process. The outcomes of this research have identified the most appropriate method and tailored it to the CNC maintenance service, therefore enabling the user to execute the quantifiable risk assessment and management techniques.

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“…Predictive analytics, machine learning algorithms, and big data analytics are being harnessed to anticipate demand, streamline distribution channels, and enhance overall operational efficiency. By leveraging data-driven insights, supply chain models can adapt dynamically to changes in market demand, regulatory landscapes, and global health trends (Cedillo-Campos et al, 2020). In an era of heightened scrutiny and evolving regulations, innovative supply chain models prioritize regulatory compliance and transparency (Richey et al, 2023).…”

Section: Exploring Innovative Pharmaceutical Supply Chain Modelsmentioning

confidence: 99%

Review of Innovative Supply Chain Models in the U.S. Pharmaceutical Industry: Implications and Adaptability for African Healthcare Systems

Osato Itohan Oriekhoe,

Bankole Ibrahim Ashiwaju,

Kelechi Chidiebere Ihemereze

et al. 2024

imsrj

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This comprehensive review explores innovative supply chain models within the U.S. pharmaceutical industry and examines their implications and adaptability for healthcare systems in Africa. The U.S. pharmaceutical sector is characterized by intricate logistics, stringent regulatory frameworks, and a dynamic market landscape. Through a detailed examination of pioneering supply chain models, this review aims to identify best practices, challenges, and opportunities that may inform strategies for enhancing pharmaceutical supply chains in African healthcare systems. Key considerations include the integration of advanced technologies, regulatory compliance, and collaborative partnerships within the pharmaceutical supply chain. The implications of these innovative models for African healthcare systems are assessed in the context of the unique challenges faced by the continent, such as limited infrastructure, diverse regulatory environments, and varying socio-economic conditions. The review underscores the potential for knowledge transfer and adaptation of successful U.S. supply chain models to bolster the efficiency, accessibility, and affordability of pharmaceuticals in Africa. Moreover, it emphasizes the importance of tailoring strategies to the specific needs of each region, considering factors such as local infrastructure, regulatory frameworks, and the socio-economic landscape. By synthesizing insights from the U.S. pharmaceutical industry and evaluating their applicability to African healthcare systems, this review contributes to the ongoing discourse on strengthening global health supply chains. It provides a foundation for policymakers, healthcare professionals, and industry stakeholders to develop contextually relevant strategies that enhance pharmaceutical accessibility, affordability, and overall healthcare outcomes across the African continent. Keywords: Supply Chain, Pharmaceutical, Healthcare, USA, Innovation.

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Special issue: Data-driven decision making in supply chains

Cited by 5 publications

References 7 publications

Tactical supply chain planning after mergers under uncertainty with an application in oil and gas

Tactical supply chain planning after mergers under uncertainty with an application in oil and gas

Risk Assessment of Computer Numerical Control (CNC) Machine Service Quality

Review of Innovative Supply Chain Models in the U.S. Pharmaceutical Industry: Implications and Adaptability for African Healthcare Systems

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