An adaptive network-based fuzzy inference system to supply chain performance evaluation based on SCOR® metrics

Lima, Francisco Rodrigues; Carpinetti, Luiz César Ribeiro

doi:10.1016/j.cie.2019.106191

Cited by 60 publications

(37 citation statements)

References 54 publications

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“…Network-based fuzzy model [57] Approach to support supply-chain performance evaluation based on adaptive network-based fuzzy inference systems Total interpretive structural model [58] To investigate the drivers of sustainable supply chain to tackle supply chain disruptions; it considers the health protocols and automation as an essential for long-term sustainability in supply chains Thus, it is also evident that researchers in supply chain have proposed different models and approaches for assessing supply chain agility in different case organization. The contribution of our study is to update the literature about the different factors contributing to achieve a sustainable agile supply chain and propose conceptual framework and assessment approach investigating the associations between capabilities, enablers, and attributes to determine the needed agility level and how to facilitate the organization's performance.…”

Section: Models Focused Onmentioning

confidence: 99%

An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization

2021

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Worldwide business organizations realize that agility of sustainable supply-chain is a requisite need for survival in a dynamic, competitive, and unpredictable market. The contribution of this research is to explore and evaluate sustainable agility in supply chains for a dairy manufacturing organization located in Saudi Arabia. Other contributions of this research are to update the literature about the different factors contributing to achieve agile supply chain, propose conceptual framework and assessment approach incorporating the relationships between sustainable supply-chain capabilities, enablers, and attributes, and shortlisting the agility barriers and how they would facilitate manufacturing organizations’ performance. The paper presents supply chain agility evaluation approach, which covers identification of agile supply-chain capabilities and drivers. It also presents a conceptual model and a framework to define agility level and barriers within the supply-chain. In the paper, fuzzy logic approach is preferred, owing to its capability to incorporate and deal with problems involving impreciseness and vagueness phenomena. Threshold-value in this study for the case organization is set to 0.24829. The outcome of the adopted approach indicates that 21 attributes performed below the threshold value; these attributes are further categorized as agility barriers. These are the barriers within their supply chain that impact the agility-level. For the case organization, the foremost priority is to enhance maintainability and serviceability to make it flexible and inexpensive to establish an agile responsive supply chain. At the same time, it should have priority to focus on development and integration of their core competencies to deal with cross-functional and cross-enterprise issues in supply chain. For the case organization, the agility level was found “very agile,” although it is below the “extremely agile.” Thus, a study was developed to understand the behaviour of the supply chain agility and assess/evaluate it to support decision makers in order to develop a strategic solution for different organizational barriers.

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Section: Models Focused Onmentioning

confidence: 99%

An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization

2021

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“…The SCOR model stipulates that major supply chain processes include sourcing, operations and manufacturing, distribution and logistics, usage and service (Huan et al, 2004). Each process is managed using various supply chain competenciesflexibility, cost, quality and time (Lima-Junior and Carpinetti, 2020). These four supply chain competencies can be utilized as measurements of supply chain performance.…”

Section: Literature Reviewmentioning

confidence: 99%

Product deletion and supply chain repercussions: risk management using FMEA

Zhu

Golrizgashti

Sarkis

2020

BIJ

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PurposeProduct portfolio management is a strategic concern. Product portfolio management includes decisions associated with adding new products, maintaining existing products and deleting or phasing out problematic products. This paper first introduces a framework to identify risks of product deletion along supply chain activities. It utilizes failure mode and effects analysis (FMEA) to identify, analyse and evaluate product deletion risks on supply chains and proposes managerial implications for risk management in dynamic business scenarios. It is meant to build upon and address a gap in the product deletion and supply chain linkage literature.Design/methodology/approachFMEA is utilized in this study to structure and manage potential risks in product deletion decision-making on supply chains. FMEA is based on an analysis of severity, occurrence and detectability of failure modes. FMEA provides methods to help identify managerial preventive solutions to avoid and mitigate risk consequences of such decisions.FindingsTen top product deletion risks are identified in this study; discussions of their negative impact on supply chain performance, and possible managerial recommendations are followed for risk control, monitor and elimination.Practical implicationsFindings help managers to predict, avoid and mitigate risk consequences of product deletion decisions; especially those related to the supply chain. A framework to structure various risks of product deletion in the supply chain can be useful to both practitioners and researchers.Originality/valueThis study advances product portfolio management through enhanced understanding of product deletion decision-making in organizations; and especially contributes to a broader investigation of such decisions in supply chain management. It also structures the factors that play a role in identifying risks.

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“…Another major challenge is data compatibility [21]. Some papers described pragmatically implementing data clearing and formatting steps to make data compatible [6,21,52], whereas most papers mentioned details of initialization, normalization, and standardization [6,21,40,50,52,53] based on scientific rigor or guidance [31,51].…”

Section: Managing Informational Uncertainty In Ai-enabled Decision Makingmentioning

confidence: 99%

“…Lima-Junior and Carpinetti [53] proposed an approach to supporting supply chain performance evaluations by combining supply chain operations reference metrics with an adaptive network-based fuzzy inference system (ANFIS). A random subsampling cross-validation method was applied to select the most appropriate topological parameters for each ANFIS model.…”

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confidence: 99%

Managing Uncertainty in AI-Enabled Decision Making and Achieving Sustainability

Shang

2020

Sustainability

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Artificial intelligence (AI) has been applied to various decision-making tasks. However, scholars have yet to comprehend how computers can integrate decision making with uncertainty management. Obtaining such comprehension would enable scholars to deliver sustainable AI decision-making applications that adapt to the changing world. This research examines uncertainties in AI-enabled decision-making applications and some approaches for managing various types of uncertainty. By referring to studies on uncertainty in decision making, this research describes three dimensions of uncertainty, namely informational, environmental and intentional. To understand how to manage uncertainty in AI-enabled decision-making applications, the authors conduct a literature review using content analysis with practical approaches. According to the analysis results, a mechanism related to those practical approaches is proposed for managing diverse types of uncertainty in AI-enabled decision making.

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An adaptive network-based fuzzy inference system to supply chain performance evaluation based on SCOR® metrics

Cited by 60 publications

References 54 publications

An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization

An Approach to Assess Sustainable Supply Chain Agility for a Manufacturing Organization

Product deletion and supply chain repercussions: risk management using FMEA

Managing Uncertainty in AI-Enabled Decision Making and Achieving Sustainability

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