Big Data Analytics and Its Applications in Supply Chain Management

Darvazeh, Saeid Sadeghi; Vanani, Iman Raeesi; Musolu, Farzaneh Mansouri

doi:10.5772/intechopen.89426

Cited by 22 publications

(11 citation statements)

References 77 publications

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“…Among the retail industry's matters contributing to supply chain shortcomings is adopting traditional methods of planning and procuring goods. According to research by the consulting giant McKinsey & Co., only 31% of retailers consider that they have adequate skills to help them manage disruptive supply chain situations (Darvazeh et al, 2020). This lack of flexibility in the supply chain is directed to stockouts, overstocking, and loss of sales, which mainly hit those companies that follow the just-in-time inventory model.…”

Section: Examples Of Industries or Companies Struggling With Outdated...mentioning

confidence: 99%

“…However, businesses behind the curve and needing to adapt to new trends stand a chance of getting stuck and losing a competitive edge (Modgil et al, 2022). In a report, IBM suggests that companies that fully experience data analytics are 2.2 times more likely to beat their peers in increased profitability (Darvazeh et al, 2020).…”

Section: Analysis Of the Potential Long-term Consequences Of Maintain...mentioning

confidence: 99%

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Integration of Emerging Technologies AI and ML into Strategic Supply Chain Planning Processes to Enhance Decision-Making and Agility

Vummadi,

Hajarath

2024

IJSCM

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Purpose: The aim of this research was to discuss the use of artificial intelligence (AI), machine learning (ML), and big data analytics as fundamental pillars of strategic supply chain management, for better decision-making, more precise forecasting, and higher supply chain agility. Methodology: The paper reviewed existing literature and industry reports to get an in-depth insight into the modern supply chain planning environment, the problems that it faces, and the efficiency of traditional techniques. It then analyzed the opportunities of utilization of AI, ML and big data analytics as well as the certain technologies or techniques that could be utilized, such as the predictive/prescriptive analytics, digital twins and blockchain. Findings: The study concluded that the traditional supply chain planning processes are becoming more and more out of style and inefficient, taking into account the business environment that are constantly changing, global supply chains, and technological advancements. It emphasized the risks to long-term performance associated to relying too much on the past practices and a call for action for progressive modernization of supply chain planning mechanisms. Unique Contribution to Theory, Practice and Policy: The report pointed to innovative ways such as AI, ML, and big data analytics for the integration into the supply chain operations for increasing the productivity, resilience and competitiveness. Moreover, it promoted the increase of budgeting on the talent side in order to obtain an appropriate use of technology and to explore new paths in the market.

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Section: Examples Of Industries or Companies Struggling With Outdated...mentioning

confidence: 99%

Section: Analysis Of the Potential Long-term Consequences Of Maintain...mentioning

confidence: 99%

Integration of Emerging Technologies AI and ML into Strategic Supply Chain Planning Processes to Enhance Decision-Making and Agility

Vummadi,

Hajarath

2024

IJSCM

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“…The use of AI and sensor technology provides revolutionary solutions ( Table 2 ) for streamlining operations in the livestock supply chain, from counting and tracking animals to predicting and optimizing the logistical routes [ 27 , 28 ]. RFID technology offers transformative potential in the field of automated cattle counting, a critical factor in disease control, inventory management, animal movement tracking, productivity enhancement, and livestock enterprise profitability [ 27 , 29 , 30 ]. Moreover, sensor technologies and AI algorithms, through real-time monitoring and predictive analytics, provide vital insights into every stage of the supply chain.…”

Section: Application Of Ai and Sensor Technology In Livestock Managementmentioning

confidence: 99%

Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation

Neethirajan

2023

Sensors

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This technical note critically evaluates the transformative potential of Artificial Intelligence (AI) and sensor technologies in the swiftly evolving dairy livestock export industry. We focus on the novel application of the Internet of Things (IoT) in long-distance livestock transportation, particularly in livestock enumeration and identification for precise traceability. Technological advancements in identifying behavioral patterns in ‘shy feeder’ cows and real-time weight monitoring enhance the accuracy of long-haul livestock transportation. These innovations offer benefits such as improved animal welfare standards, reduced supply chain inaccuracies, and increased operational productivity, expanding market access and enhancing global competitiveness. However, these technologies present challenges, including individual animal customization, economic analysis, data security, privacy, technological adaptability, training, stakeholder engagement, and sustainability concerns. These challenges intertwine with broader ethical considerations around animal treatment, data misuse, and the environmental impacts. By providing a strategic framework for successful technology integration, we emphasize the importance of continuous adaptation and learning. This note underscores the potential of AI, IoT, and sensor technologies to shape the future of the dairy livestock export industry, contributing to a more sustainable and efficient global dairy sector.

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“…It also includes supplier relationship management or customer relationship management. Supplier relationship management involves establishing discipline in strategic planning and managing all interactions with organizations' suppliers [26].…”

Section: Literature Reviewmentioning

confidence: 99%

Supply Chain Management and Big Data Concept Effects on Economic Sustainability of Building Design and Project Planning

2021

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Building design and project planning face significant challenges in the 21st century. On the one hand, it is the requirement of building users. On the other hand, new possibilities and technologies contribute to the overall efficiency of construction projects. The progress of information and communication technologies is one of the most extensive opportunities that can significantly streamline designing sustainable buildings. The big data concept is increasingly being implemented in all areas of industry. The design of buildings and the entire civil engineering industry is where these processes are becoming automated with the help of information technology. Supply chain management based on information systems represents a great potential in the design of buildings and planning of construction projects in materials procurement. These facts lead to the assumption that the concept of big data and supply chain management systems can effectively influence the sustainable design of buildings. These technologies are expected to improve economic sustainability by reducing costs and shortening materials’ delivery time and construction time. The research is carried out on a sample of construction projects. The level of use of the concept of big data and SCM systems and their impact on economic sustainability in the form of parameters such as construction project costs, delivery time of materials and building construction were examined. Data collection took place through a questionnaire survey. Within the used methods, this research worked data-free but also scaled to the Likert scale. Data processing was performed using Pearson dependence and the use of a correlation coefficient. The main goal of the research was to analyze the impact of using the concept of big data and supply chain management on the cost of the building, the time of delivery of materials and the construction of the building. It was found that the use of SCM and BD has an impact on the monitored parameters, and the correlation rate is high.

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Big Data Analytics and Its Applications in Supply Chain Management

Cited by 22 publications

References 77 publications

Integration of Emerging Technologies AI and ML into Strategic Supply Chain Planning Processes to Enhance Decision-Making and Agility

Integration of Emerging Technologies AI and ML into Strategic Supply Chain Planning Processes to Enhance Decision-Making and Agility

Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation

Supply Chain Management and Big Data Concept Effects on Economic Sustainability of Building Design and Project Planning

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