Big data for supply chain management: Opportunities and challenges

Benabdellah, Abla Chaouni; Benghabrit, Asmaa; Bouhaddou, Imane; Zemmouri, El Moukhtar

doi:10.1109/aiccsa.2016.7945828

Cited by 24 publications

(23 citation statements)

References 16 publications

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“…Companies with a disciplined strategy of using big data analytics have had better results with investments [46]. In other words, a clear and systematic strategy of big data analytics can provide a better return on investment (ROI) in certain areas of the supply chain, such as marketing, purchasing, shipping, and storage [47].…”

Section: Importance and Application Of Bda In Scmmentioning

confidence: 99%

The Impact of Big Data Analytics on Company Performance in Supply Chain Management

et al. 2019

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Big data analytics can add value and provide a new perspective by improving predictive analysis and modeling practices. This research is centered on supply-chain management and how big data analytics can help Romanian supply-chain companies assess their experience, strategies, and professional capabilities in successfully implementing big data analytics, as well as assessing the tools needed to achieve these goals, including the results of implementation and performance achievement based on them. The research method used in the quantitative study was a sampling survey, using a questionnaire as a data collection tool. It included closed questions, measured with nominal and ordinal scales. A total of 205 managers provided complete and useful answers for this research. The collected data were analyzed with the Statistical Package for the Social Sciences (SPSS) package using frequency tables, contingency tables, and main component analysis. The major contributions of this research highlight the fact that companies are concerned with identifying new statistical methods, tools, and approaches, such as cloud computing and security technologies, that need to be rigorously explored.

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Section: Importance and Application Of Bda In Scmmentioning

confidence: 99%

The Impact of Big Data Analytics on Company Performance in Supply Chain Management

et al. 2019

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“…The framework helps to translate the business need into an IT-related requirement: Do we have the hardware and software that is required to gather and process (relatively) low volumes of unstructured data in near realtime? It should, however, be noted that there are technical and data-related challenges (Benabdellah et al, 2016;Ylijoki & Porras, 2016a). Technical challenges are hardware-and software -related, such as managing vast volumes of data with a Hadoop cluster, or using a not only SQL (NoSQL) database to store unstructured data.…”

Section: Assess Current Situation and Big Data Impact: This Can Be Domentioning

confidence: 99%

Innovation capabilities as a mediator between big data and business model

Ylijoki

Sirkiä

Porras

et al. 2018

Journal of Enterprise Transformation

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The digital transformation is forcing organizations to change towards more data-driven business models. In this paper, we propose a conceptual framework that explains the role of innovation capabilities as a mediator between big data and business model. Using the design science research method approach, we built the framework based on the existing literature. We then applied the framework to the real-world context with three firms and refined it based on the feedback. This study contributes to big data research by pointing out the role of human and data-driven innovation capabilities in the big data value creation process. The developed framework is practitioner oriented, offering a systematic approach towards the development of big data capabilities.

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“…Supply chain management (SCM) systems are the most crucial parts of industries and organizations; a well-defined, effective SCM can directly influence operations, productions, and profitability of organizations [ 7 , 8 , 9 ]. As the time past, to fulfill a massively growing demand of the supply chain over the world, industries, organizations, or firms, have been adopting the advanced technologies, such as radio frequency identification (RFID) and sensing solutions, artificial intelligence (AI), and cloud computing to manage the extensively large and complex operations of the modern supply chain ecosystem [ 9 , 10 , 11 , 12 , 13 ]. Thus, gathering and managing large data in the complex and large-scale supply chain, in which entities and operations involved are distributed over various locations, undoubtedly is a big challenge.…”

Section: Introductionmentioning

confidence: 99%

Intuitive Development to Examine Collaborative IoT Supply Chain System Underlying Privacy and Security Levels and Perspective Powering through Proactive Blockchain

Shahzad

Zhang

Gherbi

2020

Sensors

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Undoubtedly, the supply chain management (SCM) system is an important part of many organizations worldwide; over time, the technologies used to manage a supply chain ecosystem have, therefore, a great impact on businesses’ effectiveness. Among others, numerous developments have been made that targeted to have robust supply chain systems to efficiently manage the growing demands of various supplies, considering the underlying requirements and main challenges such as scalability, specifically privacy and security, of various business networks. Internet of things (IoT) comes with a solution to manage a complex, scalable supply chain system, but to provide and attain enough security during information exchange, along with keeping the privacy of its users, is the great inherent challenge of IoT. To fulfill these limitations, this study designs and models a scaled IoT-based supply chain (IoT-SC) system, comprising several operations and participants, and deploys mechanisms to leverage the security, mainly confidentially, integrity, authentication (CIA), and a digital signature scheme to leverage potentially secured non-repudiation security service for the worst-case scenario, and to leverage privacy to keep users sensitive personal and location information protected against adversarial entities to the IoT-SC system. Indeed, a scaled IoT-SC system certainly opens new challenges to manage privacy and security while communicating. Therefore, in the IoT-SC system, each transaction writes from edge computing nodes to the IoT-SC controller is thoroughly examined to ensure the proposed solutions in bi-directional communication, and their robustness against adversarial behaviors. Future research works, employing blockchain and its integrations, are detailed as paces to accelerate the privacy and security of the IoT-SC system, for example, migrating IoT-centric computing to an immutable, decentralized platform.

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Big data for supply chain management: Opportunities and challenges

Cited by 24 publications

References 16 publications

The Impact of Big Data Analytics on Company Performance in Supply Chain Management

The Impact of Big Data Analytics on Company Performance in Supply Chain Management

Innovation capabilities as a mediator between big data and business model

Intuitive Development to Examine Collaborative IoT Supply Chain System Underlying Privacy and Security Levels and Perspective Powering through Proactive Blockchain

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