Role of Big Data Analytics in supply chain management: current trends and future perspectives

Maheshwari, Sumit; Gautam, Prerna; Jaggi, Chandra K.

doi:10.1080/00207543.2020.1793011

Cited by 155 publications

(95 citation statements)

References 108 publications

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“…The input variables of the neural network adopted the characteristics of the commonly used Z-score five-variable model that had been developed and matured at that time. Even if the problem of neural network algorithm solution had not been solved at that time, the model finally achieved 80% accuracy [ 6 ]. Yang and Wang used support vector machine to conduct bankruptcy early warning research on bank financial data samples and empirically tested the effectiveness of its application in this field by comparing and analyzing various previous machine learning models [ 7 ].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Construction of Financial Management Early Warning Model Based on Improved Ant Colony Neural Network

Wang

2021

Computational Intelligence and Neuroscience

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With the advent of the era of economic globalization, the world capital market is also facing financial risks. It is necessary to have a corresponding financial management early warning model to reduce economic losses. This paper uses the combination of ant colony algorithm and neural network algorithm to build a neural network improved by ant colony algorithm model. By setting relevant assumptions, the financial statements and annual report texts are predicted and analyzed and compared with the original static data forecasting model. Compared with traditional methods, the time series sequencing analysis used in this paper makes the result prediction more accurate. This allows one year’s data to be used to predict the data for the next two years. This research can provide a corresponding reference for the optimization of financial management early warning system.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Construction of Financial Management Early Warning Model Based on Improved Ant Colony Neural Network

Wang

2021

Computational Intelligence and Neuroscience

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“…Big Data refers to data sets with a massive amount of information (exceeding many zettabytes of data) and which require other utilities than commonly used software to gather, store, and process data within a short time [80,81]. Big Data allows one to efficiently manage and use the constantly growing database [12,[79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94]. For example, online stores can analyse with almost total accuracy what was sold and how promotions and special offers influenced sales; using Big Data, they can predict what a customer might like to buy next [94].…”

Section: Big Data and Industry 50mentioning

confidence: 99%

“…For example, online stores can analyse with almost total accuracy what was sold and how promotions and special offers influenced sales; using Big Data, they can predict what a customer might like to buy next [94]. Based on research carried out in the United States, the Middle East, Europe, Asia and Australia, Raman et al [85] formulated a generalisation about how Big Data affects the supply chain industry. It enables operational excellence, reduces costs, increases customer satisfaction, and reduces the communication gap between demand and supply chain management.…”

Section: Big Data and Industry 50mentioning

confidence: 99%

Internet of Things and Other E-Solutions in Supply Chain Management May Generate Threats in the Energy Sector—The Quest for Preventive Measures

Dobrowolski

2021

Energies

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Energy firms are the beneficiaries and initiators of innovation, and energy investments are a crucial area of business activity that is specially protected in any country. This is no wonder, as energy security is the basis for the functioning of states and economies. The Internet of Things and Big Data create both new challenges and new threats. This study aimed to identify the potential threats and determine preventive measures, as well as to establish the agile principles related to energy firms’ logistics. The method of the narrative summary in combination with the literature searching method was used. Two conclusions emerged: first, research serves to develop the discipline of management science; second, the identification of risks associated with innovation serves practitioners. In addition, the study defined further research directions.

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“…Hoertel et al (Hoertel et al 2020 ) developed a stochastic agent-based model of coronavirus disease with various intervention strategies. Maheshwari et al (Maheshwari et al 2020 ) stressed on the role of Big Data Analytics in the present COVID-19 transmission. Chen et al (Chen et al 2021 ) in his work addresses on the very interesting and relevant query “Can customer arrival rates be modelled by sine waves?…”

Section: Introductionmentioning

confidence: 99%

Stochastic models on the transmission of novel COVID-19

Mishra¹

2021

Int J Syst Assur Eng Manag

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New diseases have always been part of humanity’s world, and some of them had created severe threat to human kind and challenge to the researchers and medical practitioners. The deadly novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome- coronavirus -2) said to be COVID-19, the name given by WHO on February 11, 2020, is presently the most disastrous infectious disease. In the present paper our basic objective is to assess the risk of spreading the disease in human population and is measured in terms of probability. The proposed stochastic models help us to understand the probability of infection to n number of customers when these customers have spent time t in any system, say, shopping mall or public transportation or restaurant. Stochastic models are developed with arrival rate of the customers towards the system to be considered as a Poisson distribution and service time following an exponential distribution. A special case of cardiac centre is considered in this paper, where the risk of COVID-19 is highly contagion, with limited number of beds and doctors.

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Role of Big Data Analytics in supply chain management: current trends and future perspectives

Cited by 155 publications

References 108 publications

[Retracted] Construction of Financial Management Early Warning Model Based on Improved Ant Colony Neural Network

[Retracted] Construction of Financial Management Early Warning Model Based on Improved Ant Colony Neural Network

Internet of Things and Other E-Solutions in Supply Chain Management May Generate Threats in the Energy Sector—The Quest for Preventive Measures

Stochastic models on the transmission of novel COVID-19

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