scholarly journals Using big data to estimate the impact of cruise activity on congestion in port cities

Author(s):  
Agustina Calatayud ◽  
Santiago Sánchez González ◽  
Jose Maria Marquez
Keyword(s):  
Big Data ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 106
Author(s):  
Bader A. Alyoubi

Big Data is gaining rapid popularity in e-commerce sector across the globe. There is a general consensus among experts that Saudi organisations are late in adopting new technologies. It is generally believed that the lack of research in latest technologies that are specific to Saudi Arabia that is culturally, socially, and economically different from the West, is one of the key factors for the delay in technology adoption in Saudi Arabia. Hence, to fill this gap to a certain extent and create awareness about Big Data technology, the primary goal of this research was to identify the impact of Big Data on e-commerce organisations in Saudi Arabia. Internet has changed the business environment of Saudi Arabia too. E-commerce is set for achieving new heights due to latest technological advancements. A qualitative research approach was used by conducting interviews with highly experienced professional to gather primary data. Using multiple sources of evidence, this research found out that traditional databases are not capable of handling massive data. Big Data is a promising technology that can be adopted by e-commerce companies in Saudi Arabia. Big Data’s predictive analytics will certainly help e-commerce companies to gain better insight of the consumer behaviour and thus offer customised products and services. The key finding of this research is that Big Data has a significant impact in e-commerce organisations in Saudi Arabia on various verticals like customer retention, inventory management, product customisation, and fraud detection.


2021 ◽  
pp. 115076
Author(s):  
Covadonga Díez-Sanmartín ◽  
Antonio Sarasa-Cabezuelo ◽  
Amado Andrés Belmonte

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.


2021 ◽  
pp. 097226292110225
Author(s):  
Shobhana Chandra ◽  
Sanjeev Verma

Big data (BD) is making advances in promoting sustainable consumption behaviour and has attracted the attention of researchers worldwide. Despite the increased focus, the findings of studies on this topic are fragmented, and future researchers need a systematic understanding of the existing literature for identification of the research scope. This study offers a systematic review of the role of BD in promoting sustainable-consumption behaviour with the help of a bibliometric analysis, followed by a thematic analysis. The findings suggest that businesses deploy BD to create sustainable consumer experiences, predict consumer buying patterns, design and alter business models and create nudges for sustainable consumption, while consumers are forcing businesses to develop green operations and supply chains to reduce the latter’s carbon footprint. The major research gaps for future researchers are in the following areas: the impact of big data analytics (BDA) on consumerism, the role of BD in the formation of sustainable habits and consumer knowledge creation for sustainable consumption and prediction of green consumer behaviour.


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