Artificial Neural Network Models for Large-Scale Data

Artificial intelligence (ARTINT) and information have been famous fields for many years. A reason has been that many different areas have been promoted quickly based on the ARTINT and information, and they have created many significant values for many years. These crucial values have certainly been used more and more for many economies of the countries in the world, other sciences, companies, organizations, etc. Many massive corporations, big organizations, etc. have been established rapidly because these economies have been developed in the strongest way. Unsurprisingly, lots of information and large-scale data sets have been created clearly from these corporations, organizations, etc. This has been the major challenges for many commercial applications, studies, etc. to process and store them successfully. To handle this problem, many algorithms have been proposed for processing these big data sets.

Assessing the Effects of Delivery Attributes on E-Shopping Consumer Behaviour

E-consumer behaviour plays a vital role in e-commerce worldwide. This paper addresses the importance of delivery time, delivery fee, and delivery reception, and the influence of delivery fee and reception on e-consumers’ behaviour by analysing the following hypotheses: delivery attributes affect e-shopping behaviour, and delivery attributes affect e-consumers’ behaviour according to their sociodemographic characteristics. Data were obtained from a web-based survey with Brazilian e-consumers, and logistic regression and artificial neural network models were estimated to assess consumer behaviour. We found that delivery fee willingness to pay and privacy are affected by delivery times according to gender. Delivery fees affect the e-consumer according to gender, the habit of purchasing books and leisure products, privacy, promotions, and pricing, and influence the e-shopping decision by age, purchase of electronic products, and promotions. Delivery reception is relevant according to age, income, gender, frequency of e-shopping, privacy, and pricing. Furthermore, delivery fees influence the e-shopping decision by age, purchase of electronic products, and promotions. Finally, delivery fee, willingness-to-pay, and privacy are characteristics influenced by reception on the e-shopping decision. Further analyses would include the dynamic aspects of e-consumer behaviour and the impacts of COVID-19 in the e-consumption patterns and its effects on e-commerce deliveries.