ABSTRACT
University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, due to the COVID-19 pandemic. This type of education is significant because it ensures that all students receive the required learning. The statistical evaluations are limited in providing good predictions of the university’s e-learning quality. That is forcing many universities to go to online and blended learning environments. This paper presents an approach of statistical analysis to identify the most common factors that affect the students’ performance and then use artificial neural networks (ANNs) to predict students’ performance within the blended learning environment of Saudi Electronic University (SEU). Accordingly, this dissertation generated a dataset from SEU’s Blackboard learning management system. The student’s performance can be tested using a set of factors: the studying (face-to-face or virtual), percentage of attending live lectures, midterm exam scores, and percentage of solved assessments. The results showed that the four factors are responsible for academic performance. After that, we proposed a new ANN model to predict the students’ performance depending on the four factors. Firefly Algorithm (FFA) was used for training the ANNs. The proposed model’s performance will be evaluated through different statistical tests, such as error functions, statistical hypothesis tests, and ANOVA tests. © 2022 by the authors.
ABSTRACT
Online Food Delivery Platforms (OFDPs) has witnessed phenomenal growth in the past few years, especially this year due to the COVID-19 pandemic. This Pandemic has forced many governments across the world to give momentum to OFD services and make their presence among the customers. The Presence of several multinational and national companies in this sector has enhanced the competition and companies are trying to adapt various marketing strategies and exploring the brand experience (BEX) dimension that helps in enhancing the brand equity (BE) of OFDPs. BEXs are critical for building brand loyalty (BL) and making companies profitable. Customers can experience different kinds of brand experiences through feeling, emotions, affection, behavior, and intellect. The present research work is taken up to analyze the factors affecting BEX and its impact on BL and BE of the OFDPs and analyze the mediating role of BL in the relationship between BEX and BE of the OFDPs in the Indian context. A survey of 457 Indian customers was carried out. A questionnaire was used for data collection and a mediation study was used to test hypothesized relationships. Our computational analysis reveals that BEX influences the BL and BE of OFDPs. The study further indicates that BL mediates the relationship between BEX and BE of OFDPs. The effective marketing and relationship management practices will help company to enhance BEX that will enable in enhancing BL and raising BE of their product. It therefore provides a more thorough analysis of BEX constructs and their consequences than previous research. Some of the managerial implication, limitations, and scope of future research are also presented in the study. © 2021 Tech Science Press. All rights reserved.