The current research scrutinizes the relationship between the three model commitment components (affective, normative, and calculative commitment) and their various influences on customer loyalty. This is particularly in the banking sector setting in Jordan. A self-reported questionnaire was distributed to collect primary data for analysis. 333 completed questionnaires were analyzed via using PLS software to extract the effect of e-service quality on the relationship between customer commitment and loyalty. The results of this study demonstrate that the affective type of commitment has a positive impact on customer loyalty followed by normative commitment and lately by calculative commitment. Moreover, the results show that the influence of the dimensions of customer’s commitment on loyalty is moderated by e-service quality. This study indicates that affective commitment elements (self-identification, sense of belonging and emotional attitudinal components) are essential for customers when they deal with their bank. On the other hand, the cost associated with leaving has shown to have the weakest impact on customer loyalty. Companies must know that customers may switch even though the cost associated with leaving is high.

The purpose of this paper is to examine effects of hedonic and utilitarian aspects of consumer behaviour toward e-loyalty and how e-satisfaction plays a mediating role between them. A survey method was adopted to test the research model. The primary data for the survey was collected during January 2021, using the convenience sampling approach, from business school students. The structural equation modelling method was used to analyse the data with AMOS 22.0 software. The measurement model was estimated through a confirmatory factor analysis before testing the structural model framework and hypotheses (response rate 94.3%, n=264). The results showed that hedonic and utilitarian shopping values have great influence in shaping e-satisfaction. The study also highlights the importance of mediating the role of e-satisfaction between shopping values and e-loyalty. This research highlights why and how ‘satisfaction with website’ matters in the contribution of shopping values to behavioural outcomes by presenting its mediating role. The study offers implications and suggestions to e-retailers by specifying characteristics that should be given more consideration in order to increase online consumer e-satisfaction and e-loyalty. It also contributes to the present body of knowledge on shopping and buying behaviour in the online context, especially for those who have theoretical and managerial interests on the subject in emerging economies like Jordan. The novelty of the paper comes from the fact that it cumulatively captures the factors influencing online consumers’ loyalty in the Jordanian context, apart from validating the mediating role of e-satisfaction.

This study aims to examine and explain the role of brand love in mediating the effect of intensive distribution and promotion of social media on brand loyalty and e-WOM. The population of this research are customers of minimarket franchise businesses in Bali. The sample size used was 200 people with purposive sampling method. The analytical technique used is Path Analysis using SEM-PLS. The results showed that the intensive distribution had a positive and significant effect on brand loyalty and brand love. Brand love is able to mediate the effect of intensive distribution on customer loyalty, brand and e-WOM and brand love are able to mediate the effect of social media promotion on brand loyalty and e-WOM. Therefore, it is important for the minimarket franchise business to pay more attention to intensive distribution and vigorously promote social media through various choices of the latest social media platforms.

Fake news has become a major problem affecting people, society, the economy and national security. This work proposes a combined deep learning model based on the ideal distance weighting method for fake news detection. The proposed model was validated on the ISOT and COVID-19 fake news datasets. Firstly, the ISOT and COVID-19 fake news datasets were collected. Secondly, the training-based models were used to provide accuracy values. After that, these values were transformed into criteria weights using the new ideal distance weighting method. Finally, the prediction value of the proposed model is calculated by the criteria weights. The results show that the proposed method is effective to distinguish the fake news datasets.

The research is aimed to understand the influence of social media in marketing on brand awareness, which in the end influences purchase intention in the fashion industry. It uses a qualitative approach to study the three variables, namely social media marketing, purchase intention, and brand awareness. In this research, the needed number of samples are 270 respondents and data are processed using SPSS to conduct validity, reliability, normality, classic assumption, single, and multiple linear regression. Results from SPSS are also used in the Sobel Test. Complemented with secondary data from literature studies, the hypothesis is tested. From the test, every hypothesis has significant positive influences. In conclusion, a brand can influence purchase intention significantly by utilizing social media marketing. This works by stimulating brand awareness to consumers to influence purchase intention.

Social media technology as borderless media has made it easier for small and medium-sized businesses (SMEs) to interact with their customers. The application of social media has impacted the operation and information sharing of SMEs, allowing them to develop innovation opportunities, to meet customer needs, and to improve firm performance. This study examined the influence of social media use on business networking quality and product innovativeness of SMEs. The data for this cross-sectional study were gathered from jewelry crafting SMEs in Bali, Indonesia using the survey method. The data were analyzed using the covariance-based statistical analysis technique with SPSS via AMOS 23. The results indicate that, while the direct link between social media adoption and firm performance is not significant, this path is fully mediated through business networking quality and product innovativeness. Hence, these SMEs should leverage their social media adoption due to strong business networking quality and product innovativeness enabling competitive advantage that heightens firm performance. Firm-level product innovation can harness the economic performance of the SMEs. The study limitations and future research endeavors are presented at the end of this paper.

This study aims to determine the effect of e-readiness, e-learning, e-book on the achievement of graduate students; and the influence of e-readiness, e-learning, and e-books on the achievement of graduate students. The research population is graduate students with a sample of 210 doctoral students in Jakarta. The sample selection method is simple random sampling. The research method is a survey method with an associative approach. The data analysis technique is structural equation modeling (SEM) using SmartPLS 3.3.3 software and the data was obtained through the distribution of online questionnaires. The results show that there was an effect of e-readiness on graduate achievement; there was an effect of e-learning on graduate achievement; and finally, there was an effect of e-books on graduate achievement. This research can indicate that the curriculum developed by the students is in accordance with the learning outcomes, especially in the implementation of the learning process.

The purpose of this study is to analyze the influence of social media marketing on e-commerce customer satisfaction and loyalty. This study provides insight into the importance of consumer loyalty in the e-commerce industry. The approach used in this study uses quantitative methods through surveys. This study uses a sample of 222 respondents of e-commerce customers. The study uses an online questionnaire through Google Docs. The questionnaire given contains structured questions that are limited by screening, profiling questions and questions related to research variables that affect e-commerce consumer loyalty. The distribution of the questionnaires was carried out by posting on social media groups and direct messages to respondents in accordance with the research requirements. Data analysis of this research, using SEM model using SmartPLS 3.0 software. The results of this study indicate that social media marketing had a significant effect on e-commerce consumer satisfaction, social media marketing had a significant effect on e-commerce consumer loyalty and satisfaction had a significant effect on e-commerce consumer loyalty.

Structural equation modeling offers various estimation methods for estimating parameters. The most used method in covariance-based structural equation modeling (CB-SEM) is the maximum likelihood (ML) estimator. The ML estimator is typically used when fitting models with normally distributed data. The growth of partial least squares path modeling (PLS-PM), including consistent partial least squares (PLSc), has also been noticed by researchers in the SEM fields. The PLSc has elevated interest in the scholastic setting in measuring the performance of various estimation methods in structural equation modeling. The choice of estimation methods has substantial impact in yielding parameter estimates. There could be a trade-off among the estimation methods’ ability to deal with different types of data based on the model tested. Accordingly, this study aims to compare the performance of ML, generalized least squares (GLS), and scale-free least squares (SFLS) for CB-SEM as well as partial least squares (PLS) and consistent partial least squares (PLSc). Multivariate normal data were generated using Monte Carlo simulation with pre-determined population parameters and sample sizes using R Programming packages. To produce the estimated values, data analysis was performed using AMOS and SmartPLS for CB-SEM and PLS-SEM, respectively. The findings illustrate notable similarities between CB-SEM (ML) and PLS-SEM results when the true indicator loading is certainly high.

The aim of the study was to examine the impact of digital marketing capabilities on organizational ambidexterity by focusing on the Information Technology Sector in UAE. Data were primarily gathered through self-reported questionnaires created by Google Forms which were distributed to a purposive sample of managers at different levels via email. This study was conducted structural equation modeling (SEM) to test the hypotheses, which represents a contemporary statistical technique for testing and estimating the relationship between factors and variables. The results showed that the highest impact on organizational ambidexterity was for strategic approach and data content infrastructure, followed by integrating customers with employees, and finally the lowest impact belonged to the process of improving performance. Based on the study findings, the researcher hopes that the decision-makers and managers define all tasks, roles and work procedures in companies through digital marketing systems to improve their organizational ambidexterity and enhance their performance.