E-consumer rights aim to provide consumers and sellers a fair opportunity when dealing online, which requires both parties to know their rights and ethics. Therefore, the purpose of this study is to verify the impact of consumer rights available on reputed online store websites in Saudi Arabia (KSA) on the customer service, using expectation confirmation theory (ECT). A random sampling technique was used for primary data collection from a sample size of 152 faculty members. IBM Software Package for Social Sciences SPSS-26 and structural equation modeling (SEM) LISREL software programs were used for data analysis. The findings show that e-consumer rights have positive and significant effects on customers’ e-reliability and e-responsiveness. In addition, consumers’ income significantly influences their e-responsiveness, while the number of e-dealings per month significantly influences both e-reliability and e-responsiveness. The results of the study also provide an inventory of eight reasons why consumers prefer to deal with local electronic stores over foreign ones. Based on these findings, theoretical importance, practical implications, and suggestions for future research are discussed.

This study aims at investigating the factors that determine the continuous intention to use smartwatches, one of the most prevalent types of wearable devices. The study extends the expectation confirmation model (ECM) by incorporating other variables (i.e., construct) which capture the unique context of smartwatches continuous usage, namely healthology, perceived aesthetics, habit, and social influence. Hypotheses were assessed using partial least square structural equation modeling (PLS-SEM) approach on data collected from 287 actual smartwatch users. The results reveal that performance expectancy, satisfaction, healthtology, perceived aesthetics and habit significantly influence the continuous usage of smartwatches, while social influence is non-significant. The research model of this study explains 65.7% of the variance in the continuous usage intention of smartwatches. The insights provided by this study suggest fruitful opportunities for future research. They can also help smartwatches companies, developers and marketers with strategies and directions for further development and growth by ensuring users’ continuous usage of smartwatches.

This study conducted a test to see the influence of data quality analytics, business ethics, and cyber risk management on operational performance and its implication on corporate sustainability of Fintech P2P Lending companies registered and licensed in Indonesian Financial Services Authority (OJK). This study used descriptive analysis and statistical method Structural Equation Modeling (SEM)-Lisrel. The data was collected by using questionnaires given to 104 managers from 91 Fintech P2P Lending companies registered and licensed at OJK until the end of December 2021. The results show that data quality analytics and cyber risk management had a positive and significant influence on operational performance. The results also show that analytical data quality, business ethics and cyber risk management had a positive and significant influence on operational performance. The findings of this study added to the limitations of the research literature on the elaboration of variables that determine performance and business sustainability in Fintech P2P lending.

The purpose of the current paper is to identify influential aspects of published literature and future research questions to set forth future research agenda based on comprehensive literature review using bibliometric and content analysis. The study analyzed 1225 documents from the international Scopus database using bibliometric analysis and content analysis. VOSviewer software is used for bibliometric analysis. The analysis revealed that most of the information was derived from the Finance Research Letters. Moreover, the United Kingdom is the most cited country, while Tianjin University in China has the highest publications affiliations. Furthermore, the analysis shows that the keyword analysis of cryptocurrency literature had four classes of research streams in cryptocurrency, namely, cryptocurrency, Blockchain, Fintech, and currency, representing the most upcoming trends. The present study makes a significant contribution to the literature by providing a framework for future research. The framework provides opportunities to future researchers to explore the web of relations among some identified research streams as future research agenda.

The brisk spread of Covid-19 led educational policymakers and organizations to opt for better alternatives to resume the students' educational journey. In this context, Microsoft Teams remained one of the most devoted and credible online platforms that greatly facilitated the educational process across the globe. Current research also analyzed Microsoft Teams acceptance using the self-proposed conceptual model supported by the Technology Acceptance Model by Davis. We employed the survey method and examined the gathered using the applied Structural Equation Modelling (SEM). Results indicated that there is a significant impact of Covid-19 on the Perceived Ease of Use (p> 0.000) and Perceived Usefulness (p> 0.000). Besides, the relationship between Perceived Ease of Use and Perceived Usefulness also remained significant (p> 0.000). Moreover, the proposed relationship between Attitude, Perceived Ease of Use, and Perceived Usefulness also remained substantial (p> 0.009 and p> 0.000). However, the relationship between Attitude and Behavioral Intention remained insignificant (p> 0.556). Finally, the relationship between Behavioral Intention and Microsoft Teams Acceptance remained significant (p> 0.088). Thus, we concluded that Microsoft Teams is an effective study tool that unites students and instructors in the United Arab Emirates. It governs eLearning experiences and, therefore, provides a virtual environment to students and directly influences our perceptions and behavior.

This paper empirically identifies the predictors influencing the use of promo code in Jordan. This research extended TAM and TBP models with perceived enjoyment and brand image in the context of digital shopping features. The study utilized 379 surveys distributed in Jordan and analyzed the data using SEM. Findings of this study confirmed the proposed model, where brand image, perceived enjoyment, perceived behavior control and social influence significantly predict customers behavioral intention to use promo code with an R2 = 59%. The model of this study also supported the role of perceived ease of use and social influence in predicting brand image. Discussion and conclusion are depicted at the end of this paper.

This paper focuses on five-star hotels in Jordan to investigate the impact of influencer marketing on overall brand equity. The mediating role played by brand awareness and customer brand engagement between influencer marketing and overall brand equity is tested. The survey method is employed to conduct this research, and data is collected from 300 respondents. The proposed hypotheses are tested using structural equation modeling. The results indicate that influencer marketing directly influenced overall brand equity, brand awareness and customer brand engagement partially mediate the relationship between influencer marketing and overall brand equity.

In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the properties of Markov chains are fulfilled. In this case, the tweets that are received by followers only depend on the tweets from the previous followers. Knowledge Discovery in Database (KDD) in Data Mining is used to be research methodology including pre-processing, data mining process using homogeneous CTMC, and post-processing to get the influencers using visualization that predicts the number of affected users. We assume the number of affected users follows a logarithmic function. Our study examines the Indonesian Twitter data users with tweets about covid19 vaccination resulted in dynamic influencer rankings over time. From these results, it can also be seen that the users with the highest number of followers are not necessarily the top influencer.

There are various reasons why vaccine fear has resulted in public rejection. Students have raised concerns about vaccine effectiveness, leading to hesitation when it comes to vaccination. Vaccination apprehension impacts students' perceptions, which has an impact on the acceptability of an e-learning platform. As a result, the goal of this study is to look at the post-acceptance of an e-learning platform using a conceptual model with several factors. Every variable makes a unique contribution to the e-learning platform's post-acceptance. In the current study, TAM variables were combined with additional external factors such as fear of vaccination, perceived routine use, perceived enjoyment, perceived critical mass, and self- efficacy, all of which are directly associated with post-acceptance of an e-learning platform. Here, a hybrid conceptual model was used to evaluate the newly widespread use of e-learning platforms in this area in this study in the UAE. In the past, empirical investigations primarily used Structural Equation Modeling (SEM) analysis; however, this study used a developing hybrid analysis approach that combines SEM with deep learning–based Artificial Neural Networks (ANN). This study also employed the Importance–Performance Map Analysis (IPMA) to determine the significance and performance of each element. Through the findings, it was found that fear of vaccination, perceived ease of use, perceived usefulness, perceived routine use, perceived enjoyment, perceived critical mass, and self-efficiency all had a significant impact on students' behavioral intention to use the e-learning platform for educational purposes. It was also shown in the analysis of ANN as well as IPMA that the perceived ease of use of the e-learning platform is the most important indicator of post-acceptance. The proposed model, in theory, provides appropriate explanations for the elements that influence post-acceptance of the e-learning platform in terms of internet service factors at the individual level. In the practical sense, these findings will help decision-makers and practitioners in higher education institutions identify the factors that should be given extra care and plan their policies accordingly. The ability of the deep ANN architecture to identify the non-linear relationships between the factors involved in the theoretical model has been determined in this research. The implication offers extensive information about taking effective steps to decrease the fear of vaccination among people and increase vaccination confidence among teachers and educators and students, consequently impacting society.

This study is to analyze the influence of the quality of information on the decision to choose CNNIndonesia.com media either directly or through the mediation of trust variables. The tremendous growth of cyber media in Indonesia, followed by the development of online media, has made people more careful in choosing online media. Meanwhile, the use and gratification theory states that the most important role of media is to meet people's needs and motivations, how certain media are sought and selected to meet their needs. This study uses a survey method through a quantitative approach positivistic. The sample was determined by an accidental sampling technique with a sample of 115 respondents. Data analysis was performed using Partial Least Square analysis with the SmartPLS version 3 program. The data analysis shows that the quality of information has a significant effect on increasing trust in CNNIndonesia.com media, the quality of information has a significant effect in increasing the decision to choose CNNIndonesia.com media, and trust has a significant effect in increasing the decision to choose CNNIndonesia.com media. This study also found that the trust variable was able to mediate the effect of information quality on the decision to choose CNNIndonesia.com media.