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The purpose of this paper is to develop a prototype of Online Food Delivery Application that addresses the actual needs of the user and to study the factors affecting the acceptance of Food Friend Application (FFA).

This is an applied research study using design thinking to study the real needs of consumers when ordering food online during the COVID-19 outbreak. The real needs of customers were used to create FFA. Then, the key predictors of FFA adoption were studied by integrating psychological variables, including Alertness to distinction, Openness to novelty, Orientation in the present; and Technological variables Design, Information Quality and Mobility, with comprehensive data analysis. Initially, Structural Equation Modeling was used to study the statistical relationships toward FFA acceptance, while a neural network model was used to validate the first step analysis.

Analysis results from both methods confirmed that Alertness to distinction, Orientation in the present, Mobility and Openness to novelty affected FFA at statistically significant levels. Surprisingly, technological variables in terms of Design and Information Quality had no statistical relationship toward FFA.

In addition to dealing with digital disrupts, the current business world also needs to deal with the pandemic and the rapidly changing consumer behavior. COVID-19 is a clear catalyst for digital business trends, for example, food delivery that has to deal with dramatic changes in consumer behavior. The strong methodological results of this research are greatly beneficial to academics, food online delivery service providers, application developers and government agencies.

The purpose of this study was to investigate the factors that would influence the intention to use social banking during the coronavirus disease 2019 (COVID-19) pandemic. This study integrated two theories, namely the integrated technology acceptance model (TAM), which focused on the acceptance of technology by consumers, and electronic word of mouth (eWOM), which focused on consumer behavior. This study also applied the significant variables in the context of Thailand, which were trust and perceived risk.

A quantitative research method was applied by collecting data from 411 consumers during the COVID-19 pandemic in Thailand. A combined multi-analytic approach of a structural equation model (SEM)-neural network was used to analyze the data. In the first step, the SEM was used to determine the important factors that affected the adoption of social banking. In the second step, a neural network model was used to prioritize the important factors to confirm the results of the SEM method in step 1.

The empirical results of the data analysis using the SEM method showed that the perceived ease of use, perceived usefulness and trust were the most significant determinants of adopting social banking. This was consistent with the neural network method of the important factors.

The results of this research could initiate issues that should be developed for the continued use of online banking among consumers in the context of developing countries, such as Thailand.

This research model provided guidelines for the effective development of mobile banking applications for use on mobile devices. The results of this research made strong theoretical contributions to the existing literature on online banking and offered procedures and information to the relevant sectors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2022-0709

This study aims to study the adoption of online learning in higher education through the perspective of the readiness of the following factors: self-directed learning (SDL), motivation for learning (ML), online communication self-efficacy (OCE) and learner control (LC). This was an empirical study in the context of developing countries, specifically Thailand.

This research applied a quantitative study method by collecting data from 605 higher education students in autonomous government institutions. The data analysis applied a structural equation model (SEM) to identify the significant determinants that affected the adoption of online learning. Moreover, this study applied a neural network model to examine the findings from the SEM.

From the data analysis using the SEM and neural network model, the results matched each other. The results of the empirical study were firm and supported that the readiness factors of students had statistical significance in the following order: SDL, OCE, LC and ML.

The study results showed an operational perspective to be prepared for online teaching, both for the related department of the Ministry of Education to support the infrastructure for online learning and for universities and instructors to create learning conditions and design teaching processes consistently with the online learning context.

Since the learning management in the 21st century is focused on student-centred learning, the empirical results obtained from this study presented the view of learners’ readiness that would influence the acceptance of online learning. In addition, this research presented the challenges and opportunities of online instruction during the COVID-19 pandemic.

The purpose of this study was to investigate factors that influence the intention to use mobile learning (m-learning) by learners in developing countries such as Thailand. This study integrated two theories; namely, the unified theory of acceptance and use of technology (UTAUT), which focuses on technology, and uses and gratifications theory (UGT), which involves studying learners’ motivation.

Applying a quantitative research method, this study conducted a survey of 359 undergraduates. The partial least squares methods and a statistical analysis technique based on the structural equation modelling (SEM), were used to analyse the data.

The results revealed that the performance expectancy, cognitive need, affective need and social need had significant effect on intention to use m-learning. Furthermore, this study found a significant effect of the cognitive need on the performance expectancy and social need on effort expectancy.

This research model has provided guidelines for the effective development of educational applications for use on mobile devices. The findings can be applied as guidelines for public organizations to develop educational strategies to further encourage the development of online learning.

This research closed a gap of understanding from previous studies by integrating UTAUT and UGT. The method derived from the theoretically integrated model could be applied to study the intentions for the implementation the mobile learning application from the context of developing countries such as Thailand.

The purpose of this paper is to investigate the use of mobile assisted language learning (MALL) in vocabulary learning among English foreign language learners in China with a lens on academic major difference. This study hypothesizes that academic majors including Science, Technology, Engineering and Mathematics (STEM) and non-STEM differentiate the learners’ perception of computer self-efficacy (CSE) and MALL learning performance as well as moderate the effect of CSE on language learning performance.

Sample data for this study were collected from 200 university students enrolled in both STEM and non-STEM majors. Under the quasi-experiment, this study had been conducted vocabulary training, pre-test, post-test and a questionnaire. The Statistical Package for the Social Sciences, a statistical analysis technique based on ANOVA and regression were used to analyze the data.

The results support hypotheses that CSE, learning score and satisfaction are rated higher for STEM students than non-STEM ones and indicate the effect of CSE on language learning performance is stronger for STEM students than non-STEM ones in using MALL.

This paper addressed important issues in language learning on the academic major difference. The findings would be the guidelines for educational organizations to motivate and stimulate students with sustainable self-confidence important not only for improvement in students’ language learning achievements and outcomes but also for the advancement of mobile technology in language learning.

Reviewing the existing literature in the field of e-learning success reveals a considerable number of studies that primarily investigate the causal relationships proposed by the DeLone and McLean (D&M) information system (IS) success model. However, the various relationships in the D&M model have found different levels of support or even contradictory results within the empirical literature. To synthesize the existing knowledge in the field of e-learning success, the authors have conducted a meta-analysis of e-learning success studies using D&M to combine the quantitative results and validate the model in this field. Furthermore, a moderator analysis involving user types was performed to examine the situation under which they may have different effects.

For this purpose, through a systematic review of the studies, 44 independent studies were selected from 29 qualified related journals. In order to analyze the quantitative results of the studies, the meta-analysis of the effect sizes of the casual relationships in the D&M model has been used.

The findings indicated that all relationships of the model were supported. It was also revealed that the extent of effect sizes of the examined relationships depends on the type of user. Except for one relationship (user satisfaction and net benefit), all effect sizes of employees were more than those of students and teachers.

This meta-analysis reviewed the relationships found in the literature on D&M constructs in e-learning contexts. This study better explains the e-learning success factors by consolidating contradictory findings in the past researches and contributes to the existing e-learning success literature. The findings can assist educational institutions and organizations in decision-making because the findings resulting from the meta-analysis are more consistent than previous primary researches.

Despite the widespread use of the D&M model in the field of e-learning success, no study has yet consolidated the quantitative findings of these studies and the current field abounds in some controversies and inconsistent findings. This paper integrates the results of empirical studies that examined the relationships within the D&M model. The main contribution of this paper, which is the first of its kind, is to apply meta-analysis to reconcile the conflicting findings, investigate the strengths of the relationships in the D&M model and provide a consolidated view.