The Dark Side of Mobile Learning via Social Media: How Bad Can It Get?
TL;DR: In this paper, the authors examined the negative influences of mobile learning via social media on university students and found that the antecedents for both technostress and exhaustion were able to account for more than half of their respective variances.
Abstract: As the COVID-19 pandemic continues to spread at an unprecedented rate, many universities around the world halted physical forms of teaching and learning to stop the spread of the virus. As a result, many university students were forced to utilize online learning through channels such as mobile social media. Due to the novelty of this situation, there are many unknowns particularly with the negative influences of mobile learning via social media on university students. Thus, this study looks to examine this subject matter from the perspective of the stimulus-organism-response theory. The uniquely developed research model included four stimuli (i.e., social overload, information overload, life invasion, and privacy invasion), two organisms (i.e., technostress and exhaustion) as well as a response in terms of reduced intention to use mobile learning via social media. The responses were collected from 384 university students via an online survey and analyzed with the Partial-Least-Square-Structural-Equation-Modelling. It was found that the antecedents for both technostress and exhaustion were able to account for more than half of their respective variances. Furthermore, technostress and exhaustion were significant facilitators of the students' reduced intention to use mobile learning via social media. In addition to the practical insights for stakeholders in the education industry, this study also posited several theoretical implications for researchers.
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TL;DR: Both positive and negative affective constructs significantly influence continuance intention and can also serve as mediators to the cognitive variables and Interestingly, price savings and referent network size were revealed to be sources of technostress.
Abstract: PurposeThis study examines the antecedents of continuance intention to use mobile payment in the midst of a pandemic. In general, the cognitive-affective-conative (CAC) framework was used as the theoretical base. More specifically, the dynamic interrelationships between the cognitive and affective constructs were derived from a penta-dimensional perspective.Design/methodology/approachAn online survey yielded 307 responses from youths who were utilizing mobile payment through an online survey which were then analyzed using structural equation modeling (SEM) and artificial neural network (ANN).FindingsBoth positive and negative affective constructs significantly influence continuance intention and can also serve as mediators to the cognitive variables. Interestingly, price savings and referent network size were revealed to be sources of technostress. In addition, despite not having a significant direct influence, price savings should not be overlooked given its indirect significance on continuance intention.Originality/valueBased on the CAC framework, the constructs were conceptualized according to the respective dimensions to develop this study's research model. It was then used to examine their influences on the continuance intention to use mobile payment in the midst of a pandemic. Moreover, a few novel hypotheses were proposed, and the findings serve to increase the understanding of this subject matter.
25 citations
TL;DR: In this article , the authors investigated and predicted major factors in students' behavioral intentions toward academic use of Facebook/Meta as a virtual classroom, taking into account its adoption level, purpose, and education usage.
Abstract: The paper’s main aim is to investigate and predict major factors in students’ behavioral intentions toward academic use of Facebook/Meta as a virtual classroom, taking into account its adoption level, purpose, and education usage. In contrast to earlier social network research, this one utilized a novel technique that comprised a two-phase analysis and an upcoming the Artificial Neural Network (ANN) analysis approach known as deep learning was engaged to sort out relatively significant predictors acquired from Structural Equation Modeling (SEM). This study has confirmed that perceived task-technology fit is the most affirmative and meaningful effect on Facebook/Meta usage in higher education. Moreover, facilitating conditions, collaboration, subjective norms, and perceived ease of use has strong influence on Facebook usage in higher education. The study’s findings can be utilized to improve the usage of social media tools for teaching and learning, such as Facebook/Meta. There is a discussion of both theoretical and practical implications.
10 citations
TL;DR: This study investigates the change of behaviour and acceptance of using mobile learning specifically for engineering undergraduates due to this shift during the pandemic, and indicates an inclination for utilizing laptops than smartphones, while Telegram prevails as a popular tool for communicating and sharing information within the learning community.
Abstract: Mobile learning has become an essential telematic tool to facilitate and compliment online teaching and learning during the pandemic. This study investigates the change of behaviour and acceptance of using mobile learning specifically for engineering undergraduates due to this shift. The data collected pre-COVID-19 (n = 326) and post-pandemic (n = 349) indicated an inclination for utilizing laptops than smartphones, while Telegram prevails as a popular tool for communicating and sharing information within the learning community. Next, while video conferencing tools and online learning management systems utilization increased, educational games and reading behaviour via mobile devices declined. Concurrently, behavioural intention post-pandemic were found to reduce marginally as importance were also given towards establishing learning community’s via social influence compared to perceived usefulness. The outcome of this study contributes to the limited body of literature on engineering education mobile learning acceptance, and recommendations are provided for further investigation to ensure continuous sustainable use.
9 citations
TL;DR: In this paper , a multi-dimensional framework was developed to determine the antecedents that affect users' mobile shopping actual use during a pandemic, based on the integration of the Protection Motivation Theory and Transactional Theory of Stress.
Abstract: PurposeThe COVID-19 pandemic has brought about significant changes to the lives of many people. One of which is the accelerated digitalization in the commerce sector. Hence, this study looks to determine the antecedents that affect users' mobile shopping actual use during a pandemic.Design/methodology/approachThe research model was founded on the integration of the Protection Motivation Theory and Transactional Theory of Stress. This is in addition to further extending the integrated research model with other constructs to develop a multi-dimensional framework that accounted for the health, personal, technological and social dimensions. The data was collected from users of mobile shopping through an online survey which was then analyzed via Partial Least Squares–Structural Equation Modeling.FindingsThis study provides empirical support to establish the major role of COVID-19 pandemic in affecting the actual usage of mobile shopping. Furthermore, the determinants of actual usage of mobile shopping were found to be multi-dimensional. In particular, the Importance-Performance Map Analysis revealed that emphasis should be place on perceived vulnerability.Originality/valueAs other studies focused on users' intentions, this study looked into the factors that influence the actual usage of mobile shopping. Furthermore, this study emphasizes on the contextualization of time and situation in addition to a multi-dimensional approach toward the subject matter. Overall, this study offers practical insights to stakeholders to better tailor their mobile shopping services in times of a pandemic and advances the literature on actual usage of mobile shopping.
8 citations
TL;DR: In this article , the authors investigated the antecedents that influence consumers' buying intention through mobile grocery shopping, which was achieved through the use of a multi-perspective research model that included the consumers' positive and negative valences as well as consumer characteristics.
Abstract: ABSTRACT Mobile grocery shopping has gained traction recently due to the COVID-19 pandemic. Hence, this study aims to investigate the antecedents that influence consumers’ buying intention through mobile grocery shopping. This was achieved through the use of a multi-perspective research model that includes the consumers’ positive and negative valences as well as consumer characteristics. Data was collected from 400 Malaysian consumers and analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. The finding of the study indicated the significant effects of positive valences (e.g., hedonic and utilitarian value) but not negative valences (e.g., privacy concern and security risk) on consumer buying intention through mobile grocery shopping. This study among the first to examine the intricacies of varying consumer characteristics in the context of mobile grocery shopping. The implications derived from the findings of this study are discussed.
6 citations
References
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Book•
01 Jan 2014
TL;DR: The Second Edition of this practical guide to partial least squares structural equation modeling is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Abstract: With applications using SmartPLS (www.smartpls.com)—the primary software used in partial least squares structural equation modeling (PLS-SEM)—this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
13,621 citations
TL;DR: In this paper, the heterotrait-monotrait ratio of correlations is used to assess discriminant validity in variance-based structural equation modeling. But it does not reliably detect the lack of validity in common research situations.
Abstract: Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these approaches do not reliably detect the lack of discriminant validity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod matrix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.
12,855 citations
TL;DR: The results suggest that users' continuance intention is determined by their satisfaction with IS use and perceived usefulness of continued IS use, and that post-acceptance perceived usefulness is influenced by users' confirmation level.
Abstract: This paper examines cognitive beliefs and affect influencing one's intention to continue using (continuance) information systems (IS). Expectation-confirmation theory is adapted from the consumer behavior literature and integrated with theoretical and empirical findings from prior IS usage research to theorize a model of IS continuance. Five research hypotheses derived from this model are empirically validated using a field survey of online banking users. The results suggest that users' continuance intention is determined by their satisfaction with IS use and perceived usefulness of continued IS use. User satisfaction, in turn, is influenced by their confirmation of expectation from prior IS use and perceived usefulness. Post-acceptance perceived usefulness is influenced by users' confirmation level. This study draws attention to the substantive differences between acceptance and continuance behaviors, theorizes and validates one of the earliest theoretical models of IS continuance, integrates confirmation and user satisfaction constructs within our current understanding of IS use, conceptualizes and creates an initial scale for measuring IS continuance, and offers an initial explanation for the acceptance-discontinuance anomaly.
6,024 citations
TL;DR: The results, based on structural equation modeling (SEM), show that technostress creators decrease job satisfaction, leading to decreased organizational and continuance commitment, while Technostress inhibitors increase job satisfaction and organizational and Continance commitment.
Abstract: The research reported in this paper studies the phenomenon of technostress, that is, stress experienced by end users of Information and Communication Technologies (ICTs), and examines its influence on their job satisfaction, commitment to the organization, and intention to stay. Drawing from the Transaction-Based Model of stress and prior research on the effects of ICTs on end users, we first conceptually build a nomological net for technostress to understand the influence of technostress on three variables relating to end users of ICTs: job satisfaction, and organizational and continuance commitment. Because there are no prior instruments to measure constructs related to technostress, we develop and empirically validate two second order constructs: technostress creators (i.e., factors that create stress from the use of ICTs) and technostress inhibitors (i.e., organizational mechanisms that reduce stress from the use of ICTs). We test our conceptual model using data from the responses of 608 end users of ...
1,065 citations
TL;DR: Clear guidelines for using PLSpredict are offered, which researchers and practitioners should routinely apply as part of their PLS-SEM analyses and the key choices researchers need to make using the procedure are explained.
Abstract: Partial least squares (PLS) has been introduced as a “causal-predictive” approach to structural equation modeling (SEM), designed to overcome the apparent dichotomy between explanation and prediction. However, while researchers using PLS-SEM routinely stress the predictive nature of their analyses, model evaluation assessment relies exclusively on metrics designed to assess the path model’s explanatory power. Recent research has proposed PLSpredict, a holdout sample-based procedure that generates case-level predictions on an item or a construct level. This paper offers guidelines for applying PLSpredict and explains the key choices researchers need to make using the procedure.,The authors discuss the need for prediction-oriented model evaluations in PLS-SEM and conceptually explain and further advance the PLSpredict method. In addition, they illustrate the PLSpredict procedure’s use with a tourism marketing model and provide recommendations on how the results should be interpreted. While the focus of the paper is on the PLSpredict procedure, the overarching aim is to encourage the routine prediction-oriented assessment in PLS-SEM analyses.,The paper advances PLSpredict and offers guidance on how to use this prediction-oriented model evaluation approach. Researchers should routinely consider the assessment of the predictive power of their PLS path models. PLSpredict is a useful and straightforward approach to evaluate the out-of-sample predictive capabilities of PLS path models that researchers can apply in their studies.,Future research should seek to extend PLSpredict’s capabilities, for example, by developing more benchmarks for comparing PLS-SEM results and empirically contrasting the earliest antecedent and the direct antecedent approaches to predictive power assessment.,This paper offers clear guidelines for using PLSpredict, which researchers and practitioners should routinely apply as part of their PLS-SEM analyses.,This research substantiates the use of PLSpredict. It provides marketing researchers and practitioners with the knowledge they need to properly assess, report and interpret PLS-SEM results. Thereby, this research contributes to safeguarding the rigor of marketing studies using PLS-SEM.
967 citations