Examining the roles of students' beliefs and security concerns for using smartwatches in higher education

An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce

Artificial Intelligence (AI) has become essential to Electronic-Commerce technology over the past decades. Its fast growth has changed the way consumers do online shopping. Using the Technology Acceptance Model (TAM) as a theoretical framework, this research examines how AI can be made more effective and profitable in e-commerce and how entrepreneurs can make AI technology to assist in achieving their business goals. In this regard, an online survey was conducted from the online purchasers of e-commerce firms. The Partial Least Square (PLS) Smart was used to examine the data. The broadly used TAM was identified as an appropriate hypothetical model for studying the acceptance of AI technology in e-commerce. The findings of this study show that Subjective Norms positively impact Perceived Usefulness (PU) and Pursued Ease of Use (PEU), trust has a positive effect on PEU, and PEU positively impacts PU and attitudes toward use. Similarly, PU also has a positive effect on attitudes toward use and intention to use. Furthermore, the findings do not support the impact of Trust on PU and attitudes towards behavioural intention to use. Lastly, behavioural intention to use positively impacted the actual use of AI technology. This study adds theoretical and practical knowledge for adopting the TAM model in the E-commerce sector. It helps entrepreneurs to implement the TAM model in their business to use AI in a better and more appropriate way.

Exploring the Frontiers of Cybersecurity Behavior: A Systematic Review of Studies and Theories

Cybersecurity procedures and policies are prevalent countermeasures for protecting organizations from cybercrimes and security incidents. Without considering human behaviors, implementing these countermeasures will remain useless. Cybersecurity behavior has gained much attention in recent years. However, a systematic review that provides extensive insights into cybersecurity behavior through different technologies and services and covers various directions in large-scale research remains lacking. Therefore, this study retrieved and analyzed 2210 articles published on cybersecurity behavior. The retrieved articles were then thoroughly examined to meet the inclusion and exclusion criteria, in which 39 studies published between 2012 and 2021 were ultimately picked for further in-depth analysis. The main findings showed that the protection motivation theory (PMT) dominated the list of theories and models examining cybersecurity behavior. Cybersecurity behavior and intention behavior counted for the highest purpose for most studies, with fewer studies focusing on cybersecurity awareness and compliance behavior. Most examined studies were conducted in individualistic contexts with limited exposure to collectivistic societies. A total of 56% of the analyzed studies focused on the organizational level, indicating that the individual level is still in its infancy stage. To address the research gaps in cybersecurity behavior at the individual level, this review proposes a number of research agendas that can be considered in future research. This review is believed to improve our understanding by revealing the full potential of cybersecurity behavior and opening the door for further research opportunities.

Reviewing the critical challenges that influence the adoption of the e-learning system in higher educational institutions in the era of the COVID-19 pandemic

Purpose

This paper aims to review the critical challenges and factors influencing the successful adoption of electronic learning (e-learning) systems in higher educational institutions before and during the current propagation of the coronavirus disease 2019 (COVID-19) pandemic.

Design/methodology/approach

This study undertook a literature review concerning the in-depth revision of previous studies published in 2020 and 2021. A total of 100 out of 170 selected research papers were adopted to identify and recognise the factors restricting the application of e-learning systems.

Findings

The findings determine and illuminate the most challenging factors that impact the successful application of online learning, particularly during the wide propagation of the COVID-19 pandemic. The review of the literature provides evidence that technological, organisational and behavioural issues constitute significant drivers that frontier the facilitation of the e-learning process in higher educational institutions.

Practical implications

The current paper suggests a guide for managers and scholars in educational institutions and acts as a roadmap for practitioners and academics in the educational field and policymakers as this research spotlights the significant factors challenging the e-learning process before and during the pandemic crisis.

Originality/value

The provided in-depth literature review in this research will support the researchers and system designers with a comprehensive review and recent studies conducted before and during the COVID-19 pandemic considering the factors limiting the e-learning process. This paper formulates a valuable contribution to the body of knowledge that will assist the stakeholders in the higher educational institutions' context.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2022-0085.

Employing the TAM in predicting the use of online learning during and beyond the COVID-19 pandemic

Online learning systems have become an applied solution for delivering educational content, especially in developing countries, since the start of the COVID-19 pandemic. The present study is designed to identify the factors influencing the behavioral intention of agricultural students at universities in Iran to use online learning systems in the future. This research uses an extended model in which the constructs of Internet self-efficacy, Internet anxiety, and output quality are integrated into the technology acceptance model (TAM). Data analysis was performed using the SmartPLS technique. The analyses showed the proposed model to be strong in terms of predicting the attitude to online learning and the intention to use it. The extended TAM model fit the data well and predicted 74% of the intention variance. Our findings show attitude and perceived usefulness to have directly affected intention. Output quality and Internet self-efficacy indirectly affected attitude and intention. Research findings can help with the design of educational policies and programs to facilitate education and improve student academic performance.

Determining factors affecting the perceived usability of air pollution detection mobile application "AirVisual" in Thailand: A structural equation model forest classifier approach

Air pollution has been evident worldwide. It presented numerous pieces of evidence that affect health-related adverse effects causing diseases and even death and the development of technology has helped monitor the exposure of people to air pollution. This research analyzed factors affecting the perceived usability of air pollution detection on the 'AirVisual' mobile application based on the integrated model of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2). A total of 416 participants voluntarily answered a self-administered survey consisting of adapted constructs covering factors such as Performance expectancy (PE), Effort expectancy (EE), Social influence (SI), Facilitating conditions (FC), Habit (HB), Perceived risk (PR), Perceived trust (PT), Intention to use (IU), and Perceived usability (PU). Structural Equation Modeling and Random Forest Classifier were utilized to determine factors affecting perceived usability of the 'AirVisual' mobile application. The results showed that PE, EE, SI, and FC were key factors leading to very high PU among users. Moreover, IU was seen to be the most significant factor affecting PU, followed by PT, PR, and HB. This study is one of the first studies that considered the evaluation of usability among health-related mobile applications covering air pollution. The results and the framework utilized in this model may be applied to evaluate other factors and applications related to health among people. Lastly, this study can also be extended to evaluate other mobile applications worldwide.

The Effect of Value Innovation in the Superior Performance and Sustainable Growth of Telecommunications Sector: Mediation Effect of Customer Satisfaction and Loyalty

The telecommunications industry has recognized innovation as the key to growth and survival. Globalization, liberalization, and privatization, the terms most commonly associated with this sector, have resulted in fierce competition, making it more difficult for telecommunications firms to increase their market share and, as a result, their customer base, sales volume, and, ultimately, profits. The new success strategy is differentiation through innovation, with the aim of breaking out of the competition and creating an uncontested market. This can be accomplished by providing high-value, innovative services that result in customer satisfaction and promote customer loyalty. The primary goal of this study was to create and validate a conceptual model of value innovation and its impact on firm performance and long-term growth by examining the mediation effect of customer satisfaction and loyalty. The empirical analysis results were based on 304 respondents who completed a paper-based survey provided to employees of Yemeni mobile service providers using a convenience non-probability sampling technique. SmartPLS 3 was used to test the hypothesized relationships using partial least squares structural equation modeling (PLS-PM). As a result, the findings empirically validated the theoretical research model, confirming the importance of the value innovation approach to achieving company performance and long-term growth by promoting customer satisfaction and loyalty. Finally, we have provided a discussion of the study’s theoretical contributions, managerial implications, and future research directions.

The Impact of Dynamic Accounting Information System on Organizational Resilience: The Mediating Role of Business Processes Capabilities

For decades, one of the main concerns of both practitioners and academics has been the business value of dynamic accounting information systems (DAIS). A number of studies have demonstrated the positive effects of information systems capability on overall organizational performance, but our understanding of the business processes capabilities through which such gains are achieved remains limited due to a lack of focus on the turbulent business environment. As a result, the research on information systems continues to debate such a connection. The role of business process capabilities in modulating the link between dynamic AIS capability and organizational resilience was investigated in this study. Our results show that, while firm-wide dynamic AIS capability has characteristics of flexible AIS, complement BI system, and AIS-related human resource competency, the impact on organizational resilience is positively affected by mediation of business process capabilities based on 144 matched questionnaires selected from large companies from various sectors listed on the Bursa Malaysia. Our results also suggest that dynamic AIS capability has an impact on organizational resilience. According to the Resource-Based Theory (RBT) and dynamic capabilities view (DCV) viewpoints, there is a link between dynamic AIS and business process capacity to improve organizational resilience. The findings strongly support the claim that an organization’s dynamic AIS capabilities—both flexible AIS, complementary business intelligence (BI) system, and AIS-related human resource competency—can help an organization improve its resilience. This research’s practical and theoretical ramifications as well as its limitations are examined.

Educational Technology Adoption: A systematic review

During the past decades a respectable number and variety of theoretical perspectives and practical approaches have been advanced for studying determinants for prediction and explanation of user's behavior towards acceptance and adoption of educational technology. Aiming to identify the most prominent factors affecting and reliably predicting successful educational technology adoption, this systematic review offers succinct account of technology adoption and acceptance theories and models related to and widely applied in educational research. Recognised journals of the Web of Science (WoS) database were searched with no time frame limit, and a total of 47 studies published between 2003 and 2021 were critically analysed. The key research findings revealed that in educational context a vast majority of selected studies explore the validity of Technology Acceptance Model (TAM) and its many different extensions (N=37), along with TAM's integrations with other contributing theories and models (N=5). It was exposed that among numerous predictors, thematically grouped into user aspects, task & technology aspects, and social aspects, self-efficacy, subjective norm, (perceived) enjoyment, facilitating conditions, (computer) anxiety, system accessibility, and (technological) complexity were the most frequent predictive factors (i.e. antecedents) affecting educational technology adoption. Considering types of technologies, e-learning was found to be the most common validated mode of delivery, followed by m-learning, Learning Management Systems (LMSs), and social media services. The results also revealed that the majority of analysed studies were conducted in higher education environments. New directions of research along with potential challenges in educational technology acceptance, adoption, and actual use are discussed as well.