The post-adoption behavior of internet banking users through the eyes of self-determination theory and expectation confirmation model

Rahi, Samar; Mansour, Majeed Mustafa Othman; Alharafsheh, Malek; Alghizzawi, Mahmoud

doi:10.1108/jeim-04-2020-0156

Cited by 64 publications

(57 citation statements)

References 63 publications

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“…The findings supported the significant positive effect of expectation confirmation on the PU of mobile payment contactless technologies. This is consistent with the findings of previous studies (Park, 2020; Puriwat and Tripopsakul, 2021; Rahi et al , 2021). In addition, expectation confirmation also has a significant positive impact on the satisfaction of mobile payment contactless technologies, which confirms the results observed in previous studies (Singh, 2020; Tam et al.…”

Section: Discussionsupporting

confidence: 94%

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Al-Sharafi

Al-Qaysi

Iahad

et al. 2021

IJBM

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PurposeWhile there is an abundant amount of literature studies on mobile payment adoption, there is a scarce of knowledge concerning the sustainable use of mobile payment contactless technologies. As those technologies are mainly concerned with security and users' trust, the question of how security factors and trust can influence the sustainable use of those technologies within and beyond the COVID-19 pandemic is still unanswered. This research thus develops a theoretical model based on integrating the protection motivation theory (PMT) and the expectation-confirmation model (ECM), extended with perceived trust (PT) to explore the sustainable use of mobile payment contactless technologies.Design/methodology/approachThe developed model is evaluated based on data collected through a web-based survey from 523 users who used contactless payment technologies. Unlike the existing literature, the collected data were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) technique.FindingsThe data analysis results reinforced all the proposed relationships in the developed model. The sensitivity analysis results showed that PT has the largest impact on the sustainable use of mobile payment contactless technologies with 97.2% normalized importance, followed by self-efficacy (SE) (77%), satisfaction (72.1%), perceived vulnerability (PV) (48.9%), perceived usefulness (PU) (48.2%), perceived severity (PS) (40.7%), response efficacy (RE) (28.7%) and response costs (RCs) (24.1%).Originality/valueThe originality of this research lies behind the development of an integrated model based on PMT and ECM to understand the sustainable use of mobile payment contactless technologies. The study provides several managerial implications for decision-makers, policy-makers and service providers to ensure the sustainability of those contactless technologies within and beyond the COVID-19 pandemic.

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Section: Discussionsupporting

confidence: 94%

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Al-Sharafi

Al-Qaysi

Iahad

et al. 2021

IJBM

View full text Add to dashboard Cite

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“…Results of the prior power analysis indicate that sample size of 290 respondents is adequate for inferential analysis. Therefore, researcher objective is to collect maximum responses to mitigate sampling error (Rahi et al , 2021). Although there is no telemedicine application that is launched by government so far to control COVID-19, nonetheless, it is important that respondents should have basic knowledge about telemedicine applications to respond survey questionnaire meaningfully.…”

Section: Methodsmentioning

confidence: 99%

Assessing individual behavior towards adoption of telemedicine application during COVID-19 pandemic: evidence from emerging market

Rahi

2021

LHT

Self Cite

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PurposeThis study attempts to gain insight into what factors influence individual behavior towards the adoption of telemedicine application during coronavirus disease 2019 (COVID-19) pandemic. The research model incorporates two well-known theories namely the extended unified theory of acceptance and use of technology (UTAUT2) and DeLone and McLean information success model to examine individual behavior towards the adoption of telemedicine application.Design/methodology/approachThe research design of this study is based on quantitative research approach. During research survey, 350 valid responses were received from Pakistani citizens and examined to understand citizen's behavior towards the adoption of telemedicine applications. The research model was empirically tested with the latest statistical approach namely variance-based structural equation modeling (VB-SEM).FindingsThe results of the structural equation modeling have revealed that altogether performance expectancy, social influence, effort expectancy, facilitating condition, habit, hedonic motivation, price values, information quality, system quality and service quality explained 77.9% variance in determining user behavior towards adoption of telemedicine application. The predictive relevance of the research model was found substantial in measuring user behavior to adopt telemedicine applications. The research framework is further extended with moderating role of perceived severity between the relationship of user intention and actual usage behavior. Results confirmed that the positive relationship between intention to adopt telemedicine health application and usage behavior will be stronger when perceived severity is higher.Practical implicationsTheoretically, this study integrates extended UTAUT2 and DeLone and McLean information success model and contributes to e-health literature. Practically, this research suggests that by improving user performance expectancy and effort expectancy, managers and healthcare professionals can boost user confidence towards the adoption of telemedicine applications.Originality/valueThis study is unique as it integrates the extended UTAUT2 with DeLone and McLean information success model and perceived severity to investigate user behavior towards adoption of telemedicine application during COVID-19 pandemic. Additionally, the integration of theories contributes to information system literature in the context of the adoption of telemedicine applications.

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“…The structural model reveals the path coefficient, t-values and significance level of the constructs. To eliminate data normality issues, the researcher has bootstrapped data with a resample of 1,000 as suggested by Rahi et al (2021). Table 3 exhibits hypotheses results.…”

Section: Structural Modelmentioning

confidence: 99%

Does employee readiness to change impact organization change implementation? Empirical evidence from emerging economy

Rahi

Alghizzawi

Ahmad

et al. 2021

IJOES

Self Cite

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Purpose This study aims to gain insight into factors that impact employee readiness to change and organizational change management. Therefore, an integrative research model is developed with the combination of perceived competence, perceived relatedness, perceived autonomy, codification strategy and personalization strategy to investigate employee readiness to change. The research model tests the mediating role of employee readiness to change between factors underpinned self-determination theory, knowledge management strategy and organizational change management. In addition to the moderating role of self-efficacy is examined between the relationship of employee readiness to change and organizational change implementation. Design/methodology/approach This research is conducted under a positive paradigm, and therefore, a quantitative research approach is incorporated to design a research strategy. The research model is empirically tested with a sample size of 361 employees working in commercial banks of Pakistan. For data analysis, the structural equation modelling approach is applied. Findings Empirical findings indicate that altogether perceived competence, perceived autonomy, perceived relatedness, codification and personalization strategies had explained 76.8% variance in employee readiness to change. The effect size analysis shows that codification strategy has the largest impact in determining employee readiness to change. Therefore, the relatedness of employee tasks stands at the second stage in determining employee readiness to change. The predictive relevance of the research model is computed through blindfolding procedure and revealed substantial predictive relevance in measuring employee readiness to change. The findings of the research confirmed that the relationship between employee readiness to change and organizational change implementation will be stronger when self-efficacy is higher. Practical implications The current research has several contributions to theory and practice. Theoretically, this research extends the self-determination theory with knowledge management strategy and enriches literature in employee readiness to change and organizational change management context. Practically, this research suggests that policymakers should focus on factors underpinned by self-determination theory and knowledge management model to develop a positive attitude among employees towards readiness to change. Similarly, self-efficacy is another important factor that moderates the relationship between readiness to change and change implementation and should be considered for managerial implication. Originality/value This research is significant as it integrates two unique models, namely, the self-determination framework and the knowledge management model to investigate employee readiness to change. In addition to that, the research model is extended with the moderating effect of self-efficacy between the relationship of employee readiness to change and organizational change implementation.

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The post-adoption behavior of internet banking users through the eyes of self-determination theory and expectation confirmation model

Cited by 64 publications

References 63 publications

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Evaluating the sustainable use of mobile payment contactless technologies within and beyond the COVID-19 pandemic using a hybrid SEM-ANN approach

Assessing individual behavior towards adoption of telemedicine application during COVID-19 pandemic: evidence from emerging market

Does employee readiness to change impact organization change implementation? Empirical evidence from emerging economy

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