How pre-adoption expectancies shape post-adoption continuance intentions: An extended expectation-confirmation model
TL;DR: A novel extended expectation–confirmation model is proposed which explores the impact of pre-adoption expectancies and confirmation on post-ad adoption satisfaction and continuance intentions and guides the M-wallet application developers to enhance user satisfaction andContinance intentions by meeting their pre- adoption expectations through consumption-driven confirmation.
About: This article is published in International Journal of Information Management.The article was published on 2020-06-01. It has received 91 citations till now. The article focuses on the topics: Continuance.
Citations
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TL;DR: Analysis of data collected from 370 actual chatbot users reveals that information quality and service quality positively influence consumers’ satisfaction, and that perceived enjoyment, perceived usefulness, and perceived ease of use are significant predictors of continuance intention toward chatbot-based customer service.
210 citations
Proceedings Article•
01 Jan 2006TL;DR: In this paper, the authors report on a study that attempts to expand the set of post-adoption beliefs in the expectation-confirmation model (ECM) in order to extend the application of the ECM beyond an instrumental focus.
Abstract: The expectation-confirmation model (ECM) of IT continuance is a model for investigating continued information technology (IT) usage behavior. This paper reports on a study that attempts to expand the set of post-adoption beliefs in the ECM, in order to extend the application of the ECM beyond an instrumental focus. The expanded ECM, incorporating the post-adoption beliefs of perceived usefulness, perceived enjoyment and perceived ease of use, was empirically validated with data collected from an on-line survey of 811 existing users of mobile Internet services. The data analysis showed that the expanded ECM has good explanatory power (R 2 = 57.6% of continued IT usage intention and R 2 = 67.8% of satisfaction), with all paths supported. Hence, the expanded ECM can provide supplementary information that is relevant for understanding continued IT usage. The significant effects of post-adoption perceived ease of use and perceived enjoyment signify that the nature of the IT can be an important boundary condition in understanding the continued IT usage behavior. At a practical level, the expanded ECM presents IT product/service providers with deeper insights into how to address IT users' satisfaction and continued patronage.
176 citations
TL;DR: The analysis suggests that studies have started citing the relationships suggested by meta-UTAUT and researchers have reviewed it alongside other alternative models while analysing acceptance and use of technology.
Abstract: Over the past more than four decades, several theoretical models have been developed to understand the acceptance and use of information systems. Realising the dilemma in selecting the appropriate theoretical model to assess the acceptance and use of technology and considering the pattern of using the Unified Theory of Acceptance and Use of Technology (UTAUT), a modified version (meta-UTAUT) has been developed based on the synthesis of results from 162 existing studies. The aim of this article is to review the emerging literature on meta-UTAUT and offer some future research recommendations. The analysis suggests that studies have started citing the relationships suggested by meta-UTAUT and researchers have reviewed it alongside other alternative models while analysing acceptance and use of technology.
111 citations
TL;DR: In this paper, the authors examined both enablers and inhibitors of mobile wallets (m-wallets) as antecedents of valence of word of mouth (positive and negative; PWOM and NWOM), and found that only PWOM drives the continuance intentions of m-wallet users.
83 citations
TL;DR: In this paper, the authors investigated the continuance intention regarding online learning during the COVID-19 pandemic and found that technical support of promoting online learning helped student to complete course learning tasks during the pandemic.
Abstract: The prevalence of COVID-19 has changed traditional teaching modes. For many teachers, online learning effectively compensated for the absence of traditional face-to-face instruction. Online learning can support students and schools and can create unique opportunities under emergency management. Educational institutions in various countries have launched large-scale online course modes in response to the pandemic. Additionally, online learning during a pandemic differs from traditional online learning modes. Through surveying students in higher education institutions, educational reform under emergency management can be explored. Therefore, university students were surveyed to investigate their continuance intention regarding online learning during the pandemic. Expectation confirmation theory was extended using the task-technology fit model to ascertain whether the technical support of promoting online learning helped student’s complete course learning tasks during the pandemic and spawned a continuance intention to use online learning in the future. Data were collected through online questionnaires. A total of 854 valid responses were collected, and partial least squares structural equation modeling was employed to verify the research hypotheses. The results revealed that the overall research framework largely explained continuance intention. Concrete suggestions are proposed for higher education institutions to promote online learning modes and methods after the COVID-19 pandemic.
68 citations
References
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TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...
56,555 citations
Book•
27 May 1998TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
Abstract: Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation and pitfalls of structural equation modelling (SEM) in the social sciences. The book covers introductory techniques including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods such as the evaluation of non-linear effects, the analysis of means in convariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the book offers clear instructions on the preparation and screening of data, common mistakes to avoid and widely used software programs (Amos, EQS and LISREL). The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
42,102 citations
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each.
Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations.
Table of Contents
1. Introduction.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.
37,124 citations
TL;DR: In this paper, the authors provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development, and present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests.
Abstract: In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of measurement models using confirmatory factor analysis are reviewed. As background to the two-step approach, the distinction between exploratory and confirmatory analysis, the distinction between complementary approaches for theory testing versus predictive application, and some developments in estimation methods also are discussed.
34,720 citations
TL;DR: The Unified Theory of Acceptance and Use of Technology (UTAUT) as mentioned in this paper is a unified model that integrates elements across the eight models, and empirically validate the unified model.
Abstract: Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R2 of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.
27,798 citations