Information Systems Continuance Research Articles

Exploring the Factors Influencing Continuance Intention to Use AI Drawing Tools: Insights from Designers

With the continuous evolution of artificial intelligence technology, AI drawing tools have emerged as highly esteemed instruments in the modern design industry. These tools, owing to their exceptional performance and innovative features, offer creators an unprecedented artistic experience. However, the factors influencing designers’ continuance intention to use AI drawing tools remain ambiguous. This study is grounded in the expectation–confirmation model–information systems continuance (ECM-ISC) model, which is further refined and hypothesized in light of the characteristics of AI drawing tools. Using structural equation modeling, we analyzed 398 valid questionnaire responses. The results elucidated the relationships of key constructs, such as perceived usefulness, perceived ease of use, satisfaction, expectation confirmation, perceived playfulness, perceived switching cost, subjective norms, and perceived risk, on designers’ continuance intention. Notably, perceived ease of use, traditionally considered vital, did not result in a significant influence on continuance intention or perceived usefulness in this research. This insight offers new perspectives for AI drawing tool developers and designers, suggesting that while pursuing user friendliness, broader considerations affecting user decisions should be taken into account. This study not only enriches the theoretical framework but also provides valuable guidance for the practical field.

An analysis of users’ continuous use intention of academic library social media using the WeChat public platform as an example

PurposeThis study aims to discover the factors which influence user satisfaction levels and their continuous use intention (CUI) of academic library social media, and then considers how to promote and improve further work on library social media to reduce user churn and increase user satisfaction.Design/methodology/approachAn updated DeLone and McLean information systems success (D&M ISS) model and the expectation confirmation model for information systems continuance (ECM-ISC) with new variables of emotions are used to examine the factors which influence user satisfaction levels and CUI of academic library social media through 445 questionnaires. Partial least squares structural equation modelling was used to analyse the data and presented in tables.FindingsThe results show that information quality, system quality and emotions affect user satisfaction and CUI, and reveal that emotions can affect that most obviously.Research limitations/implicationsThe WeChat public platform is mainly used in China, so the study only focuses on Chinese academic libraries. There are still limitations on the settings of observed variables which cannot cover all the causes of users’ positive and negative emotions. In addition, although the respondents of this questionnaire can represent academic library users, 445 samples are still fairly low in contrast to the great number of academic library WeChat public platform users.Originality/valueThis study integrates ECM-ISC and D&M ISS models, adds positive and negative emotions as new variables, to broaden the application scope of these models, and demonstrates the applicability of these two models in the fields of researching academic library social media, expanding and deepening related theories above. This also provides practical reference for academic libraries on how to improve user satisfaction and CUI of academic library social media and academic library WeChat public platforms, promoting the development of academic library social media.

Understanding E-Government Services Usage Continuance: The Role of Service Quality and Habit

ABSTRACT In this study, we examine the citizens’ continuance intention to use e-government services after adoption. We develop a post-acceptance Information Systems continuance extended model by integrating service quality through the e-GovQual model, and habit. Our results provide corroborative evidence that the inclusion of service quality gives better results than the original model and habit has a strong influence on citizens’ continuance intention regarding e-government services usage both directly and indirectly through moderating and mediating effects.

Videoconferencing continuance and business trip reduction in the post-pandemic age

Videoconferencing (VC) software was widely adopted by organizations during the COVID-19 pandemic to maintain business communication during the suspension of business travel. In the post-pandemic age, will organizations continue to use VC software, and how will VC continuance influence the number of business trips? We conceptualize business travel as a communication problem and conduct an empirical study to investigate the use of VC during the COVID-19 pandemic and its impact on future business travel. We identify the technology–organization–environment framework as a theoretical tool to guide our research design. Using a sample of business managers in Hong Kong and the United States and the seemingly unrelated regression methodology, we identify the relative advantage, top management, and competition intensity factors that support VC continuance and business trip reduction in the post-pandemic age. This study enhances research on information systems continuance and provides practical implications for business trip planning.

An empirical study of continuous knowledge contribution of doctors in online medical communities

PurposeContinuous knowledge contribution behaviors (CKCB) are critical for the healthy development of online medical communities (OMCs). However, it is unclear that if and how contributors' prior actions and the responses they received from the community influence the nature of their future contributions. Drawing upon the Information Systems Continuance theory and Service Feedback theory, the purpose of the study is to examine the impact of knowledge contribution performance (KCP) on doctors' CKCB. Evaluation of social motivation, financial incentive and the moderating influence of expertise level (EL) provided further insight into the pathways that motivate various forms of CKCB.Design/methodology/approachIn order to better understand the CKCB of physicians in OMCs, the authors divided it into two categories: A_CKCB (active CKCB) and P_CKCB (passive CKCB). Information Systems Continuance theory and Service Feedback theory are adapted and integrated with empirical findings from previous research on OMCs to develop a model of CKCB. This study used ordinary least squares (OLS) regression to test hypotheses in the preexisting research model based on data collected from a Chinese OMC platform.FindingsThe results show that KCP helps develop several facets of CKCB. According to the findings, doctors' CKCB improved dramatically after receiving feedback from A_CKCB and P_CKCB, but feedback from peers did not promote CKCB. This study found that financial rewards only have a significant positive effect on P_CKCB, and that the level of expertise has a negative effect on the effect. The findings also demonstrated that doctors' level of expertise moderates the relationship between fA_CKCB (a comprehensive evaluation of doctors' A_CKCB) and A_CKCB.Research limitations/implicationsFuture studies should look at the role of self-efficacy as a mediator and attitudes as a moderator in the link between KCP and various forms of CKCB. This will help authors figure out how important KCP is for physicians' CKCB. And future research should use more than one way to gather data to prove the above roles.Practical implicationsThis study makes a significant contribution to understanding the association between CKCB and KCP by highlighting the significance of distinguishing between the various forms of CKCB and their underlying causes.Originality/valueThis research has advanced both the theory and practice of OMCs' user management by illuminating the central role of KCP in this context.

Enabling and Inhibiting Factors of the Continuous Use of Mobile Short Video APP: Satisfaction and Fatigue as Mediating Variables Respectively.

The short video APP has entered the stage of competition for stock, making it crucial to keep users engaged in their APP to promote continuous usage. Previous studies on the continuous use intention of mobile short video APP were relatively limited, with most studies focusing only on promoting factors. Therefore, based on the dual-factor theory of "enabling-inhibiting", and drawing on the Information System Continuance Model (ECM-ISC) and Cognitive Load Theory, this study extracted two variables, satisfaction and fatigue, to construct an integrated model to explore their enabling and inhibiting effects on continuous use intention. This study selected TikTok APP users as the respondents, obtained 681 valid questionnaires and analyzed with structural equation modeling (SEM) using SPSS24.0 and Amos23.0 software. The study investigated the factors that influence users' continuous use intention of short video APP. It shows that in enabling mechanism, perceived usefulness and social influence will increase user satisfaction and thus promote their continuous use intention, and perceived playfulness has a direct effect on the continuous use intention. In inhibiting mechanism, information overload and communication overload are positively correlated with emotional fatigue, which further reduces the continuous use intention. Based on the dual-factor theory of "enabling-inhibiting", the study established an integration model to more comprehensively reveal the impact mechanism of short video APP users' continuous use intention. The study found that the fatigue caused by information and communication overload can inhibit users' continuous use intention of short video APP. Therefore, to improve users' continuous use intention, short video APP should not only increase users' satisfaction but also reduce the fatigue caused by overload.

Technological or social? Influencing factors and mechanisms of the psychological digital divide in rural Chinese elderly

The psychological digital divide (PDD) significantly impacts participation and may hinder the development of smart rural communities. This study aimed to address the issue by conducting a questionnaire survey of 394 elderly individuals from rural China, revealing the essential characteristics and core mechanisms of PDD based on the relative deprivation theory (RDT). The study also focused on a moderation test of cognitive age to validate its critical role in the formation of PDD among rural elderly individuals. The final results confirmed the stability of the PDD induction model and highlighted that the information systems (IS) continuance intention of the elderly can be affected by both technological and social environments, through relative digital deprivation. Specifically, social exclusion and technology anxiety were identified as key drivers of PDD, with technology anxiety having a stronger impact. Furthermore, the cognitive age of elderly individuals intensifies the negative influence of relative digital deprivation on IS continuance intention, while also strengthening the relationship between social exclusion and relative digital deprivation. These findings not only shed light on the nature of PDD but also provide a theoretical framework for understanding the transition from social to digital exclusion.

Continuous usage intention of mobile health services: model construction and validation

BackgroundMobile health (mHealth) services can not give full play to their value if only it is used in the short term, and their continuous usage can achieve better effects in health management. This study aims to explore the factors that affect continuous usage intentions of mHealth services and their mechanism of action.MethodsFirst, considering the uniqueness of health services and social environmental factors, this study constructed an extended Expectation Confirmation Model of Information System Continuance (ECM-ISC) to investigate factors that may influence the intention of continuous usage of mHealth services based on three dimensions, namely individual characteristics, technology and environment. Second, the survey method was used to validate the research model. The questionnaire items were derived from validated instruments and discussed by experts and data were collected both online and offline. The structural equation model was used for data analysis.ResultsThere were 334 avidity questionnaires through cross-sectional data and these participants had used mHealth services ever. The reliability and validity of the test model were good, in which Cronbach’s Alpha values of 9 variables exceeded 0.9, composite reliability 0.8, the average variance extracted value 0.5, and the factor loading 0.8. The modified model had a good fitting effect and strong explanatory power. It accounted for 89% of the variance in expectation confirmation, 74% of the variance in perceived usefulness, 92% of the variance in customer satisfaction, and 84% of the variance in continuous usage intention. Compared with the initial model hypotheses, perceived system quality was deleted according to the heterotrait-monotrait ratio, so paths related to it were deleted; perceived usefulness wasn’t positively associated with customer satisfaction, and its path was also deleted. Other paths were consistent with the initial hypothesis. The two new added paths were that subjective norm was positively associated with perceived service quality (β = 0.704, P < 0.001), and perceived information quality (β = 0.606, P < 0.001). Electronic health literacy (E-health literacy) was positively associated with perceived usefulness (β = 0.379, P < 0.001), perceived service quality (β = 0.200, P < 0.001), and perceived information quality (β = 0.320, P < 0.001). Continuous usage intention was influenced by perceived usefulness (β = 0.191, P < 0.001), customer satisfaction (β = 0.453, P < 0.001), and subjective norm (β = 0.372, P < 0.001).ConclusionsThe study constructed a new theoretical model including E-health literacy, subjective norm and technology qualities to clarify continuous usage intention of mHealth services, and empirically validated the model. Attention should be paid to E-health literacy, subjective norm, perceived information quality, and perceived service quality to improve continuous usage intention of users and self–management by mHealth Apps managers and governments. This research provides solid evidence for the validity of the expanded model of ECM-ISC in the mHealth field, which can be a theoretical and practical basis for mHealth operators’ product research and development.

The decision-making process regarding the continuance intention of using branded apps: an integrated approach to the PAM and the TPB

PurposeAs branded apps emerge as a marketing tool in the foodservice industry, the effort to manage them increases in the long term. This study aims to explore the determinants to continue the use of foodservice apps by adopting the post-acceptance model (PAM) of information systems continuance and the theory of planned behavior (TPB).Design/methodology/approachBased on a sample from a survey of 329 participants who use foodservice apps, a structural equation model analysis tested the relationships between the core constructs of both models.FindingsThe findings revealed the user confirmation of expectation leads to continued use of the app through satisfaction. Perceived usefulness, a key technology acceptance measure, however, has no direct effect on usage but on attitude. Among the salient behavioral beliefs of the TPB, only attitude and perceived behavioral control promoted continued use of the foodservice apps.Practical implicationsThe study provided a framework to establish a practical strategy for foodservice firms by specifying important aspects, which induce the use of branded apps. Given that it is vital to meet users’ expectations to build branded-app loyalty, continuous interaction with users is required along with customized marketing.Originality/valueOn the basis of the PAM and the TPB, the findings contributed to developing and testing a model that motivates users to continue the use of foodservice branded apps. The study is significant, in that it enriched the PAM by integrating cognitive aspects to explore the psychological mechanisms in the post-adoption phase of foodservice app users.

Factors Influencing the Online Learning Success of Adults in Open and Distance Education in Southwest China

This study aims to identify the factors that influence adult learners’ perceived satisfaction, continued use, and benefits of online learning to seek ways to promote adult learners’ success in online learning. The study integrated multiple theoretical frameworks, including the Information System Success (ISS) Model, Expectation Confirmation Model for Information Systems Continuance (ECM-ISC), Technology Acceptance Model (TAM), and Technological Pedagogical Content Knowledge (TPACK) to develop a theory of Online Learning (OL) success for adults. The proposed model emphasizes the utilization of technology to enhance pedagogical practices for the delivery of online content. A total of 675 adult learners were randomly selected from five learning centres at a provincial branch of the Open University of China in Southwest China. This quantitative research study utilized Partial Least Squares-Structural Equation Modeling (PLS-SEM) for data analysis. Analysis of the results indicated that TPACK’s impact was more clearly perceived by the adult learners in this study. Further study needs to expand the scope of this investigation and verify the effectiveness and reliability of the model. The model of adult online learning success in Southwest China is the first integrated model combining TPACK theory with the Information System Success (ISS) Model, Technology Acceptance Model (TAM), and Expectation Confirmation Model (ECM). Future studies should explore teacher and administrator perspectives to determine the success factors of adult online learning from a multi-faceted approach.

The effects of digital nativity on nonvolitional routine and innovative usage

PurposeThis study explores the differences between digital immigrants (DIs) and digital natives (DNs) in the continuance of routine and innovative information system use.Design/methodology/approachA quantitative survey was conducted with two different samples comprising 100 DIs and 152 DNs in mandatory information system use contexts. Data were analyzed with structural equation modeling to examine the hypothesized relationships in the research model.FindingsResults revealed differences among digital nativity groups. The effect of confirmation of expectations about system use on satisfaction is stronger for DNs whereas the effect on task–technology fit (TTF) is similar in both digital groups. Interestingly, significant differences between digital nativity groups occur in routine use. For DIs, TTF and habit are significant while for DNs, satisfaction significantly affects routine use. The results show no difference between digital native groups regarding innovative use.Originality/valueThis study extends the concept of digital nativity to routine and innovative system use, contributing to an enhanced understanding about the differences in information systems continuance (ISC) based on digital nativity. It also provides a fine-grained discussion of how to classify digital nativity and its impact in working contexts and extends the IS continuance model by considering two types of IS usage.

Supportive Leadership and Post-Adoption Use of MOOCs

Educational institutions face significant challenges in extracting interest from their investments in massive open online courses (MOOCs). This study examined the impact of supportive leadership style on university employees' continued use of MOOCs and assessed the mediating role of their innovative work behavior. It uses a multi-theory perspective as opposed to the majority of past studies that use singular theoretical perspectives and extends the information system continuance (ISC) model with the leadership concept. Researchers collected multi-source dyadic data for this cross-sectional study from 632 employees and 316 supervisors from 19 Chinese universities. Data were analyzed using structural equation modeling with partial least squares through SmartPLS 3.2.9. Results indicate supportive leadership influences employees' innovative behavior, which mediates between supportive leadership and employees' satisfaction, perceived usefulness, and intention to continue using MOOCs.

Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach

This study extends the post-acceptance model of information systems (IS) continuance, which is widely used to explain users’ satisfaction and IS continuance intentions. The extended model includes additional variables such as perceived ease of use (PEOU), attitude, trust, and enjoyment. The proposed model was tested using meta-analytic structural equation modeling (MASEM). The analysis included 1,056 observations on fifteen relationships from 214 independent studies with a combined sample of 84,343. The results confirm the significance of all the relationships proposed in the original model. Furthermore, the findings indicate that PEOU directly influences perceived usefulness, satisfaction, and attitude. Trust and enjoyment both have a positive impact on users’ satisfaction and IS continuance, wherein the effect of enjoyment was higher than trust. post-consumption satisfaction resulted in a favorable attitude toward technology, which further affected IS continuance. From a theoretical perspective, the current study acknowledges the shift in users’ attitude toward technology and emphasizes the hedonic value of IS usage as users report a higher degree of satisfaction toward responsive, easy to use, and enjoyable technologies. Marketers should focus on the enjoyment and gratifications derived from technology to increase potential IS usage.

Factors affecting the continuation to use and e-WOM intention of online library resources by university students: A study in Indonesia

Online library resources can act as a trusted source to find various references for conducting research or writing research papers. With the increasing number of published papers, the use of online library resources becomes increasingly important for academics, including for university students. This study aims to investigate the factors that lead to the continued use of online library resources among university students in developing countries, especially Indonesia. We investigate the impact of resource quality, confirmation, satisfaction, perceived usefulness, perceived ease of use, and perceived enjoyment of users on their intention to continue using online library resources and the effect on e-WOM intention. This study will enhance the Post-Acceptance Model of Information System (IS) Continuance by adding several other constructs and tested using data from 215 university students in Indonesia who have used online library resources. The method used to analyze the data is Partial Least Squares-Structural Equation Modeling (PLS-SEM). The results of the study indicate that satisfaction and perceived enjoyment have a significant effect on the intention to continue using online library resources. In addition, it was also found that the continuation intention to use online library resources also affects the user's intention to convey it to others (e-WOM intention). This study provides insight to online library resources service providers in making improvements and formulating strategies to increase users' intentions to continue using their online library resources.

Exploring the factors influencing users' learning and sharing behavior on social media platforms

PurposeThe research goal is to understand what factors affect users' knowledge and information learning and sharing on social media platforms. This study focuses on the impact of platform characteristics on users' behavior. Specifically, the purpose of this study is to investigate (1) what factors affect users' learning and dissemination of knowledge and information on social media platforms, (2) whether knowledge and information learning behavior will have a positive effect on sharing behavior and (3) try to establish an impact model of users' learning and sharing behavior about knowledge and information.Design/methodology/approachThis study proposes an impact mechanism model to test these hypotheses. To achieve this, the authors collected data from 430 users who have used the social media platforms to acquire and share knowledge and information to test the hypothesis. The tools SPSS 26.0 and AMOS 23.0 were used to analyze the reliability, validity, model fits and structural equation modeling.FindingsThe results show that the learning of knowledge and information can influence the sharing behavior on social media platforms. Users' platform-based trust and platform-based satisfaction affect their knowledge and information learning and sharing on the platform. Factors affecting users' trust in social platforms include privacy protection effectiveness and network effects. And, perceived usefulness and perceived ease of use are related to users' satisfaction with social media platforms.Originality/valueThis study constructs an impact model on the learning and sharing of knowledge and information. The model takes the information system continuance model as the theoretical framework and integrates other factors, including the network effect, the effectiveness of privacy protection and trust. Most of the hypotheses of this research were confirmed. The conclusions provide practical guidance for the dissemination of knowledge information and platform management.

Examining key factors of beginner's continuance intention in blended learning in higher education.

With the outbreak of the COVID-19 pandemic, blended learning became exceptionally widespread, especially in higher education. As a result, many college students became beginners in this learning method. To identify key factors that impact beginners’ continuance intention in blended learning, this study surveyed 1845 first-year college students at a university in central China in the falls of 2020 and 2021 who used blended learning for the first time. Structural equation modeling was employed to verify a model that integrates intrinsic motivation and academic self-efficacy in the Expectation-Confirmation Model of Information System Continuance. The results show that performance expectancy, intrinsic motivation, and satisfaction significantly impact beginners’ continuance intention in blended learning. Moreover, performance expectancy, intrinsic motivation, and confirmation significantly impact beginners’ continuance intention through mediating variable satisfaction. Academic self-efficacy does not directly impact college students’ continuance intention but indirectly impacts their continuance intention through intrinsic motivation. Finally, this study provides suggestions for educators to improve beginners’ blended learning experience thus promoting their continuance intention in blended learning.

Towards a model of social commerce: improving the effectiveness of e-commerce through leveraging social media tools based on consumers’ dual roles

ABSTRACT Social media has been integrated into traditional e-commerce, creating an innovative technology-based approach to changing business practice and service, yet few researchers have attempted to provide an understanding of how this approach is changing consumer decision-making and purchase behaviours. Combining the expectation-confirmation theory and the expectation-confirmation model and information systems continuance, we propose a model for social commerce, illustrating how social media is utilised in online shopping as a three-fold process (pre-purchase, purchase, and post-purchase stages) from a consumer perspective. The model consists of three phases: social commerce motivation, social commerce adoption, and e-commerce effectiveness. Using two rounds of surveys, we find that (1) autonomous motivation and controlled motivation have positive effects on social commerce information seeking and sharing, and (2) social commerce information seeking formulates consumers’ pre-purchase decisions, thus affecting their actual purchase outcomes, repurchase intentions, and social commerce information-sharing intentions in the post-purchase stage. In addition, our study indicates that consumers may play dual roles in social commerce: as information seekers in the pre-purchase stage and as information providers in the post-purchase stage. Our findings have important implications for literature and practice.

Research on the Structural Relationship of Online Persistent Purchase of Museum Cultural and Creative Products in the Context of Digitalization.

With the development and support of modern technologies such as digital media and online live stream, it has become an effective way to promote the online transaction of museum cultural and creative products. Based on the Technology Acceptance Model combined with the Post-Acceptance Model of Information System Continuance and the theories on customer satisfaction index, this research introduces perceived interest (PI) and media richness (MR) as variables and constructs a model of the influencing factors of online consumers’ persistent purchase (PP) of museum products. The research model and related hypotheses were verified through structural equation modeling (SEM). The research found that perceived value (PV) and satisfaction (SAT) are the key variables that have impact on the PP of consumers. Perceived quality, brand trust, MR, PI, and perceived usefulness have significant effects on PV and SAT. Involvement in purchasing decisions positively moderates the impact on SAT of PV. The conclusion can be referred to for operators and product developers.

Quality of smart-work support service, perceived value and intention to continue smart-work: empirical evidence from Korea

PurposeSmart-work has been attracting more attention since the COVID-19 outbreak hit the world in 2020. Smart-working practices do not always run smoothly despite the necessary infrastructure being in place. Taking the quality-value-loyalty chain and information system continuance model as the basis, this study aims to identify how “smart-work support service” leads to employees’ continuance intention toward smart-work. In this study, the smart-work support service refers to the infrastructure making smart-work possible and services needed to support smart-work.Design/methodology/approachUsing data collected from a survey of 406 employees working in Korea, this study verifies the components of smart-work support service quality and dimensions of perceived value through partial least squares analysis and then tests the proposed conceptual model using structural equation modeling.FindingsThe results verified that the quality of smart-work support service consists of eight attributes while dividing the perceived value of smart-work into three dimensions and further revealed that the service quality influences the intention to continue smart-working by way of perceived value and satisfaction.Originality/valueThis study sought to explore the relationship among service quality, perceived value and satisfaction by clearly conceptualizing and measuring them in the context of smart-work, thereby ultimately understanding the impact they have on the intention to continue smart-work.

Determinants of Satisfaction and Deep Structure Usage of Post-acceptance Learning Management Systems by Malaysian Higher Education Lecturers

This study investigates factors influencing satisfaction and deep structure usage of Learning Management Systems (LMS) using a revised expectation-confirmation model of information system continuance. It addresses the gaps in the existing literature that primarily focused on behavioral intention in the acceptance stage instead of deep structure usage in the post-acceptance stage. Deep structure usage refers to using LMS features to support an underlying teaching task. The study population consists of 54 lecturers in Malaysian private universities in the post-acceptance stage of LMS implementation. Data was gathered using a web-based survey questionnaire. Various variables were analyzed through statistical correlation and regression using a statistical package for social science software. This study concludes that confirmation of expectation and perceived usefulness positively impacted satisfaction; confirmation of expectation was the strongest predictor of satisfaction. Additionally, the combined effects of satisfaction, confirmation of expectation, and perceived usefulness positively correlated with deep structure usage of LMS. This study investigates whether lecturers would use the system to its full capacity if they found the LMS features useful to a specific teaching task and if the system provides satisfaction and fulfills the lecturers’ expectations. Future research recommends extending the model to investigate determinants of satisfaction and confirmation of expectations of specific LMS features in terms of technical, design, capability, and experiential aspects. This extension would enable a more detailed understanding of aspects that determine satisfaction and confirmation of expectation, directly influencing deep structure usage.