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This research aims to integrate the unified theory of acceptance and usage of technology (UTAUT) with task technology fit to explain users' behavioral intention of using library mobile applications in university libraries.

By integrating the unified theory of acceptance and usage of technology (UTAUT) and the moderator of task-technology fit, this research proposes a library mobile applications usage intention model. The study data come from a convenience sample of 363 undergraduate and graduate students. A structural equation modelling (SEM) technique was conducted to identify causal relationships.

Results showed that the UTAUT model fits the data well. The empirical data reveal that performance expectancy, effort expectancy, social influence, and facilitating conditions determine users' behavioral intention of using library mobile applications. As a determinant in the UTAUT model, the moderating effect of task-technology fit is also significant. Moreover, individuals with different levels of task-technology fit will strengthen or weaken the relationships of determinants in the intention to use library mobile applications in university libraries.

This study addresses self-reported behavioral intentions as part of the survey; as a result, the data may have introduced inaccuracies. The implications of the proposed library mobile applications success model are discussed.

University librarians should reinforce the efficiency of library mobile applications to influence users' willingness to use such applications.

This study combines both the constructs of the UTAUT model and task-technology fit to consider intentions to use library mobile applications in university libraries.

The purpose of this paper is to examine (a)symmetric features of task-technology-performance characteristics that are most relevant to fit, satisfaction and continuance intention of using apps in mobile banking transactions.

Exploratory factor analysis was used with maximum likelihood extraction and Varimax rotation on a separate sample of 183 mobile banking apps users prior to the main data collection. The theoretical model was tested applying a factor-based structural equation modelling approach to a sample of 250 experienced mobile banking apps users.

The study unveiled that the task and performance characteristics are more relevant compared to technology characteristics when doing transactions via apps. In addition, the findings uncovered that user satisfaction and continuous intention to use apps stem from the degree of fit in online transactions. The findings of moderation analysis highlighted that users in the lower income group are more concerned about the performance characteristics of banking apps, and there are no differences across age and gender groups. Surprisingly, technology characteristic has a nonlinear nature and this study shows potential boundary conditions of technology characteristics in degree of fit, user satisfaction and continuance intention to use apps.

Findings from the conditional probabilistic queries reveal that with 83.3 per cent of probability, user satisfaction is high when using apps for banking transactions, if the levels of fit, task, performance and technology characteristics are high. Furthermore, with 72 per cent of probability, continuance intention to use apps is high, if the levels of performance and task characteristics are high.

Contributing to task-technology fit theory, this study shows that performance characteristics need to be aligned with task and technology characteristics in order to have better fit when using apps for online banking transactions.

With the outbreak of the COVID-19 pandemic, online assessment has become the dominant mode of examination in higher education institutions. However, there are contradictory findings on how students perceive online assessment and its impact on their academic performance. Thus, the purpose of this study is to evaluate the potential impact of online assessment on students' academic performance.

This study proposes a research model based on the task–technology fit theory and empirically validates the model using a survey from students in the UK. In addition, the study conducted four experiments based on paper-based and online assessments and analysed the data using paired sample t test and structural equation modelling.

The findings show that the use of online assessment has a positive impact on students' academic performance. Similarly, the results from the experiment also indicate that students perform better using online assessments than paper-based assessments.

The findings provide crucial evidence needed to shape policy towards institutionalising online assessment. In addition, the findings provide assurance to students, academics, administrators and policymakers that carefully designed online assessments can improve students' academic performance. Moreover, the study also provides important insights for curriculum redesign towards transitioning to online assessment in higher education institutions.

This study advances research by offering a more nuanced understanding of online assessment on students' academic performance since the majority of previous studies have offered contradictory findings. In addition, the study moves beyond existing research by complementing assessment results with the views of students in evaluating the impact of online assessment on their academic performance. Second, the study develops and validates a research model that explains how the fits between technology and assessment tasks influence students' academic performance. Lastly, the study provides evidence to support the wide use of online assessment in higher education.

Enterprise social media (ESM) usage has gained considerable momentum within organizations. The purpose of this paper is to seek a better understanding of ESM usage based on the task environments and the technology affordances of ESM.

This study is based on a survey consisting of 556 usable responses. Regression methods are applied to analyze the data.

This study finds strong support for the positive impact of task-technology fit on ESM usage. Considering separately, task equivocality had no impact; task interdependence had a negative effect on ESM usage; bridging social capital had a positive effect; and bonding social capital had a marginal impact on ESM usage.

This research incorporated social capital into discussions of task-technology fit. A 2×2 matrix based on task equivocality and task interdependence was developed, which may be extended to other contexts or technologies.

ESM implementation should account for both task environments and the appropriate technology affordances. Individuals access bridging social capital to a greater extent than bonding social capital using ESM, and they do not use ESM when the task environments alone are considered.

This is an original study that considers task environments and technology affordances in the context of ESM usage. The findings offer valuable and timely contributions to both scholars and practitioners.

This study aims to examine the effect of task and technology characteristics on the compatibility of technology and tasks, as well as examine the reciprocal effect between the task-technology fit and the use of information systems.

The study took place in 36 star hotels from one-star to four-star hotels in some cities and districts in South Kalimantan Province. There were 24 hotels in Banjarmasin, 7 hotels in Banjarbaru and 1 hotel in each area of Banjar, Tanah Bumbu, Tabalong, Hulu Sungai Utara and Barito Kuala. The hotels chosen were those implemented the information and communication technology as supporting administrative activities to serve hotel customers. The population was the front office staff in the existing hotels as the users of the information technology. The sampling technique used in this research was the questionnaire distribution in accordance with the number of population. Data were collected from the filled questionnaires. From the 239distributed questionnaires, 164 (68.62 per cent) were returned and used as the research data.

Task characteristics and technology characteristics have a significant and positive effect on task-technology fit, in which the higher the task characteristics and technology characteristics, the higher the task-technology fit. The task-technology fit and the use of information systems are positive and reciprocal. This means that the higher the task-technology fit, the higher the use of information systems.

The originality of this study is reciprocal relationship between the variables of use with the task-technology fit. Some researchers have found the compatibility of technological tasks affecting the use of information systems, namely, Lin and Huang (2008), Norzaidi and Salwani (2009), Larsen et al. (2009), McGill and Klobas (2009), D’Ambra and Wilson (2013), Im (2014) and Chang et al. (2015). On the other hand, in task-technology fit theory, Goodhue and Thompson (1995) state that use affects the task-technology fit.

The purpose of this paper is to : first, examine information systems (IS) infusion from a user commitment perspective, and second, examine the formation of user commitment toward the use of IS in terms of job design.

This study adopts a survey approach with structural equation modeling to test the developed research model and hypotheses.

A survey of 236 enterprise system users shows that user commitment has a positive effect on IS infusion. User commitment, in turn, is influenced by task technology fit, technology self-efficacy, and task autonomy. Further mediation and direct effects to IS infusion are explored.

This study offers implications for research, such as explaining a driver of IS infusion; and extending commitment theory by finding antecedents of user commitment.

The results of this study offer suggestions to management on how to improve IS infusion in terms of user commitment and, consequently, how to develop user commitment based on the socio-technical system (STS) design.

The study highlights the critical impact of technology autonomy on IS infusion. An individual user’s authority in using and regulating the system is required for IS infusion.

This study has proposed a theoretical model of IS infusion based on commitment and socio-technical job design factors.

This study aims to investigate the relationship between information and communication technologies (ICTs) use and work performance during the coronavirus disease 2019 (COVID-19) pandemic. Specifically, it aims to understand what the role of task–technology fit is, and what effect this has on feelings of loneliness of individuals and their subsequent work performance. As a large proportion of workers are required to work from home during the ongoing COVID-19 pandemic, understanding what aspects contribute to higher performance and reduced negative psychological outcomes is of increased practical and research interest.

To explore these questions, a quantitative approach that employed a sample population of 357 individuals who worked from home during the COVID-19 pandemic was used. Using a convenience, purposive and snowball sampling approach the authors collected data through a custom-built online questionnaire, and analyzed the data using structural equation modeling (SEM).

The results highlight the effect that high task–technology fit has in both directly and indirectly influencing work performance of individuals. The authors find that by designing ICTs based on task–technology fit principles, individuals are less likely to experience feelings of loneliness while working from home and are more prone to perform better in their work-related tasks.

This study offers a new perspective on the role fit of tasks with technology have on influencing psychological states, and indirectly influencing work-related outcomes. The authors, therefore, expand the understanding about why task–technology fit is sought after by explaining part of the psychological mechanisms through which it has an effect on work performance.

Traditionally, Task–Technology Fit (TTF) theory has been applied to examine the usefulness of technology in the work environment. Can the same approach (based on experience rather than tasks) be applied to non-work, cultural heritage environments? This is the question the authors ask in this study. This study proposes a new variation of TTF based on the experience economy model, namely Experience–Technology Fit (ETF), for the non-work environment, in particular, in the context of cultural heritage, where visitor experience is enhanced by extended reality technology, which combines immersive technologies and artificial intelligence.

Employing a quantitative survey method, the empirical analysis seeks to determine the influence of Mixed Reality (MR) characteristics (interactivity, vividness), Voice User Interface (VUI) characteristics (speech recognition, speech synthesis) and experience economy factors (education, entertainment, esthetic, escape) on satisfaction, revisit intention and actual purchase to propose a new ETF model.

VUI, MR, and experience factors were significantly associated with ETF; when combined with MR-based experience, ETF was significantly associated with satisfaction. This study’s findings further demonstrate the relationship between users' satisfaction when engaging with MR-based experience and revisit intention, while purchase intention was significantly associated with the actual purchase.

The novel contribution of this study is the proposal of the EFT model, a new variation of TTF based on the experience economy model. Overall, this study expands the applications of TTF to an experience-oriented business, thereby broadening the authors’ understanding of technological success with a specific focus on the technology fit of Extended Reality (XR) in the context of cultural heritage.

This paper aims to examine the role of the creation task–technology fit (CTTF) in the knowledge creation performance (KCP). The creation task features represented by goal-driven, goal-free and goal-frame modes (GDM, GFM and GRM) and information and communication technology (ICT) supportive features are considered. The moderation effect of cognitive style represented by analytical and intuitive styles is explored. Contributions and implications are addressed.

The literature review on creation task, ICT, cognitive behavior and fit theory, and the research gap with respect to the antecedents of KCP are presented. The research arguments are then hypothesized and the research model developed to describe that the proposed role is examined empirically.

Research findings are obtained on the basis of the data analysis of 258 valid subjects from research institutes as well as manufacturing and service industries. The effect of CTTF on creation outcomes is significantly confirmed. The ICT supportive functions are unlikely significantly related to CTTF for the analysis-styled group, but the intuition-styled group shows a likely significance because of the different means of dealing with information and knowledge processing. The analysis-styled group disagrees with the significant link of the GDM with CTTF, whereas the intuition-styled group presents the significant effects of GDM, GFM and GRM on CTTF.

The unique features of knowledge creation differentiate it from other tasks. With respect to whether the knowledge creation task presented by goal is defined or not, and how ICT better suits the creation task features to benefit the creation outcomes are yet to be discussed. The individual cognitive style is confirmed to alternate the effect of ICT and GDM on CTTF in the proposed model. The research findings are particularly obvious because a transition gap, less covered by the literature, might exist with regard to the perception connection of knowledge creation service providers, agencies, consultants and context creators.

Using the extended task‐technology fit (TTF) model, this paper aims to examine technology resistance, technology satisfaction and internet usage on students' performance.

The study was conducted at Universiti Teknologi MARA, Johor, Malaysia and questionnaires were distributed to 354 undergraduate students.

The structural equation modelling (SEM) results indicate that technology satisfaction and the internet usage significantly explains the variance on students' performance. Task‐technology fit is not a predictor of technology resistance but it does predict the internet usage. The internet usage has greater impact on technology satisfaction than technology satisfaction on the internet usage. Finally, technology resistance is not a predictor of students' performance.

The study focuses only on education in Malaysia and concentrates only on the students' performance and the relationship between technology resistance, technology satisfaction and the internet usage.

The results provide insights on how Malaysian education systems of a similar structure could improve upon their internet adoption.

This study is perhaps one of the first to address internet adoption in education using an extended task‐technology fit model (task‐technology fit, internet usage, technology resistance, technology satisfaction) to investigate their influences on students' performance.