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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.

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.

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.

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.

Information technology is a key enabler of logistics performance. Unfortunately, most logistics information systems are implemented with forward logistics processes in mind, with little, if any, consideration for the reverse channel. Informed by task‐technology fit theory, the authors aim to explore how use of complementary information technologies to support reverse logistics processes can lead to enhanced process performance.

The authors use a survey method to gather data from logistics professionals who are positioned within various reverse logistics functions. Using reverse logistics processing effectiveness and reverse logistics cost effectiveness as dependent variables, the authors use multiple regression to examine the relationships between indicators of task‐technology fit and reverse logistics performance.

The authors’ models explain 49 percent and 30 percent of the variance in reverse logistics cost effectiveness and processing effectiveness, respectively. Information technology use and reverse logistics technology innovativeness are shown to enhance levels of reverse logistics cost effectiveness; information system compatibility and reverse logistics technology innovativeness are shown to enhance levels of reverse logistics processing effectiveness.

Although limited by the sample frame, the authors’ findings remain consistent with task‐technology fit theory and suggest that employing information technologies that are designed to complement reverse logistics processes can lead to increased reverse logistics process performance.

This study supports the notion that more attention should be given to reverse logistics processes. In order to achieve maximum return on investment, managers should consider allocating resources toward information technologies and systems that directly support reverse logistics.

This research employs a theory that has seen little attention in the logistics literature to provide insight into how use of complementary information technology can enhance reverse logistics processes.

The purpose of this study is to propose a synthetic post-adoption model based on the expectation-confirmation model (ECM) and flow theory to examine whether the fit factor, network factors and psychological factors as antecedents to end-users’ beliefs can affect their continuance intention of the robo-advisor.

This study used the research model based on ECM and flow theory to examine the effects of the fit factor, network factors and psychological factors on end-users’ beliefs and continuance intention of the robo-advisor. Sample data were collected from end-users at three financial services companies in Taiwan. A total of 450 questionnaires were distributed and 360 (80.0%) usable questionnaires were analyzed using structural equation modeling.

This study proposes a solid research model that based on ECM and flow theory, three types of factors, namely, fit factor, network factors and psychological factors, as antecedents to end-users’ continuance intention of the robo-advisor have been examined and this study’s results strongly support the research model with all hypothesized links being significant.

It is particularly worth mentioning that a synthetic post-adoption model can be proposed in this study by introducing the fit factor extracted from task-technology fit model, network factors originated from the theory of network externalities and psychological factors derived from uses and gratifications theory as antecedents to perceived usefulness, confirmation, satisfaction and continuance intention referred in ECM and flow experience derived from flow theory. Thus, this study’s research model and findings can reveal deep insights into the evaluation of determinants in the field of end-users’ continuance intention of the robo-advisor.

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.

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.

Research in tourism and hospitality industry marketing has identified many highly effective applications of social media. However, studies in the existing literature do not enable a comprehensive understanding of this phenomenon because they lack a theoretical foundation. Therefore, this study systematically reviewed the literature from the perspective of the task-technology fit (TTF) theory. The purpose of this paper is to map out what is known about social media use in tourism and hospitality marketing and what areas need further exploration.

A descriptive cumulative review of the literature obtained 99 articles published in tourism and hospitality journals from 2010 to 2019.

The analysis suggests that to understand social media use in tourism marketing, researchers and practitioners in the industry must clarify the following four issues: the control variables, longitudinal analyzes and TTF concepts that should be used in future studies; the fitness of social media platforms for tourism marketing; how various social media platforms differ in terms of performance outcome; and the digital divide in the use of social media for tourism.

An integrated framework was developed to identify constructs and to understand their relationships. Recent studies in this domain are discussed; theoretical and practical suggestions and implications for future research are given.

The advancement in Internet technology has played a significant role in revolutionizing the Internet banking services. Therefore, little is discussed about factors that motivate technology user to continue the use of Internet banking services. The current study investigates Internet banking user continuance behavior toward the use of Internet banking services with the integration of two-well known information system (IS) theories namely task technology fit (TTF) and technology continuance theory (TCT).

The research design of this study is based on positivist paradigm and followed quantitative research approach. Data were collected from 360 Internet banking users of commercial banks across Pakistan. The research model was tested with structural equation modeling (SEM).

The research model had explained 53.9% variance in Internet banking user continuance intention. Next to this, the predictive relevance of the research model was tested with Stone-Geisser's Q² values using blindfolding procedure. Results revealed that the newly developed integrated technology continuance research model has substantial power to predict Internet banking user continuance intention. Moreover, the effect size analysis revealed that factors like satisfaction and user expectation were the most important factors in determining Internet banking user continuance intention.

For practical implications importance performance matrix analysis (IPMA) has used to see the importance and performance of the underpinned factors. Findings indicate that managers and policy makers should focus on user satisfaction, perceived usefulness and expectation confirmation in order to enhance the Internet banking user continuance intention toward the use of Internet banking services. Some of the ways banks can do this is to develop esthetic Internet banking website with charm of novelty, relevant information and smooth flows with less complex redirects.

Unlike prior studies that focus on Internet banking user pre-adoption issues, the current study examines post-adoption issue of Internet banking users and investigates Internet banking user continuance intention. This study is significant as it integrates two-well known theories namely TCT and TTF in Internet banking user continuance intention and augments the IS literature by developing an integrated technology continuance model (TCM).