Task-technology Fit Research Articles

The Moderating Role of Flow Experience on Mobile Commerce Continuance Intention: The Integrative View of User Adaptation, Expectation-Confirmation, and Task-Technology Models

This study examines mobile commerce continuance intention based on integrating expectation-confirmation and task-technology models and incorporating flow experience and user adaptation perspectives in an emerging context of Vietnam. The dataset ( n = 519) of face-to-face responses from mobile commerce consumers utilizing convenience and snowball sampling techniques was examined employing the partial least squares structural equation modeling SmartPLS4.0. The findings confirm that confirmation, perceived usefulness, and satisfaction are all positively related to continuance intention. Additionally, the findings show that while task-technology fit affects perceived usefulness and user adaptation, it does not directly predict satisfaction. Furthermore, the study indicates that flow and task-technology fit impact continuance intention. Remarkably, this study is the first to unveil the significant moderating effect of flow on the relationship between adaptation and continuation intention. The study offers insightful implications for firms to retain customers effectively by boosting the factors forming continuance intention.

Understanding perceived performance impacts of mobile phone use among smallholders in Uganda: the influence of task-technology fit and current use

Understanding perceived performance impacts of mobile phone use among smallholders in Uganda: the influence of task-technology fit and current use

Are students ready for robots in higher education? Examining the adoption of robots by integrating UTAUT2 and TTF using a hybrid SEM-ANN approach

Robots have been heavily utilized in many industries, including education. However, the determinants driving robot adoption for educational purposes, particularly in developing countries, are not yet well understood. Additionally, the existing literature does not examine the fitness between robot capabilities and education-related tasks. Therefore, this research integrates the extended unified theory of acceptance and use of technology (UTAUT2) and task-technology fit (TTF) to examine robot adoption in higher education. Based on 177 responses collected from university students, the proposed model is verified using a hybrid structural equation modeling and artificial neural network (SEM-ANN) approach. The findings indicated that effort expectancy is positively affected by individual technology fit and task technology fit. Further, performance expectancy is significantly driven by task technology fit, but not individual technology fit. The results also supported the role of performance expectancy, social influence, facilitating conditions, and hedonic motivation in affecting behavioral intention, with a variance of 65% in the latter. With a normalized value of 94.5%, the ANN results revealed that social influence is the most important factor affecting robot adoption. These empirical findings provide several theoretical contributions and will help higher education institutions to promote students’ adoption of robots while enhancing their practical value.

The influences of four dimensions of perceived fit on individuals’ utilisation of SPOCs: an extension of the task-technology fit model

ABSTRACT Small Private Online Courses (SPOCs) platform enables individuals to carry out their online and offline learning activities. In order to understand individuals’ utilisation of SPOCs, this study develops a research model to examine the joint influences of four dimensions of perceived fit manifested in perceived technology-task fit (TTF), perceived individual-technology fit (ITF), perceived online-offline task fit (OTF), and perceived online-offline interactivity fit (OIF). A survey is conducted at a famous university in China, and 371 data are collected from students who select courses on the SPOC platform. Structural equation modelling method is used to examine the research model. The empirical results suggest that ITF is the most significant antecedent of individual performance expectancy, followed by OTF, TTF, and OIF. Furthermore, individual performance expectancy positively influences satisfaction and continuance intention in the SPOC platform. Moreover, this study incorporates self-regulation as a moderator to explore behavioural differences between individuals with high and low self-regulation. This study extends the traditional perceived fit framework by introducing OTF and OIF and uncovers the antecedents and boundary conditions of individuals’ utilisation of SPOCs in the emerging research context.

Assessing the Curvilinear Relationship in Employee Digital Performance: A Task-Technology Fit Perspective

In the context of the digital economy, one of the most important issues facing business managers is that of how to improve employee digital performance (EDP), however, extant studies exploring this problem are quite limited. The purpose of this paper is to investigate how the characteristics of task and technology represented by enterprise social media (ESM) affect task-technology fit (TTF), which in turn affects EDP. Using TTF theory, this paper proposes a research model to validate the research question. An ordinary least squares method is used to analyze 284 questionnaire responses drawn from 33 provinces in China. The results indicate that task complexity has an inverted U-shaped effect on TTF, whereas task interdependence has no effect on TTF. Work-related function of ESM has a U-shaped effect on TTF, while social-related function of ESM has a positive effect on TTF. TTF positively influences both employee digital-enabled task performance and employee digital-enabled innovative performance. Employee digital literacy strengthens the impact of TTF on employee digital-enabled task performance, but does not moderate the relationship between TTF and employee digital-enabled innovative performance. Organizational digital culture strengthens the impacts of TTF on both employee digital-enabled task performance and employee digital-enabled innovative performance. From a theoretical perspective, this paper makes a contribution to TTF theory by revealing the curvilinear relationship between the characteristics of task, the characteristics of ESM technology and TTF. This paper also contributes to the EDP literature by clarifying how TTF affects EDP, and by identifying the boundary conditions (namely employee digital literacy and organizational digital culture) between TTF and EDP. From a practical point of view, this paper provides managers with the insights to improve EDP in terms of task assignment, employee training, enterprise culture building, etc.

Refueling convenience and range satisfaction in electric mobility: Investigating consumer willingness to use battery swap services for electric vehicles

Battery swap service (BSS) is a game-changing innovation for achieving electric vehicle (EV) refueling, driving range satisfaction, and convenience. BSS is an avenue for swapping a worn-out EV battery for a pre-charged one, eliminating the long charging times of batteries. However, consumer adoption of BSS is overlooked, lacking empirical support. BSS is encouraged as it makes clean ‘fuel’ readily available for EV use. Consumer willingness to patronize BSS is pivotal to EV usage, sustainable transport, and pollution mitigation. Consequently, the innovation diffusion theory is extended with attitude, perceived risk, green self-identity, and task-technology fit to investigate consumer willingness to use BSS. Utilizing a partial least squares-structural equation model (PLS-SEM), 618 responses were analyzed. The outcome revealed that relative advantage, compatibility, attitude, green self-identity, and task-technology fit positively impacted willingness to use BSS. Perceived risk had a significant adverse effect on willingness to use BSS. Attitude mediated the impact of relative advantage and task-technology fit. Also, perceived risk negatively affected attitude. Further, ANOVA analysis confirmed the impact of consumer demography on the willingness to use BSS. Policies involving swapping standardization and synchronization, public sensitization, monetary incentives, and battery performance enhancement are recommended for enhancing BSS acceptance, usage, and proliferation.

Task-Technology Fit Analysis: Measuring the Factors that influence Behavioural Intention to Use the Online Summary-with Automated Feedback in a MOOCs Platform

The purpose of this study was to evaluate the factors that influence behavioural intention (BI) to use the Online Summary-with Automated Feedback (OSAF) in a MOOCs platform. Task-Technology Fit (TTF) was the main framework used to analyse the match between task requirements and technology characteristics, predictng the utilisation of the technology. The relationships between TTF and BI was moderated by students’ performance. This TTF provides an illustration of the extent to which the suitability of technology support for tasks will affect the performance and utilization of technology. There were 9 hypotheses examined in this study. The participants consisted of 151 students at a public university in East Java, Indonesia. In order to analyse the collected data, PLS-SEM (partial least squares - structural equation modeling) was employed, using SmartPLS 3.0. In this study, several points can be concluded, namely: 1) task characteristics and technology characteristics were not positively and significantly effected by TTF, while students' characteristics had a positive and significant effect on TTF; 2) TTF and utilization which are influenced by social influence, have a positive effect on performance impact. In this case the performance impact is constructed from 3 dimensions, namely: learning performance, personal integrity, self-confidence, except TTF were not postitive and were significantly affected by self-confidence. 3) TTF and performance impact positively influence behavioural intention, except in the dimension of performance impact, personal integrity was not postively and significantly effected by behavioural intention.

From theory to practice: An integrated TTF-UTAUT study on electric vehicle adoption behavior.

In Industry 4.0, the adoption of new technology has played a major role in the transportation sector, especially in the electric vehicles (EVs) domain. Nevertheless, consumer attitudes towards EVs have been difficult to gauge but researchers have tried to solve this puzzle. The prior literature indicates that individual attitudes and technology factors are vital to understanding users' adoption of EVs. Thus, the main aim is to meticulously investigate the unexplored realm of EV adoption within nations traditionally reliant on oil, exemplified by Saudia Arabia. By integrating the "task technology fit" (TTF) model and the "unified theory of acceptance and usage of technology" (UTAUT), this research develops and empirically validates the framework. A cross-section survey approach is adopted to collect 273 valid questionnaires from customers through convincing sampling. The empirical findings confirm that the integration of TTF and UTAUT positively promotes users' adoption of EVs. Surprisingly, the direct effect of TTF on behavioral intentions is insignificant, but UTAUT constructs play a significant role in establishing a significant relationship. Moreover, the UTAUT social influence factor has no impact on the EVs adoption. This groundbreaking research offers a comprehensive and holistic methodology for unravelling the complexities of EV adoption, achieved through the harmonious integration of two well-regarded theoretical frameworks. The nascent of this research lies in the skilful blending of technological and behavioral factors in the transportation sector.

How to build better environments that reinforce adaptation of online learning?——Evidence from a large-scale empirical survey of Chinese universities

This study is based on a comprehensive review of existing literature. Drawing upon the theories of task-technology fit (TTF) and technology adoption model (TAM), an integrated theoretical framework is developed. The framework places adaptability as a critical outcome variable and quality standard. This study constructs a student-centered online learning process model oriented towards effectiveness. The research is intended to utilize data from the "National Survey of Undergraduate Education Teaching Quality in Ordinary Universities" encompassing 123,894 Chinese university students from 272 undergraduate institutions. Through a questionnaire-based survey, the study comprehensively investigates the influence paths and mechanisms of several key factors, including environmental support (ES), teaching satisfaction (TS), perceived ease of use (PEU), task-technology fit (TTF), and learning adaptability (LA). The structural equation model largely validates the study's hypotheses, demonstrating significant correlations among the variables. The task-technology fit (TTF) and adaptability of university students are found to be influenced by teaching satisfaction (TS), perceived ease of use (PEU), and environmental support (ES). task-technology fit (TTF) emerges as a pivotal process variable in online learning. teaching satisfaction (TS) and perceived ease of use (PEU), as foundational elements, positively influence learning adaptability (LA) through the mediating role of task-technology fit (TTF). However, environmental support (ES) negatively predicts task-technology fit (TTF). The study findings offer empirical support for designing an environment conducive to enhancing students' adaptability in online learning. Furthermore, the outcomes guide policy formulation and practical strategies in various aspects, including optimizing teacher instruction in the online setting, enhancing students' perceived usability of digital technologies, and promoting the supply of online technological functionalities. Ultimately, these efforts contribute to the welfare of students' learning experiences.

Computerized accounting information systems: An application of task technology fit model for microfinance

This study investigates the factors of Computerized Accounting Information Systems (CAIS) and the application of Task Technology Fit (TTF) in 190 decision-makers at accredited microfinance in Indonesia that apply technology adoption in decision-making processes. The results of analysis with SEM AMOS highlighted some findings: (1) The system quality of the computerized accounting information system and task analyzability have a significant effect on Task Technology Fit (TTF), (2) Task Technology Fit (TTF) has a positive relationship with perceived usefulness and sustainable performance. Furthermore, this study contributes to the development of TTF theory in optimizing integrated technological capabilities, accounting information systems, and task characteristics toward Sustainable Performance. The prominent contribution of this research is the importance of technology (including CAIS and Core Micro Banking System). Finally, this study will enrich references in the field of Accounting and Finance, especially for the application of technology for Sustainable Performance in Microfinance.

Navigating the Learning Landscape: Social Cognition and Task-Technology Fit as Predictors for MOOCs Continuance Intention by Sales Professionals

Massive open online courses (MOOCs) have gained popularity among sales professionals who use them for self-directed learning and upskilling. However, research related to their intentions to continue learning is scarce. Drawing from the social cognition theory, this research aimed to address this gap by investigating the role of task-technology fit, self-development, and social recognition in sales professionals’ continued use of MOOCs. The study hinged on empirical research and used a survey to collect data from 366 sales professionals. The results suggest that task-technology fit, self-development, and social recognition play a significant role in sales professionals’ continued use of MOOCs. The study has practical implications for organizations promoting employee learning and development. The findings provide valuable information for MOOC designers and providers to develop more effective courses that meet the needs of sales professionals.

Self-Efficacy and Technology Adoption for Micro, Small and Medium Enterprises: An Integrated Model of Task-Technology Fit and Technology Acceptance

The development and digitization of the MSMEs ecosystem are accelerated steps towards realizing digital MSMEs that have an impact on the country's economy in the digital transformation era. This study aims to determine self-efficacy, which is an external variable, and technology adoption by MSMEs when implementing the integration of two technological models, namely task-technology fit (TTF) and technology acceptance (TAM), in their business activities. Data were collected through a questionnaire survey distributed to 269 MSMEs using convenience sampling and analyzed using PLS-SEM. The findings of this study indicate that self-efficacy has a greater influence than TTF on perceived ease of use, and the hypothesis about the components of TTF and TAM are supported based on the data on attitudes towards and intentions to use them. This study provides practical recommendations for stakeholders to empower MSMEs and for MSMEs themselves to leverage technology adoption in their business activities. The implications of this research provide practical recommendations for stakeholders to strengthen Micro, Small, and Medium Enterprises (MSMEs) and enhance the adoption of technology in their business activities, thereby driving the growth of the country's economy in the digital transformation era.

The Impact of Recommendation System on User Satisfaction: A Moderated Mediation Approach

A recommendation system serves as a key factor for improving e-commerce users’ satisfaction by providing them with more accurate and diverse suggestions. A significant body of research has examined the accuracy and diversity of a variety of recommendation systems. However, little is known about the psychological mechanisms through which the recommendation system influences the user satisfaction. Thus, the purpose of this study is to contribute to this gap by examining the mediating and moderating processes underlying this relationship. Drawing from the traditional task-technology fit literature, the study developed a moderated mediation model, simultaneously considering the roles of a user’s feeling state and shopping goal. We adopted a scenario-based experimental approach to test three hypotheses contained in the model. The results showed that there is an interaction effect between shopping goals and types of recommendation (diversity and accuracy) on user satisfaction. Specifically, when a user’s shopping goal aligns with recommendation results in terms of accuracy and diversity, the user satisfaction is enhanced. Furthermore, this study evaluated the mediating role of feeling right and psychological reactance for a better understanding of this interactive relationship. We tested the moderated mediation effect of feeling right and the psychological reactance moderated by the user shopping goal. For goal-directed users, accurate recommendations trigger the activation of feeling right, consequently increasing the user satisfaction. Conversely, when exploratory users face accurate recommendations, they activate psychological reactance, which leads to a reduction in user satisfaction. Finally, we discuss the implications for the study of recommendation systems, and for how marketers/online retailers can implement them to improve online customers’ shopping experience.

Adopting human resource information system and work-related outcomes in emerging market SMEs: unified theory of acceptance and use of technology

PurposeThis study investigates the psychological adoption of technology in relation to employees' mental beliefs about using technology in their workplace, because it is necessary to investigate the direct and indirect effects of information systems (IS) on employees' work-related results that underpin creativity and engagement.Design/methodology/approachUsing a cross-sectional design, data were collected from 153 human resource (HR) employees who used human resource information systems (HRIS) in small- and medium-sized enterprises (SMEs) in Malaysia.FindingsThe results show that effective acceptance and adoption of an HRIS enables HR employees and management in SMEs to be creative, balanced and engaged. Facilitating conditions and task-technology fit positively affect the behavioral intention to accept and adopt an HRIS. Additionally, organizational citizenship behavior moderates the relationship between the behavioral intention to accept and adopt an HRIS and employee creativity.Originality/valueThis study significantly advances the fields of human resource management and IS by elucidating the factors influencing employees' adoption of technology. In an effort to address a research gap in existing research, it introduces a unified theory of acceptance and use of technology, which precedes the psychological adoption process by individuals. Furthermore, it offers both empirical and theoretical insights into the interplay between technology adoption factors and their subsequent impact on work-related outcomes.

Assessing The General Sentiment of Malaysian Manufacturers in Adopting Blockchain Technology to Improve Supply Chain Processes

The popularity of blockchain technology has seen a dramatic increase throughout the year of 2021 and 2022, with numerous use cases in various global industries. This includes the use of cryptocurrencies, non-fungible tokens, decentralized autonomous organizations, and others. In Malaysia, there is also an apparent increase in general awareness towards the technology, with Bank Negara Malaysia and Securities Commission actively participating in the Committee for Blockchain and Distributed Ledger Technology. This study specifically examined at the Malaysian manufacturing industry, attempting to assess their general sentiments towards blockchain technology and how it could help to improve various supply chain processes. The quantitative study received 114 valid responses from management level employees with Malaysian manufacturers, enabling the researchers to assess the task technology fit, perceived ease of use (PEOU), perceived usefulness (PUSE), and technology readiness index (TRI). The analysis indicated that there is indeed a high task technology fit in the Malaysian manufacturing sector. In addition, this industry showed a positive sentiment towards blockchain technology, with high scores in PEOU, PUSE, and TRI. The high TRI numbers also had a positive significant relationship on the decision to adopt this technology within the manufacturing companies to improve various supply chain processes.

Factors influencing consumers’ continuance usage intention toward Food Delivery Apps during COVID-19 in Bangladesh

The aim of this research is to identify the factors that are crucial to formulating consumers’ attitude toward using food delivery apps (FDAs) continuingly during the coronavirus pandemic. Due to the pandemic, the catering enterprises changed their way of doing business significantly and gone through a digital transformation to survive. Consequently, this marked a shift in consumers’ attitude towards FDAs. To understand the shift and how consumers’ technological and mental perceptions are contributing to continuance usage intentions, a hypothetical model was proposed using variables from Unified Theory of Acceptance and Use of Technology (UTAUT), Expectancy Confirmation Model (ECM) and the Task-Technology fit Model. A structured questionnaire was used to collect feedback from the repeat users of the FDAs through online social media sites and food review groups. In total 198 valid responses were gathered and analyzed. Structural Equation Modeling (SEM) through AMOS 26 was utilized to test the proposed model fit. Some items in the constructs had to be dropped off to make the model fit. Initially four hypotheses were proposed. Among them only two were validated. The outcomes show that satisfaction and social influence have significant positive impact in determining continuance usage intention toward FDAs among Bangladeshi consumers. While perceived Task-technology fit and trust have non-significant relationship with consumers’ continuance intention. These insights might prove helpful for both online food aggregators and catering businesses in designing marketing plan and formulating effective strategies to build a sustainable consumer base. Future research can extend the model by adding more variables to understand relevant technology’s continuance usage intention. This paper is a unique contribution to the existing literature on FDA continuance intention on coronavirus emergency because no previous studies were undertaken to investigate Bangladeshi consumers. So, this is an original piece of work according to the best of the researchers’ knowledge

Adopting artificial intelligence driven technology in medical education

PurposeArtificial intelligence (AI) is a growing paradigm and has made considerable changes in many fields of study, including medical education. However, more investigations are needed to successfully adopt AI in medical education. The purpose of this study was identify the determinant factors in adopting AI-driven technology in medical education.Design/methodology/approachThis was a descriptive-analytical study in which 163 faculty members from Tabriz University of Medical Sciences were randomly selected by nonprobability sampling technique method. The faculty members’ intention concerning the adoption of AI was assessed by the conceptual path model of task-technology fit (TTF).FindingsAccording to the findings, “technology characteristics,” “task characteristics” and “TTF” showed direct and significant effects on AI adoption in medical education. Moreover, the results showed that the TTF was an appropriate model to explain faculty members’ intentions for adopting AI. The valid proposed model explained 37% of the variance in faulty members’ intentions to adopt AI.Practical implicationsBy presenting a conceptual model, the authors were able to examine faculty members’ intentions and identify the key determining factors in adopting AI in education. The model can help the authorities and policymakers facilitate the adoption of AI in medical education. The findings contribute to the design and implementation of AI-driven technology in education.Originality/valueThe finding of this study should be considered when successful implementation of AI in education is in progress.

Employee Acceptance of Human Resource Management Information System: Integrated UTAUT and TTF Model in a Selected Public Firm in Sri Lanka

Aim: In the modern digital world, many companies are moving towards technology-based applications to perform human resource administration work. Employees nowadays are capable of accessing a web-based Human Resource Management Information System (HRMIS) to obtain critical data from recognized techniques such as System Applications and Products (SAP), PeopleSoft, Bann and Lawson. This study aims to investigating the factors affecting the adopting intention of HRMIS in a selected public firm in Sri Lanka.
 Design: Acknowledging the vital concepts on accepting or resisting technology, six components (performance expectancy, effort expectancy, social influence, facilitating conditions, task characteristics, and technology characteristics) from the Unified Theory of Acceptance and Use of Technology (UTAUT) model and the Task Technology Fit (TTF) model were contextualized to investigate the drivers influencing HRMIS adoption intentions in a selected public firm in Sri Lanka. Target population was identified as the Executives, Supervisors/Technical Officers, Clerical and Allied employees of the chosen public company in Sri Lanka. A structured online questionnaire, including 30 items, was used to collect data.
 Findings: Multiple regression analysis results revealed that the factors of Performance Expectation, Task Characteristics, and Technology Characteristics have a positive influence on users’ adoption intention to HRMIS. Effort Expectancy, Social Influence, and Facilitating Conditions had negative influence.
 Implications: The outcomes highlight the necessity of combining TTF components with technology acceptance theories when evaluating the factors influencing acceptance of HRMIS or other information systems. The study's findings will aid management in making the required organizational changes to encourage employees to use the HRMIS application.

Experiences Among Patients With Cystic Fibrosis in the MucoExocet Study of Using Connected Devices for the Management of Pulmonary Exacerbations: Grounded Theory Qualitative Research.

Early detection of pulmonary exacerbations (PEx) in patients with cystic fibrosis is important to quickly trigger treatment and reduce respiratory damage. An intervention was designed in the frame of the MucoExocet research study providing patients with cystic fibrosis with connected devices and educating them to detect and react to their early signs of PEx. This study aims to identify the contributions and conditions of home monitoring in relation to their care teams from the users' point of view to detect PEx early and treat it. This study focused on the patients' experiences as the first and main users of home monitoring. A qualitative study was conducted to explore patients' and professionals' experiences with the intervention. We interviewed patients who completed the 2-year study using semistructured guides and conducted focus groups with the care teams. All the interviews were recorded and transcribed verbatim. Their educational material was collected. A grounded analysis was conducted by 2 researchers. A total of 20 patients completed the study. Three main categories emerged from the patients' verbatim transcripts and were also found in those of the professionals: (1) task technology fit, reflecting reliability, ease of use, accuracy of data, and support of the technology; (2) patient empowerment through technology, grouping patients' learnings, validation of their perception of exacerbation, assessment of treatment efficacy, awareness of healthy behaviors, and ability to react to PEx signs in relation to their care team; (3) use, reflecting a continuous or intermittent use, the perceived usefulness balanced with cumbersome measurements, routinization and personalization of the measurement process, and the way data are shared with the care team. Furthermore, 3 relationships were highlighted between the categories that reflect the necessary conditions for patient empowerment through the use of technology. We discuss a theorization of the process of patient empowerment through the use of connected devices and call for further research to verify or amend it in the context of other technologies, illnesses, and care organizations. ClinicalTrials.gov NCT03304028; https://clinicaltrials.gov/ct2/show/results/NCT03304028.

How does big data affect organizational financial performance in turbulent markets? The role of customer-linking and selling capabilities

The information age provides vast opportunities for organizations to improve their efficiencies by relying on big data-AI empowered analytics (BDA). The purpose of this study is to address the critical question of how BDA-fit affects organizational financial performance, taking into consideration differences between markets and customer change caused by technology turbulence. Using data collected at the firm level and building on Task-Technology Fit Theory and Dynamic Capabilities Theory, empirical results indicate that BDA-fit is important to drive organizational financial performance through the development of customer-linking and selling capabilities. These results vary across markets, with BDA-fit having stronger effects on selling capabilities and organizational financial performance in highly turbulent markets. BDA allows organizations to upturn challenges and hindrances caused by market turbulence into opportunities to increase sales revenues. Based on the findings, theoretical contributions and managerial implications are provided.