Influential Factors of Behavioral Attention in Using Chinese Travel Agencies’ Mobile APPs : the Integrated Model of Technology Acceptance Model and Task Technology Fit

2018 ◽  
Vol 30 (10) ◽  
pp. 165-185
Author(s):  
Li-Na Wang ◽  
Bo-Young Min
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Mobile Apps ◽  
Integrated Model ◽  
Influential Factors ◽  
Travel Agencies ◽  
Task Technology Fit ◽  
Acceptance Model ◽  
And Task

scholarly journals Big Data Analytics Usage and Business Performance: Integrating the Technology Acceptance Model (TAM) and Task Technology Fit (TTF) Model

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
Hemlata Gangwar
Keyword(s):  
Big Data ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Data Analytics ◽  
Business Performance ◽  
Big Data Analytics ◽  
Integrated Model ◽  
Task Technology Fit ◽  
Acceptance Model ◽  
And Task

The purpose of this study is to propose a unified model integrating both the technology acceptance model (TAM) and task technology fit (TTF) model, and explore the organizational and environmental fit of the integrated model in order to investigate usage of Big Data Analytics and its effect on business performance. A questionnaire was used to collect data from 280 companies in CPG & Retail, Healthcare, Banking and Telecom in India. The data were analysed using exploratory and confirmatory factor analyses. Further, structural equation modelling was used to test the proposed model. The findings show that the research model for integrating the TAM for adoption and TTF model for utility provides a more comprehensive understanding of Big Data Analytics usage. The study identified task technology fit , individual technology fit, organizational data fit, organizational process fit, and business strategy fit as Tidd important variables for affecting Big Data Analytics usage using perceived ease of use (PEOU) and perceived usefulness (PU) as mediating variables. Competitive fit and partner support/customer fit were also found to be directly affecting Big Data Analytics usage, which in turn has significant influence on business performance. The model explained 71.4 percent of Business performance. The integrated model may be used as a guideline to ensure a positive outcome of Big Data Analytics usage in organizations. This study combined both the key ideas of TAM and TTF to show that they were necessary in predicting Big Data Analytics usage and business performance.

scholarly journals Sharp Connection

2011 ◽  
pp. 34-56
Author(s):  
Paul Hendriks ◽  
Wendy Jacobs
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
The Other ◽  
Competitive Intelligence ◽  
Stepping Stone ◽  
Natural Connection ◽  
Task Technology Fit ◽  
Acceptance Model ◽  
The Relationship ◽  
And Task

Assessing the value of ICT to support Competitive Intelligence presumes an understanding of the relationship between the two. The chapter argues that starting from either the ICT or CI side to this relationship and linking to the other, as most studies do, cannot secure a fully adequate conception of ICT’s value to CI. Instead, the challenge is to find an appropriate foundation in the relationship itself and use it as a stepping stone for developing an understanding of both ICT and CI. The chapter proposes to use and develop the concept of acceptability to provide that foundation. Acceptability offers a natural connection between the technology and CI sides. An object—e.g., a technology—cannot be acceptable in a void, but presumes a relation to a context or a subject—e.g., the CI function—to be considered acceptable or unacceptable. The Technology Acceptance Model (TAM) and Task-Technology Fit model (TTF) provide useful elements to develop this approach further. The chapter presents the case of an intranet to support CI, called IntraTel, to illustrate the argument.

I want to learn more! Integrating technology acceptance and task–technology fit models for predicting behavioural and future learning intentions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alessandro Lo Presti ◽  
Assunta De Rosa ◽  
Enrico Viceconte
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Ease Of Use ◽  
Perceived Ease Of Use ◽  
Content Type ◽  
Moderated Mediation Model ◽  
Task Technology Fit ◽  
Acceptance Model ◽  
Training Opportunities ◽  
Future Learning

Purpose Constant and frequent technological changes within organizations call for further scholarly attention, as behavioural intentions need to be coupled also with future learning intentions to predict the present and prospective individual adaptations and performance. This study, grounded on the technology acceptance model, aims to examine the association between training opportunities and behavioural and future learning intentions also taking into account the role of task–technology fit as a moderator. Design/methodology/approach A survey was carried out within a single organization in the water processing sector on a sample of 200 workers who recently experienced a technological change through the adoption of System Application and Product in data processing. A moderated–mediation model was estimated through regression analyses with bootstrapping. Findings The results were consistent with study hypotheses. In particular, task–technology fit amplified the positive association between perceived ease of use and training opportunities as well as the indirect effect of this latter on both behavioural and future learning intentions through perceived ease of use and perceived usefulness. In sum, the hypothesized moderated–mediation model was confirmed. Originality/value Three novelty factors of this study can be stressed: it is among the few studies carried out on Italian workers in the realm of technology adoption, it expanded the technology acceptance model by including traditional behavioural intentions and future learning intentions as outcome variables and it integrated the task–technology fit perspective within the technology acceptance model.

Exploring customers’ attitudes to the adoption of robots in tourism and hospitality

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamed Abou-Shouk ◽  
Hesham Ezzat Gad ◽  
Ayman Abdelhakim
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Service Robots ◽  
Content Type ◽  
Factors Affecting ◽  
Positive Attitudes ◽  
Travel Agencies ◽  
Tourism And Hospitality ◽  
Acceptance Model

Purpose This study aims to explore the factors affecting customers’ attitudes to the adoption of robots in hotels and travel agencies. Design/methodology/approach Structural equation modelling was used to test the extended technology acceptance model based on data collected from 570 customers of hotels and travel agencies. Findings The findings revealed that hotel customers have more positive attitudes to service robots than their peers in travel agencies. Originality/value This research contributes to the literature on robots in tourism and responds to the call to investigate customers’ attitudes to the adoption of robots in developing countries.

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