2006•Information Systems JournalRequires access

Predicting consumer intention to use mobile service

Yi‐Shun Wang, Hsin‐Hui Lin, Pin Luarn

Open publisher page 640 citations

Abstract

Abstract. Advances in wireless technology have increased the number of people using mobile devices and accelerated the rapid development of mobile service (m‐service) conducted with these devices. However, although many companies are today making considerable investments to take advantage of the new business possibilities offered by wireless technology, research on mobile commerce suggests potential consumers may not adopt these m‐services in spite of their availability. Thus, there is a need for research to identify the factors that affect consumer intention to use m‐services. Based on the technology acceptance model (TAM), theory of planned behaviour (TPB) and Luarn & Lin's 2005 mobile banking acceptance model, the current research respecifies and validates an integrated model for predicting consumer intention to use m‐service by adding one trust‐related construct (‘perceived credibility’) and two resource‐related constructs (‘self‐efficacy’ and ‘perceived financial resources’) to the TAM's nomological structure and re‐examining the relationships between the proposed constructs. Data collected from 258 users in Taiwan were tested against the research model using the structural equation modelling approach. The results strongly support the proposed model in predicting consumer intention to use m‐service. Several implications for information technology/information system acceptance research and m‐service management practices are discussed.

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What this paper is about

Abstract. Advances in wireless technology have increased the number of people using mobile devices and accelerated the rapid development of mobile service (m‐service) conducted with these devices. However, although many companies are today making considerable investments to take advantage of the new business possibilities offered by wireless technology, research on mobile commerce suggests potential consumers may not adopt these m‐services in spite of their availability. Thus, there is a need for research to identify the factors that affect consumer intention to use m‐services. Based on the technology acceptance model (TAM), theory of planned behaviour (TPB) and Luarn & Lin's 2005 mobile banking acceptance model, the current research respecifies and validates an integrated model for predicting consumer intention to use m‐service by adding one trust‐related construct (‘perceived credibility’) and two resource‐related constructs (‘self‐efficacy’ and ‘perceived financial resources’) to the TAM's nomological structure and re‐examining the relationships between the proposed constructs. Data collected from 258 users in Taiwan were tested against the research model using the structural equation modelling approach. The results strongly support the proposed model in predicting consumer intention to use m‐service. Several implications for information technology/information system acceptance research and m‐service management practices are discussed.

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Available abstract

Abstract. Advances in wireless technology have increased the number of people using mobile devices and accelerated the rapid development of mobile service (m‐service) conducted with these devices. However, although many companies are today making considerable investments to take advantage of the new business possibilities offered by wireless technology, research on mobile commerce suggests potential consumers may not adopt these m‐services in spite of their availability. Thus, there is a need for research to identify the factors that affect consumer intention to use m‐services. Based on the technology acceptance model (TAM), theory of planned behaviour (TPB) and Luarn & Lin's 2005 mobile banking acceptance model, the current research respecifies and validates an integrated model for predicting consumer intention to use m‐service by adding one trust‐related construct (‘perceived credibility’) and two resource‐related constructs (‘self‐efficacy’ and ‘perceived financial resources’) to the TAM's nomological structure and re‐examining the relationships between the proposed constructs. Data collected from 258 users in Taiwan were tested against the research model using the structural equation modelling approach. The results strongly support the proposed model in predicting consumer intention to use m‐service. Several implications for information technology/information system acceptance research and m‐service management practices are discussed.

Key concepts: Technology acceptance model, Structural equation modeling, Mobile commerce, Service (business), Theory of planned behavior, Construct (python library), Knowledge management, Business

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