Understanding Consumers' Continuance Intention and Word of Mouth in Mobile Commerce Based on Extended UTAUT Model

Understanding Consumers' Continuance Intention and Word of Mouth in Mobile Commerce Based on Extended UTAUT Model

Veljko Marinković, Zoran Kalinić
Copyright: © 2020 |Pages: 18
DOI: 10.4018/978-1-7998-0050-7.ch006
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Although until recently considered a novelty, mobile commerce (m-commerce) is nowadays one of the most popular mobile services, becoming mainstream in digital commerce. The objective of this study is to determine the predictors of consumers' continuance intention in m-commerce. In addition, it is well known that word of mouth communication is a very effective marketing technique, particularly for new products and services. Therefore, the study also models and examines the determinants of consumers' willingness to recommend m-commerce as a valuable service to their relatives, friends, and peers. The research model is based on unified theory of acceptance and use of technology (UTAUT) model, extended with additional variables like perceived trust and individual mobility. The results show that the main antecedent of continuance intentions towards m-commerce is social influence, while continuance intention was found as the most important predictor of word-of-mouth.
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Literature Review

Technological advancements in the last few decades brought us many new devices and services, and while some of them were adopted by a lot of people in a short time period, others failed that and were forgotten. The problem of explaining and predicting consumer behavior attracts scientists for decades, as well-predicted factors which impact the adoption of some new technology solution may significantly influence its marketing strategy and product/service success. Therefore, many theories and models related to the adoption of new technologies were developed and tested. One of the most important and most frequently used was Technology Acceptance Model (TAM), developed by Davis (1989). This model is based on the theory of reasoned action (TRA), derived by Fishbein and Ajzen (1975) and as main determinants of behavioral intention to use a new technology it suggests attitude towards use, as well as perceived usefulness and perceived ease of use of a new technology. TAM model, with some modifications, was tested in the acceptance prediction of several mobile technologies and services (Kalinic & Marinkovic, 2016). Other important theories used in prediction of acceptance of new technologies are Diffusion of Innovation (DOI) theory, introduced by Rodgers (1995), by which the diffusion of technological innovation is determined by factors such as relative advantage, complexity, trialability and observability, and Task-technology fit (TTF) model, proposed by Goodhue and Thompson (1995), which takes into account how well new technology fits with the tasks it supports. Both models were already successfully tested in the m-commerce acceptance, alone or combined with TAM (Chong, Chan, & Ooi, 2012; Shih & Chen, 2013; Wu & Wang, 2005).

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