2021
DOI: 10.1504/ijmc.2021.111893
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Investigating users switching intention for mobile map services: an extension of the push-pull-mooring model

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Cited by 13 publications
(13 citation statements)
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“…In addition, regret as the negative feelings of the customers could create negative word of mouth and affect the purchase of the product (Le and Ho, 2020; Sarwar et al , 2020). The results are in line with previous studies that found regret influences the switching intention behavior (Fan et al , 2020; Dey et al , 2020; Zeng et al , 2021; Liu and Lee, 2020).…”
Section: Discussionsupporting
confidence: 93%
“…In addition, regret as the negative feelings of the customers could create negative word of mouth and affect the purchase of the product (Le and Ho, 2020; Sarwar et al , 2020). The results are in line with previous studies that found regret influences the switching intention behavior (Fan et al , 2020; Dey et al , 2020; Zeng et al , 2021; Liu and Lee, 2020).…”
Section: Discussionsupporting
confidence: 93%
“…The above practice is suggested by prior service or technology adoption studies (e.g. Shen et al, 2018;Liu et al, 2021;Liao et al, 2021;Hu et al, 2021). We noticed that social desirability bias (Nederhof, 1985) might exist in the self-report questionnaire.…”
Section: Research Methods 31 Data Collection and Samplementioning
confidence: 82%
“…The PPM framework usually involves push, pull and mooring factors. Specifically, push factors refer to negative product-related features that users perceive as pushing them away from existing products (or services); pull factors refer to positive attribute of products that pull users toward alternative products; mooring factors refer to personal or social factors that hinder or facilitate switching decisions (Bansal et al, 2005;Chang et al, 2014;Wang et al, 2019;Liu et al, 2021). Specifically, based on the features of offline and mobile wealth management services, this paper takes perceived information asymmetry and perceived inconvenience as push factors, and ubiquity, transaction efficiency, perceived personalization and mobile wealth management scenarios as pull factors.…”
Section: Introductionmentioning
confidence: 99%
“…Secondly, the prior study chose only low service satisfaction ( Liu et al., 2021 ), low enjoyment ( Liu et al., 2021 ), inconvenience ( Lai et al., 2012 ), etc., for the pull effect, and alternative attractiveness ( Lai et al., 2012 ), peer influence ( Lai et al., 2012 ), etc., for the push effect. This research proposed new pull and push effect variables, such as perceived ease of use, knowledge-based trust, negativity perceived value, etc., that substantially influence users' switching intentions in the framework of ELS.…”
Section: Discussionmentioning
confidence: 99%