Online loyalty and its interaction with switching barriers

Mutum, Dilip S.; Ghazali, Ezlika M.; Nguyen, Bang; Arnott, David C.

doi:10.1016/j.jretconser.2014.08.012

Cited by 34 publications

(23 citation statements)

References 52 publications

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“…The consumer behaviour literature identifies a number of antecedent factors of online loyalty, among them satisfaction, perceived value, trust, switching costs, website design, engagement, and user experience (Bilgihan, 2016;Molinillo, Anaya-Sánchez, & Liébana-Cabanillas, 2019;Molinillo, Gómez-Ortiz, Pérez-Aranda, & Navarro-García, 2017;Mutum, Ghazali, Nguyen, & Arnott, 2014;Shankar, Smith, & Rangaswamy, 2003). Within the framework of equity theory (Huppertz et al, 1978;Oliver & DeSarbo, 1988), it is worth highlighting that customer perceived value is one of the most important predictors of customer loyalty (Parasuraman & Grewal, 2000;Yang & Peterson, 2004).…”

Section: Mobile Game Loyaltymentioning

confidence: 99%

Impact of perceived value on casual mobile game loyalty: The moderating effect of intensity of playing

Molinillo

Japutra

Liébana‐Cabanillas

2020

J of Consumer Behaviour

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The retention rate of mobile game players is one of the subjects that spark most interest in the industry, as many abandon the games only a few hours after downloading them. This study examines the antecedents of loyalty towards mobile games from the perspective of perceived value and explores the moderating effect of intensity of playing. The results revealed that hedonic value (i.e., perceived enjoyment and perceived attractiveness) and, to a lesser extent, utilitarian value (i.e., effort expectancy and perceived usefulness) are crucial in the loyalty that players feel towards mobile games. Intensity of playing weakens the relationship between perceived usefulness, perceived enjoyment and loyalty intention. Based on the findings, theoretical and practical implications are provided.

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Section: Mobile Game Loyaltymentioning

confidence: 99%

Impact of perceived value on casual mobile game loyalty: The moderating effect of intensity of playing

Molinillo

Japutra

Liébana‐Cabanillas

2020

J of Consumer Behaviour

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“…In online businesses, competition can easily enter the market because of low entry barriers (Wang et al., 2016). From the customer perspective, they have low switching costs to shop from one online store to another (Mutum et al., 2014). In physical businesses and online businesses, customer shopping experience influences future customer behavior, including repurchase intention, store revisit intention, and word of mouth (WOM) (Chang and Wang, 2011).…”

Section: Introductionmentioning

confidence: 99%

The impact of e-service quality and customer satisfaction on customer behavior in online shopping

Rita

Oliveira

Farisa

2019

Heliyon

564

328

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The purpose of this study is to develop new knowledge to better understand the most important dimensions of e-service quality that have impact on customer satisfaction, customer trust, and customer behavior, building on existing literature on e-service quality in online shopping. This study focuses on the four-dimensions of e-service quality model that better predict customer behavior. It not only tests the impact of customer satisfaction on customer behavior such as repurchase intention, word of mouth, and site revisit, but also the impact of customer trust. The result is expected to extend the knowledge about different country culture vis-á-vis different relevance of e-service quality attributes. Data from an online survey of 355 Indonesian online consumers was used to test the research model using structural equation modelling. The analytical results showed that three dimensions of e-service quality, namely website design, security/privacy and fulfilment affect overall e-service quality. Meanwhile, customer service is not significantly related to overall e-service quality. Overall e-service quality is statistically significantly related to customer behavior. Future research should consider a variety of product segments and/or other industries to make sure that the measurement works equally well. In other industry setting, the measurement may need to be adjusted. Future research could also use different methodologies such as focus group and interviews.

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“…This means that customer loyalty is the best predictor of switching barriers. Previous research has shown that satisfaction may not be the best predictor of customer loyalty and that the presence (or lack) of switching barriers may be the reason a customer stays with (or leaves) a firm [31]. Thus, it is expected that switching barriers will be frequently used to assess the performance of customer loyalty in the future study.…”

Section: Discussionmentioning

confidence: 99%

The Relationship between Social Factor, Dependency, Addiction, and Behavioral Intentions of Smartphones

Kim¹,

Shin

2016

IJUNESST

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Online loyalty and its interaction with switching barriers

Cited by 34 publications

References 52 publications

Impact of perceived value on casual mobile game loyalty: The moderating effect of intensity of playing

Impact of perceived value on casual mobile game loyalty: The moderating effect of intensity of playing

The impact of e-service quality and customer satisfaction on customer behavior in online shopping

The Relationship between Social Factor, Dependency, Addiction, and Behavioral Intentions of Smartphones

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