What drives customer satisfaction and word of mouth in mobile commerce services? A UTAUT2-based analytical approach

Kalinić, Zoran; Marinković, Veljko; Djordjević, Aleksandar; Liébana‐Cabanillas, Francisco

doi:10.1108/jeim-05-2019-0136

Cited by 80 publications

(90 citation statements)

References 79 publications

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“…Nonetheless, research has questioned the linearity of relationships in the models of technology adoption (Rondan-Cataluña et al, 2015 ). However, the most recent works that have applied non-linearity to technology acceptance models have used the Artificial Neural Networks (ANN) analysis tool (Sharma et al, 2016 ; Ooi et al, 2018 ; Chavoshi and Hamidi, 2019 ; Kalinić et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

et al. 2021

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This study analyzes the most important predictors of acceptance of social network sites in a sample of Chilean elder people (over 60). We employ a novelty procedure to explore this phenomenon. This procedure performs apriori segmentation based on gender and generation. It then applies the deep learning technique to identify the predictors (performance expectancy, effort expectancy, altruism, telepresence, social identity, facilitating conditions, hedonic motivation, perceived physical condition, social norms, habit, and trust) by segments. The predictor variables were taken from the literature on the use of social network sites, and an empirical study was carried out by quota sampling with a sample size of 395 older people. The results show different predictors of social network sites considering all the samples, baby boomer (born between 1947 and 1966) males and females, silent (born between 1927 and 1946) males and females. The high heterogeneity among older people is confirmed; this means that dealing with older adults as a uniform set of users of social network sites is a mistake. This study demonstrates that the four segments behave differently, and many diverse variables influence the acceptance of social network sites.

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Section: Introductionmentioning

confidence: 99%

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

et al. 2021

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“…When the residents are satis ed with PPAPs, meaning that they are satis ed with the services provided by the State Grid, then they will rely on State Grid and continue to participate in PPAPs. The predecessors also found a signi cant role between trust and customers' satisfaction [32,57]. Inadequate power supply and unreliable power service will lead to end-users' dissatisfaction with power service [60].…”

Section: Discussionmentioning

confidence: 99%

“…This study de nes satisfaction as the sense of happiness formed by the bene ciaries through the previous expectation and actual perception. Some scholars con rmed a close connection between trust and users' satisfaction in mobile commerce [32,58]. In addition, scholars found that consumers' green satisfaction has a signi cant effect on green trust in the research on users' word-of-mouth intentions of the green hotel industry [43].…”

Section: Bene Ciaries' Satisfactionmentioning

confidence: 99%

Does Beneficiaries’ Satisfaction Enhance Their Trust in State Grid for Solar PV Adoption? – An Evidence From PAPs in Rural China

Ding

Yin

Dai

et al. 2021

Preprint

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Background: Photovoltaic Poverty Alleviation Projects (PPAPs) have been implemented in Chinese rural areas since 2014. As a new energy policy, PPAPs have played an important role in alleviating rural poverty. However, the adoption of solar PV faces multiple barriers from the perspective of beneficiaries. Therefore, this study basically aims to discuss and analyze factors affecting beneficiaries’ satisfaction and their trust in State Grid, promoting the adoption of solar PV. Methods: Based on the integrated American Customer Satisfaction Index (ACSI) and Unified Theory of Acception and Use of Technology (UTAUT) model, this study uses the Structural Equation Model (SEM) to reveal how the beneficiaries’ satisfaction enhance their trust in State Grid. The data were obtained from a survey of 928 PPAPs’ beneficiaries by stratified and random sampling in Chinese rural areas. Results: The results confirm that environmental perception in this study positively impacts on beneficiaries’ satisfaction. And perceived quality also has a positive effect on beneficiaries’ satisfaction and trust in State Grid, however, social influence has a negative impact on beneficiaries’ satisfaction; behavior expectation can directly promote beneficiaries’ satisfaction, while indirectly propel their trust in State Grid. Conclusions: This study constructs an integrated customer satisfaction model from the perspective of beneficiaries and proposes relevant measures to promote the adoption of solar PV that can be applied to poverty reduction of other developing countries worldwide.

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“…Its precedents lie in perceived usefulness, extrinsic motivation and fit in the job. In addition to the original study (Venkatesh et al, 2003 ), this construct has been used extensively in later research (Chauhan and Jaiswal, 2016 ; Lakhal, 2017 ; Cabrera-Sánchez and Villarejo-Ramos, 2019 ; Kalinić et al, 2019 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Predicting Big Data Adoption in Companies With an Explanatory and Predictive Model

et al. 2021

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The purpose of this paper is to identify the factors that affect the intention to use Big Data Applications in companies. Research into Big Data usage intention and adoption is scarce and much less from the perspective of the use of these techniques in companies. That is why this research focuses on analyzing the adoption of Big Data Applications by companies. Further to a review of the literature, it is proposed to use a UTAUT model as a starting model with the update and incorporation of other variables such as resistance to use and perceived risk, and then to perform a neural network to predict this adoption. With respect to this non-parametric technique, we found that the multilayer perceptron model (MLP) for the use of Big Data Applications in companies obtains higher AUC values, and a better confusion matrix. This paper is a pioneering study using this hybrid methodology on the intention to use Big Data Applications. The result of this research has important implications for the theory and practice of adopting Big Data Applications.

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What drives customer satisfaction and word of mouth in mobile commerce services? A UTAUT2-based analytical approach

Cited by 80 publications

References 79 publications

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

Segmentation of Older Adults in the Acceptance of Social Networking Sites Using Machine Learning

Does Beneficiaries’ Satisfaction Enhance Their Trust in State Grid for Solar PV Adoption? – An Evidence From PAPs in Rural China

Predicting Big Data Adoption in Companies With an Explanatory and Predictive Model

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