Fashion shopping on the go: A Dual-stage predictive-analytics SEM-ANN analysis on usage behaviour, experience response and cross-category usage

Ng, Felicity Zi-Xuan; Yap, H.K.; Tan, Garry Wei–Han; Lo, Pei-San; Ooi, Keng‐Boon

doi:10.1016/j.jretconser.2021.102851

Cited by 48 publications

(18 citation statements)

References 58 publications

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“…Additionally, PLS-SEM is also ideal for non-normal data. As the p -values for Mardia's multivariate skewness and kurtosis were less than 0.001, the use of PLS-SEM in this study is further justified (Ng et al. , 2022).…”

Section: Discussionmentioning

confidence: 84%

How to generate loyalty in mobile payment services? An integrative dual SEM-ANN analysis

Dang

Tan

et al. 2023

IJBM

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PurposeThe surging entrance of new mobile payment merchants into the growing market has prompted the need for an in-depth understanding of loyalty formation to retain customers. This study examines customers' loyalty generation process in mobile payment services by exploring the serial effect of cognitive drivers (i.e. brand awareness, perceived quality, brand image, perceived value and layout) on affective response, satisfaction and loyalty.Design/methodology/approachA survey using self-administered questionnaires was conducted. The data was collected from 370 consumers who have experience using mobile payment services in Vietnam. The data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural networks (ANN) analysis.FindingsThe results indicated that all the proposed cognitive drivers show significant impacts on affective response, which, in turn, translates into satisfaction and loyalty. The post-hoc analysis revealed enjoyment as the vital affective response in determining satisfaction. Moreover, the multigroup analysis indicated that the relationship between affective response and satisfaction is stronger for the female group. In addition, the ANN's nonlinear result revealed complementary insight into the importance of cognitive drivers.OriginalityThe current study revealed both linear and nonlinear mechanisms that explicate the roles of cognitive drivers and affective responses in fostering loyalty toward mobile payment merchants. The findings add to the existing literature that emphasizes consumers' initial mobile payment adoption.

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Section: Discussionmentioning

confidence: 84%

How to generate loyalty in mobile payment services? An integrative dual SEM-ANN analysis

Dang

Tan

et al. 2023

IJBM

Self Cite

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“…With reference to Table 7, the Q 2 values for AU, TS and SI are 0.207, 0.427 and 0.077 respectively. Given that the values are above 0, this indicates that the model exhibits predictive relevance (Chen and Li, 2020;Wang et al, 2022;Ng et al, 2022). In addition, the research model was able to account for 30.6%, 53.2% and 10.0% of the variance in AU, TS and SI respectively.…”

Section: Inner Structural Modelmentioning

confidence: 87%

“…Given that the values are above 0, this indicates that the model exhibits predictive relevance (Chen and Li, 2020; Wang et al. , 2022; Ng et al. , 2022).…”

Section: Discussionmentioning

confidence: 99%

Embracing mobile shopping: what matters most in the midst of a pandemic?

Loh

Lee

Tan

et al. 2022

IMDS

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PurposeThe COVID-19 pandemic has brought about significant changes to the lives of many people. One of which is the accelerated digitalization in the commerce sector. Hence, this study looks to determine the antecedents that affect users' mobile shopping actual use during a pandemic.Design/methodology/approachThe research model was founded on the integration of the Protection Motivation Theory and Transactional Theory of Stress. This is in addition to further extending the integrated research model with other constructs to develop a multi-dimensional framework that accounted for the health, personal, technological and social dimensions. The data was collected from users of mobile shopping through an online survey which was then analyzed via Partial Least Squares–Structural Equation Modeling.FindingsThis study provides empirical support to establish the major role of COVID-19 pandemic in affecting the actual usage of mobile shopping. Furthermore, the determinants of actual usage of mobile shopping were found to be multi-dimensional. In particular, the Importance-Performance Map Analysis revealed that emphasis should be place on perceived vulnerability.Originality/valueAs other studies focused on users' intentions, this study looked into the factors that influence the actual usage of mobile shopping. Furthermore, this study emphasizes on the contextualization of time and situation in addition to a multi-dimensional approach toward the subject matter. Overall, this study offers practical insights to stakeholders to better tailor their mobile shopping services in times of a pandemic and advances the literature on actual usage of mobile shopping.

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“…Based on the results from the ANN model we find that cyber aggression (CYA) is one of the most significant and important (86.93% normalized relative importance) predictors of users' mental and emotional well-being (MEW), followed by GMA (gamification addiction-56.63% normalized relative importance), PRI(privacy invasion-39.24% normalized relative importance), CYB (cyberbullying-28.98% normalized relative importance) and EXH (exhaustion-10.44% normalized relative importance) predictor of MEW (users mental and emotional well-being). The study followed the recommendation of Ng et al. (2022) to compare the results between PLS-SEM and ANN using path coefficient and normalized relative importance, respectively which deliver consistent results for both PLS-SEM and ANN modeling (See Table A10).…”

Section: Data Analysis Methodsmentioning

confidence: 96%

Examining the dark side of using gamification elements in online community engagement: an application of PLS-SEM and ANN modeling

Srivastava¹,

Bag

Rahman

et al. 2022

BIJ

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PurposeThe negative influence of gamification on online communities has received little attention in the available literature. The study examines the adverse effects of gamification during engaging in online communities.Design/methodology/approachGap-spotting methods were used to develop the research questions, followed by model development using the social exchange and social-network theories. Data were collected from 429 samples. The study applied partial least squares structural equation modeling to test the research hypotheses followed by ANN application.FindingsThe study identified five factors related to gamification that have a significant adverse effect on the mental and emotional well-being of the users. Furthermore, the results of PLS-SEM were then compared through an artificial neural network (ANN) analytic process, revealing consistency for the model. This research presents a theoretical contribution by providing critical insights into online gamers' mental and emotional health. It implies that gamification can even bring mental and emotional disturbance. The resulting situation might lead to undesirable social consequences.Practical implicationsThe result highlights the managerial and social relevance from the perspective of a developing country. As respondents are becoming more engrossed in online gaming, managers and decision-makers need to take preventive measures to overcome the dark side of online gaming.Originality/valueThe present study shows that the dark side of gamification has some adverse effects on human mental and emotional health. The study's findings can be used to improve gamification strategies while engaging online communities.

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Fashion shopping on the go: A Dual-stage predictive-analytics SEM-ANN analysis on usage behaviour, experience response and cross-category usage

Cited by 48 publications

References 58 publications

How to generate loyalty in mobile payment services? An integrative dual SEM-ANN analysis

How to generate loyalty in mobile payment services? An integrative dual SEM-ANN analysis

Embracing mobile shopping: what matters most in the midst of a pandemic?

Examining the dark side of using gamification elements in online community engagement: an application of PLS-SEM and ANN modeling

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