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9 result(s) for "Dang, Tri-Quan"
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How to generate loyalty in mobile payment services? An integrative dual SEM-ANN analysis
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.
Can you resist the virtual temptations? Unveiling impulsive buying in metaverse retail
PurposeThe main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.Design/methodology/approachGrounded in purposive sampling, 451 individuals with previous metaverse experience were recruited to accomplish the objectives of this research. Next, to identify both linear and nonlinear relationships, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) approaches.FindingsThe findings underscore the significance of the virtual store environment and online trust in shaping impulsive buying behaviors within the metaverse retailing setting. Theoretically, this study elucidates the impact of virtual store atmosphere and trust on impulsive buying within a metaverse retail setting.Practical implicationsFrom the findings of the study, because of the importance of virtual shop content, practitioners must address its role in impulse purchases via affective online trust. The study’s findings are likely to help retailers strategize and improve their virtual store presentations in the metaverse.Originality/valueThe discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.
Impulsive Buying and Compulsive Buying in Social Commerce: An Integrated Analysis using the Cognitive-Affective-Behavior Model and Theory of Consumption Values with PLS-SEM
The expansion of social commerce on a global scale has been remarkable, and this trend shows no symptoms of abating. Consequently, this market has witnessed an increase in the prevalence of impulsive purchasing. In this context, grounded in the Cognitive-Affective-Behavioral model and the theory of consumption value, the primary objective of this study is to investigate the antecedents of impulsive purchasing and determine whether impulsive purchasing tendencies are associated with the development of compulsive purchasing tendencies within the domain of social commerce. 366 participants whose nationality was Vietnamese and who had engaged in purchasing activities on social commerce platforms like Facebook, TikTok, and Instagram were included in the sample. A significant positive correlation was found between multidimensional perceived value, affective response, and impulsive and compulsive purchasing behaviors. These findings highlight the central role of perceived value in shaping users’ overall value perceptions in social commerce. Plain language summary Understanding impulsive and compulsive buying in social commerce The rapid growth of social commerce worldwide shows no signs of slowing down, and impulsive buying has become increasingly common in this market. This study explores what drives impulsive buying in social commerce and whether it can lead to compulsive shopping habits. We based our research on two key psychological models: the Cognitive-Affective-Behavioral model and the Theory of Consumption Value. To conduct the study, we surveyed 366 Vietnamese participants who had made purchases on social commerce platforms like Facebook, TikTok, and Instagram. Our findings revealed a strong link between perceived value, emotional responses, and impulsive as well as compulsive buying behaviors. These results suggest that how people perceive value plays a crucial role in shaping their shopping habits on social media platforms.
The future of non-contact commerce: the role of voice payments
Voice payment systems have emerged as a revolutionary mode of transaction, transforming the way individuals interact with financial services. By incorporating two additional factors (trust and perceived security) into the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, this study was conducted to address existing research gaps, specifically the dearth of studies on emerging payment methods in Vietnam. The purpose of this study is to investigate and analyze the factors influencing people’s intention to use voice payment, shedding light on the determinants shaping individuals' attitudes and behaviors in adopting this innovative payment method. A survey utilizing self-administered questionnaires was conducted, gathering data from 435 users experienced in using mobile payment services in Vietnam. The collected data underwent partial least square structural equation modeling (PLS-SEM). The findings indicate that performance expectancy (PE), social influence (SI), and trust (TR) positively impact both behavioral intention (BI) and voice payment adoption (VPA). This study contributes academically by introducing novel constructs to assess users' likelihood of embracing financial technology. In addition, the findings inform business executives and service providers regarding the expansion prospects that voice payment presents and aid them in comprehending the adoption of this technology. By offering recommendations, this research aids voice payment providers in enhancing the quality of their services and increasing customer satisfaction considering the findings.
A mixed methods analysis of palm payment adoption based on UTAUT2 and perceived trust
The emergence of palm payment systems signals a transformative shift in digital transaction. While widely adopted in developed countries, their presence in developing economies remains limited and under-researched. This study examines factors influencing the adoption intention of palm payment through the UTAUT2 framework, integrating perceived trust as a key determinant. Data from 413 respondents were analyzed mix methods (PLS-SEM, ANN, and fsQCA). Firstly, this study employs the PLS-SEM approach due to its suitability for small sample sizes and its robustness against violations of multivariate normality assumptions. However, a major limitation in prior research using single-method approaches, particularly PLS-SEM, is the inability to fully address measurement errors. This study overcomes this issue by integrating ANN and fsQCA to validate and complement PLS-SEM results. ANN helps mitigate measurement error concerns by identifying patterns beyond linear relationships, reducing reliance on strict parametric assumptions. Meanwhile, fsQCA provides a configurational perspective, testing how different combinations of factors lead to adoption, thereby compensating for potential biases in individual variable estimates. The combined use of methods strengthens result reliability by cross-verifying findings through distinct analytical lenses, reducing the risk of over-or underestimating effects due to measurement inconsistencies. Findings reveal that hedonic motivation, price value, habit, perceived trust, social influence, facilitating conditions, performance expectancy, and effort expectancy significantly drive adoption intention. Theoretically, this study extends UTAUT2 by revealing the role of biometric trust in contactless payments. Methodologically, it confirms the value of a mixed-methods approach. Practically, it offers insights for enhancing biometric payment adoption in emerging markets.
Blockchain Applications in Value Added Tax Refund: A Deep Learning-Based Dual-Stage SEM-ANN Analysis
This study examines the determinants of businesses' readiness to implement blockchain technology for value-added tax (VAT) refunds. This study enhances Technology Acceptance Model 2 (TAM2) by incorporating the concept of perceived risk into the framework. This study utilized a two-stage approach that integrated Partial Least Squares Structural Equation Modeling (PLS-SEM) with Artificial Neural Network (ANN) predictive analytics to test the proposed hypotheses. The ANN technique was employed to identify and analyze the potential nonlinear effects within the model. A total of 175 self-administered questionnaires were used for the analysis. The study found that a significant relationship between TAM2s' constructs and intention to use blockchain technology can markedly enhance the efficiency of VAT refund operations from a managerial standpoint. The theoretical implications of blockchain technology are substantial, as it introduces novel concepts of trust and accountability in tax interactions, disrupts traditional intermediaries, modifies the balance of information, and redefines contract enforcement.
Comprehensive Analysis of Mobile Payment's Customer Loyalty: The SEMANN Approach
This research aims to bridge this gap by employing the Expectation-Confirmation Theory to elucidate the underpinnings of customer loyalty in mobile payment. This study examines mobile payment customer loyalty using the Expectation- Confirmation theory and second-order constructs of perceived usefulness and perceived risk. The model was tested on 213 mobile payment users using a partial least square structural equation modeling-artificial neural network (PLS-SEM-ANN), capturing linear and nonlinear relationships. Mobile payment system adoption is more likely in people who can understand and analyze complex concepts like risk perception and perceived usefulness. ANN analyses show that confirmation and satisfaction are the most critical factors affecting satisfaction and continuance intention in mobile payment usage. An integrated model that accounts for 40.5% of customer loyalty variance examines feature-level perceived utility and risk to understand mobile payment better. The study ranks factors that sustain mobile payment usage, guiding executive decisions. Perceived usefulness, a secondorder construct, positively affects continuance intention in mobile payment loyalty. Notably, the study reveals loyalty drivers essential for developing nations' post-pandemic economic recovery. These findings help developing countries' mobile payment service providers and management increase usage and customer loyalty.
The Capability of E-reviews in Online Shopping. Integration of the PLS- SEM and ANN Method
Purpose: The aim of this study is to investigate the impact of e-review on iGen's propensity to purchase online. Especially, it can be better understood by dissecting the relationship among 3 variables of e-review (review valence, quantity of e-review and quality of e-review), e-satisfaction, and intention to buy.   Theoretical framework: This study classifies e-reviews according to their valence, quantity, and quality based on the study of Khammash (2008).   Design/methodology/approach: The PLS-SEM method was used to analyze data collected from online surveys administered to a sample of 222 iGen in Ho Chi Minh City to assess the hypotheses behind the study. Additionally, the Artificial Neural Network technique was used to separate SEM predictors that were relatively important.   Findings:  There are three results from the investigation: It has been found that (1) e-satisfaction is positively affected by valence, (2) e-satisfaction is generally increased with the high quality of e-review, but the quantity of e-review does not necessarily affect customers' e-satisfaction, and (3) e-satisfaction given in the context of an e-commerce platform has a strong effect on customers' online shopping intention. This study sheds new light on iGen's online buying habits and offers valuable management implications for iGen, online merchants, and e-commerce sites.   Research, Practical & Social implications:  E-reviews have become a significant factor in determining consumers' online purchase decisions. They also assist iGen in understanding how a qualified e-review—one that is clear, understandable, helpful, and has enough justification to support the opinions—will be advantageous for other consumers who wish to shop online.   Originality/value:  Provides the theory of e-review and its role in the online business environment. In addition, understand more about the behavior of igen, an age with a huge amount of spending on an online shopping platform.
THE CAPABILITY OF E-REVIEWS IN ONLINE SHOPPING. INTEGRATION OF THE PLSSEM AND ANN METHOD
Purpose: The aim of this study is to investigate the impact of e-review on iGen's propensity to purchase online. Especially, it can be better understood by dissecting the relationship among 3 variables of e-review (review valence, quantity of e-review and quality of e-review), e-satisfaction, and intention to buy. Theoretical framework: This study classifies e-reviews according to their valence, quantity, and quality based on the study of Khammash (2008). Design/methodology/approach: The PLS-SEM method was used to analyze data collected from online surveys administered to a sample of 222 iGen in Ho Chi Minh City to assess the hypotheses behind the study. Additionally, the Artificial Neural Network technique was used to separate SEM predictors that were relatively important. Findings: There are three results from the investigation: It has been found that (1) esatisfaction is positively affected by valence, (2) e-satisfaction is generally increased with the high quality of e-review, but the quantity of e-review does not necessarily affect customers' e-satisfaction, and (3) e-satisfaction given in the context of an ecommerce platform has a strong effect on customers' online shopping intention. This study sheds new light on iGen's online buying habits and offers valuable management implications for iGen, online merchants, and e-commerce sites. Research, Practical & Social implications: E-reviews have become a significant factor in determining consumers' online purchase decisions. They also assist iGen in understanding how a qualified e-review-one that is clear, understandable, helpful, and has enough justification to support the opinions-will be advantageous for other consumers who wish to shop online. Originality/value: Provides the theory of e-review and its role in the online business environment. In addition, understand more about the behavior of igen, an age with a huge amount of spending on an online shopping platform.