Search results

The 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.

A 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.

The 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.

The 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.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.

Consumers nowadays are no longer bystanders in the process of production but are proactive collaborators with the power to co-create value with brands. This study aims to explore the impact of social commerce on the co-creation process of brand value in a social commerce setting.

A questionnaire survey was conducted online to gather 300 eligible responses. The data were empirically validated using the partial least squares structural equation modelling (PLS-SEM) method.

The results indicated that brand engagement (BEN) is vital to brand co-creation (BCC) in social commerce, which could be driven by social-hedonic value (SHV) and social information sharing (SIS).

This study stresses the influence of consumer autonomy in the process of BCC by probing the role of SIS. Moreover, by considering the prevailing trend in social media, this study offers a nuanced perspective on the values of social commerce from the viewpoint of SHV.

This study may serve as a useful guide for practitioners to improve their digital outreach strategy on social commerce to forge stronger relationships, encourage further engagements and promote value co-creation within their brand community.

This examines the effect of relationship quality (RQU) and BEN on BCC through a relational viewpoint.

The main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.

Grounded 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.

The 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.

From 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.

The discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.

The 2019 coronavirus disease (COVID-19) pandemic has profoundly affected family and school life. Evidence demonstrates how pandemic-induced online learning and home confinement can influence family dynamics and, consequently, students’ mental health and quality of life. This chapter extends the literature by building upon the perspective of family systems theory and focusing the analysis on graduate students who are underrepresented in COVID-19 research. Drawing from an online survey among 337 graduate students enrolled in a state university in the Philippines during the second year of the pandemic, this study examines the three family relationship domains (cohesion, expressiveness, and conflict), their predictive relationships with life satisfaction, and the mediating role of mental well-being on these relationships. Findings indicate favorable levels of cohesion, expressiveness, and conflict in the family. Respondents’ age, sex assigned at birth, and marital status were significantly correlated with at least one domain of family relationship. Cohesion and expressiveness yielded significant positive predictive relationships on mental well-being and life satisfaction. Furthermore, findings indicate the partial mediation of mental well-being on the relationship between cohesion and life satisfaction and full mediation on expressiveness and life satisfaction.

Health disparities affecting lesbian, gay, bisexual, transgender and queer (LGBTQ) populations have been reported in many countries. For Singapore, no large quantitative studies on mental health and well-being in the local LGBTQ community have been published. The authors conducted a community-based survey (National LGBT Census Singapore, 2013; NLCS2013) that covered a comprehensive set of demographic, social and health indicators. Here, the authors investigated mental health status and its correlates in 2,350 LGBTQ individuals within the NLCS2013 sample.

The NLCS2013 was an anonymous online survey conducted amongst self-identified LGBTQ adults (aged ≥ 21 years) residing in Singapore. The survey included the World Health Organisation Well-being Index (WHO-5) as a measure of mental well-being, with low WHO 5 scores (<13/25) indicating poor mental well-being. The authors analysed relationships between low WHO-5 score and a range of respondent characteristics using multivariate logistic regression.

Strikingly, 40.9% of 2,350 respondents analysed had low WHO-5 scores, indicating poor mental well-being. Parental non-acceptance, experience of conflict at home and bullying/discrimination in the workplace or educational environments were all significantly associated with poor mental well-being. Conversely, community participation appeared protective for mental well-being, as respondents who participated in LGBTQ community organisations or events were less likely to have poor mental well-being than non-participants.

The NLCS2013 represents one of the first broad-based efforts to comprehensively and quantitatively capture the sociodemographic and health profile, including mental health status, within Singapore’s resident LGBTQ population. These findings affirm the need to address the mental health needs of LGBTQ individuals in Singapore and to foster safe spaces and allyship.

Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.

The aim of the study is to determine the benefits of transforming a destination into smart destination (SD) to restart tourism after the COVID-19 outbreak, to match the dimensions of SD with restarting strategies, and to make conceptual inferences to serve this. For this purpose, two reports published by the World Tourism Organization (WTO) in 2020 were examined: Priorities for Tourism Recovery and Global Guidelines to Restart Tourism. Then, the contents of these reports and the dimensions of SDs were matched and a guiding model for tourism decision-makers was developed.

Augmented reality (AR) has emerged as a new interactive technology, swiftly transforming the field of marketing. Driven by its rapid uptake in marketing practices, academic research on AR has proliferated. This study aims to offer a holistic view of the past, present and future of augmented reality marketing (ARM) scholarship by analyzing its current and evolving research profile as well as its social and conceptual structures to inspire further research.

This study enriches the ARM scholarship by integrating a quantitative bibliometric analysis with a chronological-thematic review and a qualitative content analysis to develop a more comprehensive understanding of this novel area and suggest future research courses.

The bibliometric analysis reveals the key performance indicators as well as the social and conceptual structure of the ARM research field. The chronological-thematic review exhibits the advancement of ARM research over time and forecasts the emerging trends for the domain. Finally, the content analysis of recent articles reveals the current research hotspots and provides future research directions.

The database limits the selection of literature, as the information in databases such as Scopus is updated regularly, resulting in alterations in the number of articles and citations.

AR developers and brand managers may use this study’s findings to understand the current ARM landscape better and make strategic decisions based on AR adoption and consumption patterns.

This study is singular in using a mixed methods approach by integrating the findings from bibliometric and content analyses for more reliable results and to offer a holistic perspective of the ARM sector, thereby significantly advancing the field of technology-led marketing.