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This research aims to comprehend the factors that impact the emerging inclination of consumers toward mobile finance technology (fintech) services over banking institutions. The study focuses on users' demographics and psychographics to delineate their unique segments and profiles.

The study proposes a segmentation and profiling framework that includes variance analysis, two-step cluster analysis and pairwise statistical tests. This framework is applied to a dataset of customers using a range of mobile fintech services, specifically robo-investment, peer-to-peer (P2P) payments, robo-advisory and digital savings. The analysis creates distinct customer profile clusters, which are later validated using pairwise statistical tests based on segmentation output.

Empirical results reveal that P2P payment service users exhibit a higher frequency of usage, proficiency and intention to continue using the service compared to users of robo-investment or digital savings platforms. In contrast, individuals utilizing robo-advisory services are identified to have a significantly greater familiarity and intention to sustain engagement with the service compared to digital savings users.

The findings provide financial institutions, especially traditional banks with actionable insights into their customer base. This information enables them to identify specific customer needs and preferences, thereby allowing them to tailor products and services accordingly. Ultimately, this understanding may strategically position traditional banks to maintain competitiveness amidst the increasing prominence of fintech enterprises.

This research provides an in-depth examination of customer segments and profiles within the mobile fintech services sphere, thus giving a nuanced understanding of customer behavior and preferences and generating practical recommendations for banks and other financial institutions. This study thereby sets the stage for further research and paves the way for developing personalized products and services in the evolving fintech landscape.

This study aims to identify the role of consumer characteristics in cultural consumption tendencies. Additionally, the study examines whether country differences and prior experience in the country affect consumers' cultural consumption tendencies.

The effects of cosmopolitanism, consumer ethnocentrism, individual innovativeness, and lifestyle on cultural consumption tendencies were tested. Moreover, we assess whether country type and prior experience are differentiating factors for cultural consumption tendencies. To this end, two countries – the USA and South Korea, representing Western and Eastern cultures, respectively – were selected to achieve comparable results in two different cultures. The research data were collected from 775 people using an online survey method and analyzed using path analysis and an independent samples t-test.

Consumer characteristics affect cultural consumption tendencies. These effects are culture-specific and cultural product-specific. Cosmopolitanism has a positive impact on cultural consumption tendencies, while consumer ethnocentrism has a negative impact. Individual innovativeness and lifestyle partially affected cultural consumption tendencies. Notably, these effects differ by country type. However, cultural consumption tendencies do not differ according to consumers' prior experience.

This study provides insightful information for e-retailers to be mindful of global consumer characteristics. Accordingly, cultural consumption patterns can be used as the basis for market segmentation. In addition, understanding global consumer characteristics and their cultural product- and culture-specific effects on consumption will help cultural industry players in their segmentation and targeting decisions.

Notwithstanding the rich body of literature on cultural consumption, this study provides consumer-level comparative empirical research from a marketing perspective. Essentially, the study is novel as it reveals the consumer characteristics that affect cultural consumption tendencies.

The purpose of this paper is to explore the prospect of using neurophenomenology to understand, design and test phygital consumer experiences. It aims to clarify interpretivist approaches to consumer neuroscience, wherein theoretical models of individual phenomenology can be combined with modern neuroimaging techniques to detect and interpret the first-person accounts of phygital experiences.

The argument is conceptual in nature, building its position through synthesizing insights from phenomenology, phygital marketing, theoretical neuroscience and other related fields.

Ultimately, the paper presents the argument that interpretivist neuroscience in general, and neurophenomenology specifically, provides a valuable new perspective on phygital marketing experiences. In particular, we argue that the approach to studying first-personal experiences within the phygital domain can be significantly refined by adopting this perspective.

One of the primary goals of this paper is to stimulate a novel approach to interpretivist phygital research, and in doing so, provide a foundation by which the impact of phygital interventions can be empirically tested through neuroscience, and through which future research into this topic can be developed. As such, the success of such an approach is yet untested.

Phygital marketing is distinguished by its focus on the quality of subjective first-personal consumer experiences, but few papers to date have explored how neuroscience can be used as a tool for exploring these inner landscapes. This paper addresses this lacuna by providing a novel perspective on “interpretivist neuroscience” and proposes ways that current neuroscientific models can be used as a practical methodology for addressing these questions.

This study aimed to identify subgroups of esports players based on their gaming behavior patterns across game genres and compare self-efficacy, social efficacy, loneliness and three dimensions of quality of life between these subgroups.

324 participants were recruited from prolific academic to complete an online survey. We employed latent profile analysis (LPA) to identify subgroups of esports players based on their behavioral patterns across genres. Additionally, a one-way multivariate analysis of covariance (MANCOVA) was conducted to test the association between cluster memberships and development and well-being outcomes, controlling for age and gender as covariates.

LPA analysis identified five clusters (two single-genre gamer groups, two multigenre gamer groups and one all-genre gamer group). Univariate analyses indicated the significant effect of the clusters on social efficacy, psychological health and social health. Pairwise comparisons highlighted the salience of the physical enactment-plus-sport simulation genre group in these outcomes.

This study contributes to the understanding of the development and well-being benefits experienced by various esports consumers, as well as the role of specific gameplay in facilitating targeted outcomes among these consumer groups.

This study aims to empirically investigate the relationship between artificial intelligence (AI) in marketing (AIM) and business performance from the resource-based view (RBV) perspective.

A survey strategy was used in this study to collect data from 225 small and medium enterprises (SMEs) respondents who were on the registered list of the Ghana Enterprise Agency in the Eastern Region of Ghana. Structural equation modeling – path analysis was used to estimate the impact of AIM on the performance of SMEs.

The analyzed data shows that AIM has significant impact on the financial performance, customer performance, internal business process performance and learning and growth performance in the case of SMEs in Ghana. This study establishes the significance of AIM approach in achieving financial performance, customer performance, internal business process performance and learning and growth performance through the application of AIM determinants including, Internet of Things (IoT), collaborative decision-making systems (CDMS), virtual and augmented reality (VAR) and personalization.

Aside the aforementioned significance of this research study, this study has limitations. The sample size of this research study can be expanded to include SME respondents in other geographical areas that were not considered in this study. Future research studies should concentrate on how AIM can analyze customer communications and information such as posts on social media to develop future communications that may enhance customer engagement.

The practical implications comprise of two key items. First, this research study encourages SME owners and managers to develop an AIM method as a fundamental strategic goal in their pursuit to improve SME performance. Second, SME owners and managers should increasingly implement the four determinants of AIM indicated in this research study (i.e., IOT, CDMS, VAR and personalization) to develop essential resources for effective application of AIM to improve their performance.

The results of this study provide a strong support to RBV theory and the proposition that AIM and its determinants (i.e., IOT, CDMS, VAR and personalization) should be recognized as an essential strategic resource for improving the performance (i.e., financial performance, customer performance, internal business process performance and learning and growth performance) of SMEs. This study also contributes to the current body of knowledge on AIM and management, particularly in the context of an emerging economy.

The recent pandemic disrupted the way in which businesses transact with each other. In response to maintaining cleanliness in business-to-business (B2B) settings, artificial intelligence (AI)-enabled robots have been adopted as substitutes for cleaning personnel, yet their implications remain largely underexamined. This study aims to examine B2B buyer responses to cleaning information notices (human vs AI-enabled agent) placed at either the entry to the premises or the sales counter, thereby adding to the nascent literature in this line of inquiry.

Three field experiments were conducted across diverse B2B businesses (wholesalers in Studies 1–2 and a commercial business in Study 3). To achieve greater empirical rigor and generalizability, this research used diverse stimuli across different B2B settings. In addition, the results ruled out alternate explanations and shed light upon political ideology as a boundary condition. Finally, a single-paper meta-analysis confirmed H1, consolidating the established effect.

Featuring over 1,000 B2B buyers, the results show that politically liberal B2B buyers express greater preference for human over AI-performed cleaning while labor-orientated buyers are indifferent. Importantly, this effect is driven by greater relaxation associated with humans, which in turn, increases their future patronage and referral intent.

The results enrich the collective knowledge of the adoption of AI-enabled robots, reinforcing for marketing practitioners and businesses that the reliance on human-based outcomes remains a preferred touchpoint in B2B settings, particularly for liberals.

This paper aims to present a summary of the green consumer behaviour (GCB) research conducted during the 2001–2021 period using the bibliometric analysis and to carry out a thematic and content analysis on the three clusters which comprise 57 articles resulting from the co-citation analysis and identify the significant green purchasing factors.

The three-pronged methodology applied to this research analysis includes performance analysis of the literature using biblioshiny and R Studio; network mapping analysis using VOSviewer and Gephi; thematic analysis using word clouds generated with R Software and content analysis of each paper with the aid of within and between-study analyses.

Cluster one acted as a base for the theoretical foundations of GCB which aids in understanding the basic concepts of green marketing, its evolution and the methodologies, whereas cluster two determined the predictors of everyday green behaviour, which helps in gaining knowledge about the everyday sustainable activities the consumers indulge and the factors motivating to do so. Cluster three mainly focused on the psycho-socio demographic determinants of GCB, which assists in segmentation and predicting the purchase behaviour of the various consumer segments.

The significant variables and major gaps in each of the clusters were identified and authors have drawn the implications for future researchers and marketing managers.

The purpose of this study is to understand how consumers' green trust and green brand equity (GBE) vary by perceived brand greenness and age in the US market from the lens of brand knowledge (brand awareness and brand image).

Three multiple-group comparisons of structural equation modeling were used to analyze the data collected from a questionnaire. An experimental design was applied (high vs. low perceived brand greenness). A total of 440 usable responses were collected from an online consumer panel. With a higher percentage of participants older than 60 years, two groups were used, younger (under 55) and older (over 55), within each brand condition to conduct age comparisons.

Consumers' previous brand experience is important. The most promising indicators are brand image and green trust for GBE. A difference was observed between the group comparisons. For the less perceived green brand, existing brand image played a more important role in the process, and there is a need to enhance its green trust. For the higher perceived green brand, more factors should be included to explain their GBE, especially for consumers under 55.

This study identified two moderators, perceived brand greenness and age, in the formation of GBE, which has not been widely explored in the literature. The findings provide significant insights for generational cohorts, focusing for the first time on the joint catalyst effect of greenness and age regarding the influence of GBE on consumers' commitment to green brands. Additionally, the fact that a higher percentage of participants are Baby Boomers enables this study to add to the existing body of literature and bring unique perspectives to understand their and their younger counterparts' attitude toward green consumption.

This study is based on the heuristic-systematic model (HSM) to dynamically examine the effect of review variance on sales and the boundary conditions that mitigate this effect.

Based on the theoretical domain of HSM, a conceptual model is proposed that analyzes the nonlinear relationship between review variance and sales and the interaction and motivation factors that moderate these relationships. Review data from websites targeting the film industry in the USA and South Korea (Korea) were collected to empirically analyze the authors' hypothesis, and panel regression analysis was used for confirmation.

Moderated by interactive and motivational factors, review variance exhibits an inverse-U-shaped relationship with review variance. Specifically, as an interaction factor, review valence and owned social media (OSM) resulted in positive interaction effects, and as a motivation factor, the number of alternatives exhibited a positive interaction effect with review variance. The effect of review variance was less pronounced in the USA than in Korea.

The study outcomes reveal a nonlinear relationship between review variance and sales, thus supporting the contradictory findings of previous studies. This study contributes to the literature by using the HSM as a theoretical framework to verify various HSM mechanisms using online review data. This exploratory study also contributes to the international marketing literature by showing that the effects of review variance vary across cultures.

This paper aims to classify tourist accommodation using data from Booking.com and TripAdvisor and analyse the extent to which the different segments identified differ in terms of being adults-only.

In total, 1,535 properties located in nine Spanish sun and beach destinations were examined using a latent class cluster analysis (LCCA). The bias-adjusted three-step approach was used to investigate the differences between belonging to adults-only accommodation or not among the identified clusters.

Results show that adults-only accommodation tends to belong to the cluster with higher online ratings. In small Spanish islands, adults-only hotels account for a large share (more than 25%) of hotels.

It was not possible to analyse whether the higher rating was due to the accommodation being better or due to the tourists being more satisfied with their stay.

In urban destinations, the model is not widely used. However, in coastal destinations, it is becoming more than a novelty or a new trend.

In small Spanish islands, people traveling with children are becoming a minority. Families may feel discriminated against and express dissatisfaction with this situation in the future.

This study covers the gap in the academic literature on this growing hotel segment.