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All presidential and legislative candidates want to be the winner. However, they do not know the determinants of voters' reasons for making choices. This study aims to investigate the role of education level, political party brand reputation, religiosity brand personality and e-WOM on voters' decisions with implications for voters' loyalty.

The survey method was used to collect data from 1206 respondents who have the right to vote through offline and online using Google forms shared on social media platforms—data analysis using Structural Equation Modeling using the SmartPLS 4.0 program.

The results showed that Brand Reputation of Politics can encourage brand Religious Personality and e-WOM. Brand Religious Personality is a factor that causes the decision to vote. However, the level of education is not a determining factor for Brand Religious Personality and e-WOM. In addition, brand religious personality, e-WOM and Decision to vote can mediate Brand Reputation of Political loyalty.

The findings from this study can help political parties and candidates develop strategies tailored to voters' needs and increase their chances of winning elections.

The novelty in this study is the development of a model that has never been tested before that uses factor sources from marketing science literacy such as Brand, e-WOM and Loyalty. This study also used moderation variables namely choosing decisions, e-WOM, and religious brand personality. The object of this research was conducted in Indonesia, which is included in the list of developing countries but has never been done in any country. The analysis tool uses the new SEM-PLS version 4.0, so it has a level of novelty and implications that are important for political marketing.

The purpose of this paper is to explore the effect of the image of country of origin (COO) and word of mouth (WOM) toward brand equity (BE).

Questionnaire was deployed to collect data. Prior to data collection, validity, and reliability tests were performed. Valid and reliable questionnaire was distributed to car customer in Jabodetabek region. It was succeeded to distribute 389 questionnaires and completely filled up by respondents. Structural equation modeling further was deployed to analyze the data.

COO and WOM significantly influence BE indirectly thorough BE dimensions. WOM exhibited stronger influence toward BE. The influence of COO and WOM toward BE dimension was also investigated. WOM showed stronger influence toward BE dimension, in descending order are brand loyalty (BL), brand association (BAS), perceived quality (PQ), and brand awareness (BA). COO showed weaker influence and different order, in descending order are BA, PQ, BL, and BAS.

Role of WOM in marketing has been extensively discussed by researchers. It is generally acknowledged playing a considerable role in influencing and forming consumer attitudes and behavioral intentions. However, up to this date role of WOM on BE has not been explicitly studied by researchers. COO in another hand has been related to BE although in a limited references. Those studies were performed outside of Indonesian consumer. Up to this date study of COO of Indonesian consumer behavior remains unaccounted.

Brand image remains a “nebulous” construct with very few frameworks dedicated to understanding the process of uncovering brand image. This is supported by explicit calls for greater clarity on how to examine brand image, particularly in different settings. Political branding is one setting that has received some attention, however, research has focused on “party” political brands and neglected “non-party” brands (independent candidates). Therefore, this study aims to examine how young citizens interpret independent non-party brands through the theoretical lens of brand image in the context of Guernsey and develop a systematic brand image framework that provides greater clarity to this topic area.

A qualitative interpretivist approach using focus group discussions was adopted to investigate the phenomenon from the perspective of young voters 18–24 years of age. Focus group discussions ceased upon reaching theoretical saturation and a six-staged thematic analytical strategy was adopted to analyse the findings.

This study revealed deep insight into the political brand image of non-party brands from the perspective of young voters in an under-explored context. More specifically, this study uncovered that Guernsey’s political brands were seen as “accessible”; however, there was little differentiation, identification and connection between young voters and politicians. Further, this study uncovered a series of opportunities for strategists such as the desire for a younger generational view and younger representation in the Guernsey Parliament and greater clarity, distinction and authenticity related to political brand image.

This study addresses explicit calls for further research on brand image with a distinct focus on non-party political brands. Further, this study concludes by presenting the “consumer brand image schema”; a systematic framework which can be used to uncover brand image within and beyond the setting of politics. Further, the framework operationalises the complex concept of brand image and provides a three-stage process to examine and develop brand image. This will enable strategists to develop targeted strategies and adopt appropriate tactics to manage brand image to ensure brands are differentiated and interpreted as authentic, relatable, engaging, accessible and identifiable.

To enhance the fit, comfort and overall satisfaction of lower body attire for online shoppers, this study introduces a reclassification method of the lower body profiles of young females in complex environments, which is used in the framework of remote clothing mass customization.

Frontal and lateral photographs were collected from 170 females prior, marked as size M. Employing a salient object detection algorithm suitable for complex backgrounds, precise segmentation of body profiles was achieved while refining the performance through transfer learning techniques. Subsequently, a skeletal detection algorithm was employed to delineate distinct human regions, from which 21 pivotal dimensional metrics were derived. These metrics underwent clustering procedures, thus establishing a systematic framework for categorizing the lower body shapes of young females. Building upon this foundation, a methodology for the body type combination across different body parts was proposed. This approach incorporated a frequency-based filtering mechanism to regulate the enumeration of body type combinations. The automated identification of body types was executed through a support vector machine (SVM) model, achieving an average accuracy exceeding 95% for each defined type.

Young females prior to being marked as the same lower garment size can be further subdivided based on their lower body types. Participants' torso types were classified into barrel-shaped, hip-convex and fat-accumulation types. Leg profile shapes were categorized into slender-elongated and short-stocky types. The frontal straightness of participants’ legs was classified as X-shaped, I-shaped and O-shaped types, while the leg side straightness was categorized based on the knee hyperextended degree. The number of combinations can be controlled based on the frequency of occurrence of combinations of different body types.

This methodological advancement serves as a robust cornerstone for optimizing clothing sizing and enabling remote clothing mass customization in E-commerce, providing assistance for body type database and clothing size database management as well as strategies for establishing a comprehensive remote customization supply chain and on-demand production model.

The advancement of artificial intelligence (AI) has brought intelligent online shopping experiences to customers. AI-powered retail platforms deliver personalized shopping experiences through tailored recommendations, promotions and assistance. Given the increasing preference for online shopping, it is crucial to explore methods to optimize the adoption of AI-powered retail platforms. To address this, this study aims to examine the impact of technology readiness motivators (optimism and innovativeness) and inhibitors (discomfort and insecurity) on perceived trust, perceived usefulness and purchase intention toward AI-powered retail platforms.

Data were collected from 276 customers in Egypt, primarily from the millennial and Gen Z demographic segments. The collected data were then analyzed using the statistical package for social sciences (SPSS) and partial least squares structural equation modeling (PLS-SEM).

The findings revealed that optimism, innovativeness and discomfort significantly influence perceived trust, while optimism, insecurity and perceived trust significantly influence perceived usefulness. Both perceived trust and usefulness are significant predictors of purchase intention. Perceived trust mediates the effects of technology readiness motivators on perceived usefulness and purchase intention. Moreover, perceived usefulness mediates the effects of technology readiness motivators, insecurity and perceived trust on purchase intention.

To date, there are few investigations regarding the acceptance and adoption of AI-powered retail platforms in developing countries. Thus, this study offers valuable theoretical and practical implications in the context of smart retail technology adoption.

This study aims to examine the role of various Instagram contents on customer behavior. The studied case is associated with herbal teas sold on active Instagram pages.

A structured questionnaire is exploited to collect data from customers. The integration of two entropy weight methods and weighted sum method are used to evaluate the priority of contents. In addition, model development is illustrated through which Instagram broadcasting tools are prioritized benefiting from fuzzy cognitive map method.

The results illustrate that customer behavior is moderated by content types, which empirically enhances the profitability of the business. The results of this study reveal that educational live, show other ones experience at live as well as motivational lives are the most effective contents. This study is a pioneering one to practically assess the construct of social media engagement through the effects of content types on the Instagram platform.

The effects of various contents, including motivational content, other customers’ experiences, products, educational content and purchase bill, on customer behavior are studied.

This study addresses the information asymmetry issue in e-commerce, particularly prevalent in the clothing industry, leading to high product returns and environmental harm. The research aims to fill gaps in the existing literature by holistically examining multiple information cues and considering intercultural differences, utilizing signaling theory.

An Adaptive Choice-Based Conjoint experiment involving German (n = 332) and Chinese (n = 331) respondents from Generation Y is conducted. This cross-cultural comparison explores consumer preferences for sustainable clothing and analyses factors influencing their choices, including price, shipping costs, sustainability labels and online customer reviews.

German online shoppers exhibit a stronger preference for sustainable clothing compared to their Chinese counterparts, with notable differences in the emphasis placed on various factors. Chinese respondents prioritize monetary aspects (e.g. price and shipping costs), while Germans attach greater importance to sustainability labels and online customer reviews.

This research contributes to the existing literature by providing a comprehensive analysis of information cues in e-commerce, considering cultural variations. The findings shed light on the distinct preferences of German and Chinese respondents from Generation Y, offering valuable insights for businesses aiming to address information asymmetry and enhance environmental sustainability in online clothing retail.

This study examines the psychological factors that directly influence individuals’ intentions to book or arrange reservations through resort hotel websites within the context of the Unified Theory of Acceptance and Use of Technology (UTAUT). Specifically, this study focused on identifying and understanding the key drivers of online purchase intentions, including performance expectancy, effort expectancy, social influence and facilitating conditions within the UTAUT model.

This study used the UTAUT as a theoretical framework. A quantitative research approach was adopted and data were collected through surveys using a five-point Likert scale. The sample consisted of 270 participants, selected through purposive sampling. Data analysis was performed using Smart PLS software.

The results indicate that performance and effort expectancy significantly influence online purchase intentions. However, social influence did not significantly affect online purchase intention. By contrast, facilitating conditions significantly and positively influence online purchase intention.

These findings have practical implications for hotel managers and marketers. Emphasizing performance, effort expectations and facilitating conditions can improve customer perceptions of website usefulness and directly increase their intention to book. The limited impact of social influence suggests the need to focus less on social recommendations or endorsements in online marketing efforts and prioritize individual factors and objective information.

This study contributes to the field of technology and tourism by examining the psychological factors that directly influence users’ intention to purchase from resort hotel websites. This extends the understanding of online purchase intentions in the context of resort tourism and highlights the importance of facilitating conditions. This study also partially confirms the applicability of the UTAUT model in this domain and provides insights for future research on online purchase intentions in resort tourism.

This paper aims to investigate to what extent sustainable and nonsustainable attributes can be used to characterize different clusters of consumers in an emerging market, where economic conditions can increase the relevance of price. Consumers seem reluctant to engage frequently in pro-sustainable behavior, mainly for financial reasons. However, purchasing decisions can be understood as a multidimensional process.

The authors conducted quantitative and descriptive research employing a choice-based conjoint/hierarchical Bayes (CBC/HB) experiment in malls in a low-income city in northeast Brazil with 1,287 potential buyers of denim jeans. The conjoint analysis therefore collected data on preferences in the course of actual decision-making. The authors then took the individual part-utility from each respondent and ran a cluster analysis to identify similar groups in the sample. The classification and regression tree (CART) method was used to determine the relationship between the conjoint attributes and the sociodemographic characteristics.

The data demonstrate that buying decisions constitute a complex process of interplay between many different factors, often involving trade-offs between a wide variety of nonsustainable and sustainable attributes. The survey confirmed that price is still of paramount importance when it comes to consumer choices. The authors also found that sustainable attributes played a relatively more significant role than brand or origin of production. The authors identify notable differences between groups of consumers in the “pro-sustainable” and “non-pro-sustainable” clusters and different levels of importance regarding the sociodemographic characteristics.

Although price emerged as the most significant attribute, the research also demonstrates that there is a market in Brazil for products and practices based on a genuine commitment to the natural environment and social issues. The findings suggest that marketing managers and policymakers should consider different combinations of concerns over sustainability with product attributes and include sociodemographic variables rather than considering the textile market as uniform or thinking that there is no space for sustainability in fashion.