Search Results (383)

Digital food-ordering apps make it simple to buy indulgent drinks yet hard to judge their health risks. We conducted five online experiments (N = 1048) to compare two messages for sugary beverages: self-promotion that stresses taste and self-disclosure that plainly warns “high sugar/high calories”. Brands that chose self-disclosure were seen as more socially responsible and transparent, which in turn raised trust and lifted purchase intent. These gains were strongest for users who care deeply about the category or the brand and remained robust even among highly health-conscious shoppers. The results show that, for “vice” foods, honest warnings can outperform glossy claims. Our study extends signaling and attribution theories to digital food markets and offers managers a straightforward playbook for complying with new labeling rules while still driving sales. Full article

Energy-efficient consumption has become a strategic priority to mitigate global climate change and enhance national energy security. While social media has reshaped online consumption behavior, the mechanisms through which these digital platforms influence energy-efficient purchasing remain underexplored. This study extends the Theory of Planned Behavior (TPB) by integrating price perception variables and applies multi-group structural equation modeling to examine how social media shapes Chinese consumers’ intentions to purchase energy-efficient air conditioning. The results show that (1) social media exposure strengthens energy-efficient purchasing intentions indirectly via behavioral attitude, subjective norm, and perceived behavioral control; (2) price perception is negatively associated with purchase intention; and (3) these effects vary by age cohort, gender, and income—Generation Z and female consumers are more susceptible to social media influence, while low-income groups exhibit heightened price sensitivity. These findings advance TPB theory and offer guidance for digital platform policies aimed at promoting energy-efficient consumption. Full article

Driven by digital technology, live streaming business is becoming increasingly common worldwide. Unlike traditional online shopping, live streaming commerce integrates real-time interaction, social communication, and e-commerce. It also eliminates the limitations of one-way information transmission and promotes purchasing behavior by conveying signals such as products, brands, and the personal charm of live streamers to consumers through real-time communication. The core issues explored in this study are whether the cues between the signal transmitters and receivers are consistent and how they affect consumers’ purchasing behavior. In this study, the consistency of the signal is measured by five dimensions, namely self–product fit, live streamer–product fit, live content–product fit, danmaku content–product fit, and self–live streamer fit. In order to study this problem, we constructed a structural equation modeling (SEM) model. In the causal relationship between signal consistency and purchase intention, performance responses have also been discussed as mediating variables. Accordingly, signal consistency enables consumers to perceive performance expectancy, whereby consumers believe that products that perform well positively influence satisfaction. To verify these hypotheses, 443 randomly collected valid questionnaires were used in empirical analyses. The results showed that most of our hypotheses were validated, aside from the relationship between self–live streamer fit and perceived performance expectancy. The findings suggest that signal consistency cues such as live streamer–product fit, live content–product fit, danmaku content–product fit, and self–product fit positively influence consumers’ perceived performance expectancy and satisfaction, which in turn promote purchase intention. These findings not only enrich the application of signaling theory in the field of live streaming commerce but also expand consumer behavior theory. Moreover, they also inspire practitioners in live streaming commerce by helping them to improve live streaming sales and bolster their market competitiveness through signal display optimization, content planning, and precision marketing. Full article

This paper explores the role of artificial intelligence (AI) in personalizing social media marketing strategies and its impact on customer experience, with a focus on consumers within the MENA region. Using data collected from an online questionnaire completed by 893 individuals, the study confirms that AI significantly enhances social media marketing by offering personalized content, optimizing influencer selection, and enabling real-time consumer interaction. These capabilities not only increase customer awareness but also improve user experience and purchase intentions. Key AI tools such as influencer marketing, content optimization, and customization are effective in capturing consumer attention, although further research is necessary to deepen understanding. By examining AI’s ability to analyze vast datasets and support targeted marketing efforts, the study contributes to both academic and practical discourse, offering insights that businesses can use to refine their AI-driven social media strategies. Ultimately, the research aims to guide marketers through the complexities of AI deployment, ensuring its benefits are fully realized for consumers. Full article

Digital franchising is increasingly recognized as a technological advancement and a specialized subset of e-commerce, yet its unique entrepreneurial dynamics remain insufficiently explored in the existing literature. Previous studies have primarily focused on platform usability or general e-commerce adoption, often overlooking the motivational, contextual, and capability-based factors that influence individuals’ willingness to engage in digital franchising as either entrepreneurs or consumers. To address this research gap, the present study applies the Motivation-Opportunity-Ability (MOA) framework to examine how personal motivations (e.g., self-expression, financial rewards), perceived platform opportunities (e.g., support, attractiveness), and individual capabilities (e.g., digital literacy, self-efficacy) shape entrepreneurial intention and, in turn, influence consumption adoption intention in digital franchising environments. An online survey was conducted using a non-probability purposive sampling method. The final sample consisted of 491 respondents from Taiwan, all of whom were either entrepreneurs operating digital franchises in the fashion industry or consumers who had purchased fashion products through digital franchising platforms, thereby ensuring contextual relevance to the study’s focus. Data were analyzed using structural equation modeling (SEM). The results indicate that expected external rewards (β = 0.456, p < 0.001) and platform support (β = 0.315, p < 0.001) are the most influential factors in shaping entrepreneurial intention. Furthermore, entrepreneurial intention significantly mediates the relationship between MOA antecedents and consumption adoption intention (β = 0.176, p < 0.001), highlighting its role as a key behavioral mechanism. These findings extend the MOA framework to a new empirical setting and offer practical implications for platform developers, franchisors, and policymakers seeking to promote participation in digital franchising. Future research is encouraged to explore cross-industry comparisons, generational differences, and longitudinal approaches to further enrich the understanding of digital franchising adoption dynamics. Full article

This study aims to investigate consumers’ preferences for inland and coastal seafood in the context of e-commerce, along with the underlying neural and psychological mechanisms influencing their online purchase decisions. By integrating questionnaire surveys with event-related potentials (ERPs), this research explores both behavioral patterns and neural responses associated with seafood choices. The survey results indicate that consumers have significantly higher purchase intentions for coastal seafood compared to inland seafood, which is consistent with the findings from behavioral experiment. Furthermore, the ERP data reveal that, compared to the inland seafood condition, the coastal seafood condition elicited lower N200 and N400 amplitudes, suggesting reduced cognitive conflict and semantic incongruence processing. Moreover, the higher LPP amplitude reflects greater emotional arousal. Based on cognitive dissonance theory, the study highlights the psychological conflicts and perceived risks related to inland seafood, providing neuroscientific insights into consumer decision making. These findings can support the optimization of market strategies for inland seafood in the growing e-commerce sector. Full article

This study investigates how social media exposure shapes young adults’ attitudes and intentions toward sustainable products in Kuwait—a high-income, oil-dependent context undergoing a digital and cultural shift. Integrating the Theory of Planned Behavior (TPB) and the Elaboration Likelihood Model (ELM), the research explores the mediating roles of environmental responsibility, social influence, and consumer attitudes in the formation of sustainable purchase intentions. Data were collected via an online survey of 702 respondents aged 18–30 and analyzed using structural equation modeling (SEM). The findings reveal that social media usage significantly influences sustainable purchase intention, social influence, and consumer attitudes. Environmental responsibility emerges as a key driver of both attitudinal and normative pathways. Notably, the study finds no direct link between consumer attitude and intention, highlighting a persistent attitude–behavior gap. The results offer theoretical insights into digital persuasion and normative influence while providing practical guidance for marketers and policymakers promoting sustainability in digitally connected, non-Western societies. Full article

The growing use of Instagram and its influencers in marketing demonstrates their substantial influence on customer behavior intentions. Despite this, further research into the effects of Instagram mega-influencers on purchase intention is needed among Generation Z (born between 1997 and 2012) consumers. The main aim of the study was to assess the influence of attractiveness, expertise, perceived ease of use, and perceived usefulness on intention to purchase due to Instagram mega-influencers among Generation Z in South Africa. This study combined purposive and snowball non-probability sampling methods using a quantitative approach. An online questionnaire was used to assess the effect of Instagram mega-influencers on young consumers’ purchase intention, which resulted in 497 Generation Z respondents. Positive associations were found between attractiveness, expertise, perceived ease of use, and perceived usefulness on intention to purchase. Perceived ease of use was also found to mediate the positive effects of attractiveness and expertise on intention to purchase. This analysis provides businesses with practical information about the use of Instagram mega-influencers in digital marketing to connect with Generation Z consumers and improve profitability. The research contributes to the theoretical development of constructs in the technology acceptance and source credibility models and generation cohort theory. Full article

Generation Z is emerging as a powerful force in shaping global consumer behavior, particularly in the market of digital and technological products. This study examines how specific branding dimensions, such as online brand experience, engagement, image, trust, loyalty, awareness, behavioral intention, and brand knowledge, influence Gen Z’s purchase intention, emphasizing sustainable consumption. Sustainable consumption, in this context, refers to the preference for tech products that minimize the environmental impact through eco-friendly design, energy efficiency, and responsible sourcing. Using a quantitative approach, this cross-sectional research explores the effects of online brand experience, engagement, image, trust, loyalty, awareness, behavioral intention, and knowledge on purchasing newly launched technological products that align with sustainability. Data were collected from a Gen Z sample using a combination of convenience and systematic sampling, and multiple regression analysis identified the most significant predictors of purchase intention. The results indicate that online brand experience, brand image, brand trust, and brand loyalty play the most crucial roles, having a greater effects on Gen Z’s purchase intention, while brand awareness and knowledge also contribute. However, brand engagement and behavioral intention have weaker effects. These findings suggest that brands targeting Gen Z should prioritize building a strong, trustworthy, and engaging online presence while highlighting their sustainability efforts, and when Gen Z consumers have favorable digital interactions with a brand, perceive its image positively, trust it, and feel loyal to it, they are more likely to consider purchasing its sustainable offerings. This study enhances the understanding of Gen Z’s consumer behavior and offers insights for businesses seeking to foster sustainable consumption by highlighting the importance of developing marketing strategies that strengthen online brand experience, cultivate trust and loyalty, and clearly communicate sustainability values, such as through engaging digital content, transparent messaging, and eco-conscious branding, to effectively foster sustainable consumption among this environmentally conscious and digitally driven generation. Full article

As the online shopping user base continues to grow rapidly, livestream e-commerce has emerged as a pivotal commercial phenomenon. However, consumers’ impulse purchase intentions in this environment are influenced by numerous interrelated factors, and the underlying mechanisms remain complex. To address the limitations of traditional approaches in modeling nonlinear relationships and hierarchical structures, this study introduces an integrated DEMATEL-AISM approach tailored for the livestream e-commerce context. The $\lambda$-intercept method is applied to simplify the system structure and highlight key influencing factors. Based on prior literature, we designed and distributed structured questionnaires to 558 consumers and industry experts, followed by in-depth interviews with five domain experts. Through this process, an indicator system was developed encompassing 15 factors across three dimensions: product, consumer, and livestream room. Using DEMATEL-AISM, we conducted a causal analysis of these factors. The results reveal that: (1) discount intensity, livestream promotional frameworks, and time pressure are the three most critical factors influencing impulse purchase intentions; (2) product monetary value and design features act as fundamental drivers; and (3) consumer upward and downward anticipated regret, perceived product quality, perceived product scarcity, and perceived streamer’s product knowledge have direct impacts on impulse purchase. By identifying these key factors and revealing their interconnections, this study offers strategic, evidence-based recommendations for enhancing consumer engagement and profitability in livestream e-commerce. The proposed DEMATEL-AISM also provides a novel and effective methodological contribution for analyzing the complex influencing factors of impulse purchase intentions in the e-commerce environment. Full article

(1) Live streaming commerce has refined online consumer engagement by fostering a real-time, socially enriched shopping environment. Despite its growing prominence, the role of social scene characteristics in consumer purchase decisions in live streaming remains insufficiently examined. (2) This study uses the Cognition-Affection-Conation (C-A-C) framework to examine how these social characteristics influence purchase intention through the mediating roles of emotional and cognitive trust, with privacy concerns as a moderator factor. The research employs Structural Equation Modeling (SEM) to test the hypothesis using data from 504 valid responses. (3) The results demonstrate that the characteristics of social scenes proposed in this study enhance consumer trust and positively impact purchase intention. Moreover, privacy concerns weaken the effect of interactivity atmosphere and scene immersion on emotion trust, though they do not weaken the effect of social identity on emotion trust. (4) These findings contribute to the theoretical understanding of live commerce by identifying the psychological mechanisms linking the social service scene to purchasing behavior. They also offer practical implications for platforms and merchants seeking to improve consumer engagement and trust in competitive digital marketplaces. This research highlights the importance of integrating social scenes and privacy management into the strategic design of live streaming commerce services. Full article

With the rapid development of metaverse technology in the marketing field, it has become increasingly important to understand consumer purchase intentions for AI Brand Endorsers (AIBEs) within this digital environment. Based on cognitive–affective–behavioral (CAB) theory, this study constructs a new theoretical framework to explore the key factors influencing consumer purchase intentions for AIBE-recommended products in the context of the metaverse. We conducted an online survey with 302 Generation MZ consumers who have purchasing experience, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) for in-depth data analysis and model evaluation. Additionally, we performed Multi-Group Analysis (MGA) to reveal differences among various occupations and generations. The findings indicate that attractiveness (ATT), anthropomorphism (ANT), and interactivity (INT) significantly influence hedonic motivation (HM) and social presence (SP). Furthermore, authenticity (AUT) positively affects both SP and trust in AIBEs (TAI). Consumer purchase intention (PI) is significantly impacted by SP but is not directly influenced by HM and TAI. Notably, technology readiness (optimism and innovativeness) positively and significantly influences consumer PI but does not alter the potential moderating effects of HM, SP, and TAI. This study not only broadens and deepens the application of CAB theory but also elucidates the potential development of AIBEs in future metaverse research, providing practical implications and guidance for marketers to enhance consumer purchase intentions and boost product sales. Full article

The ever-expanding market has made organic food a popular research topic, with the primary question being what factors facilitate or hinder consumers in making an organic purchase. The most relevant studies have been conducted in an offline context. As selling organic food online has become a common practice and is underresearched, this study aims to (1) explore the drivers and barriers of online organic food shopping and (2) investigate the shopping behavior of organic food from an omnichannel perspective. The results of partial least square structural equation modeling (PLS-SEM), with 278 valid samples, indicate that trust in organic labels and positive review sentiment significantly contribute to the intention to purchase organic food online, which in turn influences online purchase behaviors. For online shopping behavior, the investigation shows that Taiwanese consumers, on a monthly basis, make an average of 3.22 organic food purchases and spend US$156.44 through offline channels, whereas they make 2.34 purchases of organic food and spend US$114.71 via online channels. Organic vegetables and fruits are the most frequently purchased organic foods. Among online channels, consumers prefer visiting the websites of general grocery stores and specialty stores over social media platforms. Our findings suggest that the determinants of organic food shopping differ between offline and online contexts and reveal interesting behavioral patterns of online organic shopping. Full article

The present study investigates the association between perceived authenticity (PAU), GCON, and behavioral intention within heritage restaurants in Hail, Saudi Arabia. By integrating cognitive appraisal theory (CAT) and the Stimulus-Organism-Response (SOR) framework, this research explores how authenticity perceptions influence both cultural and gastronomic experiences and contribute to sustainable consumption behavior. Also, it investigates the moderating role of consumer knowledge (CKNOW) in enhancing GCON and its subsequent impact on the behavioral intention (BINT) to dine at heritage restaurants. Employing a mixed-methods approach, this study first conducted a content analysis on online reviews to identify key attributes that shape authenticity perceptions. Subsequently, Smart PLS software was employed to conduct an analysis of 417 valid customers of heritage restaurants in Hail. The current study aims to investigate the customers of heritage restaurants in Hail, Saudi Arabia. The current findings showed that students formed a significant market share of heritage restaurants in Hail, Saudi Arabia. The findings confirm that perceived authenticity significantly enhances consumers’ cultural and gastronomic experiences, which in turn fosters GCON and strengthens the behavioral intention to visit authentic restaurants. Furthermore, GCON mediates the association between authenticity, cultural experiences, and purchase intention. Consumer knowledge further moderates this relationship, amplifying the positive effect of GCON on behavioral intention. This study contributes to the growing literature on sustainable gastronomy tourism by demonstrating the crucial interplay between authenticity, sustainability, and consumer knowledge in the heritage restaurant sector. It also offers practical recommendations for restaurant managers, policymakers, and tourism marketers to enhance the authentic dining experience while promoting environmentally responsible behavior. By fostering an awareness of cultural and environmental values, heritage restaurants can serve a critical role in advancing sustainable tourism development in Hail and beyond. Full article

The main objective of this study was to investigate European consumers’ intentions to purchase cosmetics and detergents with green ingredients made from recycled CO₂. Aiming to better understand both moral and practical criteria of consumers’ intentions, a combination of the Values-Beliefs-Norms and the Theory of Planned Behaviour models served as the basis of this study’s theoretical framework. The combination was extended with risk perception about global warming, scepticism and media influence. Online interviews were conducted with stratified samples based on gender and age distributions in France, Germany, Greece and Spain. Structural equation modelling and moderation analyses were employed to analyse the data. The results indicated that consumption intentions are generated by consumers’ biospheric values and a sequence of risk perception, awareness of consequences, and ascription of responsibility while they are directly determined (in declining order) by perceived behavioural control, personal norms, attitudes and subjective norms. Subjective norms indicated additional indirect impacts on consumption intentions through personal norms and ascription of responsibility. Moderation also indicated that the relationship between perceived behavioural control and consumption intentions is stronger in consumers, who are less sceptical towards ecological claims on packaging, while the relationship between personal norms and consumption intentions is stronger in consumers, who are less influenced by advertisements. Theoretical, managerial and social implications were derived from the results. Full article