Search Results (271)

International shopping is a significant motive for outbound travel; however, evidence on the experiential drivers of luxury travel retail among Chinese luxury travelers remains limited. This study investigates the factors shaping overseas shopping experiences and assesses the adequacy of the luxury customer experience (LCX) framework in this episodic, time-constrained, cross-border context. A quantitative survey of Chinese luxury travelers (N = 407) was conducted and analyzed using IBM SPSS Statistics (Version [30.0], Mac) within the LCX framework. The results show that modern artistic visual merchandising positively predicts overall experience evaluation (β = 0.162, p < 0.001), and emotional connection significantly predicts repurchase intention (β = 0.197, p < 0.001). We find that overall experience evaluation and subsequent behavioral responses are shaped by specific drivers, including service-related post-purchase factors, emotional fulfillment and brand trust, visual appeal, and affective/cognitive evaluations. These results point to possible gaps in theory when LCX is used in short-term travel retail contexts. To address these gaps, we propose the transient experience, relationship quality, action outcomes, connection, and engagement (TRACE) conceptual framework for analyzing feedback-driven encounters throughout the travel experience. Overall, this study extends LCX to episodic, time-constrained contexts and introduces TRACE as a conceptual complementary model to guide future theory testing and model validation in luxury travel retail contexts. Full article

This study investigates online community marketing as a strategy to cultivate brand–consumer-relationship sustainability. Blind boxes have recently gained worldwide popularity but are increasingly criticized for sustainability concerns. While previous research mainly assumes cooperation among members, we highlight cooperative and competitive emotional interactions in building a sustainable online community. Integrating the conditioned-expectancy theory of vicarious emotion with social comparison theory, we propose a dual emotional mechanism consisting of brand love and brand jealousy to reflect cooperative and competitive emotions. This study obtained 601 valid responses from online communities of blind boxes. The results show that online community marketing is positively related to purchase intention. Although they are paradoxical, brand love and brand jealousy coexist, and both mediate the abovementioned relationship. We also find a serial mediation through brand love and jealousy and then engagement. In post hoc analysis, we further find a curvilinear mediation via brand love, which accelerates the emotional engagement in community marketing, while brand jealousy maintains a linear position. This study provides new insights on sustainable community marketing and suggests practical implications for innovative marketing approaches. Full article

Environmentally friendly packaging has become a widely adopted food retail strategy, yet its impacts on consumer food perceptions (e.g., healthiness, taste, ethical concerns) remain fragmented. Notably, how it shapes healthiness perceptions is understudied. Across three studies, this study demonstrates that consumers often associate eco-friendly packaging with healthiness perception, driven by the heuristic associations of its original-ecology sensory cues, sustainable connotations, and morality signals, which further contribute to purchase intention. In addition, the effect of packaging eco-friendliness on purchase intention is moderated by environmental consciousness and food type. Specifically, the above positive effect of eco-friendly packaging is more prominent for consumers with higher environmental consciousness, and for hedonic (vs. utilitarian) food. The findings advance understanding of how eco-friendly packaging shapes food perceptions, and offer strategic insights for customized packaging design in food marketing. Full article

This study explains repeat purchase intentions on e-commerce platforms as a problem of fit between what the interface signals (Customer Service Orientation, CSO) and what the system delivers (Internal Service Quality, ISQ). Using survey data from Chinese platform users (N = 605), second-order polynomial models with response-surface analysis (RSA) show that repurchase intention rises when CSO and ISQ increase together, exhibits diminishing returns at high joint levels, and declines as the two diverge. A structural equation model (SEM) provides cross-sectional evidence consistent with mediation via pride in membership; when CSO and ISQ are modeled jointly with pride, CSO shows the larger direct association with repurchase. We also find that trust and security awareness initiatives act as a structural assurance that flattens the CSO–ISQ surface, attenuating both slopes and curvatures. Taken together, the results advance a fit-based account of digital service in which outcomes depend on the alignment of interface signals with executional capability and operate through identity-based pride, with platform-level assurances bounding marginal returns. Managerially, the findings imply prioritizing the closure of CSO–ISQ gaps and reducing execution variance before pursuing further single-dimension upgrades. Full article

The transition to electric mobility requires salespeople to go beyond technical expertise and develop advanced social–cognitive skills that shape consumer decision-making. This study examines how empathy, perspective-taking, and trust influence interactions between salespeople and potential buyers of electric vehicles (EVs). Through a systematic literature review and bibliometric analysis, we identify the key cognitive and emotional competencies that enable sales professionals to interpret customer intentions, manage uncertainty, and guide rational yet emotionally influenced purchase decisions. Findings suggest that successful EV sales rely on understanding consumer beliefs about sustainability, risk, and technology, as well as on the salesperson’s ability to align messages with these cognitive frames. Based on this analysis, we propose a competency development framework that emphasizes empathy-driven communication, adaptive reasoning, and the integration of social cognition into training strategies. This perspective contributes to the broader understanding of how social–cognitive processes affect human judgment and decision-making in the emerging electric vehicle market. Full article

Consumer digital hoarding is becoming increasingly common in agricultural live social e-commerce, where the abundance of product information, seasonal promotions, and origin-based narratives make consumers more inclined to accumulate digital content such as product links, coupons, and live-stream screenshots. This phenomenon not only affects consumers’ digital mental health, consumption behavior, and decision-making ability, but also poses challenges to agricultural merchants and platforms in terms of customer conversion, precision marketing, and supply chain management. Drawing on the SOR model and integrating construal level theory, this paper constructs a research framework to analyze the key factors influencing consumers’ willingness to digitally hoard in the context of agricultural live social e-commerce. Based on a questionnaire survey of 322 consumers, and using the Ordered Probit (O-Probit) model, the empirical results show that emotional interaction significantly influences digital hoarding intention through the chain mediating effects of emotional attachment and fear of missing out (FOMO). Furthermore, social distance and immersion serve as boundary conditions in this mechanism. Our findings not only deepen the understanding of consumer digital hoarding behavior in agricultural live e-commerce, but also provide new insights for agricultural merchants and platforms to better design interaction strategies, balance consumers’ digital accumulation with actual purchasing conversion, and enhance the efficiency of agricultural product marketing. Full article

Previous survey research has documented that consumers place value on socially responsible firms. This support includes the intention to be more loyal to these firms and also the willingness to pay higher prices for their products. Our study connects the customer intentions documented in survey research with actual measures of financial performance from published financial statements. The study uses gross profits scaled by total assets as a proxy for customers’ willingness to pay higher prices and sales increases as a proxy for loyalty. Additionally, the study examines differences in the aforementioned measures between customers in the business-to-business (B2B) and business-to-consumer (B2C) segments. These differences have been documented in studies that suggest customers in these segments value different characteristics of suppliers when making their purchases. Finally, customers must be made aware of a firm’s sustainability practices; therefore, the study looks at three different approaches firms use to communicate the quality of their sustainability practices. These approaches include external assurance of the social responsibility report, the auditor’s review of the firm’s internal controls, and the firm’s advertising intensity. Data used in this study includes financial performance measures of North American firms and corporate social responsibility data from disclosures collected by the Global Reporting Initiative. Using ordinary least squares, the results suggest that customers require some sort of assurance of a company’s socially responsible disclosures when making decisions about whether to support the company. Full article

In an era where digital ecosystems transcend national boundaries, TikTok has emerged as a globally influential platform, reshaping international marketing strategies. This study examines the factors influencing Thai consumers’ purchase intention on TikTok using the Stimulus–Organism–Response framework. Specifically, it explores how advertisement characteristics (interactivity, entertainment, informativeness) and customer brand engagement shape consumer perceptions of value and trust, which drive purchase intention. Data were collected from 400 Thai TikTok users and analyzed using structural equation modeling. The findings reveal that interactivity, informativeness, and brand engagement significantly affect perceived value, while brand engagement does not significantly influence brand trust. Moreover, perceived value contributes positively to trust, and brand trust significantly influences purchase intention. Notably, entertainment did not significantly influence perceived value, whereas brand engagement showed a meaningful positive effect. Additionally, customer brand engagement did not affect trust significantly in this context. This study focuses on a high-engagement digital platform within an emerging market and, thus, provides fresh insights into how digital advertising stimuli operate within international marketing ecosystems. The theoretical and managerial implications are discussed for global marketers aiming to optimize content strategies on dynamic platforms such as TikTok. Full article

Integrating recommendation systems with dynamic pricing strategies is essential for enhancing product sales and optimizing revenue in modern business. This study proposes a novel product recommendation model that uses Reinforcement Learning to tailor pricing strategies to customer purchase intentions. While traditional recommendation systems focus on identifying products customers prefer, they often neglect the critical factor of pricing. To improve effectiveness and increase conversion, it is crucial to personalize product prices according to the customer’s willingness to pay (WTP). Businesses often use fixed-budget promotions to boost sales, emphasizing the importance of strategic pricing. Designing intelligent promotions requires recommending products aligned with customer preferences and setting prices reflecting their WTP, thus increasing the likelihood of purchase. This research advances existing recommendation systems by integrating dynamic pricing into the system’s output, offering a significant innovation in business practice. However, this integration introduces technical complexities, which are addressed through a Markov Decision Process (MDP) framework and solved using Reinforcement Learning. Empirical evaluation using the Dunnhumby dataset shows promising results. Due to the lack of direct comparisons between combined product recommendation and pricing models, the outputs were simplified into two categories: purchase and non-purchase. This approach revealed significant improvements over comparable methods, demonstrating the model’s efficacy. Full article

Due to the highly perishable nature of fresh products, consumers often worry about product quality, which significantly dampens their purchase intentions. To address this and boost consumers’ willingness to pay, many fresh foods enterprises resort to sales manipulation tactics as a way to attract customers and gain a competitive edge. To further explore whether such yields net benefits to competing firms and the fresh product market, this research develops a game model involving two competing members selling fresh products. The model analyzes how sales manipulation affects the product prices, market shares, and profits of both firms across four scenarios. Finally, numerical analysis supports the robustness of findings and provides insights for establishing management guidelines for fresh product enterprises and the market. Full article

This study conceptualizes how artificial intelligence (AI)-based customer engagement strategies can shape consumers’ green purchasing intentions, focusing on the theorized roles of attitude and perceived risk toward green products as articulated in prior literature. Building on contemporary research in sustainable marketing and consumer psychology, the article proposes a conceptual framework in which AI-enabled engagement influences green purchase intention via attitudes, with perceived risk operating as a boundary condition that moderates these effects. To qualitatively substantiate the salience and practical relevance of these constructs, an exploratory sentiment analysis of Amazon reviews for green products was conducted to surface emotional responses, perceived value drivers, and behavioral cues. The review corpus predominantly reflects positive sentiment alongside mixed subjectivity and factual commentary, highlighting recurring decision factors such as product quality, packaging, sustainability claims, and price sensitivity. Consistent with literature, the evidence aligns with the view that personalization and transparency can bolster trust and more favorable attitudes, while perceived risks—spanning greenwashing concerns, cost, and performance doubts—remain obstacles to adoption. Crucially, the sentiment analysis is presented as illustrative and does not statistically test the proposed mediation or moderation pathways; rather, it offers qualitative support that complements the literature-based conceptual model. The study contributes by integrating insights from digital technologies, consumer psychology, and sustainable marketing to guide authentic, strategic engagement practices that can encourage eco-conscious behavior. Full article

Using platform self-operation, customer reviews, and compensation commitments as traditional benchmarks, this study foregrounds blockchain traceability as a technology-enabled authenticity signal in cross-border cosmetic e-commerce (CBEC). Using an 8-scenario orthogonal experiment, we test a model in which perceived risk mediates the effects of authenticity signals on purchase intention. We probe blockchain boundary conditions by examining their interactions with traditional signals. Our results show that blockchain is the only signal with a significant direct effect on purchase intention and that it also exerts an indirect effect by reducing perceived risk. While customer reviews show no consistent effect, self-operation and compensation influence purchase intention indirectly via risk reduction. Moderation tests indicate that blockchain is most effective in low-trust settings—i.e., when self-operation, reviews, or compensation safeguards are absent or weak—while this marginal impact declines when such safeguards are strong. These findings refine signaling theory by distinguishing a technology-backed signal from institutional and social signals and by positioning perceived risk as the central mechanism in CBEC cosmetics. Managerially speaking, blockchain should serve as the anchor signal in high-risk contexts and as a reinforcing signal where traditional assurances already exist. Future work should extend to field/transactional data and additional signals (e.g., brand reputation, third-party certifications). Full article

Augmented reality (AR) technologies—such as Instagram filters—bridge the digital and physical worlds by allowing users to virtually try on clothing, thereby reducing the risk of virus transmission. In the T-shirt retail industry, AR enables product personalization, decreases the need for physical production, minimizes textile waste, and lowers carbon emissions. It also benefits individuals with limited mobility or those who prefer shopping online. This study tested several hypotheses on 105 active Instagram filter users using filters from the ’Apprecio’ account on mobile devices. Data analyzed using the partial least squares method revealed that interactivity significantly influences both purchase intention and continued use of digital platforms. While hedonic and vivid features enhance the user experience, they have a limited impact on driving purchases or long-term engagement. Customers’ engagement and buying intent are more strongly shaped by practical and interactive elements. The study recommends that companies invest in developing interactive AR features to boost customer satisfaction and foster trust. Future research should involve larger participant samples and investigate specific interactive elements—such as virtual try-on tools—to better understand their impact on consumer behavior. This study highlights the critical role of interactivity in AR for delivering meaningful and engaging shopping experiences. Full article

The quantification of emotional value and accurate prediction of purchase intention has emerged as a critical interdisciplinary challenge in the evolving emotional economy. Focusing on Generation Z (born 1995–2009), this study proposes a hybrid algorithmic framework integrating text-based sentiment computation, feature selection, and random forest modeling to forecast purchase intention for therapeutic toys and interpret its underlying drivers. First, 856 customer reviews were scraped from Jellycat’s official website and subjected to polarity classification using a fine-tuned RoBERTa-wwm-ext model (F1 = 0.92), with generated sentiment scores and high-frequency keywords mapped as interpretable features. Next, Boruta–SHAP feature selection was applied to 35 structured variables from 336 survey records, retaining 17 significant predictors. The core module employed a RF (random forest) model to estimate continuous “purchase intention” scores, achieving R² = 0.83 and MSE = 0.14 under 10-fold cross-validation. To enhance interpretability, RF model was also utilized to evaluate feature importance, quantifying each feature’s contribution to the model outputs, revealing Social Ostracism (β = 0.307) and Task Overload (β = 0.207) as dominant predictors. Finally, k-means clustering with gap statistics segmented consumers based on emotional relevance, value rationality, and interest level, with model performance compared across clusters. Experimental results demonstrate that our integrated predictive model achieves a balance between forecasting accuracy and decision interpretability in emotional value computation, offering actionable insights for targeted product development and precision marketing in the therapeutic goods sector. Full article

This research proposes an adaptation of the quality–loyalty model in which affective commitment is integrated as a key factor in the proposed framework. The study presented a comprehensive framework encompassing 11 hypotheses formulated from an extensive literature review. Empirical data collected from 679 environmentally conscious consumers predominantly residing in Vietnam’s three principal urban centers were employed to evaluate these hypotheses. The assessment was executed utilizing the partial least squares structural equation modeling technique. The results of this research authenticate the appropriateness of the integrated model in studying green consumption, verify the critical role of affective commitment in the newly introduced model, and identify the high impact of affective commitment on green loyalty intention and green purchase behavior. This research also shows that other factors of the quality–loyalty model have significant influences on affective commitment and green loyalty intention. Moreover, this study signifies the crucial role of green perceived quality in fostering affective commitment and green loyalty intention. Green perceived quality was identified as a key factor influencing green loyalty intention and played a crucial role in encouraging customers to purchase environmentally friendly products. Full article