Search Results (6,843)

Against the backdrop of the rapid proliferation of electric vehicles (EVs), gender-oriented behavioral mechanisms remain underexplored, particularly the unique pathways of female users in usage experience, value assessment, and purchase decision-making. This study constructs an integrated framework based on the Stimulus–Organism–Response (SOR) model, leveraging social media big data to analyze in depth how gender differences influence EV users’ purchase intentions. By integrating natural language processing techniques, grounded theory coding, and structural equation modeling (SEM), this study models and analyzes 272,083 pieces of user-generated content (UGC) from Chinese social media platforms, identifying key functional and emotional factors shaping female users’ perceptions and attitudes. The results reveal that esthetic value, safety, and intelligent features more strongly drive emotional responses among female users’ decisions through functional cognition, with gender significantly moderating the pathways from perceived attributes to emotional resonance and cognitive evaluation. This study further confirms the dual mediating roles of functional cognition and emotional experience and identifies a masking (suppression) effect for the ‘intelligent perception’ variable. Methodologically, it develops a novel hybrid paradigm that integrates data-driven semantic mining with psychological behavioral modeling, enhancing the ecological validity of consumer behavior research. Practically, the findings provide empirical support for gender-sensitive EV product design, personalized marketing strategies, and community-based service innovations, while also discussing research limitations and proposing future directions for cross-cultural validation and multimodal analysis. Full article

Short-form video platforms have shifted advertising from standalone, time-bounded spots to feed-embedded, swipeable stimuli, creating a high-velocity processing context that can penalize casting complexity. We ask whether a “one face, many roles” casting strategy (a single actor playing multiple characters) outperforms multi-actor executions, and why. A two-phase pretest (N = 3500) calibrated a realistic ceiling for “multi-actor” casts, then four experiments (total N = 4513) tested mechanisms, boundary conditions, and alternatives. Study 1 (online and offline replications) shows that single-actor ads lower cognitive load and boost account evaluations and purchase intention. Study 2, a field experiment, demonstrates that Need for Closure amplifies these gains via reduced cognitive load. Study 3 documents brand-type congruence: one actor performs better for entertaining/exciting brands, whereas multi-actor suits professional/competence-oriented brands. Study 4 rules out cost-frugality and sympathy using a budget cue and a sequential alternative path (perceived cost constraint → sympathy). Across studies, a chain mediation holds: single-actor casting reduces cognitive load, which elevates brand authenticity and increases purchase intention; a simple mediation links cognitive load to account evaluations. Effects are robust across settings and participant gender. We theorize short-form advertising as a context-embedded persuasion episode that connects information-processing efficiency to authenticity inferences, and we derive practical guidance for talent selection and script design in short-form campaigns. Full article

Impulsive purchasing behavior among university students has gained increased attention in the context of digital consumption settings; however, much of the existing research is product-specific and quantitative, leaving the subjective nuances of this phenomenon underexplored. This study investigates how college students perceive and explain their impulsive purchase behavior across various product categories and platforms, using qualitative data from focus groups (n = 72). By revealing the prevalence of key patterns—interest-aligned, emotional relief, hedonistic lifestyle, social influence, inquisitive reviewer, presentation appeal, and controlled purchase—this research uncovers the underlying identity-affirming practices, internal emotional negotiations, and external sociotechnical cues that shape such behavior. Ultimately, it reframes impulsive buying as a socially embedded, identity-driven act rather than an act of irrationality. These findings advance our understanding of consumer psychology by emphasizing the lived experiences and self-construction processes of young consumers navigating media-saturated, algorithmically curated purchasing environments. Full article

Existing research on live-streaming e-commerce consumption behavior is mostly limited by a single disciplinary framework, unable to systematically parse the mechanism of macro-policies and cultural values on intergenerational consumer psychology. This study takes ASEAN cross-border live-streaming e-commerce as a scenario, integrates theories of economics, political science, and sociology, and constructs an innovative three-layer analysis model of “macroeconomic system–meso-market–micro-behavior” based on multi-source data from 2020 to 2024. It empirically explores the formation mechanism of intergenerational differences in impulse buying. The results show that the behavior differences of different groups are significantly driven by income gradient, cross-border policies (tariff adjustment and consumer protection regulations), and collectivism/individualism cultural orientations. The innovative contribution of this study is reflected in three aspects: Firstly, it breaks through the limitation of a single discipline, and for the first time, it incorporates structural variables such as policy synergy effect and family structure change into the theoretical framework of impulse buying, quantifying and revealing the differentiated impact of institutional heterogeneity in ASEAN markets on intergenerational behavior. Secondly, it reconstructs the transmission path of “cultural values–family structure–intergenerational behavior” and finds that the inhibitory effect of collectivism on impulse buying tends to weaken with age. Thirdly, it proposes a “policy instrument–generational response” matching model and verifies the heterogeneous impact of the same policy (such as tariff reduction) on different generations. This study fills the gaps in related research and can provide empirical support for ASEAN enterprises to formulate stratified marketing strategies and for policymakers to optimize cross-border e-commerce regulation. which is of great significance to promote the sustainable development of the regional live-broadcast e-commerce ecology. Full article

Aiming at the problems of high-dimensional nonlinear constraints, multi-objective conflicts, and low solution efficiency in microgrid optimal scheduling, this paper proposes a multi-objective Harris Hawk–Grey Wolf hybrid intelligent algorithm (IMOHHOGWO). The problem of balancing the global exploration and local exploitation of the algorithm is solved by introducing an adaptive energy factor and a nonlinear convergence factor; in terms of the algorithm’s exploration scope, the stochastic raid strategy of Harris Hawk optimization (HHO) is used to generate diversified solutions to expand the search scope, and constraints such as the energy storage SOC and DG outflow are finely tuned through the α/β/δ wolf bootstrapping of the Grey Wolf Optimizer (GWO). It is combined with a simulated annealing perturbation strategy to enhance the adaptability of complex constraints and local search accuracy, at the same time considering various constraints such as power generation, energy storage, power sales, and power purchase. We establish the microgrid multi-objective operation cost and carbon emission cost objective function, and through the simulation examples, we verify and determine that the IMOHHOGWO hybrid intelligent algorithm is better than the other three algorithms in terms of both convergence speed and convergence accuracy. According to the results of the multi-objective test function analysis, its performance is superior to the other four algorithms. The IMOHHOGWO hybrid intelligent algorithm reduces the grid operation cost and carbon emissions in the microgrid optimal scheduling model and is more suitable for the microgrid multi-objective model, which provides a feasible reference for future integrated microgrid optimal scheduling. Full article

As Generation Z increasingly dominates the consumer market, understanding their purchasing behaviour in online marketplaces has become crucial for businesses aiming to engage this digitally native and environmentally conscious demographic. The present study aims to explore Generation Z′s purchasing behaviour in e-commerce platforms through the lens of the Technology Acceptance Model (TAM), while incorporating additional factors such as sustainability and environmental awareness. A partial least squares structural equation modelling (PLS-SEM) analysis using WarpPLS 8.0 was conducted on a sample of 636 Generation Z respondents from Romania. The results suggest that online marketplaces can enhance consumer engagement by integrating eco-friendly practices and emphasizing sustainable product offerings. This research contributes to the e-commerce literature by extending the TAM framework and by providing valuable insights for businesses targeting environmentally conscious digital consumers. Full article

With the widespread integration of Artificial Intelligence-Generated Content (AIGC) into e-commerce platforms, understanding how users perceive, evaluate, and respond to such content has become a critical issue for both academia and industry. This study examines the influence mechanism of AIGC Content Quality (AIGCQ) on users’ Purchase Intention (PI) by constructing a cognitive model centered on Trust (TR) and Perceived Risk (PR). Additionally, it introduces two moderating variables—Ethical Concern (EC) and Perceived Platform Responsibility (PLR)—to explore higher-order psychological influences. The research variables were identified through a systematic literature review and expert interviews, followed by structural equation modeling based on data collected from 507 e-commerce users. The results indicate that AIGCQ significantly reduces users’ PR and enhances TR, while PR negatively and TR positively influence PI, validating the fundamental dual-pathway structure. However, the moderating effects reveal unexpected complexities: PLR simultaneously amplifies both the negative effect of PR and the positive effect of TR on PI, presenting a “dual amplification” pattern; meanwhile, EC weakens the strength of both pathways, manifesting a “dual attenuation” effect. These findings highlight the nonlinear cognitive mechanisms underlying users’ acceptance of AIGC, suggesting that PLR and EC influence decision-making in more intricate ways than previously anticipated. By uncovering the unanticipated patterns in moderation, this study extends the boundary conditions of the trust–risk theoretical framework within AIGC contexts. In practical terms, it reveals that PLR acts as a “double-edged sword,” providing more nuanced guidance for platform governance of AI-generated content, including responsibility frameworks and ethical labeling strategies. Full article

Electric vehicle (EV) adoption is a critical step toward achieving sustainable transportation and reducing carbon emissions, especially in regions like Saudi Arabia that are undergoing rapid urban development and energy diversification. However, the widespread adoption of EVs is hindered by a variety of interrelated economic, infrastructural, and policy-related factors. This study aims to systematically identify and structure these influencing factors using Interpretive Structural Modeling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis. Based on a thorough literature review and expert consultation, 17 key factors affecting EV adoption in Saudi Arabia were identified. The ISM results reveal that purchase price, long-term savings, resale value, urban planning, and accessibility are among the most influential drivers of adoption. The MICMAC analysis complements these insights by categorizing the variables based on their driving and dependence power. The developed hierarchical model provides insights into the complex interdependencies among these factors and offers a strategic framework to support policymakers and stakeholders in accelerating EV uptake. The study contributes to a deeper understanding of the dynamics influencing EV adoption in emerging markets. Full article

In response to the rising demand for sustainable transportation, electric vehicles (EVs) are increasingly regarded as viable alternatives to conventional vehicles. This study investigates the intention of Malaysian consumers to choose EVs as their preferred mode of transportation. Consumption values were conceptualized as a multi-dimensional construct comprising functional value, symbolic value, emotional value, novelty value, and conditional value. This study examines the relationships between these consumption values, consumer attitudes, and intention to purchase EVs. In addition, this study also examines the mediating role of attitude and the moderating role of infrastructure readiness. Data were gathered using a proportionate stratified sampling method from 264 respondents in Klang Valley, Malaysia. Of the twelve (12) hypotheses tested, four (4) were supported. The analysis indicates positive relationship between attitude and emotional value with consumers’ intention to purchase EVs. Consumers’ attitudes mediate the relationship between functional value, emotional value, and intention to purchase EVs. Infrastructure readiness does not moderate the relationship between consumers’ attitudes towards EVs and their purchase intentions. This study enhances the existing knowledge of consumers’ multifaceted value views about EVs and offers practical guidance for marketers and serves as a reference for policymakers to improve the marketability of EVs. Full article

This multidisciplinary comparative study investigates consumption patterns, health-related properties, and quality attributes of trademarked and local extra virgin olive oil (EVOO) samples. It highlights the importance of localization in promoting agricultural sustainability, strengthening regional economies, and enhancing socio-economic impacts within EVOO production and consumption systems. In terms of quality characteristics, significant differences were observed in color parameters (L*, a*, b*, Chroma, Hue angle) among EVOO samples (p < 0.05). Regarding nutritional and functional properties, total phenolic content (TPC) measured with the Folin–Ciocalteu method ranged from 58.15 to 176.29 mg of gallic acid equivalents/kg of oil, while total antioxidant capacity (TAC) measured by CUPRAC and DPPH assays varied between 3.42 and 6.54 and 8.56–10.71 µmol of Trolox equivalents/g of oil, respectively. TPC and TAC were also evaluated for their stability during in vitro gastro-intestinal digestion, demonstrating that EVOO’s bioactive potential remains stable under gastric and intestinal conditions. Local samples exhibited significantly higher TACs than trademarked products across undigested, gastric, and intestinal phases (p < 0.05). Concurrently, a face-to-face consumer survey assessed purchasing behaviors and preferences, revealing that 71.3% of consumers preferred local EVOO and showed a low tendency to purchase commercial brands (p < 0.05). Cooperatives were identified as the main distribution channel, playing a crucial role in sustaining local production systems. This study offers valuable insights into EVOO’s bioactive content and consumer behavior, providing a foundation for developing both localized and commercial products that support health outcomes. Additionally, the findings contribute to policy development concerning sustainable food systems and geographical indications. Full article

Background and Objective: Prostate cancer (PC) is the most common cancer among males in the Western World. Androgens are key growth regulators both in normal and malignant prostate growth. Several new types of androgen pathway inhibitors (ARPIs) have been developed for the treatment of PC. Despite the lack of evidence, sequential use of ARPIs has been adopted into everyday clinical practice. This study aimed to assess real-life ARPI use patterns, especially sequential use and treatment costs, in Finland. Methods: Nationwide register data on all ARPI (enzalutamide, apalutamide, darolutamide, abiraterone) purchases recorded in the National Health Insurance scheme register maintained by the Social Insurance Institution of Finland from January 2012 to December 2023 were used. The data included patient demographics and medicine purchase details, which were descriptively analysed. Results: During the study period, 8369 patients initiated ARPIs. The median age of the users was 75.1 years. Of these, 32.1% (n = 2685) used at least two ARPIs sequentially. The proportion of treatment initiations leading to sequential use increased from 36% in 2012 to 56% in 2017, then decreased to 14% in 2022. The total cost of sequential use was €43.8 million. Limitations include the unrecorded phase of PC. The study’s strength is its inclusion of all reimbursed ARPI purchases nationwide. Conclusions: Despite the lack of evidence, sequential ARPI use was initially prevalent but declined after the introduction of new guidelines. Randomised trials are needed to guide the sequential use of these medicines. Patient summary: Androgen pathway inhibitors (ARPIs) are widely used in prostate cancer in Finland. One-third of patients use at least two ARPIs sequentially to inhibit testosterone effect. However, there are no large clinical trials published demonstrating the benefits of sequential treatment. More evidence is needed to justify sequential use. Full article

Amid rising sustainability demands, the automotive industry must understand how its Environmental, Social, and Governance (ESG) management influences consumer purchase decisions for high-involvement products. This study investigates this relationship by examining the mediating roles of brand value, perceived quality, and corporate trust. To test the research model, we analyzed survey data from Korean automotive market consumers using partial least-squares structural equation modeling. The findings reveal that governance transparency and social responsibility significantly enhance corporate trust and brand value, which are the primary drivers of purchase intention. In contrast, environmental initiatives do not directly foster trust, and the effect of perceived quality is fully mediated by brand value and corporate trust. This study advances value-driven consumption theory by demonstrating that non-financial ESG dimensions—especially governance and social responsibility—can supersede functional quality in shaping purchase decisions in high-involvement contexts. These findings suggest that automakers should prioritize governance and social initiatives as strategic levers to build trust and strengthen long-term consumer loyalty. Full article

Three-wheelers (3Ws—autos or auto-rickshaws) occupy a unique yet salient and substantive position within the context of India’s urban mobility. They provide critical first-and-last-mile connectivity, fill public transit coverage gaps, boost local and urban agglomeration economies, and are a major income source for millions. Their value and utility are especially pronounced in rapidly emerging Tier-II cities such as Amritsar. The city’s 7500-strong diesel 3W (d3W) fleet is the backbone of its transportation network but also contributes to air pollution. Though Amritsar’s favorable policies to transition the d3W fleet to electric (e3W) have reduced purchase costs by 40–60%, barriers remain. This study investigates the influence of the e3W user experience through a first-of-a-kind three-day pilot trial for ~300 d3W drivers. By leveraging a pre- and post-intervention framework combining surveys and trip diaries, this study evaluated how direct exposure influences adoption intentions, perceptions, and the social dynamics underpinning decision-making. In total, ~6% of participants switched to e3Ws following the trial, and there was a 20% drop in “don’t know” answers regarding charging duration and range. The results show non-random and meaningful shifts in attitudes, a greater awareness of range and charging times, improved views on charging convenience and vehicle safety, and air quality benefits. Full article

Personalized marketing presents a powerful but delicate strategy, as its benefits can be negated by rising consumer privacy concerns. To illuminate this tension, this study investigates what causes personalization to fail, focusing on the interaction between the level of message personalization and situationally activated privacy concerns. We conducted a 3 (Message Personalization: Low, Medium, High) × 2 (Situational Privacy Concern: Low, High) between-subjects experiment with 360 participants. These personalization levels were designed as an ecologically valid “intrusiveness ladder,” moving from a generic message to one using contextual data and to one using personally identifiable information (PII). Situational privacy concern was experimentally induced using a news article prime, after which participants were exposed to one of the marketing messages. The results revealed a significant interaction effect that demonstrates a critical “tipping point.” In the low privacy concern condition, increasing personalization boosted purchase intention. Conversely, when privacy concerns were activated, a ‘backfire effect’ occurred: highly intrusive, PII-based personalization was no more effective than a generic message and was significantly less effective than moderate, contextual personalization. Our findings provide causal evidence for the moderating role of situational privacy concern, demonstrating that activating this state is a key condition that triggers a non-linear consumer response. Practitioners must calibrate the level of data intrusiveness, as the most aggressive tactics can be counterproductive when consumer privacy sensitivities are high. Full article

The transformation of the transportation sector is critical for achieving Sustainable Development Goal 7 (SDG 7). As the world’s largest auto market, China has implemented various policies to promote sustainable transportation, particularly through the adoption of new energy vehicles (NEVs), thereby increasing the share of renewables in energy consumption and improving energy efficiency. Among these policies, the NEV driving restrictions exemption (NEV-DRE) policy has emerged as a key non-financial incentive to stimulate NEV demand. This study focuses on how the NEV-DRE policy affects the demand side of NEVs in the transportation sector. Employing a difference-in-differences design on a comprehensive dataset of vehicle transactions across 82 prefecture-level pilot cities from 2011 to 2019, this study provides robust causal evidence that the NEV-DRE policy significantly increases NEV sales. Furthermore, this study finds that this growth in demand is primarily driven by an increased consumer preference for domestic pure electric sedans. The policy proves more effective in cities with general driving restrictions, purchasing restrictions, and greater environmental awareness. Our findings demonstrate how innovative traffic management measures can be transformed into effective industrial policy tools, accelerating the adoption of renewable energy in the transportation sector. This study offers valuable insights for policymakers in China and elsewhere on how to design non-financial incentives to promote sustainable transportation, thereby promoting sustainable energy transitions and contributing to the achievement of SDG 7. Full article