Search Results (1,506)

Internet advertising, while enabling unprecedented commercial reach, has become a pervasive vehicle for deceptive practices that inflict measurable harm on consumers. This study empirically investigates the structural relationships between internet advertising falsity and consumer harm by integrating analyses of the mediating role of consumer cognitive processes and the moderating role of consumer vulnerability within a unified structural framework. Survey data were collected from 600 adult consumers with online purchase experience in the Republic of Korea—an advanced digital economy characterized by exceptionally high mobile-commerce penetration, mature e-commerce infrastructure, and evolving digital consumer protection regulation—and analyzed using structural equation modeling (SEM) with AMOS 24.0, supplemented by Hayes’ PROCESS macro Model 59 for conditional process analysis. All 13 hypotheses were supported, although path magnitudes varied substantially across falsity dimensions and mediator pathways—with direct effects ranging from β = 0.156 (false scarcity) to β = 0.224 (performance exaggeration), and indirect effects dominated by the risk assessment distortion pathway. Among the four sub-dimensions of advertising falsity—factual misrepresentation, performance exaggeration, price deception, and false scarcity—performance exaggeration exerted the strongest direct effect on consumer harm. The three cognitive mediators—perceived advertising credibility, risk assessment distortion, and purchase decision pressure—all demonstrated significant partial mediation, with risk assessment distortion emerging as the most powerful indirect pathway. All four consumer vulnerability dimensions—digital literacy level, demographic vulnerability, prior victimization experience, and impulsive buying tendency—significantly moderated the falsity–harm relationship, with low-digital-literacy consumers experiencing approximately 1.7 times the adverse effect of high-literacy counterparts. Moderated mediation analysis revealed that the conditional indirect effect for the high-vulnerability group was approximately 2.3 times that of the low-vulnerability group, confirming that the cognitive harm mechanism intensifies systematically for vulnerable consumers. These findings advance consumer vulnerability theory in the digital context and offer evidence-based implications for consumer protection policy, platform governance, and digital literacy education. Full article

Generation Z (Gen Z) consumers exhibit a distinctive multi-platform purchase behavior: they habitually discover products through social commerce (S-commerce) stimuli—including influencer content and livestream shopping—yet systematically migrate to e-marketplaces to complete their transactions. Despite the strategic importance of this behavioral pattern for platform operators, brand managers, and policymakers, the underlying mechanisms remain poorly understood. This study advances a Consumer Decision Journey framework comprising five stages—Social Commerce Stimuli, Discovery, Risk Evaluation, Marketplace Evaluation, and Purchase Decision—and integrates Stimulus-Organism-Response theory and the Elaboration Likelihood Model to explain how Gen Z consumers navigate cross-platform purchase decisions. Employing a sequential explanatory mixed-methods design, we conducted a large-scale survey (n = 423 Gen Z respondents) analyzed via Partial Least Squares Structural Equation Modeling, complemented by 18 in-depth qualitative interviews. Results confirm that influencer persuasion, livestream engagement, and perceived product authenticity drive product discovery; price comparison mediates, and price sensitivity moderates the discovery-to-risk pathway. Critically, perceived risk in S-commerce paradoxically accelerates cross-platform migration and elevates trust in e-marketplaces. Trust in e-marketplaces and logistics reliability each moderate the risk-to-purchase relationship. Qualitative analysis reveals that cross-platform behavior is a deliberate, internalized strategy among Gen Z—a platform arbitrage norm. These findings have substantial implications for S-commerce platform design, influencer marketing strategy, and e-marketplace positioning in emerging economies. Full article

Food waste poses a serious threat to global food sustainability, and consumer rejection of suboptimal food due to perceived risks is a significant factor exacerbating this issue—a phenomenon particularly pronounced in the Chinese context. Using survey data from 1022 Chinese consumers, this study investigates how multidimensional perceived risk and demographic characteristics jointly influence purchase intention toward suboptimal food. The results indicate that perceived quality risk, perceived health risk, and perceived social risk exert significant negative effects on purchase intention, whereas perceived psychological risk shows no significant effect. Moreover, the effect of perceived risk varies significantly across key demographic dimensions. Perceived health risk mediates the relationship between perceived quality risk and purchase intention. A significant interaction also emerges between perceived quality risk and perceived social risk: under conditions of high perceived social risk, high perceived quality risk substantially reduces purchase intention; under low perceived social risk, this negative effect persists but is attenuated. By delineating the differential effects and underlying mechanisms through which distinct risk dimensions shape purchase intention, this study not only advances the theoretical understanding of the interplay between multiple risk perceptions in consumer decision-making but also provides empirical evidence for reducing food waste from the consumption side, offering important implications for promoting sustainable consumption practices. Full article

External electricity supplementation for islanded microgrids at expressway service areas is often settled under tiered electricity pricing based on cumulative energy consumption, where marginal prices increase discontinuously once tier thresholds are exceeded. This mechanism reshapes battery dispatch behavior and may alter economically optimal storage sizing. This paper proposes a unified planning—operation optimization framework for wind–PV–battery microgrids that jointly determines the storage capacity and hourly scheduling while enforcing power balance, battery state-of-charge dynamics, and tiered settlement costs. By introducing tier-wise energy allocation variables and tier cap constraints, the nonlinear settlement rule is reformulated into an equivalent piecewise-linear structure, leading to a mixed-integer linear programming (MILP) model that can be solved using standard optimization solvers. A season-weighted annualized case study using four typical seasonal days reveals critical cross-tier dispatch behaviors, where charging–discharging schedules shift near tier boundaries and external electricity purchases are actively suppressed from entering higher-priced tiers. The proposed framework quantifies the premium-avoidance value of storage and provides a practical decision support tool for premium risk-aware sizing and operation of islanded expressway service-area microgrids. Full article

In recent years, scientific and technological development has made trade-in programs for innovative electronic products more and more popular. Many of these innovative companies that continue to launch new products offer trade-in and cash-out sales strategies to stimulate purchase. This paper studies when a company launches these two sales strategies and how to ensure optimal pricing that maximizes profits, while taking into account the degree of the consumer’s strategy, the degree of the new product’s innovation, the residual value of the old products, and the cost. We construct a two-period dynamic pricing joint optimization model with four core decision variables and derive the closed-form optimal solution through strict mathematical derivation including Hessian matrix analysis and KKT condition verification. We have adopted a dynamic pricing strategy that conforms to the actual market. The results show that this study provides new mathematical insights for dynamic pricing research, and reveals the substantive rule that companies are more likely to gain greater benefits when the degree of product innovation is not high and the consumer’s strategy degree is moderate. Statistics show that companies are more likely to gain greater benefits when the degree of product innovation is not high and the consumer’s strategy degree is moderate. Full article

Purchasing portfolio models, particularly the Kraljic matrix, are widely used to support sourcing decisions under supply risk. Yet, they are often criticized for relying on subjective assessments and focusing mainly on upstream uncertainty while neglecting downstream demand volatility. This study develops a quantitatively grounded purchasing portfolio framework that integrates demand volatility and lead-time volatility into a unified measure of supply risk to support more sustainable sourcing decisions. Using transactional data for 876 stock-keeping units (SKUs) from a pharmaceutical distribution company, demand and lead-time volatility are measured through coefficients of variation and combined using an adjusted multifactor model that accounts for their interdependence. Financial importance is measured objectively through gross profit and classified according to the 80–20 Pareto principle. These metrics are incorporated into a revised purchasing portfolio matrix that classifies items into strategic, leverage, bottleneck, and routine categories. The findings reveal substantial variation in combined volatility across SKUs and show that incorporating demand uncertainty significantly changes portfolio positioning compared with traditional approaches. By linking purchasing and marketing perspectives, the proposed model reduces subjectivity, improves risk visibility, and supports sustainable sourcing and inventory decisions in volatile environments. Full article

This study examines the impact of explainable artificial intelligence (XAI) features on user satisfaction and purchase intention in Saudi mobile shopping applications, utilising the stimulus–organism–response (S–O–R) framework. With the increasing reliance on AI-driven decision support in e-commerce, enhancing transparency, fairness, trustworthiness, and interpretability has become crucial for shaping consumer perceptions and behavioural responses. The research employed a quantitative methodology using partial least squares structural equation modelling (PLS-SEM) to examine the relationships among stimulus factors, cognitive and affective states, consumer satisfaction, and purchase intention. In a survey of 597 respondents from Jeddah and Makkah, Saudi Arabia, the findings highlight that fairness and bias detection, trustworthiness, and transparency significantly influence consumers’ cognitive and affective states, which in turn enhance satisfaction and intention to purchase. Consumer satisfaction emerged as a critical mediator, reinforcing the role of positive emotional and cognitive experiences in driving purchase behaviours. However, interpretability showed limited impact, suggesting that consumers may prioritise fairness and trustworthiness over technical clarity of explanations. Theoretically, this study contributes to advancing knowledge on the role of XAI in consumer behaviour by integrating fairness, transparency, and affective responses into the S–O–R paradigm. From a managerial perspective, the results underscore the importance for mobile shopping platforms to design AI systems that foster trust, reduce perceived bias, and ensure transparency, thereby improving consumer engagement and purchase outcomes. By addressing gaps in interpretability and transparency, businesses can strengthen user trust and loyalty, ultimately enhancing competitive advantage in Saudi Arabia’s rapidly growing e-commerce sector. Full article

Under fault conditions, Photovoltaic-Storage-Charging Integrated Stations (PSCISs) are regarded as a key resource for enhancing distribution network resilience. However, traditional centralized optimization fails to account for conflicts of interest between the distribution network and PSCISs and neglects the actual response behavior of EV users. To address these issues, a coordinated emergency operation strategy for distribution networks and PSCISs based on the master–slave game is proposed. Firstly, a bilevel optimization framework based on the master–slave game is constructed, where the upper level performs system-level coordination and the lower level handles autonomous decision-making. For the upper level, the minimization of distribution network operation cost is set as the optimization objective by the dispatching center to determine power purchase prices and load shedding rates, which serve as guidance signals for lower-level PSCISs. In terms of the lower level, a dual-factor S-shaped response curve is introduced into the lower-level model to precisely characterize EV users’ nonlinear response behavior to price incentives. Furthermore, based on the signals received from the upper level, the maximization of each PSCIS’s profit is set as the optimization objective to determine the PV output, storage dispatch, and V2G incentive prices. Subsequently, Model Predictive Control (MPC) is employed to implement rolling optimization during the fault period, addressing the source-load uncertainties. Finally, an improved IEEE 33-node distribution network is used for case analysis and validation of the proposed operation strategy. The results indicate that the proposed strategy can effectively coordinate the interests of multiple parties, achieving synergistic improvements in both the economy and reliability of the distribution network. Full article

To explore the evolutionary dynamics of green product markets under bounded rationality, this study develops a tripartite evolutionary game model involving the government, passenger vehicle enterprises, and consumers, using China’s new energy vehicle (NEV) market as a case study. By integrating system dynamics with real-world data and policies, the paper simulates strategy evolution paths and identifies equilibrium conditions. The results show a unique evolutionarily stable strategy: the government refrains from regulation, enterprises actively produce NEVs, and consumers actively purchase green products. The government’s strategy is primarily influenced by enterprises, while enterprises’ strategy is mainly driven by consumers. Numerical analysis reveals that when the premium payment ratio of green products (price difference relative to conventional vehicles) is controlled between 27.27% and 31.82%, the market evolves most rapidly toward the ideal equilibrium. Furthermore, when the additional positive benefit ratio of green consumption falls below 36.36%, market formation and development are severely hindered; raising this ratio to 40.91% yields significant promotion effects, beyond which marginal benefits diminish. These findings provide quantitative benchmarks for policy design and strategic decision-making to foster self-sustaining green product markets. Full article

Consumer decisions play an important role in shaping sustainable consumption outcomes. This study focuses on green purchase intention among young adult consumers in Turkey and examines how cognitive factors, social factors, and consumer individual characteristics are related to intention formation, with green loyalty considered as a moderating element. The data was obtained from 200 young adults via online surveys and though social networks commonly used in Turkey, and analyzed using partial least squares structural equation modeling (PLS-SEM). The analysis shows that green purchase intention varies in relation to these factor groups, and that green loyalty influences the way several relationships operate within the model. The study contributes to ongoing discussions in consumer behavior and sustainable marketing by providing context-specific evidence relevant to organizations aiming to encourage eco-friendly product choices and more responsible consumption among younger consumers. This study is grounded in consumer behavior theory and uses selected elements of the theory of planned behavior and the attitude–behavior–context framework to organize the analytical framework. The findings offer insights that are relevant for both academic research and marketing practice within a sustainable consumption context. Full article

In digital marketing, consumers often face decision dilemmas due to either excessive or insufficient green information. How can firms manage green information load to enhance green purchase intention? Grounded in the principle of least effort and uncertainty reduction theory, this study examines the impact of green information load on green purchase intention and its underlying mechanisms. Results from six experiments show that: (1) Green information load positively influences green purchase intention; (2) Information credibility mediates this relationship; (3) Digital literacy moderates the effect of green information load on credibility, and this moderating effect is context-dependent: negative under low-load levels, positive under medium-load levels, and insignificant under high-load levels; (4) Green self-efficacy positively moderates the effect of credibility on purchase intention. Taken together, these findings suggest a nonlinear moderating role of digital literacy, offering a potential extension to cognitive bias theory, and provide preliminary practical guidance for businesses seeking to tailor information strategies to populations with varying levels of digital literacy. Full article

This study adopts the theory of planned behavior to investigate consumers’ purchasing decisions under extreme weather conditions. Specifically, this paper examines how extreme global weather events motivate consumers to consider purchasing green products and prioritize environmental sustainability in their consumption choices. It further explores whether consumers’ adoption of green products enhances their satisfaction under abnormal global climate conditions, as well as how consumer satisfaction subsequently improves individuals’ mood, anxiety, and cognitive states. Structural equation modeling was employed to test the hypothesized model using data collected from 352 valid respondents in China. As the global community strives to achieve net-zero CO₂ emissions by 2050, numerous firms and manufacturers have incorporated green product concepts to advance sustainable operations. The empirical results reveal that anxiety and cognition are positively related to green purchasing decisions, which in turn exert a positive influence on consumer satisfaction. Based on these findings, this study proposes actionable strategies to promote green consumption behavior by accounting for relevant psychological factors. Full article

The article provides a comprehensive review of empirical studies on consumer attitudes, motivations, and behaviors in the functional food market. The main objective of this study is to identify groups of determinants and to update and systematize current knowledge on the influence of various factors on consumer purchasing decisions in this market. Based on an analysis of international research published between 2004 and 2025, four key groups of determinants were identified: (1) health- and trust-related factors, (2) cognitive and psychological factors, (3) perceptual and product-related factors, and (4) socio-demographic and segmentation factors. The analysis confirms that purchasing decisions in this product category are complex and multidimensional. They result from the interaction between rational factors (health-related and cognitive) and emotional-symbolic factors (psychological and sensory). The strongest predictors of functional food acceptance include perceived health benefits, trust in producers and information sources, sensory attractiveness, and product naturalness. Socio-demographic characteristics, such as age, education level, and income, further differentiate purchasing intentions and behaviors. Overall, the findings highlight the need for further comparative and cross-cultural research, as cultural and economic conditions may significantly shape consumer decisions across markets. The results obtained have both theoretical and practical implications. They contribute to a better understanding of consumer decision-making processes and emphasize the importance of promoting health awareness. Full article

In recent years, the literature has concentrated on consumers’ sustainable attitudes and purchases, and the underlying mechanisms behind consumers’ sustainable buying decisions. Yet, to the best of our knowledge, studies that examine the impact of culture on attitudes and purchase behaviors towards sustainable fashion, through the prism of consumption values, and moderated by gender, are fragmented and limited. Elaborating on the dynamics of culture, gender, and consumption values, this study applies an online survey with 171 U.S. and 157 Greek participants to delve into sustainable fashion consumption. Notably, it reveals the effect of country on purchase behavior via consumption values and attitudes toward sustainable fashion, in the moderating presence of gender. U.S. (vs. Greek) men demonstrate higher attitudes and purchase behaviors towards sustainable fashion, driven by enhanced emotional and social value. U.S. (vs. Greek) women exert enhanced purchase behavior and social consumption value, while Greek women demonstrate higher levels of emotional value. These findings provide fruitful evidence with respect to the impact of cultural and demographic dynamics on sustainable fashion consumption, through the prism of consumption values. The study also highlights potential paths for future research that could help marketers delve into understanding sustainable fashion consumption. Full article

Like other agricultural products, food legumes production faces uncertainty risks stemming from climate change, which may affect yields and consequently impact farmers’ livelihoods. Agricultural insurance serves as one of the climate change adaptation measures available to farmers, helping mitigate the impacts of climate change on agricultural production and livelihoods. While considerable attention has been paid to climate change adaptation through production-side measures, comparatively fewer micro level studies examine insurance adoption as an adaptive response, particularly among food legume farmers. Based on a survey of 460 food legume farmers in Baicheng City, Jilin Province of China, this study employs a binary probit regression model to analyze the relationship between climate change perceptions and farmers’ adoption of agricultural insurance as an adaptation measure. Farmers’ climate change perception is measured through four indicators: perceived changes in average annual temperature, precipitation, drought severity, and frost severity over the past five years. Robustness tests are conducted by using a replacement econometric model, altering the climate change perception variable, and implementing sample restriction. Results indicate that food legume farmers’ perceptions of climate change exhibits significant correlation with their agricultural insurance purchasing behavior. Farmers who perceive lower temperatures and more severe frosts are more inclined to purchase agricultural insurance. Participation in food legume production cooperatives and prior experience with yield reductions exert significant positive correlation with insurance purchase decisions. Therefore, enhancing targeted outreach and education, leveraging the role of cooperatives in insurance promotion, and implementing differentiated insurance promotion based on disaster experiences hold positive implications for reducing farmers’ exposure to climate change risks. The findings further offer valuable insights into climate adaptation policy in other drought-prone, legume-growing regions. Full article