Search Results (457)

This study investigates the relationship between materialism and pro-environmental behavior, focusing on the moderating role of narcissism in the attitude–behavior gap. A mixed-method research design was employed, combining a preference-based conjoint experiment with psychometric scales including the Material Values Scale (MVS), Recurring Pro-Environmental Behavior Scale (PEB), and Narcissistic Admiration and Rivalry Questionnaire short scale (NARQ-S). A convenience sample of 71 participants evaluated pro-environmental behavior-related choices while also self-reporting their materialistic and pro-environmental values. Results revealed that profiles emphasizing low materialism and high pro-environmental attitudes were most preferred, supporting the hypothesized negative relationship between materialism and pro-environmental choices. The materialism–success dimension showed the strongest behavioral influence. However, narcissism did not significantly moderate the relationship between attitudes and behavior. These findings contribute to dual-attitude theory and impression-management literature by showing that materialists may endorse pro-environmental behavior when it supports social identity signaling. The results have implications for both marketers and policymakers in designing strategies that appeal to reputation-sensitive consumers. Full article

Public understanding of complex sustainability concepts like life cycle assessment (LCA) is crucial for promoting environmentally responsible consumption yet remains a significant educational challenge. This study introduces and evaluates Paper Goes Green, a competitive board game designed to make abstract LCA principles tangible and personally relevant. The game simulates the paper production chain, compelling players to make strategic decisions about resource allocation, production pathways (conventional vs. green), and waste management to fulfill paper orders. Through a single-group pre-test/post-test design with 85 participants (25 environmental educators and 60 public members), the game’s efficacy was assessed. Paired-sample t-tests revealed significant improvements in participants’ perceived knowledge of green chemistry/LCA (pre-game mean 2.05, post-game 3.24 on a 5-point scale, p < 0.001), pro-environmental attitudes (3.38 to 4.22, p < 0.001), and behavioral intentions toward green consumption (3.97 to 4.44, p < 0.001). These gains correspond to medium-to-large effect sizes (Cohen’s d = 0.94 for knowledge, 0.70 for attitude, 0.71 for behavior), indicating substantial practical impact. Qualitative feedback further highlighted the game’s engaging and thought-provoking nature. Notably, specific design features—such as immediate feedback, player control, and interactivity—were identified as key contributors to learning, fostering systems thinking in players. These findings suggest that Paper Goes Green is a promising educational tool for translating complex environmental science into an engaging, impactful learning experience. The game effectively bridges the gap between abstract concepts and real-world consumer choices, fostering life cycle thinking and empowering players to make greener choices in their daily lives. Full article

This study explores how contextual framings influence sustainable decision-making in everyday situations. Building on the literature about the intention–behaviour gap, we examine the combined effect of role activation and environmental risk on pro-environmental preferences. A scenario-based behavioural experiment, conducted via oTree, integrated within-subject role framing (citizen, consumer, neutral) with randomised environmental risk conditions. Participants completed repeated binary choice tasks, where Eco-Preference was defined as the frequency with which they chose the sustainable option. The results indicate that activating a citizen role significantly increased Eco-Preference compared to consumer or neutral framings, while high-risk contexts did not directly boost sustainable behaviour. Instead, risk cues had an indirect effect through motivational states, highlighting the mediating role of Eco-Preference. Theoretically, this study advances Eco-Preference as a latent behavioural construct linking identity-based theories of responsibility with decision-based models of sustainability. Practically, the findings underscore the potential of role-based communication strategies to enhance ecological responsibility, suggesting that both policy and organisational interventions can benefit from fostering civic identities. Ultimately, the framework is applicable across cultures by offering a behavioural measure less prone to survey bias, supporting future comparative research on environmental decision-making. Full article

Omni-channel retailers arise to address the deficiencies in consumers’ online shopping experiences; the resulting competition between such retailers and traditional online platforms presents substantial challenges for green product manufacturers. A three-level game model is established to examine a manufacturer’s green contract design (product pricing and greenness determination) and mode selection under the competition between an online platform and a new retailer providing omni-channel services to end customers. The manufacturer can select between two modes: supplying a green product to the online platform and new retailer (mode RR) or selling it directly through the online platform and reselling it to the new retailer (mode PR). Our findings indicate that, first, even if the relationship between the manufacturer and new retailer has changed from cooperation under mode RR to competition and cooperation under mode PR, the manufacturer still favors two-channel sales over single-channel sales and affects consumer channel choices to adjust market shares through mode selection. Second, regarding the impacts of the key parameters on the manufacturer, downstream e-commerce platform retailers and environment are intricate and nuanced. While raising the omni-channel service level enhances profitability in the new retailer across both modes, its environmental impacts differ significantly between them. Additionally, it can harm the online platform in some cases. Nevertheless, when the parameters fall within suitable ranges, the manufacturer and both downstream retailers have a consistent preference for improved omni-channel services under both modes. Finally, there is a significant divergence in mode preferences among the manufacturer and both downstream platform retailers. Due to the first-mover advantage, the manufacturer opts for mode RR over mode PR in most cases. Notably, within a specific range of parameters, they consistently prefer mode RR, which also proves beneficial for the environment, resulting in a Pareto optimal outcome. This proposes a concrete cooperation mechanism among the manufacturer, retailers, and consumers from quantitative insights, which can promote green products to achieve the objective of low-carbon environmental protection. Full article

Students must navigate large catalogs of courses and make appropriate enrollment decisions in many online learning environments. In this context, identifying key concepts and their relationships is essential for understanding course content and informing course recommendations. However, identifying and extracting concepts can be an extremely labor-intensive and time-consuming task when it has to be done manually. Traditional NLP-based methods to extract relevant concepts from courses heavily rely on resource-intensive preparation of detailed course materials, thereby failing to minimize labor. As recent advances in large language models (LLMs) offer a promising alternative for automating concept identification and relationship inference, we thoroughly investigate the potential of LLMs in automatically generating course concepts and their relations. Specifically, we systematically evaluate three LLM variants (GPT-3.5, GPT-4o-mini, and GPT-4o) across three distinct educational tasks, which are concept generation, concept extraction, and relation identification, using six systematically designed prompt configurations that range from minimal context (course title only) to rich context (course description, seed concepts, and subtitles). We systematically assess model performance through extensive automated experiments using standard metrics (Precision, Recall, F1, and Accuracy) and human evaluation by four domain experts, providing a comprehensive analysis of how prompt design and model choice influence the quality and reliability of the generated concepts and their interrelations. Our results show that GPT-3.5 achieves the highest scores on quantitative metrics, whereas GPT-4o and GPT-4o-mini often generate concepts that are more educationally meaningful despite lexical divergence from the ground truth. Nevertheless, LLM outputs still require expert revision, and performance is sensitive to prompt complexity. Overall, our experiments demonstrate the viability of LLMs as a tool for supporting educational content selection and delivery. Full article

This research investigates consumer behavior and intention to buy (ITB) for sustainable goat cheese made from milk sourced through extensive farming systems. By integrating sensory experiment with stated preference data on credence and search attributes—such as sustainability claims, labeling, and quality certifications—and analyzing them using Partial Least Squares Structural Equation Modeling (PLS-SEM), this research offers a comprehensive perspective on the drivers of consumer decision-making, bridging actual sensory perception with hypothetical market choices. The findings clarify the trade-offs consumers are willing to make between taste and sustainability. Notably, the results reveal that a compelling sensory experience can lead consumers to deprioritize sustainability indicators and labeling claims, indicating that when sensory satisfaction is high, informational cues exert less influence on purchase intentions. To deepen the analysis, this study also explores the mediating role of consumer attitude, demonstrating that attitudes significantly translate product perceptions—particularly sensory and extrinsic attributes—into buying intentions. This integrated approach contributes a novel methodological framework and offers both theoretical and practical insights for marketers and policymakers aiming to promote sustainable food choices. Full article

The global automotive industry’ s rapid transformation has led to electric vehicles (EVs) capturing a significant market share as a sustainable transportation option. To sustain this growth, it is crucial to not only attract new users but also retain existing ones through repurchases. This decision is shaped by both vehicle attributes and users’ prior experiences. This study examines the impact of five dimensions of expected utility and experienced utility gap (including cost utility, functional utility, emotional utility, environmental utility, and social utility) on the repurchase intentions of 863 Chinese EV users. Discrete choice experiments were used to analyze these factors, considering both vehicle and personal attributes. The results show that when emotional utility exceeds expectations, users are more likely to repurchase pure electric and plug-in hybrid electric vehicles. However, if environmental and social utilities fall short of expectations, users may be discouraged from choosing these two vehicle types. In contrast, decisions regarding gasoline vehicles are primarily driven by economic and habitual factors, with minimal influence from emotional, environmental, or social utilities. Additionally, EV users show a preference for medium-sized models that offer shorter charging times and longer driving ranges. These findings offer insights for enhancing consumer acceptance, accelerating EV market penetration, and supporting the automotive industry’s sustainable development, thereby contributing to the achievement of environmental sustainability goals. Full article

As AI recommendation systems become increasingly important in consumer decision-making, leveraging sound cues to optimize user interaction experience has become a key research topic. Grounded in the theory of perceptual contagion, this study centers on sound cues in AI recommendation scenarios, systematically examining their impact on consumer choice and choice satisfaction, as well as the underlying psychological mechanisms. Study 1 (hotel recommendation, N = 155) demonstrated that embedding sound cues into recommendation interfaces significantly increased consumer choice and choice satisfaction. Study 2 (laptop recommendation, N = 155) further revealed that this effect was mediated by preference fluency. Contrary to expectations, AI literacy did not moderate these effects, suggesting that sound cues exert influence across different user groups regardless of technological expertise. Theoretically, this study (1) introduces the theory of perceptual contagion into AI-human interaction research; (2) identifies preference fluency as the core mediating mechanism; and (3) challenges the traditional assumptions about the role of AI literacy. Practically, this study proposes a low-cost and highly adaptable design strategy, providing a new direction for recommendation systems to shift from content-driven to experience-driven. These findings enrich the understanding of sensory influences in digital contexts and offer practical insights for optimizing the design of AI platforms. Full article

This study, performed in an Iranian context, explores how specific architectural attributes of shopping centers can influence public preferences, with the aim of supporting the development of more sustainable and user-oriented urban environments. A discrete choice experiment involving 260 participants was conducted to assess preferences across seven architectural variables, each presented at varying levels: entrance position, openness (i.e., transparency through windows), architectural style, materials, window shape, scale, and symmetry. Participants evaluated paired facade images and selected their preferred designs, enabling an analysis of how these attributes impact consumer choices. The findings indicate that most variables significantly influenced facade preferences, except for arched windows and low levels of openness. In contrast, high openness emerged as the strongest positive predictor of preference. Participants also showed a marked preference for large-scale (inhumanly scaled) facade attributes, rectangular windows, extruded entrances, asymmetrical compositions, and concrete materials. Moderate preferences were observed for symmetrical designs, mixed window shapes, contemporary and postmodern styles, and brick materials. Conversely, neoclassical style, recessed entrances, stone material, and smaller-scale (humanly scaled) facades received the lowest preference ratings. These results might offer valuable insights for architects and urban planners and guide the creation of more attractive and functional shopping centers, ultimately enhancing the quality of urban life. Full article

Postprandial hyperglycemia, marked by the blood glucose level exceeding the normal range after consuming a meal, is a critical indicator of progression toward type 2 diabetes in people with prediabetes and in healthy individuals. A key metric for understanding blood glucose dynamics after eating is the postprandial Area Under the Curve (AUC). Predicting postprandial AUC in advance based on a person’s lifestyle factors, such as diet and physical activity level, and explaining the factors that affect postprandial blood glucose could allow an individual to adjust their behavioral choices accordingly to maintain normal glucose levels. In this work, we develop an explainable machine learning solution, GlucoLens, that takes sensor-driven inputs and utilizes advanced data processing, large language models, and trainable machine learning models to estimate postprandial AUC and predict hyperglycemia from diet, physical activity, and recent glucose patterns. We use data obtained using wearables in a five-week clinical trial of 10 adults who worked full-time to develop and evaluate the proposed computational model that integrates wearable sensing, multimodal data, and machine learning. Our machine learning model takes multimodal data from wearable activity and glucose monitoring sensors, along with food and work logs, and provides an interpretable prediction of the postprandial glucose patterns. GlucoLens achieves a normalized root mean squared error (NRMSE) of 0.123 in its best configuration. On average, the proposed technology provides a 16% better predictive performance compared to the comparison models. Additionally, our technique predicts hyperglycemia with an accuracy of 79% and an F1 score of 0.749 and recommends different treatment options to help avoid hyperglycemia through diverse counterfactual explanations. With systematic experiments and discussion supported by established prior research, we show that our method is generalizable and consistent with clinical understanding. Full article

Soils are critical natural resources, yet their abiotic contributions to ecosystem services remain largely unexplored in valuation studies. This pilot study represents, to the best of our knowledge, the first attempt to assess the perceived value of geosystem services (GSs) from a consumer perspective. Using a discrete choice experiment with 200 respondents, we evaluated preferences for Rotella apples and Moscatello wine through mixed multinomial logit and latent class models. Results show that attributes related to soil use and soil control were consistently significant drivers of consumer utility (e.g., odds ratios of 9.38 and 5.78 for Moscatello wine and 8.46 and 5.56 for Rotella apples, respectively; p < 0.01). These attributes align more closely with the concept of a “geological fingerprint” than with existing geographical labeling schemes such as the Protected Designation of Origin. Price effects were statistically insignificant, indicating virtually no influence on choices. Both estimated models revealed preference heterogeneity and a substantial number of no-buy responses. This suggests both limited consumer familiarity with GS concepts and a limitation of our attribute descriptions, which likely failed to convey information needed for effective purchasing decisions. This study is exploratory and limited by its convenience sample, imperfect price specification, and inability to estimate willingness-to-pay measures. Nevertheless, it provides empirical support for introducing geological footprint labeling and highlights the need for improved consumer information, policy tools, and public campaigns to promote recognition and sustainable management of geodiversity in agriculture. Full article

This paper describes the ScratchJr Bots project aimed at helping young children develop maker literacies, which is the ability to design, program, and build technology-rich projects with developmentally appropriate tools to express themselves. Maker literacies can involve hands-on learning, collaborative experimentation, critical thinking, and problem-solving, as well as the development of socio-emotional skills. By engaging with the design process, children become active creators rather than passive consumers—brainstorming ideas, prototyping, testing, and making improvements toward sharing a final project. Maker literacies engage children in Positive Technological Development in the form of six behaviors—content creation, creativity, choices of conduct, communication, collaboration, and community building. Additionally, children develop character strengths, or virtues, such as patience, generosity, and forgiveness while making. This paper will first introduce the concept of maker literacies as it applies to early childhood and the theoretical background supporting this work. Then, it will introduce the ScratchJr Bots project developed by the DevTech Research Group, a new technology and curriculum that affords the development of maker literacies. Finally, by using design-based research as the methodological approach, two pilot projects are described, including children’s learning experiences, to illustrate the positive behaviors and character strengths that children can exhibit while engaging with ScratchJr Bots. Full article

Agricultural production systems and certificates of origin determine consumers’ preferences for agri-food products, attributes which have mainly been investigated separately. In this study, we examined the joint effect of these two quality criteria and how they influence agri-food choices. To this end, a choice experiment exercise was applied for extra virgin olive oil agri-food in a protected geographical area of south-eastern Spain where non-conventional production systems (organic and integrated pest management) and product origin labels (protected designation of origin and sustainable local brand) associated with the territory are being used. The results demonstrated that consumers’ choices to purchase extra virgin olive oil were primarily influenced by the type of production system, with a clear preference evident for organic systems. Furthermore, consumer preferences for sustainable local over generic national certificates of origin were also confirmed. In concrete terms, the willingness to pay for organic extra virgin olive oil is more than double that of the conventional one, while the surcharge for local origin may rise up to 75%. This work contributes to the understanding of how information related to the type of production system and its interaction between different origin certification labels applies in agri-food products, offering broader implications for producers and policy makers. Full article

Pale lager dominates global beer markets. However, rising living standards and changing consumer expectations have reshaped sensory preferences, highlighting the importance of understanding consumers’ true sensory priorities. In this study, a twenty-eight-item questionnaire, refined through multiple rounds of optimization, was distributed across China and yielded 1837 valid responses. Spearman correlation analysis and partial least-squares regressions showed that educational background and spending willingness exerted the strongest independent effects on sensory priorities. A hybrid analytic hierarchy process–entropy weight method–Delphi procedure was then applied to quantify sensory attribute importance. Results indicated that drinking sensation (30.92%) emerged as the leading driver of pale lager choice, followed by taste (26.60%), aroma (24.77%), and appearance (17.71%), confirming a flavor-led and experience-oriented preference structure. Weighting patterns differed across drinking-frequency cohorts: consumers moved from reliance on overall mouthfeel, through heightened sensitivity to negative attributes, to an eventual focus on subtle hedonic details. Based on these findings, a new sensory evaluation scale was developed and validated against consumer preference rankings, showing significantly stronger alignment with consumer preferences (ρ = 0.800; τ = 0.667) than the traditional scale. The findings supply actionable metrics and decision tools for breweries, supporting applications in product development, quality monitoring, and targeted marketing. Full article

This study utilizes a discrete choice experiment (DCE) to estimate consumer valuation of sustainable aquaculture certification for Atlantic salmon (Salmo salar), one of the most important imported seafood products in South Korea. This experiment investigates consumer preferences across five product attributes: country of origin, product type, preparation method, sustainability certification, and price. Data were collected through an online survey administered by a professional research firm that yielded 24,000 valid choice observations from 1000 respondents. Conditional logit estimates revealed that all specified attributes significantly influenced consumer choices among seafood alternatives. Among the key product attributes, sustainability certification has emerged as the most influential factor affecting consumer decisions. The marginal willingness to pay for sustainably certified aquaculture is estimated to be USD 1.33 per 100 g. These findings provide valuable insights for seafood marketers and policymakers who seek to promote sustainable aquaculture in South Korea. Full article