Search Results (109)

To explore the mechanism of consumers’ battery electric vehicle (BEV) purchase behavior in depth and address research gaps related to insufficient consideration of psychological latent variables and neglect of consumer heterogeneity in existing studies, this study constructs a latent class model (LCM) that integrates personal attributes, vehicle attributes, and six psychological latent variables: perceived usefulness, perceived ease of use, perceived risk, environmental awareness, purchase attitude, and purchase intention. Based on 1044 valid questionnaires collected from Urumqi, latent profile analysis (LPA) is used to classify consumers. The results indicate that BEV consumers can be divided into five distinct latent profiles with significant differences in purchase preferences: the risk-avoidance type, the moderate–low intention wait-and-see type, the utility-oriented and low environmental concern type, the high utility cognition and low-risk proactive type, and the all-dimensional high-intention core type. Socioeconomic and vehicle-related factors exert heterogeneous impacts on the psychological variables and purchase decisions of each profile. This study clarifies the intrinsic psychological mechanism of BEV purchase behavior, providing a theoretical basis and targeted strategy references for the government and enterprises to promote BEV adoption and advance sustainable transportation development. Full article

Blockchain technology is increasingly adopted in supply chains to record product carbon footprints and environmental attributes on tamper-resistant ledgers. By improving the transparency and verifiability of emission-related information for governments, firms and consumers, blockchain reshapes the incentive effects of environmental taxes and subsidies that target emission abatement. This paper presents a government-manufacturer-consumer tripartite game model to analyze the abatement effects of tax and subsidy policies and their differences under heterogeneous consumer demand in a blockchain-driven framework. The results indicate that: (1) Both subsidy and tax policies can facilitate environmental improvement. When consumers’ green preference exceeds a specific threshold $X^{*}/\left(1+\gamma \right)$, the greenness of the tax policy is superior to that of the subsidy policy, and vice versa. (2) Under blockchain technology, tax and subsidy instruments differentially affect the profits of conventional and green manufacturers, shifting profits from high-emission sectors to green sectors. (3) The improvement of consumers’ environmental awareness can gradually reduce the implementation of the policy, urge enterprises to reduce emissions, and improve their profits. Nevertheless, the privacy concerns associated with blockchain technology present a significant obstacle to the effective implementation of carbon emission reduction strategies. Full article

Digital platforms face a fundamental strategic decision between subscription-only, advertising-only, and freemium (hybrid) monetization models. We develop a game-theoretic framework that unifies these strategies, explicitly modeling consumer heterogeneity in both willingness-to-pay and advertising disutility, while incorporating network effects through the platform’s valuation of user-base size. Our analysis yields closed-form solutions identifying optimal strategy thresholds based on advertising market conditions. We show that subscription-only dominates when advertising prices are low, advertising-only prevails when prices are high, and freemium emerges as strictly optimal in the intermediate region. Under freemium, we demonstrate strategic complementarity: both subscription fees and advertising intensity exceed their levels in pure strategies because each instrument’s effectiveness is amplified by the other through user reallocation across tiers. Network effects universally reduce monetization intensity but alter instruments’ relative sensitivities differently across regimes—when advertising prices are moderate, freemium adjusts ad length more aggressively, while the opposite holds at high prices. Critically, freemium’s profitability requires sufficient consumer heterogeneity in ad tolerance. As consumer preferences converge, the screening mechanism fails and freemium collapses to the superior pure strategy. These results provide operational guidance for platform monetization decisions and clarify when hybrid models create value beyond traditional approaches. Full article

Rising ocean temperatures driven by climate change are impacting the distribution of fish stocks. In the Northeastern United States, fish scientists predict that well-known local species will shift further north and will be replaced by lesser-known southern species in the local waters. It is unclear whether New England seafood consumers will accept these unfamiliar species when they enter the market, posing a threat to the resiliency of fishing communities. This paper investigates how New England seafood consumers might respond to a shifting supply of seafood by conducting an online stated preference survey. The choice experiment leveraged in the survey revealed that, compared to Atlantic Cod, consumers are willing to pay less for the unfamiliar fish species. However, significant heterogeneity was detected in the consumers’ preferences for purchasing these species. We find the varying degree of willingness to pay being affected by factors such as the type of venues they purchase seafood from and whether they fish recreationally. Our results suggest there will be a challenge in marketing these species, although with proper marketing strategies and coordination among the industry, these challenges may be reduced. Full article

Frequent gradient exchange and heterogeneous data distribution in federated learning can lead to serious privacy leakage risks. Traditional privacy-preserving strategies fail to meet the personalized privacy needs from different users and may cause a decrease in model accuracy and convergence difficulties. The symmetry of federated learning may lead to the insufficiency of contribution evaluation mechanisms in protecting the privacy of sensitive data holders. However, federated learning avoids the risk of privacy leakage caused by data centralization because the raw data is always stored on the local device during the training process, and only encrypted model parameters or gradient updates are exchanged. To address these issues, this paper proposes an adaptive personalized differential privacy federated learning scheme APDP-FL. First, we propose an adaptive noise addition method that scores each round of training based on the parameters generated during training and dynamically adjusts the noise level for the next round. This method adds larger noise scales in the early stages of training, consuming less privacy budget, and gradually reduces noise addition during training to accelerate model convergence. Second, we design a personalized privacy protection strategy that adds noise tailored to individual needs for participating clients based on their privacy preferences. This solves the problem of insufficient or excessive privacy protection for some participants due to identical privacy budget sets for all clients, achieving personalized privacy protection for clients. Finally, we conduct extensive experimental simulations, comparisons, and analyses on three real federated datasets, MNIST, FMNIST, and CIFAR-10, verifying the advantages of APDP-FL in terms of privacy protection, model accuracy, and convergence speed. Full article

The trade-in service can enhance product sales and increase consumer loyalty; however, heterogeneity in consumer quality preferences significantly influences the provision and implementation of trade-in activities. By constructing a dynamic dual-supply chain model, this study examines the optimal choices for trade-in providers and the impact of consumer quality preferences on mode selection. The findings indicate that the decision of who should provide the trade-in service largely depends on the product’s quality decay rate. When the quality decay rate is low, collaboration between the manufacturer and the retail platform favors manufacturer-led trade-in service. Conversely, when the quality decay rate is high, both parties tend to fall into a prisoner’s dilemma, each preferring to dominate the trade-in process independently. Notably, as the share of pragmatic consumers increases, both sides of the supply chain are more inclined to prefer the manufacturer offering trade-in service. In our extended research, we found that the influence of government subsidies on mode selection primarily depends on the price discounts provided by the dominant party in trade-in arrangements within each mode. We also considered scenarios with asymmetric net residual values of recovered products, and the results robustly validate the stability of our core findings. Full article

As environmental and social sustainability become an increasingly critical concern, retailers are under rising pressure from both eco-conscious consumers and evolving regulatory frameworks to enhance the environmental, social, and governance (ESG) performance of their supply chains. Given that most ESG-related violations originate from upstream suppliers, downstream retailers are compelled to invest in promoting responsible practices beyond their immediate operations. To capture this dynamic, we develop a two-tier supply chain model in which a single supplier distributes products to multiple retailers engaged in Cournot competition. Each retailer independently determines its level of investment aimed at improving the supplier’s ESG outcomes while accounting for heterogeneous consumer preferences between supplier-driven and retailer-driven sustainability efforts. Our findings reveal that retailers are only incentivized to invest when the number of market participants falls below a critical threshold. We further extend the analysis to an asymmetric setting, where only a subset of retailers engage in ESG investments and pay a premium wholesale price. In contrast to the baseline scenario, this structure may encourage higher investment levels among participating retailers when more of them are involved. Moreover, under conditions of strong consumer preference heterogeneity, a larger number of investing retailers can incentivize the supplier to reduce the wholesale price, thereby reinforcing investment incentives and facilitating improved ESG performance across the supply chain. In summary, the results provide valuable managerial implications for retailers, suppliers, and policymakers seeking to foster coordinated and sustainable ESG investment within supply chains. Full article

Manufacturing firms may lose profits after a servitization transition due to a mismatch between service offerings and demand, causing them to fall into the servitization paradox. The purpose of this paper is to address the reality of the mismatch between the heterogeneous needs of consumers and the levels of services provided by firms. This paper constructs a two-stage game model and proposes a servitization pricing strategy based on consumers’ willingness to pay. The results show that a premium pricing strategy yields optimal profits; a value-for-money pricing strategy is preferred only when consumers’ willingness to pay is extremely high. Further, we propose to optimize the level of demand matching by matching hidden demand. Considering the characteristics of services, this paper proposes programs based on experience and word-of-mouth marketing to achieve hidden demand matching. It was verified that based on Nash equilibria, the level of supply–demand matching and the profit of firms were improved. In practice, this research provides firms with guidance on servitization pricing strategies and offers a reference path to break the servitization paradox. Full article

Beer consumption behaviors within China exhibited significant regional heterogeneity. To elucidate the specific differences in beer consumer behaviors across different regions and their influencing factors, this study systematically analyzed the sensory preference characteristics of consumers in the Chinese beer market based on machine learning methods, and further revealed the core driving mechanisms influencing their consumption behaviors. By integrating consumer data from different regions, a comprehensive dataset was constructed encompassing sensory attribute evaluations (bitterness, malt flavor, hop aroma, smoothness of mouthfeel, foam characteristics, etc.) and other dimensional consumption behavior variables (brand, beer packaging, etc.). Utilizing an ensemble learning framework (LightGBM), Support Vector Machine (SVM), and decision tree models for feature mining, the study identified important factors influencing the consumption behaviors of Chinese beer consumers. Specifically, consumers in mature and upgrading markets placed greater emphasis on the overall drinking experience and drinkability when purchasing beer, whereas consumers in scale-dominant and mainstream competitive markets considered foam persistence, fineness, and light brown color as core quality indicators. Conversely, consumers in potential growth and emerging cultivation markets demonstrated strong brand orientation. This indicated that the factors influencing beer consumption behaviors varied significantly across regions. Through a data-driven paradigm, this study revealed the underlying regional mechanisms behind consumption decisions in different regional beer markets in China, providing a theoretical foundation and empirical support for cross-regional product customization, precision marketing, and resource optimization. Full article

Plant-based meat analogues (PBMAs) are positioned as promising alternatives to animal-based foods due to their potential environmental and health benefits. This study aimed to investigate the acceptability of PBMAs among trend-sensitive Swedish consumers, including both those who already eat PBMAs and those who do not. A questionnaire with both closed and open-ended questions was distributed digitally via social media using convenience/snowball sampling (n = 291). Data were analyzed using descriptive statistics, chi-square tests, and qualitative content analysis. The results show that PBMA consumption was significantly more common among women, urban dwellers, and individuals identifying as flexitarians or vegetarians. Environmental concerns and animal welfare were the most important motivators for PBMA consumption, whereas non-consumers cited issues such as imported ingredients, high processing levels, and poor sensory qualities as barriers. Consumers valued flavor and visual appeal more than production or nutritional attributes. Interestingly, while current PBMA consumers did not seek meat-like sensory properties, non-consumers and potential users preferred products resembling meat in taste and texture. The name “plant-based protein” was rated most appealing, compared to alternatives like “meat analogue” or “meat substitute.” The study highlights the heterogeneity in consumer expectations and emphasizes the need for tailored product development and communication strategies. Improving sensory quality, enhancing nutritional value, and positive product naming may support a broader acceptance of PBMAs. Full article

This paper introduces a novel ratio-based framework for analyzing how consumer heterogeneity translates into product differentiation in vertically structured monopoly markets. We consider a monopolist facing a continuum of consumers and a strictly convex production cost function and identify conditions under which the heterogeneity of preferences, measured by the length of the consumer type interval, maps into a corresponding range of offered qualities. The analysis shows that this mapping depends on the curvature of the marginal cost function: under linear costs, the relationship is proportional; under convex costs, heterogeneity expands faster than segmentation; and under concave costs, the reverse occurs. These findings offer a new lens for understanding endogenous market granularity in monopoly settings and have potential applicability in markets with vertically differentiated goods. We also show that under partial market coverage, this proportionality breaks down - even in the linear case - revealing a critical asymmetry in equilibrium structure. Full article

This study considers consumers’ risk perceptions and safety preferences as external shock factors in food safety incidents. These factors are incorporated into a general equilibrium model defined by the food safety hierarchy, and the computational experiment method is employed to examine the direction of spillover effects. According to the findings, the spillover direction and intensity of food safety incidents are jointly influenced by the characteristics of consumers, food and the market. When an incident raises consumers’ safety concerns, a negative effect occurs throughout all food sectors. When an incident has a specific impact on consumers’ risk perception, the direction of the spillover is contingent upon the safety level of the product in question. In the event that the food involved in an incident is extremely secure, it may have a detrimental effect on unrelated food goods; conversely, it may have a beneficial effect on unrelated food goods. The incident’s impact has increased in proportion to the market share of the affected food. When the market share remains constant, the impact intensity increases as the degree of food safety improves. Higher market-wide risk levels are associated with more pronounced and quicker effects. This study improves understanding of spillover patterns in food safety situations, which aids in the formulation of focused policy responses and initiatives. 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

Background: Access to healthy food in emerging-economy cities is challenged by last-mile constraints and poor infrastructure. Aligned with the UN SDGs on Zero Hunger and Sustainable Cities, this study examines how a strategically located nanostores network can help close these gaps while fostering local resilience. Focusing on Colombia’s Sabana Centro region, we designed a nanostore network that maximizes spatial coverage, proximity, and affordability. Methods: A competitive facility-location model combined with a discrete choice model captures consumer heterogeneity in price and location preferences. Results: Results show that locating nanostores in peripheral rather than central areas improves equity: the proposed network meets about 65,400 kg of weekly demand—51% fruit, 36% vegetables, 13% tubers—representing 16% of total regional demand and reaching underserved municipalities. This is notable given that existing nanostores already satisfy roughly 37% of household needs. Conclusions: By linking consumer behavior with sustainable spatial planning, the research offers both theoretical insight and practical tools for equitable distribution. Future work should evaluate supportive policies and supply chain innovations to secure nanostores’ long-term viability and community impact. Full article

E-commerce growth has reshaped consumer behavior and retail services, driving parcel demand and challenging last-mile logistics. Existing research predominantly relies on survey data and global regression models that overlook intra-urban spatial heterogeneity in shopping behaviors. This study bridges this gap by analyzing e-commerce demand’s spatial distribution from a retail service perspective, identifying key drivers, and evaluating implications for omnichannel strategies and logistics. Utilizing waybill big data, spatial analysis, and multiscale geographically weighted regression, we reveal: (1) High-density e-commerce demand areas are predominantly located in central districts, whereas peripheral regions exhibit statistically lower volumes. The spatial distribution pattern of e-commerce demand aligns with the urban development spatial structure. (2) Factors such as population density and education levels significantly influence e-commerce demand. (3) Convenience stores play a dual role as retail service providers and parcel collection points, reinforcing their importance in shaping consumer accessibility and service efficiency, particularly in underserved urban areas. (4) Supermarkets exert a substitution effect on online shopping by offering immediate product availability, highlighting their role in shaping consumer purchasing preferences and retail service strategies. These findings contribute to retail and consumer services research by demonstrating how spatial e-commerce demand patterns reflect consumer shopping preferences, the role of omnichannel retail strategies, and the competitive dynamics between e-commerce and physical retail formats. Full article