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Consumer dissatisfaction and damage are increasing worldwide due to the increase in defects caused by the decline in housing quality, and disputes over housing defects are expanding. The number of housing units, a representative standard related to housing quality, is used in Canada, Japan, and Korea. Generally, quality costs increase as the number of housing units increases, and each country’s laws apply stricter management standards. Therefore, the quality is expected to be better as the number of units increases. In 2020, South Korea added a new regulation requiring inspections by a quality inspection team by a public institution only when building housing complexes with more than 300 households. There is a debate about whether this direction of regulation is appropriate. This study examines whether the number of households is being used appropriately as a criterion related to housing quality. It aims to determine whether the limit of 300 households is appropriate for distinguishing housing quality. In addition, since the contractor’s role is vital in housing construction, the contractor’s capabilities and supply–demand relationship were also considered as factors affecting housing quality. The ratio of defect repair costs to construction costs was used as a quality measure for 285 housing complexes in Korea. Generally, the lower the defect repair–construction costs ratio, the better the quality. A comparative study was conducted through a variance analysis on the scale of 300 households and the status of the contractor’s capability, whether they were among the top 10 construction companies with excellent construction performance, and whether a sole contract was made. The results showed that the quality was better in the cases with 300 or more households than in the cases with fewer than 300 households. The quality was better in the cases built by higher-ranking contractors than in those built by other contractors, but there was no difference according to supply-and-demand relationships. The results of the comprehensive analysis indicated that the quality was better when higher-ranking contractors built housing complexes with 300 or more households than when lower-ranking contractors built housing complexes with fewer than 300 households. Therefore, the direction of the Korean regulation requiring quality inspections for housing complexes with more than 300 households is incorrect and should be improved to regulate housing complexes with fewer than 300 households, and of low quality. In addition, the standard of determining housing quality based solely on the number of households should be revised, and the direction should be changed to strengthen quality control and the public supervision of housing built by low-capacity contractors. If the results of this study are utilized with this view in mind, a reasonable system to protect housing consumers will be promoted. Full article

This study explores how customers recognize and accept artificial intelligence devices (AIDs) in the realm of sustainable banking services, applying the Artificially Intelligent Device Use Acceptance (AIDUA) model. This research not only seeks to corroborate the AIDUA model in the banking sector, but also aims to enrich it by introducing technological literacy as a moderating factor, particularly in the perspective of sustainable banking. Data were collected through 435 valid, self-administered face-to-face surveys from bank customers in China, determined through convenience sampling. The hypotheses, covering both direct and moderating effects, were examined using structural equation modeling. This study verifies the applicability and reliability of the AIDUA model, in assessing customer acceptance of AIDs within sustainable banking services. The findings indicate that customer acceptance of AIDs unfolds in three distinct phases. Initially, the consumers’ perceptions of social influence (SI), hedonic motivation (HM), and perceived anthropomorphism (PA) positively influence their green performance expectancy (GPE) and green effort expectancy (GEE) concerning AIDs. As a result, greater GPE and GEE among bank customers lead to stronger positive emotions, which greatly contribute to increased AIDs usage and a reduction in resistance to their implementation. Additionally, the findings determine that technological literacy plays a substantial moderating role in the association connecting green performance expectancy and customer emotions in relation to adopting AIDs, thereby highlighting its importance in advancing sustainable banking initiatives. Full article

The development and popularization of navigation applications are increasing expectations for their quality and functionality. Users need continuous navigation not only outdoors, but also indoors. In this case, however, the perception of space and movement is somewhat different than it is outside. One potential method of meeting this need may be the use of so-called geo-descriptions—multi-level textual descriptions relating to a point, line or area in a building. Currently, geo-descriptions are created manually. However, this is a rather time-consuming and complex process. Therefore, this study undertook to automate this process as much as possible. The study uses classical methods of spatial analysis from GIS systems and text generation methods based on artificial intelligence (AI) techniques, i.e., large language models (LLM). In this article, special attention will be paid to the second group of methods. As part of the first stage of the research, which was aimed at testing the proposed concept, the possibility of LLMs creating a natural description of space based on a list of features of a given place obtained by other methods (input parameters for AI), such as coordinates and categories of rooms around a given point, etc., was tested. The focus is on interior spaces and a few selected features of a particular place. In the next stages, it is planned to extend the research to spaces outside buildings. In addition, artificial intelligence can be used to provide the input parameters mentioned above. Full article

Given the increasing environmental concerns and energy consumption, the transformation of the new energy vehicle industry is a key link in the innovation of the energy structure. The shift from traditional fossil fuels to clean energy encompasses various dimensions such as technological innovation, policy support, infrastructure development, and changes in consumer preferences. Predicting the future ownership of electric vehicles (EVs) and then estimating the energy demand for transportation is a pressing issue in the field of new energy. This study starts from dimensions such as cost, technology, environment, and consumer preferences, deeply explores the influencing factors on the ownership of EVs, analyzes the mechanisms of various factors on the development of EVs, establishes a predictive model for the ownership of motor vehicles considering the penetration of electric vehicles based on system dynamics, and then simulates the future annual trends in EV and conventional vehicle (CV) ownership under different scenarios based on the intensity of government funding. Using energy consumption formulas under different power modes, this study quantifies the electrification energy demand for transportation flows as fleet structure changes. The results indicate that under current policy implementation, the domestic ownership of EVs and CVs is projected to grow to 172.437 million and 433.362 million, respectively, by 2035, with the proportion of EV ownership in vehicles and energy consumption per thousand vehicles at 28.46% and 566,781 J·km⁻¹, respectively. By increasing the technical and environmental factors by 40% and extending the preferential policies for purchasing new energy vehicles, domestic EV ownership is expected to increase to 201.276 million by 2035. This study provides data support for the government to formulate promotional policies and can also offer data support for the development of basic charging infrastructure. Full article

High-pressure air injection (HPAI) is an enhanced oil recovery process in which compressed air is injected into deep, light oil reservoirs, with the expectation that the oxygen in the injected air will react with a fraction of the reservoir oil at an elevated temperature to produce carbon dioxide. The different chemical reactions taking place can be grouped into oxygen addition, thermal cracking, oxygen-induced cracking, and bond scission reactions. The latter reactions involve the combustion of a flammable vapor as well as the combustion of solid fuel, commonly known as “coke”. Since stable peak temperatures observed during HPAI experiments are typically below 300 °C, it has been suggested that thermal cracking and combustion of solid fuel may not be important reaction mechanisms for the process. The objective of this work is to assess the validity of that hypothesis. Therefore, this study makes use of different oxidation and combustion HPAI experiments, which were performed on two different light oil reservoir samples. Modeling of those tests indicate that thermal cracking is not an important reaction mechanism during HPAI and can potentially be ignored. The work also suggests that the main fuel consumed by the process is a flammable vapor generated by the chemical reactions. This represents a shift from the original in situ combustion paradigm, which is based on the combustion of coke. Full article

Traceability is a cornerstone of sustainable honey production and consumption. Honey fraud and a lack of traceability have been recently highlighted by the European Commission. Innovative systems aimed at guaranteeing food safety ’from farm to fork’ and improved controls are highly recommended. Within the framework of the BPRACTICES project, part of the European Union’s Horizon 2020 research and innovation program, and the ERA-Net SusAn initiative—focused on Sustainable Animal Production Systems—an advanced traceability system has been developed. This system utilizes QR code and radio-frequency identification (RFID) technology, along with a user-friendly web application, to facilitate direct interactions between producers and consumers. Despite existing research, studies on the information needs of Italian consumers regarding honey and its traceability remain limited. Understanding these needs is vital for creating effective communication strategies that enhance consumer satisfaction and trust. This study aims to identify the needs of Italian consumers’ honey during the purchasing and consumption decisions. To explore consumer perceptions, behaviors, expectations, and needs regarding honey, we employed diverse social research methodologies, including a quantitative online survey, paper-and-pencil interviews, and focus groups. The results of this study indicate a robust demand for more information on honey’s origin, production processes, and beekeeping practices, aligning with the recent EU Directive 2024/1438, which mandates clear labeling. Italian consumers would be willing to pay a premium for honey that offers detailed information about production practices and transparency. The positive reception of QR code technology by consumers suggests a growing openness to digital tools that enhance transparency and access to information. Ultimately, this research emphasizes the need for the beekeeping sector to adopt sustainable practices, improve traceability systems, and actively engage with consumers to foster trust and ensure long-term viability in the honey market. By addressing these information needs, the sector can align itself with increasing consumer demand for quality, sustainability, and transparency. Full article

Service quality is crucial to consumer loyalty. However, it is challenging to understand and meet customer expectations effectively. Translating customer feedback into actionable insights in the service industry poses difficulties, particularly without a systematic approach that balances customer requirements with business constraints and strategic objectives. This study proposes an approach that integrates customer perspectives into multi-criteria decision models by utilizing the fuzzy Kano model to capture service perceptions and minimize response uncertainty. It also uses 5W2H and PROMETHEE II to formulate service improvement actions and establish prioritizations, providing a structured framework for managerial implementation. When implemented in the food truck sector, this framework proves effective in addressing unique challenges, enhancing service quality, boosting customer satisfaction, and fostering loyalty. This study offers a valuable contribution to management by presenting a replicable model that aids managers in making strategic decisions, aligning customer perspectives with management efforts, and providing insights for continuously improving initiatives within the food service industry. Full article

Virtual streamers, as a typical application of AI-enabled digital humans, are increasingly being utilized in live-streaming commerce due to technological advancements and industry innovations. Although virtual streamers present several benefits, there is potential for adverse effects when they do not align with consumer expectations. Drawing upon expectancy violations theory, this study developed a theoretical model to explore whether and how consumers’ expectation violations during human–virtual streamer interactions affect consumers’ discontinuance behavior. Through an online questionnaire survey of 307 Chinese consumers with prior experience interacting with virtual streamers, this study used a partial least squares structural equation model to analyze the research model. The empirical results indicated that professionalism expectation violation, empathy expectation violation, and responsiveness expectation violation positively influenced consumers’ distrust and dissatisfaction, which subsequently led to discontinuance behavior. This study contributes to the literature on live-streaming commerce, human–AI interaction, and expectancy violation theory. Furthermore, the findings offer valuable insights for practitioners in the field of live-streaming commerce by enabling them to formulate preventive or remedial strategies to mitigate potential negative outcomes when implementing virtual streamers. Full article

This paper takes corporate social responsibility goodwill and consumers’ reference low-carbon level as endogenous variables of joint carbon emission reduction in the “supplier–manufacturer–retailer–consumer” supply chain system. The joint carbon emission reduction strategies of this four-tier system are analyzed from a dynamic perspective by considering random factors that affect the endogenous variables. Three stochastic differential games are proposed to examine the mechanism between each player, namely the cooperative model, Nash non-cooperative model, and Stackelberg master–slave model. Compared to the Nash non-cooperative game, the manufacturer/supplier-led Stackelberg master–slave game leads to Pareto improvement in the profits of the entire supply chain system and each player. The cooperative game demonstrates the highest expected emission reduction and corporate social responsibility goodwill, but also the highest variance. More importantly, the reference low-carbon level embraces consumers’ subjective initiative in the dynamic of carbon emission reduction. This level is an internal benchmark used to compare against the observed low-carbon level. This paper provides a theoretical foundation for strategic decision-making in emission reduction, contributing to sustainable development. By addressing environmental, economic, and social sustainability, it promotes climate action through carbon reduction strategies and offers policy recommendations aligned with the Sustainable Development Goals. Full article

Coastal aquaculture and local fisheries interact in shared marine environments, influencing each other synergistically and/or antagonistically. Salmon farming, notably with open-net sea cages along the Norwegian coast, attracts wild fish due to increased food availability from uneaten feed, but it also exposes wild fish to farm emissions like waste and toxic chemicals (de-lice treatments, antifouling and medical agents). The attraction behaviour of wild fish can impact fatty acid composition in fish tissues, influenced by the high terrestrial fat content in salmon aquafeed. We study how the Atlantic cod, aggregating around salmon farms in a subarctic fjord in Northern Norway, can be affected, potentially altering their natural diet and fatty acid profiles. Our study compares the muscle-tissue fatty acid compositions of cod caught near aquaculture facilities (impact) versus fish caught in neighbouring fjords (control), and we hypothesise decreased omega-3 fatty acids near farms. The analysis revealed no significant differences in the fatty acid concentrations or categories between the impacted and control fish, challenging our initial expectations. However, differences were found for C18:1(n9)t (elaidic acid), with a higher value in the impacted fish. These findings suggest that salmon farming’s influence on cod’s fatty acid profiles in the flesh (i.e., relevant for the nutritional quality of the fillets that consumers eat) may be limited or minimal despite their aggregative behaviours around farms. The threshold levels of salmon feed consumed by wild cod before it affects the quality and survival of, e.g., sperm or other life stages, are not known and require new investigations. This study underscores the complexity of interactions between aquaculture and wild fisheries, impacting both ecological dynamics and consumer perspectives on seafood quality and health benefits. Full article

The research states that the exacerbation of the climate crisis observed in recent years is accompanied by an increase in ground-level temperatures, natural disasters, loss of water resources, and other extreme weather events, which significantly impact the economy, water, and food security of water-dependent countries and the expected consequences shortly. For this purpose, during this research, data from the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan were studied, and a sample of private indicators of the country’s agribusiness digitalization potential was made, which were further normalized to construct a mathematical model of the correlation between the level of digitalization of the agricultural sector and the volume of water consumed by agribusiness. The feasibility of using agricultural notes (electronic agricultural receipts) in Kazakhstan’s agribusiness as an innovative tool for attracting funds to develop agricultural production is justified. It is highlighted that the agricultural note has the potential to become a successful tool for attracting funds for the digitalization of the agricultural sector, provided it acquires the status of a full-fledged market product, in which state regulation of Kazakhstan’s agribusiness digital transformation plays a significant role. Full article

Europe has set a target to become a decarbonised continent by 2050. To achieve this, intervention in buildings is crucial, as they serve as significant energy consumers and greenhouse gas emitters. This intervention encompasses two essential pathways: renovation and digitalisation. The combination of these two aspects gives rise to elements such as the Digital Building Logbook (DBL), a digital data repository expected to enhance the pace and quality of renovation efforts. This paper introduces, for the first time, a European DBL data model with a specific focus on building renovation purposes—the DBrL. It outlines its initial requirements, constituent entities, relationships, and attributes. While acknowledging the need to address issues related to data protection, integration with existing data sources, and connections with Building Information Modelling (BIM) and Geographic Information System (GIS) in subsequent design phases, the study’s outcome represents a significant stride in defining this tool. Full article

The preparation of traditional wood-based panels mostly uses adhesives such as urea-formaldehyde resin and phenolic resin, which not only consumes petrochemical resources but also releases formaldehyde, posing potential health risks to the human body. Lignin, a natural adhesive in plant cells, is characterized by high reactivity, and it is expected to aid in the development of a new generation of green formaldehyde-free adhesives. However, current studies of lignin adhesives have revealed that while strides have been made in reducing formaldehyde emissions, its residual presence remains a concern, an issue which is compounded by inadequate water resistance. Dehydrogenated Polymer (DHP) has a lignin-like structure and good water resistance, offering a new option for the development of formaldehyde-free adhesives. In this paper, DHP and glucuronic acid were reacted with each other in a simulated hot-pressing environment to obtain DHP-glucuronic acid complex, and then the structure of the complex was characterized by infrared nuclear magnetic resonance to verify whether DHP can be efficiently connected with hemicellulose components under hot-pressing conditions. The results showed that the thermal condensation reaction of DHP and glucuronic acid can generate ester bonds at the Cα position in a simulated hot-pressing environment. This paper explores the thermal condensation mechanism of DHP and glucuronic acid, which is helpful for understanding the bonding process between adhesives and components of wood-based panels in the hot-pressing process, and provides key theoretical support for the design of more sustainable lignin adhesives. Full article

The development of smart agriculture has become a critical issue for the future of smart cities, with large-scale management of aquaculture posing numerous challenges. Particularly in the fish farming industry, producing single-sex fingerlings (especially male fingerlings) is crucial for enhancing rearing efficiency and could even provide key support in addressing future global food demands. However, traditional methods of manually selecting the gender of broodfish rely heavily on experienced technicians, are labor-intensive and time-consuming, and present significant bottlenecks in improving production efficiency, thus limiting the capacity and sustainable development potential of fish farms. In response to this situation, this study has developed an intelligent identification system based on the You Only Look Once (YOLO) artificial intelligence (AI) model, specifically designed for analyzing secondary sexual characteristics and gender screening in farmed fish. Through this system, farmers can quickly photograph the fish’s cloaca using a mobile phone, and AI technology is then used to perform real-time gender identification. The study involved two phases of training with different sample sets: in the first phase, the AI model was trained on a single batch of images with varying parameter conditions. In the second phase, additional sample data were introduced to improve generalization. The results of the study show that the system achieved an identification accuracy of over 95% even in complex farming environments, significantly reducing the labor costs and physical strain associated with traditional screening operations and greatly improving the production efficiency of breeding facilities. This research not only has the potential to overcome existing technological bottlenecks but also may become an essential tool for smart aquaculture. As the system continues to be refined, it is expected to be applicable across the entire life cycle management of fish, including gender screening during the growth phase, thereby enabling a more efficient production and management model. This not only provides an opportunity for technological upgrades in the aquaculture industry but also promotes the sustainable development of aquaculture. The smart aquaculture solution proposed in this study demonstrates the immense potential of applying AI technology to the aquaculture industry and offers strong support for global food security and the construction of smart cities. Full article

Different refund policies offered by e-commerce platforms provide diverse options for consumers and are crucial for enhancing after-sales service. This study constructs a refund and ordering decision model based on three typical refund policies: both basic refund and refund guarantee option (‘Policy I’), basic refund only (‘Policy II’), and refund guarantee option only (‘Policy III’). We examine scenarios where demand is influenced by price, refund policies, and stochastic factors, and returns are affected by refund policies, aiming to determine the optimal refund and ordering decisions for fresh produce e-commerce platforms. Our results indicate that, under the same parameters, the platform achieves the maximum order quantity and highest expected profit with Policy I. The return rate under Policy I is always higher than under Policy III, but not consistently higher than under Policy II. Additionally, as the sensitivity of demand to the refund policy increases, both the order quantity and basic refund price rise, while the refund guarantee option price decreases. Conversely, as the sensitivity of returns to the refund policy increases, the opposite occurs. Although market demand uncertainty does not impact the basic refund or refund guarantee option prices, the platform must increase order quantities to manage market volatility. Full article