During the operation of a nuclear power plant (NPP), the generation of radioactive waste, including dry active waste (DAW), concentrates, spent resin, and filters, mandates the implementation of appropriate disposal methods to adhere to Korea’s waste acceptance criteria (WAC). In this context, this study investigates the potential use of polymer concrete (PC) as a high-integrity container (HIC) material for solidifying and packaging these waste materials. PC is a versatile composite material comprising binding polymers, aggregates, and additives, known for its exceptional strength and chemical stability. A comprehensive analysis of PC’s long-term integrity was conducted in this study. First, its compressive strength, which is crucial for ensuring the structural stability of HICs over extended periods, was evaluated. Subsequently, the resilience of PC was tested under various stress conditions, including biological, radiological, thermal, and chemical stressors. The findings of this study indicate that PC exhibits remarkable long-term properties, demonstrating exceptional stability even when subjected to diverse stressors. The results therefore underscore the potential viability of PC as a reliable material for constructing high-integrity containers, thus contributing to the safe and sustainable management of radioactive waste in NPPs.

In the realm of dental prosthesis fabrication, obtaining accurate impressions has historically been a challenging and inefficient process, often hindered by hygiene concerns and patient discomfort. Addressing these limitations, Company D recently introduced a cutting-edge solution by harnessing the potential of intraoral scan images to create 3D dental models. However, the complexity of these scan images, encompassing not only teeth and gums but also the palate, tongue, and other structures, posed a new set of challenges. In response, we propose a sophisticated real-time image segmentation algorithm that selectively extracts pertinent data, specifically focusing on teeth and gums, from oral scan images obtained through Company D's oral scanner for 3D model generation. A key challenge we tackled was the detection of the intricate molar regions, common in dental imaging, which we effectively addressed through intelligent data augmentation for enhanced training. By placing significant emphasis on both accuracy and speed, critical factors for real-time intraoral scanning, our proposed algorithm demonstrated exceptional performance, boasting an impressive accuracy rate of 0.91 and an unrivaled FPS of 92.4. Compared to existing algorithms, our solution exhibited superior outcomes when integrated into Company D's oral scanner. This algorithm is scheduled for deployment and commercialization within Company D's intraoral scanner.

Healthy and environmentally friendly food is a subject of increasing prominence all around the world, and especially so in developing countries such as India, where consumption of agricultural goods produced in a sustainable environment with a low reliance on pesticides, antibiotics, hormones, and genetic manipulation is a real challenge. Consumer interest in green food items is increasing as safety and health concerns grow, and researchers are calling for further investigation of green food consumer behavior. Although a large number of research was done on environmental performance in industrialized countries, very little research has been conducted among Indian consumers. Furthermore, the gap between intention to consume green food products and actual behavior remains under-investigated. This gap can be investigated through the prism of theory of planned behavior (TPB). This theory has been widely used in green consumer studies: it seeks to explain how individuals make decisions and take actions based on their attitudes, beliefs, and perceived behavioral control. However, the TPB has not been extended to account for cultural values (i.e., Hofstede’s cultural framework), which can play an important role in shaping consumer attitudes and behaviors. Therefore, this research investigates the application of the extended TPB model in the context of green food products with a quantitative survey among Indian consumers (N=387). The results show that long-term (health) orientation and collectivism influence both green purchase intention and behavior. This effect is explained by subjective norms, perceived value, and environmental attitudes of the consumers.

Previous research has compared still images employing the actor’s perspective to those employing the observer’s perspective and found that the former increases service evaluations if the consumers are promotion-focused, whereas the latter increases service evaluations if the consumers are prevention-focused. The research compares three kinds of vlogs, i.e., vlogs employing the actor’s perspective, vlogs employing the observer’s perspective without the actor’s face, and vlogs employing the observer’s perspective with the actor’s face. The results show that the highest service evaluations are induced by the actor’s perspective in case of promotion-focused consumers, whereas they are induced by the observer’s perspective without the actor’s face in case of prevention-focused consumers.

Algorithms are rapidly altering the way society operates (SIOP, 2020). Algorithms are used in modern businesses for tasks such as hiring, advising investors on financial matters, recommending new products to customers (Shankar, 2018). However, lay people frequently oppose them, a phenomenon known as algorithm aversion (e.g., Dietvorst et al., 2015). While prior research tries to address this issue by identifying cognitive and affective predictors of algorithm aversion, we seek to contribute to the algorithm aversion literature by investigating an understudied antecedent of people’s support for algorithm adoption—their cultural values (Dietvorst & Bartels, 2022).

Plastic pollution is one of the biggest environmental problems in the world. In modern society, the consumption of single-use plastics in the food service industry has increased along with the increase in food-away-from-home. The COVID-19 pandemic has attacked the consumption of single-use plastic in the restaurant industry. During the COVID-19 pandemic, especially the US has retracted the related laws and policies regarding using single-use plastic for fast food and carry-out food, and customers have increased their use of single-use plastic for fast food and carry-out food due to worries about hygiene. Even though sustainability has been a novel topic in hospitality literature, a majority of studies have focused on the consumers’ perception, attitude, or behavioral willingness toward sustainability. To fill this gap in research, finding an effective way to influence consumers’ behavioral change becomes important and necessary.

Non-fungible tokens (NFTs) exploded onto the global digital landscape in 2020, spurred by pandemic-related lockdowns and government stimulus (Ossinger, 2021). An NFT is a unit of data stored on a blockchain that represents or authenticates digital or physical items (Nadini, 2021). Since it resides on a blockchain, NFTs carry the benefits of decentralization, anti-tampering, and traceability (Joy et al., 2022). Fashion brands quickly capitalized on these features, launching fashion NFT collections and garnering significant profits from the sale of fashion NFTs in 2021 (Zhao, 2021). For example, Nike’s December 2021 acquisition of RTFKT (pronounced “artifact”) resulted in USD 185 million in sales less than a year after their acquisition (Marr, 2022).

There are a lot of brand experience in Metaverse. For example, we can participate in Samsung Galaxy Fan party, UC Berkeley graduation class, and even Ralph Lauren store in Metaverse. When the consumers experience such events in Metaverse, they have to use their avatar by making a user name. They have the option of using either their real or fictional name in Metaverse. There are two types of avatar in Metaverse. First, they can use actual self-avatar by using their real name. Second, they can create totally new avatars using made up name. The name is one of the symbols of self. Therefore, we can easily predict that consumer experience with avatar will affect the consumer perception differently. Which type of avatar will then enhance the brand engagement? Results show that the consumer experience with avatars affected brand attitudes differently. Also, the consumer's experience with avatars based on their actual images in the Metaverse affected the positive brand attitude. This study suggests that Metaverse avatars can also let people interact with themselves and with each other in parasocial ways. This study examines the role of avatar in virtual world; consumers experience with avatar can provide useful implications in terms of digital transformation.

The sharing economy claims for research on its particularities and implications for management. This paper explores the way hosts of Peer-to-Peer Accommodation (P2P) develop relationship marketing with their guests and how it influences the business. The researchers conducted 30 semi-structured interviews to hosts of Airbnb, in order to obtain their perspective on the importance and application of relationship marketing in this context. Hosts with a B2C and a C2C business perspective were interviewed, and cultural differences in the relationship approach were also considered. The results show that the hosts are aware of the importance of interactions and personal contact with guests. Different results were identified depending on the type of business, accommodation, the culture and nationality of guests. Findings show that relationship marketing is highly explored in P2P sharing accommodation, exploring the interactivity of digital platforms to deepen those relationships.

How do people perceive new technology-embedded machines? Based on the previous literature on mind perception, this research proposes how people perceive the mind of machines including artificial intelligence (AI), robots, recommendation systems, chatbots, and self-service technologies (SSTs).

Since consumers have expanded their interest in global countries with the ease of access to global content through online platforms such as YouTube, marketing practitioners endeavor to uncover an underlying mechanism on how consumers’ interest in global countries would prompt their digital shopping behavior. However, prior literature has not concentrated on the influence of watching videos about global countries on consumers’ digital shopping intentions. By scrutinizing a proprietary dataset regarding consumers’ YouTube watching history and shopping website/app usage behavior, we find that watching global content could increase consumers’ digital shopping duration. In addition, we also find that consumers watching more global content have variety-seeking tendencies when they use shopping websites and apps. Furthermore, we investigate the moderating factors such as social media search and consumers’ sentiment toward different countries on digital shopping. Our findings contribute to the international marketing literature and provide managerial implications to digital media platforms and global companies that utilize target recommendations strategy for marketing communication.