Social networking sites (SNS) is an image-oriented sharing platform and can form social relationships among users. This allows individuals to create and share the contents which include their stories, ideas, reviews, opinions, and evaluations, etc. Consumers who sympathize with and trust these contents will follow them and form the relationships. Contents created and shared by individual users is more effective than advertisements delivered by brands in generating electronic word of mouth (e-WOM). Accordingly, opinion leaders and influencers who influence potential customers based on their opinions and style related contents have emerged in various fields such as health, fitness, fashion, beauty, food, and high-tech.

The body of knowledge from psychology has been useful to marketing for understanding consumer minds and behaviors (Jia et al., 2018). Daily activities, such as movie watching, grocery shopping, online shopping, drinking coffee (with friends or alone), and making an in-app purchases on social media, all involve consumption which is affected by the perceptions, attitudes, and behaviors of the decision maker (i.e., consumers). But when the ways in which we sense and interact with the world change, how does it shift our ways of communicating with each other and the processes of forming perceptions, attitudes, and behaviors?

Consumers' online reviews have become more powerful in the Internet market. Consumers share reviews, post comments and constantly evaluate products online. In previous studies, the analysis of online reviews mainly focused on purchasing products based on consumers' own use experience, but in innovative products, it was difficult to find an analysis of product acceptor's response to product user reviews. In particular, there is no online review study of VR covered in this study. This study not only quantitatively analyzed online reviews of consumers who purchased VR products on Amazon, an online distribution site, but also qualitatively analyzed them through crawling. This study used Amazon's VR product user review, where purchases were confirmed, to select algorithms that are more likely to be matched by predicting a helpful review and presenting a predictive model. In addition, the online review extracted deep text associated with Helpful and conducted topical modeling. As a result, topics related to 1) experience in use, 2) post-product evaluation, 3) product composition and peripherals, 4) immersion, and 5) comfort were highly acceptable to potential inmates. To enhance the acceptability of innovative products through online reviews, it is not just highlighting the product advantages of VR, but also suggests that the link between smartphones and applications can bring in more potential users. Also, interworking with other peripheral devices (speakers or screens) can be predicted as a way to increase the acceptability of VR products. From a marketing perspective, this study has found targeted topics that help consumers in pioneering the VR market, which will help potential customers create the services they want.

Covid-19 pandemic has significantly affected online advertising market. The pandemic has changed customers’ shopping behavior by decreasing customer traffic in offline businesses but increasing customers’ online activities that has led to growth of online shopping and advertising. While the outbreak of Covid-19 has sparked growth of online advertising in general, its impact on various industries may not be the same, given the differences in product characteristics and consumer behavior across different products and services. This paper aims to address this question by empirically examining how Covid-19 has affected online search advertising market. First, we examine how Covid-19 has affected the behavior of online users and advertisers, the main stakeholders in the search advertising market, in terms of user traffic and clicks and advertiser bids and payments. Second, we examine if the impacts of Covid-19 on behavior of online users and advertisers would be different in various industries.

Coffee has become one of the most popular beverages since the 1960s. These days, coffee is more about pleasure, experience, success, lifestyle, high concentration, and social status. Bhumiratana et al. (2014) state that individuals consume coffee with the intention of eliciting positive high-energy emotions, which can help in reducing fatigue, increasing alertness, improving work performance, and promoting a focused mental state, such as feeling motivated, productive, in-control, or clear-minded. Aguirre (2016) and Bhumiratana et al. (2014) also suggest that people drink coffee to stay awake. As coffee has popularized, café has become important as a place for people meetings. However, customers may tend to evaluate coffee as a service product depending on what service encounter they faced. They might perceive the taste and quality of coffee differently by following their mindset and stereotypes about perfect coffee. Customers pay attention to many factors in consuming coffee depending on service encounters. They may pay less for coffee prepared by robots and evaluate coffee prepared by humans as more precious. Therefore, this study proposes a specific factor theoretical framework of customers’ mindset about coffee prepared by human baristas and robot-barista. The study aims to determine how customers evaluate coffee prepared by baristas and robot-barista. Specifically, to which characteristics they pay attention in barista or robot-barista cases. Then, the study examines relationship between expected and perceived coffee characteristics and intentions to revisit café. Finally, the study compares customers' expectations about coffee depending on contact (barista) or untact (robot-barista) service.

With the development of information technology, online food delivery services have significantly changed people’s food consumption patterns. The outbreak of COVID-19 has further facilitated the development due to restaurant restrictions and social distancing measures. Due to the emergence of online food delivery services, scholars have paid increasing attention to this popular topic, and a large number of studies have examined which factors are related to consumers’ intention to use online food delivery services. However, previous studies showed inconsistent findings, and relationships between variables lack a comprehensive understanding. Therefore, this study aimed to develop a research model and examine the factors influencing consumers’ intention to use online food delivery services. By reviewing and analyzing 52 studies with 53 independent samples (N = 22,937), the meta-analytic structural equation modeling approach was carried out to assess the research model. The findings indicate that two attributes of online food delivery services (i.e., convenience and price-saving orientation) play different roles in the research model. Specifically, convenience significantly impacted perceived ease of use but had no direct impact on perceived usefulness. Price-saving orientation significantly influenced both perceived ease of use and perceived usefulness. Moreover, relationships between perceived ease of use, perceived usefulness, and perceived trust were significant, and these factors ultimately significantly led to the intention to use food delivery services. The findings contribute to theoretical advancement in the extant literature on food delivery services and help firms develop to provide better food delivery services for consumers’ continuous usage.

Customers’ service experience is related to the perceived state in the process of interacting with the target at various channel touchpoints (Kaushal & Yadav, 2023). Furthermore, positive customers’ service experiences can increase the repurchase intention of buyers by strengthening the interconnection and cooperation between buyers and suppliers in business-to-business (B2B) firms and reinforcing corporate competitive positioning.

Even though more than half a century has passed since the concept of Corporate Social Responsibility (CSR) emerged, many people still have an interest in CSR. According to a survey, eighty-seven percent of American consumers said they would purchase a product produced by a corporation that supported at least one specific social issue. Also, more than three-quarters (76%) would refuse to buy a product if they found out the company endorsed the issue contrary to their beliefs. These numbers align with consumers’ intent to purchase or boycott based on CSR commitment. Do CSR activities affect sales? Many studies have been conducted to answer this question in the academic field, but the results have not been consistent. Some articles reported that CSR activities positively impact the firm’s various aspects, including financial performance. But other studies reported that the impact of CSR on firms’ performance is unclear or even harmful.

Metaverse provides technology for people to connect, find communities, and grow businesses. Its sales have seen growth during the COVID-19 pandemic. In an era of metaverse, luxury brands such as Gucci, Ralph Lauren, Burberry, Balenciaga, and Dolce & Gabbana are trying to adapt to new changes. They launched NFT(Non-fungible token) goods, digital fashion, and virtual luxury goods on various metaverse platforms such as Zepeto, Roblox, and Fortnite. For example, Ralph Lauren in Zepeto provides various types of luxury items, immerses in virtual performances, and has a game plot interaction. As people immerse themselves in the Metaverse, they feel happy from various activities—such as watching advertisements, drinking juice, and playing with friends. Thus, what factors should be considered when the luxury brands manage the metaverse?

This research intends to examine whether these types of data – behavioral versus social networking data – affect consumer response to personalized ads. With the advancement in technology, marketers have access to various types of personal data, including their online/offline behaviors and social networking activities, and use those data to retarget consumers. Moreover, this research examines the moderating role of SNS privacy concerns on consumer response to different types of retargeted ads. The findings of this research may offer theoretical and practical implications to understand consumers' responses to retargeted ads that use social networking information.

We propose a sales prediction model based on the number of new members, online advertising, and consumer reviews for a short period. Considering purchase behaviors of new and existing members, we predict reliable sales amounts, which can be monthly updated. Our study provides digital marketers with a feasible prediction approach.

The propagation speed of a circumstellar pattern revealed in the plane of the sky is often assumed to represent the expansion speed of the wind matter ejected from a post-main-sequence star at the center. We point out that the often-adopted isotropic wind assumption and the binary hypothesis as the underlying origin for the circumstellar pattern in the shape of multilayered shells are, however, mutually incompatible. We revisit the hydrodynamic models for spiral-shell patterns induced by the orbital motion of a hypothesized binary, of which one star is losing mass at a high rate. The distributions of transverse wind velocities as a function of position angle in the plane of the sky are explored along viewing directions. The variation of the transverse wind velocity is as large as half the average wind velocity over the entire three dimensional domain in the simulated models investigated in this work. The directional dependence of the wind velocity is indicative of the overall morphology of the circumstellar material, implying that kinematic information is an important ingredient in modeling the snapshot monitoring (often in the optical and near-infrared) or the spectral imaging observations for molecular line emissions.

본 연구는 아시아의 국제관계가 변화하는 맥락에서 "아시아 나토"의 실 행 가능성과 잠재적 영향을 검토한다. 아시아 버전 나토의 가능성을 분 석하기 위해 세 가지 목표를 추구한다: (1) 나토의 성격을 조사하고 아시 아에서의 잠재적 적용을 검토한다, (2) 세력균형이론과 위협균형이론의 관점에서 나토의 과거 실패를 검토한다, (3) 정치와 군사적 도전을 고려 한 아시아 나토의 실행 가능성을 평가한다. 이 연구는 미국과 일본을 중 심으로 아시아 나토에 대한 관심이 증가한 지정학적 변화를 탐구한다. 현재 미중 균형과 위협 사이의 균형은 양자 및 삼자 동맹을 설정하는 데 이르렀지만 아시아 나토의 가능성은 여전히 쉽지 않다. 그러나 중국이 지역 패권 추구로 인한 압도적인 외부 위협을 초래하면, 아세안 국가들 은 집단 안보 체제에 가입할 수 있다. 본 논문은 특히 이러한 상황에서 한국이 직면할 수 있는 문제점에 대해서도 지적한다.

To broaden the utilization of nuclear energy, uranium as a fuel should be mined indispensably. Mining accounts for the largest portion of the cost of producing the uranium assembly. Therefore, this study analyzes the trends of uranium prices, which have a significant impacts on the mining cost. Uranium production contributing to the price fluctuations is explained in five periods from 1945 to the present. Moreover, the series of events affecting uranium prices from the 1970s until the present are verified. Among them, the most recent incidents considered in this study are the following: COVID-19 pandemic, Kazakhstan unrest, and Russia-Ukraine war. European countries have started to reconsider the transition to nuclear power to reduce their dependence on Russian oil and gas, which has contributed to the surge in uranium prices. Based on the results of this study, various international issues have been closely associated with the nuclear power industry and uranium, affecting the production of uranium and its price.

Compared to operational wastes, nuclear power plant (NPP) decommissioning wastes are generated in larger quantities within a short time and include diverse types with a wider range of radiation characteristics. Currently used 200 L drums and IP-2 type transport containers are inefficient and restrictive in packaging and transporting decommissioning wastes. Therefore, new packaging and transport containers with greater size, loading weight, and shielding performance have been developed. When transporting radioactive materials, radiological safety should be assessed by reflecting parameters such as the type and quantity of the package, transport route, and transport environment. Thus far, safety evaluations of radioactive waste transport have mainly targeted operational wastes, that have less radioactivity and a smaller amount per transport than decommissioning wastes. Therefore, in this study, the possible radiation effects during the transport from NPP to disposal facilities were evaluated to reflect the characteristics of the newly developed containers and decommissioning wastes. According to the evaluation results, the exposure dose to transport workers, handling workers, and the public was lower than the domestic regulatory limit. In addition, all exposure dose results were confirmed, through sensitivity analysis, to satisfy the evaluation criteria even under circumstances when radioactive materials were released 100% from the container.

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

Large amounts of waste and wastewater from aquaculture have negatively impacted ecosystems. Among them, shrimp aquaculture wastewater contains large amounts of nitrogen contaminants derived from feed residues in an aerobic environment. This study isolated candidate strains from adult rockworms to treat shrimp aquaculture wastewater (SAW) in an aerobic environment. Among 87 strains isolated, 25 grew well at the same temperature as the shrimp aquaculture with excellent polymer degradation ability (>0.5 cm clear zone). Six isolates (strains AL1, AL4, AL5, AL6, LA10, and PR15) were finally selected after combining strains with excellent polymer degradation ability without antagonism. 16S rRNA sequencing analysis revealed that strains AL1, AL4, AL5, AL6, LA10, and PR15 were closely related to Bacillus paramycoides, Bacillus pumilus, Stenotrophomonas rhizophila, Bacillus paranthracis, Bacillus paranthracis, and Micrococcus luteus, respectively. When these six isolates were applied to SAW, they reached a maximum cell viability of 2.06×105 CFU mL-1. Their chemical oxygen demand (CODCr) and total nitrogen (TN) removal rates for 12 h were 51.0% and 44.6%, respectively, when the CODCr/TN ratio was approximately 10.0. Considering these removal rates achieved in this study under batch conditions, these six isolates could be used for aerobic denitrification. Consequently, these six isolates from rockworms are good candidates that can be applied to the field of aquaculture wastewater treatment.

채소는 여러 건강상의 이점을 주는 식이섬유를 다량 함 유하고 있다. 채소는 국내에서 다양한 형태로 섭취되고 있 으며, 특히 생으로 먹거나 나물의 형태로 가장 많이 섭취 되고 있다. 나물은 여러 조리 방법이 있는데, 가장 흔한 방법은 데치고 무치는 형식이다. 한국에서 나물로 흔히 섭 취되는 국내산 참나물, 깻잎, 곰취, 우엉, 마늘쫑을 데친 후, 데친 채소와 생 채소를 한국 식품공전에 따라서 식이 섬유와 유리당을 분석하고 비교하였다. 참나물, 우엉뿌리 와 깻잎은 데친 후에 총 식이섬유가 감소하였으나, 곰취 와 마늘쫑은 각각 6.09±0.49에서 6.43±0.01 g/100 g 과 4.52±0.35 에서 5.09±0.04 g/100 g으로 증가하였다. 유리당 분석 결과, 깻잎을 제외한 채소들에서 sucrose, glucose와 fructose가 검출되었으며, 깻잎은 sucrose가 검출되지 않았 다. 분석한 채소들 중에서 sucrose 함량이 가장 높은 채소 는 우엉 뿌리 (1.71±0.07 g/100 g) 였으며, glucose와 fructose는 각각 1.65±0.02 와1.73±0.02 g/100 g로 마늘쫑 이 가장 높게 나타났다. 채소를 데친 후, 곰취 (0.10±0.01 에서 0.14±0.01 g/100 g)와 마늘쫑 (0.76±0.00 에서0.83±0.01 g /100 g)에 함유된 sucrose를 제외한 다른 유리당 함량은 전 부 감소하였다. 이 연구를 통해 채소를 데치면 채소에 함 유된 유리당과 식이섬유의 함량이 증가하거나 감소할 수 있다는 것을 나타낼 수 있다. 또한, 이러한 영양 정보를 통해 소비자들에게 어떠한 조리 상태의 채소를 섭취할지 선택할 때에 도움을 줄 수 있을 것이다.

In this paper, the basic and the extensional meaning of the Chinese word, shui (水), and the Korean word, mul (물), were compared for their similarities and differences, based on the different word meaning characteristics. Both words have the basic meaning of “water.” The extensional meaning and usage of these two words overlap semantically under certain conditions, but they have different characteristics in the two languages from the perspective of word formation, reflecting the differences in thinking and cognitive framework of the different cultural backgrounds. The research also found that the words differ greatly in terms of semantic extension. Mul in particular had a far richer and more diverse extended semantic meaning than shui.