이 연구에서는 선택실험법을 통해 수집한 진술선호자료를 기반으로 세 가지 모형을 이용하여 축산물(쇠고기, 돼지고기 제품)의 이력추적성과 원산지 속성에 대한 소비자 선호도를 분석하였다. 우리의 연구 결과에 따르면 쇠고기의 경우 한우 제품에 대한 지불의사금액 대비 이력추적성 속성에 대한 지불의사금액의 비율이 92~97%로 매우 높았다. 돼지고기의 경우에는 한돈 제품에 대한 지불의사금액 대비 추적가능한 속성에 대한 지불의사금액의 비율은 약 76~82% 수준이었다. 이러한 결과는 국내 소비자들이 국내산 육류 제품에 대한 선호도에 따라 어느 정도 식품 안전 속성(추적성)에 높은 가치를 두고 있음을 의미한다. 다시 말해 축산물 이력제가 쇠고기와 돼지고기의 식품안전성에 대한 소비자의 신뢰를 구축하는 데 크게 기여하고 있음을 보여준다고 할 수 있다.

This study was conducted to select representative agricultural products (4 types of fruits and 4 types of wild vegetables) in Chungju, define their sensual characteristics, derive suitable flavour-pairing and recipes for each ingredient, and use them as a cornerstone in the development of menus. For the experiment, 10 experts were selected to choose 8 representative agricultural products in Chungju, and 18 menus were selected through a flavour-pairing survey. A consumer panel (a total of 413 people, 105 in their 20s, 103 in their 30s, 103 in their 40s, and 102 in their 50s) for evaluating the characteristics of consumer preferences was selected. After the flavour-pairing survey ‘sweet taste’, ‘light flavour’, ‘soft flavour’, ‘savoury flavour’, ‘familiar flavour’, ‘harmonious flavour’, ‘softness’, and ‘harmoniousness with food ingredients’ were determined as drivers of liking, on the other hand, ‘disturbance with food ingredients’ and ‘soybean fishy smell’ were determined as drivers of disliking. The degree of consumer preference and overall acceptance were found to be related to the consumers' familiarity, suggesting that if a menu should be developed using unfamiliar local agricultural products, it should be configured with familiar recipes and seasoning methods.

Food upcycling has emerged as an effective approach to sustainably utilize the food waste generated within the food supply chain. This review article examines upcycled food with respect to its definition, consumers’ knowledge and perception on it, and the process by which by-products from the food supply chain are utilized for the creation of upcycled food products. The definition of upcycled food varied among manufacturers, research institutions, and the Upcycled Food Association, depending on the specific values and objectives of each sector. This has resulted in the use of different keywords to highlight the distinctive characteristics of their respective interpretations of upcycled food. This review also summarizes the various consumer traits that can influence the awareness and acceptance of upcycled food, encompassing functional, empirical and emotional, symbolic and self-expressive, and economic benefits. Additionally, the review presents strategies to utilize by-products produced in large quantities in Korea, while also addressing the control of hazardous components to ensure biological or chemical safety and the changes in nutritional value that may occur during the utilization of these byproducts.

AI recommendation service is adopted in consumption consulting such as high-tech and fashion consumption (Thapliyal & Ahuj, 2021). Now, for high-tech and fashion products, the advance selling strategy is widely adopted. Thus, this study targets to detective the consumers’ preference toward AI agents comparing human agents under advance selling and spot selling. The independent variable of this study is consumption type: Pre-sale Products vs. Spot Products. Pre-sale Products are quite popular currently, especially technological products. Construal-level theory (CLT) offers a valuable framework to explain the mechanisms that trigger evaluations, predictions, and behaviors by linking the degree of mental abstraction (the construal level) to psychological distance (Trope & Liberman, 2000; 2003; 2010). Four dimensions including temporal, special, social, and probability distance are argued to present the psychological distance (Trope et al., 2007). Liberman et al. (2022) discuss the time distance and argue the distant-future events are represented in a more abstract, structured, high-level manner than near-future events. Kim & Duhachek (2020) draw on a dimension of persuasion by AI agents to posit that AI agents are perceived as low-construal agents because of the fact that people hold a lay theory that AI agents do not have superordinate goals and cannot learn from their experiences or possess consciousness like humans do. Consequently, they find that individuals perceive greater appropriateness and are more persuaded when an AI agent’s persuasive messages highlight low-construal as opposed to high-construal features. Moreover, consumers prefer abstract information related to a certain product rather than concrete information when a purchase is to take place in the distant future or when construal levels are high (Hernandez et al., 2015). Thus, this research hypothesizes: When consumers buy pre-sale products (vs. spot products), human agents will be the more favorable service provider than AI agents since the consumer is under a high level of construal. This research proposes to adopt a 2 (Advance Selling vs. Spot Selling) x 2 (Short Psychological Distance vs. Far Psychological Distance) x 2 (AI Agents vs. Human Agents) between groups experimental study to test the main effects and mechanism (H1). Furthermore, this study would identify the key moderating effects to discuss the boundary effects of the mechanism for establishing marketing strategies with AI services for managers.

The rapid advancement of technology has created unprecedented opportunities for brands to engage with their existing and potential consumers through digitally enriched products. One such technology that enables the digital enrichment of analog products is augmented reality (AR). Through AR, consumers are able to directly interact with brands, for example, by scanning a product to unlock animated digital content that prompts them to take reciprocal actions. Recognizing that technologies that fail to actively engage consumers may struggle to realize their full potential, our study incorporates consumer brand engagement as a key factor of investigation. Consumer engagement with the brand signifies a higher level of commitment and aids in building lasting and beneficial relationships, as well as enhancing brand knowledge, ultimately positively influencing consumer-based brand equity.

The market for counterfeit luxury goods is growing rapidly, with estimates suggesting that counterfeit trades are valued at around $4.5 trillion globally, with 60% to 70% of this being made up of counterfeit luxury goods. Research has shown that counterfeits dilute the perceived quality of luxury brands and reduce consumers' purchase intentions. Non-fungible tokens (NFTs) are a form of ownership record that is linked and stored on a blockchain.

Since radon was detected in mattresses of famous bed furniture brands in 2018, the nuclear safety and security commission (NSSC) announced the radiation safety management act in April 2021 to protect the public health and environment. This act stipulates the safety management of radiation that can be encountered in the natural environment such as the notification of radioactivity concentration of source materials, process by-products, the installation and operation of radioactive monitors. In this study, a model was established to predict radioactive exposure dose from radioactive materials such as radon and uranium detected in consumer products such as bed mattresses, pillows, shower, bracelets and masks in order to identify major radioactive substances that largely affect the exposure dose. A period of seven years from 2014 to 2020 was investigated for the source materials and exposure doses of consumer products containing naturally occurring radioactive materials (NORMs). We analyzed these using machine learning models such as classification and regression tree (CART), Random Forest and TreeNet. Index development and verification were performed to evaluate the predictive performance of the models. Overall, predictive performance was highest when Random Forest or TreeNet was used for each consumer product. Thoron had a great influence on the internal exposure dose of bedding, clothing and mats. Uranium had a great influence on the internal exposure dose of other consumer products except whetstones. When the number of data is very small or the missing value rate is high, it is difficult to expect accurate predictive performance even with machine learning techniques. If we significantly reduce the missing value rate of data or use the limit of detection value instead of missing values, we can build a model with more accurate predictive performance.

How much do you like a person who loves the brands you hate? We investigated an effect we call the brand negativity bias, which occurs when an unfavorable brand reduces the attitudes toward an associated target product or person. Using a person perception paradigm in the context of brand placements, Experiment 1 established that unfavorable brands reduced attitudes toward a new digital product (i.e., a movie) in which the brand was placed. Experiment 2 showed this effect was driven by a reduced ability to connect with the character in the movie who was associated with an unfavorable brand in two serial processes (lower perceived similarity leading to lower empathy). These results provide the first evidence showing how unfavorable brands can reduce empathy between people. Supporting the brand negativity bias, we found that unfavorable brands yielded stronger effects across every evaluative outcome suggesting that unfavorable brands held more influence over consumer judgment compared to favorable brands. Lastly, these results add a layer of complexity to B2B partnerships and tell a cautionary story of when unfavorable brand associations transfer between entities.

This study examined factors that influence purchase intention of ethically produced fashion products. Theory of Reasoned Action was used to understand consumer attitude formation and purchase intention of ethically produced fashion products. Two unique variables were studied (environmental awareness, environmental concern) with the consumer attitude toward the purchase intention of ethically produced products. The influence of subjective norms on purchase intention was also examined. The results showed the influence of environmental concern on both attitude and purchase intention along with the influence of attitude on purchase intention. The findings of this study contribute to the body of the existing knowledge in the area of ethical production by providing explanations and a broad understanding of the factors that influence purchase intention of ethically produced fashion products. The results will also provide insight to firms wanting to effectively convey pro-environmental efforts to consumers that will help branding, positioning, and potential sales increase.

This study aimed at examining fashion consumers’ awareness during the COVID-19 pandemic. Big data analysis methods, such as text mining, social network analysis, and regression analysis, were applied to user posts about fashion on Korean portal websites and social media during COVID-19. R 3.4.4, UCINET 6, and SPSS 25.0 software were used to analyze the data. The results were as follows. In researching the popular fashion-related topics during COVID-19, the prevention of infection and prophylaxis were significant concerns in the early stage (Jan 1 to Jan 31, 2020), and changed to online channels and online fashion platforms. Then, various topics and fashion keywords appeared with COVID-19-related keywords afterwards. Fashion-related subjects concerned prophylaxis, home life, digital and beauty products, online channels, and fashion consumption. In comparing fashion consumers’ awareness during COVID-19 with SARS and MERS, “face masks” was the common keyword for all three illnesses; yet, the prevention of infection was a major consumer concern in fashion-related subjects during COVD-19 only. As COVD-19 cases increased, the search volume for face masks, shoes, and home clothes also increased. Consumer awareness about face masks shifted from blocking yellow dust and micro-dust to the sociocultural significance and short supply. Keywords related to performance turned out to be the major awareness as to shoes, and home clothes were repurposed with an expanded range of use.

This study aimed to analyze the performance of Disney-collaborated fashion lines based on online consumer reviews. To do so, the researchers employed text mining and network analysis to identify key words in the reviews of these products. Blogs, internet cafes, and web documents provided by Naver, Daum, and YoutTube were selected as subjects for the analysis. The analysis period was limited to one year after for the 2019. Data collection and analysis were conducted using Python 3.7, Textom, and NodeXL. The research terms in question were as follows: ‘Disney fashion collaboration’ and ‘Frozen fashion collaboration’. Preliminary survey results indicated that ‘Elsa’s dress’ was the most frequently mentioned term and that the domestic fashion brand Eland Retail was the most active in selling Disney branded clothing through its own brand. The writers of reviews for Disney-collaborated fashion products were primarily mothers with daughters. Their decision to purchase these products was based upon the following factors; price, size, stability of decoration, shipping, laundry, and retailer. The motives for purchasing the product were the positive response of the consumer’s child and the satisfaction of the parents due to the child’s response. The problems to be solved included insufficient quantity of supply, delay in delivery, expensive price considering the number of times children’s clothes are worn, poor glitter decoration, faded color, contamination from laundry, and undesirable smells immediately after the purchase.

본 연구는 SNS(social network service)를 통한 화훼상품 구매인식과 화훼상품 이미지 선호도를 알아보고자 국내 성인남녀 311명을 대상으로 설문을 진행하였다. 소비자들이 SNS를 통해 화훼상품을 구매하는 가장 큰 이유로는 트렌드에 맞는 디자인을 판매하기 때문이며, 해당 항목에 대하여 20대가 가장 높은 평균으로 나타났다. 연령에 따라 20대와 30대의 응답자는 40대에 비해 SNS를 통해 판매하는 화훼상품의 가격이 덜 합리적이라고 생각하였으며, 50대 이상의 연령에서는 SNS를 통해 판매하는 화훼상품의 품질과 꽃의 신선도에 대해 낮게 신뢰하는 것으로 나타났다. 응답자들은 SNS에 게시된 화훼 상품의 이미지가 구매할 상품 선택에 많은 도움을 준다고 인식하였으며, SNS상의 화훼상품 이미지에 대해 긍정적으로 생각하는 것을 알 수 있었다. 또한 화훼상품의 이미지가 보정효과로 다듬어진 것이라고 인식하였으나, 실제 상품과 비슷할 것이라고 생각하는 경향을 보였다. 화훼상품 구매결정에 영향을 미치는 이미지 특성으로는 전체적인 분위기가 가장 중요하다고 인식하였으며, 절화 화훼상품 이미지에서 꽃다발과 꽃바구니 화훼상품에 따라 선호하는 배경에 약간의 차이가 나타났다. 구도에 따른 선호도는 꽃다발과 꽃바구니 모두 정면에서 촬영한 이미지를 가장 선호하였으며, 이미지 보정에 대한 선호도에서는 밝은 느낌의 채도가 높은 이미지를 가장 선호하는 반면, 어두운 느낌의 이미지는 선호하지 않는 것으로 나타났다. 화훼상품 이미지 보정효과에 대한 감성인식을 의미변별척도법(semantic differential scale)에 따라 조사한 결과, 채도에 상관없이 밝은 느낌의 이미지는 ‘풍부한’, ‘세련된’, ‘고급스러운’, ‘기품 있는’과 같이 긍정적인 감성어휘 쪽이 높은 것으로 나타났다. 반면 어두운 느낌의 이미지는 전반적으로 부정적인 감성어휘 쪽이 높은 것으로 나타났다. 화훼상품 이미지의 배경, 구도, 보정효과에 따라 소비자의 선호도와 감성반응에 차이가 나타났으나, 소비자의 성별, 연령 및 직업 특성에 따른 유의한 차이는 없었다. 이를 통해, 소비자가 선호하는 이미지를 구축하여 SNS를 통한 화훼상품을 판매하는 것이 소비자들의 구매상품 선택에 도움이 될 것으로 확인되었다.

The aim of this study was to explore the effect of combinations of diverse methods notifying price discounts (i.e., reference price, odd price, and discount rate signs) and the relationships among product attribute perception, discount perception, attitude toward product, and purchase intention of product. Experiments were conducted where 12 stimuli of different price discount information notifications regarding T-shirt advertisements were presented to 352 informants. The results showed that notification of each type of discount information increased discount perception, whereas no effect due to the size of letters used in the discount rate notification was found. As more price discount information notifications were used, discount perception tended to become stronger. The results of ANOVA analysis show that both product attribute perception and discount perception affected attitude toward the product. In addition, product purchase intention was determined by attitude toward the product as well as price discount perception. Based on these findings, marketers may want to use a combination of methods of price discount notifications in advertisements to deliver price discount information clearly to consumers. Confirmation of discount information using multiple cues would help consumers to notice and perceive price discount information provided by retailers more effectively. Discount information is crucial for increasing both purchase intention and favorable attitude, therefore, diverse strategies regarding discount information presentations should be developed, tested and applied in the real world of retailing.

본 연구는 패션제품에 QR코드를 부착하여 소재와 세탁 등의 전문적 정보의 제공뿐 아니라 기업과 소비자, 소비자와 소비자를 연결하는 기능을 부여할 수 있도록 하기 위한 기초연구로 QR코드 적용 시 요구되는 정보에 대한 소비자의 인식과 선호를 조사하였다. 타 연령대보다 스마트폰 보급률이 높고 1인 가구의 비율이 높아 비대면 정보교환의 필요성이 높을 것으로 생각되는 20대를 대상으로 설문하였다. 현행 라벨을 통한 의류제품의 정보제공 방법에 대해서 개선의 필요성이 확인되었으며 특히 불충분한 정보제공, 전문적인 용어 사용, 세탁 기호의 불확실함이 불만족의 요인이었다. 따라서 다양한 방식으로 많은 정보를 전달할 수 있는 QR코드는 패션제품의 관리 정보제공의 효율적인 대안이 될 수 있을 것이다. 또한 응답자들은 아웃도어, 패딩, 정장 등의 고관여 의류 상품과 신체에 닿는 언더웨어류에 대해서 자세한 세탁방법, 사용 및 보관 시 유의사항, 소재의 기능성에 대한 정보를 얻고 싶어 했으며 캐주얼웨어, 코트에 대해서는 제품을 활용한 SNS 데일리룩, 제품과 어울리는 다른 상품, 비슷한 아이템의 추천 등 스타일링이나 의복 구매 정보를 제공받고 싶어했다. 따라서 QR코드를 이와 같은 다양한 정보 제공을 위한 웹사이트 또는 SNS의 연결수단 으로 사용한다면 소비자들의 정보추구 욕구의 충족과 함께 현명한 제품 사용을 도울 수 있을 것이며 초 연결시대 패션제품의 새로운 역할을 부여하는 대안이 될 수 있을 것이다.

Recently, the textile and fashion industry has adopted 3D printing technology, through which filaments are accumulated continuously in the form of sections to produce digitalized three-dimensional fashion products. Little research has been done regarding the consumer perspectives on 3D printed fashion product. Therefore, the purpose of this study was to investigate the effects of consumer innovativeness, uniqueness, and perception factors on consumer attitudes and purchasing intentions for 3D printed fashion products. A questionnaire was given to consumers living in Seoul and Kyunggi, South Korea. The data obtained from the 159 completed questionnaires was analyzed by regression analysis, factor analysis, and Cronbach’s alpha using SPSS 24.0. The results were as follows: First, consumer innovativeness and uniqueness, in descending order, positively affect the perceived social image. Consumer innovativeness positively affects perceived aesthetics and consumer uniqueness positively affects perceived novelty. Second, social image has a positive effect on consumer attitudes to 3D printed fashion products. Third, consumer attitude positively affects purchasing intentions towards 3D printed fashion products. Fourth, consumer innovativeness and uniqueness, in descending order, have a positive effect on consumer attitudes and purchasing intentions for 3D printed fashion products. Fifth, social image and novelty, in descending order, positively affect purchase intentions for 3D printed fashion products. Therefore fashion firms should develop their marketing strategy to focus on innovative, unique consumers as a main target and aim to enhance buyers’ social image by using 3D printed fashion products.