Food is essential for sustenance and reflects a country’s identity, making it crucial to identify the cultural needs for effectively localizing Korean food. This study surveyed 825 adults from four continents (eight countries) to examine their preferences, familiarity, and attitudes toward Korean food. Significant correlations(p< .001) were found between the familiarity and preference for Korean food, with variations observed across continents. Among the representative Korean food items, the average preference score was 4.67, and the purchase/recommendation intention score was 4.88. Seven items received above-average ratings (e.g., gogi-deopbap and kimchi-bokkeumbap), while some items showed high liking but low purchase/recommendation intention (e.g. dak-jjim and galbi-jjim). In addition, items such as gimbap and tteokbokki had high purchase/recommendation intention but low liking, and kimchi and vegetable foods etc. received low liking and purchase/recommendation intentions. In terms of the preferred meat according to the cooking method and seasoning, beef respondents preferred grilled · stir-fried and soup·stew·hot pot cooking methods, while pork or chicken respondents preferred grilled · stir-fried and frying methods. Soy sauce was the most preferred seasoning for all meat responses, followed by red pepper paste. These research findings provide fundamental data for developing Korean food products, segmented by continent.

Korea's facility horticultural heating costs account for a high proportion. Therefore, it is the most important factor to consider in greenhouse construction. It is important to assess the heating load of greenhouses. But there is not much data from the weather station. This study determined the heating load for each segmented area using the spatial correction method. The heating degeneration calculated from standard weather data (AHDH and BHDH) and total weather data (CHDH and DHDH) is consistent. However, there was a big difference between AHDH and DHDH. Therefore, the updated heating load data for each region is needed. Each of the four types of set temperatures (8℃, 12℃, 16℃, 20℃) was provided, and the heating temperature setpoint (℃) for each region of 168 cities and counties was presented. As a result of the analysis, the reliability of about 99% was confirmed in most of the regions suggested in this study. By using the calculated heating load for each region, it is possible to predict and utilize energy consumption and management costs.

국회의 국무총리·국무위원 해임건의제도는 대통령의 독주와 전제를 방지하 고 책임정치 구현에 미흡하다는 대통령제 정부형태의 취약점을 보완하기 위하여 현행 헌법이 마련하고 있는 국정통제장치이다. 현행 헌법상의 해임 건의제도가 대통령을 법적으로 구속하는지 여부에 관해서는 정부형태를 이 해하는 시각에 따라 견해가 대립된다. 우리 헌법재판소는 『대통령노무현 탄핵』사건 결정문에서 헌법 제63조 국회의 해임건의가 대통령을 법적으로 구속하지 않는다고 함으로써 대통령이 국회의 해임건의에 응하지 않더라도 헌법위반으로 볼 수 없다고 판시하였다. 헌법재판소의 해당 결정 이후 대 통령은 국회의 해임건의에 응하지 아니하는 것이 헌법적 관행으로 굳어지 고 있다. 이와 같은 헌법 현실은 여소야대 환경에서 국회로 하여금 해임건 의제도를 배제하고 탄핵소추 수단을 남용하도록 유도할 위험성이 높다. 국 회의 탄핵소추 의결만으로도 피소추자의 직무집행이 정지되는 효과를 가져 오므로 심각한 정치 양극화와 정쟁의 격화를 가져온 작금의 정치 현실에 서 국회 다수당은 헌법재판소에서 탄핵인용결정이 선고될 것인지에 관해서 는 전혀 개의치 않고 탄핵소추에 더욱 매몰될 것이기 때문이다. 탄핵소추 의 남발은 행정부의 정상적인 운영을 저해하고 헌법재판소에 적지 않은 부담을 가하는 폐단을 가져다준다. 따라서 현행 헌법이 규정하고 있는 국 회의 해임건의가 아무런 의미가 없는 무용지물인 제도로 전락한 것을 교 정하고 헌정 현실에서 그 본래의 기능을 발휘하도록 하기 위해서는 국회 의 해임건의가 대통령을 법적으로 구속한다고 해석하는 것이 타당하다.

The increasing number of technology transfers from public research institutes in Korea has led to a growing demand for patent recommendation platforms for SMEs. This is because selecting the right technology for commercialization is a critical factor in business success. This study developed a patent recommendation system that uses technology transfer data from the past 10 years to recommend patents that are suitable for SMEs. The system was developed in three stages. First, an item-based collaborative filtering system was developed to recommend patents based on the similarities between the patents that SMEs have previously transferred. Next, a content-based recommendation system based on TF-IDF was developed to analyze patent names and recommend patents with high similarity. Finally, a hybrid system was developed that combines the strengths of both recommendation systems. The experimental results showed that the hybrid system was able to recommend patents that were both similar and relevant to the SMEs' interests. This suggests that the system can be a valuable tool for SMEs that are looking to acquire new technologies.

본 연구는 IPA 기법을 이용하여 중국인 골프장 이용객의 골프장 선택속성 요인에 대한 재방문 의도 및 추천의도에 미치는 영향을 규명하는데 목적이 있다. 본 연구를 수행하고자 중국인 골프장 이용객 388명을 대상으로 설문조사를 실시하여 자료처리 및 IPA 분석을 실시한 결과, 다음과 같은 결론을 얻었다. 첫째 선택속성의 중요도는 직원 예절, 만족도는 식당 및 식음료 가격이 가장 높게 나타났다. 둘째, IPA 매 트릭스 분석 결과, 지속유지에는 8개, 집중개선은 14개, 낮은 우선순위는 5개, 과잉노력지양은 3개의 선택 속성이 분포하였다. 셋째 비용, 접근성, 코스시설, 부대시설, 캐디 전문성, 이용객 관리의 만족도가 재방문 과 추천 의도에 모두 영향을 미치는 것으로 나타났다. 본 연구는 중국인 골프장 이용객으로 한정하였기 때 문에 골프문화가 다른 국가에서 연구된 선행연구와는 그 결과를 비교하는데 있어 차이가 있을 수 있기 때 문에 문화의 다양성을 고려한 연구들이 향후에 진행되어야 할 것이다.

In recent years, the trend of customer demand and personalization has become more and more obvious. The previous innovation model can no longer meet the diversified needs of consumers. Therefore, firms vigorously develop open innovation to promote internal and external innovation (von Hippel, 1988). With the rapid development of AI technology, open innovation communities have more interactions with the users. Organizations continue to rely on their open innovation community to collect innovative ideas from non-professional customers and then integrate them into their new product development process to produce innovative products that are more in line with customer preferences (Bayus, 2013). At present, the research on user design focuses on how to increase user design implementation and the idea popularity (Yang et al., 2022; Zhang et al., 2022). Few studies discussed how to motivate consumers to participate in innovative content output from the source. In addition, academic research on user design is mostly limited to management comments, lacking in-depth empirical research (Franke et al. 2008). Previous studies have proved that the number of leading users in the open innovation community is far less than that of non-leading users (Hofstetter et al., 2018), so it is very necessary to improve the willingness of users to participate in community creative activities. With the vigorous development of the new technology, it is an urgent problem to be solved to encourage users to participate in innovation activities and improve the innovation performance of firms (Chesbrough, 2012). Today, firms pay more and more attention on the implementation of AI technology. With AI and user design as the research background, “AI recommendation” and “willingness to design” as the key variables, and the “S-O-R model” and “Self-determination Theory” as the basis, this paper deeply explores whether AI recommendation can be used as a factor affecting user’s participation in design activities from the perspective of users, focusing on the intermediary role of user’s inspiration, competency and self-expression. It also puts forward that product involvement and aesthetic experience openness (Donghwy and Youn, 2018) are the boundary conditions that affect user’s willingness to participate in design. The results show that user’s willingness to participate in design is higher when providing AI recommedation, and the sense of inspiration, competence and self-expression play a mediating role in it. Furthermore, the results show that when product involvement is high, users are more willing to participate in design. Similarly, users with a high degree of aesthetic experience openness are more willing to participate in design activities. This study enriches the theory of enterprise community management, promote the internal information flow of the open innovation community, and provide theoretical guidance and reference for firms to optimize the new product design process.

본 연구는 최근 기업체에서 많이 사용하고 있는 세무회계서비스에 대한 추천 의향을 조사하여 그 결과를 분석하는 것이다. 특히 비용이나 시간적 측면에서 상대적으로 어려움을 겪는 100인 이하의 소규모 기업체를 대상으로 하여 해 당 기업체들에 더 나은 서비스가 되기 위한 방향성을 찾는 것을 목적으로 한다. 이를 위하여 100명의 기업체 관계자 대상으로, 회사 근무자 규모, 직급, 사업자 유형 등 사업체 기본 정보는 물론 이용 중인 세무회계서비스 형태, 서비스에 대한 추천 점수, 점수에 대한 이유, 기타 세무회계서비스 관련 의견 등을 조사한다. 특히 추천 점수는 단순 만족도를 묻는 일반적인 고객의 만족도 조사보다 고객의 의견을 파악하는데 더 효과적이라고 알려진 NPS(Net Promoter Score) 방식을 사용함으로써 더 효과적인 결과를 얻고자 한다. 조사 결과 추천도에 대한 NPS 점수는 -33점으로 나왔으며 이는 일반적인 NPS 점수 평가 기준을 참고할 때 낮은 편에 해당하여 세무회계서비스에 대한 개선이 필요하다는 것을 알 수 있었다. 더 구체적으로는 비추천 점수를 준 응답자들의 의견에서 불편하지도 편하지도 않고 그냥 무난해서 도움 이 되는지 잘 모르겠다, 차별성이 없으며 대안도 특별히 없다 등의 의견이 있었음을 볼 때 비추천 점수를 높이기 위해서는 차별적인 서비스가 필요하다는 결론을 얻을 수 있었다. 본 조사는 100인 이하의 기업체 관계자를 대상으로 추천 도 중심으로 조사한 것으로 이후에는 기업체 규모와 조사 항목을 더 다양하게 한 조사 진행이 추가로 필요하다.

본 논문은 지각된 가치가 적용된 관광 행동의도 정보를 이용한 지능형 클라우드 환경에서의 관광추천시스템을 제안한다. 이 제안 시스템은 관광정보와 관광객의 지각적 가치가 행동의도에 반영되는 실증적 분석 정보를 와이드 앤 딥러닝 기술을 이용하여 관광추천시스템에 적용하였다. 본 제안 시스템은 다양하게 수집할 수 있는 관광 정보와 관광객이 평소에 지각하고 있던 가치와 사람의 행동에서 나타나는 의도를 수집 분석하여 관광 추천시스템에 적용하였다. 이는 기존에 활용되던 다양한 분야의 관광플랫 폼에 관광 정보, 지각된 가치 및 행동의도에 대한 연관성을 분석하고 매핑하여, 실증적 정보를 제공한다. 그리고 관광정보와 관광객의 지각적 가치가 행동의도에 반영되는 실증적 분석 정보를 선형 모형 구성요소와 신경만 구성요소를 합께 학습하여 한 모형에서 암기 및 일반화 모두를 달성할 수 있는 와이드 앤 딥러닝 기술을 이용한 관광추천 시스템을 제시하였고, 파이프라인 동작 방법을 제시하였다. 본 논문에서 제시한 추천시스템은 와이드 앤 딥러닝 모형을 적용한 결과 관광관련 앱 스토어 방문 페이지 상의 앱 가입률이 대조군 대비 3.9% 향상했고, 다른 1% 그룹에 변수는 동일하고 신경망 구조의 깊은 쪽만 사용한 모형을 적용하여 결과 와이드 앤 딥러닝 모형은 깊은 쪽만 사용한 모형 대비해서 가입률을 1% 증가하였다. 또한, 데이터셋에 대해 수신자 조작 특성 곡선 아래 면적(AUC)을 측정하여, 오프라인 AUC 또한 와이드 앤 딥러닝 모형이 다소 높지만 온라인 트래픽에서 영향력이 더 강하다는 것을 도출하였다.

Purpose: The purpose of this study was to examine the effects of simulation-based training applying situation-background-assessment-recommendation on self- efficacy and communication skills in new nurses. Method: This study applied a one group pretest-posttest design, with 88 new nurses in a general hospital in S city, Korea. Data were collected from March to November 2017. The participants completed their simulation education program in 4 weeks. Data were analyzed using paired t-test with SPSS program. Results: After SBAR simulation education, self- efficacy (t=-2.40, p=.014) and communication skills (t=-5.24, p<.001) significantly improved. Conclusion: This suggests that simulation-based training applying SBAR, improved self- efficacy and communication skills in new nurses.

Definitions of customer experience typically relate to memories of an event which stand out amidst noise present in a consumer’s environment. In this study we investigate the effects on memorability when consumers seek to commit their experience to electronic media, either for their own subsequent consumption, or shared consumption with others. We specifically investigate whether the intervention of electronically recorded experience influences subsequent recall of a service experience, and subsequentrecommendation of it to others, compared with a baseline situation of no external recording of an experience. The research is underpinned by models of memory structure and recall (Ericsson & Kintsch, 1995). A longitudinal study is undertaken in the context of an art gallery. Participants recorded behavioural and affective components of their visit over a period of six months. Intensity of use of social media during the experience mediated outcomes of satisfaction and likelihood of recommendation to others. Initial findings indicate differences in participants’ recalled satisfaction, partially mediated by level of social media engagement during their visit.

This research examined whether the (in)congruence between the geographical distance between the viewer and the destination, and the dynamic distance experienced via zoomin and zoom-out affects the recommendation likelihood of the travel destination. Specifically, when the viewer’s motivation is utilitarian (e.g., travelling for work), we expect the congruence effect (H1): a higher recommendation likelihood when the geographic distance is congruent with the dynamic distance; that is, the viewer is more likely to recommend the travel destination when the destination is geographically far away from (close to) with a zoom-out (zoom-in) view. By contrast, when the viewer’s motivation is hedonic (e.g., travelling for fun), we expect the incongruence effect (H2): a higher recommendation likelihood when the geographic distance is incongruent with the dynamic distance; that is, the viewer is more likely to recommend the travel destination when the destination is geographically far away from (close to) with a zoom-in (zoomout) view. We test these ideas in an experimental study.

New product entails risk, causing resistance to adoption. The recommendation system may decrease the psychological risk by guiding decision making process to be more efficient (Häubl and Trifts, 2000). AI (Artificial Intelligence) has been getting smarter and smarter and widely applied to the recommendation system. Even while you are browsing on your Facebook, AI recommends you the products that you may like based on the customized analysis of your interest. However, do people always love to adopt the smart recommends from AI? Definitely no! Then when and why people reluctantly accept AI recommendation? We assume that the product or service where the sense and feeling is important, people might be reluctant to accept the recommendation from artificial intelligence. This is because people might feel threatened when the AI challenges against human uniqueness (Gray and Wegner, 2012). Thus, in this study we investigated how the recommendation system types (AI vs. Human) affect brand attitude depending on the brand image (Symbolic vs. Functional). We found consumers are reluctant to accept a recommendation from AI in symbolic brand where human sense and feel are considered to be critical factors (Study1). This effect was further explained by uncanny-feeling toward the AI recommendation system (Study2). This research is meaningful in that it is the first attempt to apply the artificial intelligence recommendation concept to the marketing strategy by incorporating the concept of brand image. We predicted and found AI based recommendation system is reluctantly accepted for symbolic brand. Furthermore, we discovered the underlying process for this phenomenon as uncanny feeling. People seemed to have uncomfortable feelings against AI recommendation when the brand image is related to sense and feel considered as nature of human uniqueness. Thus, marketers should be very cautious when utilizing the AI recommendation system not to threaten human uniqueness area.

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The ‘cold-start’ problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

This study was conducted to survey the perception and preferences of customers that have dined at Korean restaurants in China and investigate the importance and performance level of quality attributes, customer satisfaction, revisit intention and recommendation intention. The survey was conducted January 31~March 1, 2016 in China. The 293 questionnaires (97.7%) were analyzed using SPSS(Ver. 23.0) and AMOS(Ver. 21.0). Results of this study are as follow: Customers that dined at a Korean restaurant in China were composed of 157 women and 136 men. Regarding the reason for preferring Korean cuisine, taste, hygiene and nutritional value of Korean food were the most significant quality factors. Regarding complaints about Korean food, Chinese people placed much emphasis on freshness of ingredients when dining out, based on the majority of complaints about ingredients that were not fresh. The main reason for leftover food were personal eating habits and that of customers revisiting food taste and nutrition. Path model among customer satisfaction, revisit intention and recommendation intention revealed the factor of menus and attributes of menu items regarding customer’s age that had an impact on customers’ satisfaction, and association with customers’ satisfaction, revisit intention and recommendation intention as well.

This study was conducted to examine the effects of Chinese perceptions of quality attributes on customer’s satisfaction, revisit intention and recommendation intention for coffee shops in Beijing, China. Subjects of this study included 200 customers who had visited a coffee shop at least once during the last year. Statistical analyses were performed using SPSS v23.0 and AMOS v21.0. In this study, the majority of customers visited a coffee shop once or twice a week with friends. Respondents preferred tall-sized warm coffee in the store. The coffee shop quality attributes of were derived from five exploratory factors identified upon analysis of 30 observational variables. It was important to maintain and strengthen the quality attributes of coffee shops in this area because IPA(Importance Performance Analysis) analysis showed that “Doing great, keep it well” part was a desirable area because it had high importance and performance. Finally, path analysis revealed that customer satisfaction was influenced by employee attitude and affected revisit intention and recommendation intention.