• Title/Summary/Keyword: innovation studies

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Analysis of Customer Evaluations on the Ethical Response to Service Failures of Foodtech Serving Robots (푸드테크 서빙로봇의 서비스 실패에 대한 직업윤리적 대응에 대한 고객 평가 분석)

  • Han, Jeonghye;Choi, Younglim;Jeong, Sanghyun;Kim, Jong-Wook
    • Journal of Service Research and Studies
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    • v.14 no.1
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    • pp.1-12
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    • 2024
  • As the service robot market grows among the food technology industry, the quality of robot service that affects consumer behavioral intentions in the restaurant industry has become important. Serving robots, which are common in restaurants, reduce employee work through order and delivery, but because they do not respond to service failures, they increase customer dissatisfaction as well as increase employee work. In order to improve the quality of service beyond the simple function of receiving and serving orders, functions of recovery effort, fairness, empathy, responsiveness, and certainty of the process after service failure, such as serving employees, are also required. Accordingly, we assumed the type of failure of restaurant serving service as two internal and external factors, and developed a serving robot with a vocational ethics module to respond with a professional ethical attitude when the restaurant serving service fails. At this time, the expression and action of the serving robot were developed by adding a failure mode reflecting failure recovery efforts and empathy to the normal service mode. And by recruiting college students, we tested whether the service robot's response to two types of service failures had a significant effect on evaluating the robot. Participants responded that they were more uncomfortable with service failures caused by other customers' mistakes than robot mistakes, and that the serving robot's professional ethical empathy and response were appropriate. In addition, unlike the robot's favorability, the evaluation of the safety of the robot had a significant difference depending on whether or not a professional ethical empathy module was installed. A professional ethical empathy response module for natural service failure recovery using generative artificial intelligence should be developed and mounted, and the domestic serving robot industry and market are expected to grow more rapidly if the Korean serving robot certification system is introduced.

The effect of R&D investment in Chinese private firms on firm performance and value: The moderating effect of ESG score (중국 민영기업의 R&D 투자가 경영성과와 기업가치에 미치는 영향: ESG 성과지수의 조절효과)

  • Youngsoo Park
    • Analyses & Alternatives
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    • v.8 no.2
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    • pp.87-115
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    • 2024
  • This study examines the effect of R&D investment on firm performance and value of Chinese private firms. Through R&D investment, firms aim to acquire knowledge and technological resources to create innovation and competitive advantage, which ultimately enhances firm performance and value. However, unlike other investments, R&D investments are characterized by high adjustment costs and risks, uncertainty and asymmetric information. In addition, the effect of R&D investment on firm performance and value has been shown to be mixed results due to various internal and external contextual factors. Therefore, this study intends to consider how the ESG activities of firms, which have recently attracted attention, act as a contextual factor in the results of R&D investment. This is because interaction with stakeholders through ESG activities is considered to be an important factor in securing competitive advantages and sustainable growth. In this context, this study measures the effect of a firm's R&D investment on its business performance by dividing it into financial performance and value, respectively, and examines the moderating effect of ESG score on the relationship. Based on empirical analysis of all Chinese private firms from 2010 to 2019, the results show that a firm's R&D investment has a negative impact on performance and a positive impact on value. Furthermore, a high ESG score of private firms positively moderates each relationship, emphasizing the importance of ESG activities.

A Study on the Development of AI Utilization Guide Components at a Christian University (기독교대학의 AI활용가이드 구성요소 개발 연구)

  • Sungwon Kam;Minho Kim
    • Journal of Christian Education in Korea
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    • v.77
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    • pp.171-201
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    • 2024
  • Purpose of Research : Since ChatGPT's 2022 release, the educational sector faces mixed reactions to generative AI, sparking innovation but raising concerns about student cognition and communication. While Christian colleges employ AI reflecting their values, secular institutions stress ethical usage. This study explores ethical AI use in these settings, aiming to integrate findings into educational practices. Research content and method : Analyzing AI use and ethics guidelines from 50 domestic and international universities, differences between Christian and secular institutions were explored. Data was categorized, conceptualized via open coding, and components were identified through axial coding. The importance of components for Christian colleges' AI guides was assessed based on the initial data and previous research, leading to the development of tailored AI utilization components for Christian universities. Conclusion : Studies revealed secular institutions have six AI guide components, while Christian colleges found seven in both utilization and ethics guides, focusing on truthfulness, responsibility, and diversity. Emphasizing the need for ethical AI use in Christian colleges, the findings advocate developing AI ethics guidelines to aid marginalized groups and establish a new educational paradigm through further research.

A Study on Customer Experience with Food Truck Services: Focusing on Topic Modeling Techniques (푸드트럭 서비스 이용객 경험에 관한 연구: 토픽모델링 기법 중심으로)

  • Jooa Baek;Yeongbae Choe
    • Journal of Service Research and Studies
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    • v.14 no.3
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    • pp.188-205
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    • 2024
  • The food truck business, which involves selling various types of food from mobile vehicles, has gained significant popularity in urban centers and at events. These food trucks have rapidly expanded due to their relatively low initial investment and high flexibility, attracting customers with unique menus and personalized services. However, as competition increases, the need to manage service quality to boost customer satisfaction and encourage repeat visits has become more critical. Despite this growing importance, there has been limited empirical research on the topic. This study aims to analyze customer experiences with food truck services to gain strategic insights for improving service quality. By applying structural topic modeling to customer review data, the study identified 50 key topics. The process included a comprehensive evaluation of model diagnostics and interpretability to determine the optimal number of topics, ultimately selecting the most relevant ones related to service experiences. The impact of these identified topics on overall customer satisfaction was empirically tested using regression analysis. The results showed that aspects such as "Food Taste," "Friendly Staff," and "Positive Emotion" had a positive influence on customer satisfaction, whereas "Delayed Service," "Negative Emotion," and "Beverage Service" had a negative impact. Based on this analysis, the study proposes concrete methods for food truck operators to systematically analyze customer feedback and use it to drive service improvements and innovation. This research highlights the importance of data-driven decision-making in small business environments like food trucks and contributes to expanding the application of topic modeling in the service industry.

The Digital Innovation of Secretarial Roles: An Examination of Changing Work Environments and Required Competencies (비서직의 디지털 혁신: 업무 환경의 변화와 요구 역량 고찰)

  • Kim, Sukyung;An, Jaeyoung;Yun, Haejung
    • Journal of Service Research and Studies
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    • v.14 no.3
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    • pp.102-130
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    • 2024
  • The accelerated pace of change in the business environment and the advent of new information and communication technologies since the onset of the pandemic have had a profound impact on the way in which work is conducted. These developments are also affecting the nature of secretarial roles, with the adoption of digital workplaces rendering online-based work that transcends physical time and space the norm. The role of the secretary is also undergoing a transformation, with the capacity to utilize digital technology and communicate in person emerging as crucial competencies. The objective of this study is to provide an exploratory account of the evolving work environment and the newly required competencies of secretaries in the digital workplace. The research methodology comprised in-depth interviews with current assistants, the objective of which was to explore the cultural, spatial, technological, and workplace changes and the new competencies required. The study revealed that the role of secretaries in the digital workplace is undergoing a significant transformation. This is characterised by a decline in traditional face-to-face work, an increased reliance on digital platforms, and the digitisation of information management. The competencies deemed essential for success in this evolving environment include digital literacy, proficiency in text-based communication, the ability to maintain a consistent attitude towards online and offline work, and the capacity to adapt to new situations. The findings of this study contribute to the academic understanding of the digital workplace for secretaries and provide a useful basis for the development of practical secretarial education and career development programs. Furthermore, this study aims to provide a more comprehensive examination of secretarial work in the digital workplace and to identify areas where secretaries may require additional support.

Suppression of Glioblastoma Stem Cell Potency and Tumor Growth via LRRK2 Inhibition

  • Saewhan Park;Kyung-Hee Kim;Yun-Hee Bae;Young Taek Oh;Hyemi Shin;Hyung Joon Kwon;Chan Il Kim;Sung Soo Kim;Hwan-Geun Choi;Jong Bae Park;Byoung Dae Lee
    • International Journal of Stem Cells
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    • v.17 no.3
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    • pp.319-329
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    • 2024
  • Leucine-rich repeat kinase 2 (LRRK2), a large GTP-regulated serine/threonine kinase, is well-known for its mutations causing late-onset Parkinson's disease. However, the role of LRRK2 in glioblastoma (GBM) carcinogenesis has not yet been fully elucidated. Here, we discovered that LRRK2 was overexpressed in 40% of GBM patients, according to tissue microarray analysis, and high LRRK2 expression correlated with poor prognosis in GBM patients. LRRK2 and stemness factors were highly expressed in various patient-derived GBM stem cells, which are responsible for GBM initiation. Canonical serum-induced differentiation decreased the expression of both LRRK2 and stemness factors. Given that LRRK2 is a key regulator of glioma stem cell (GSC) stemness, we developed DNK72, a novel LRRK2 kinase inhibitor that penetrates the blood-brain barrier. DNK72 binds to the phosphorylation sites of active LRRK2 and dramatically reduced cell proliferation and stemness factors expression in in vitro studies. Orthotopic patient-derived xenograft mouse models demonstrated that LRRK2 inhibition with DNK72 effectively reduced tumor growth and increased survival time. We propose that LRRK2 plays a significant role in regulating the stemness of GSCs and that suppression of LRRK2 kinase activity leads to reduced GBM malignancy and proliferation. In the near future, targeting LRRK2 in patients with high LRRK2-expressing GBM could offer a superior therapeutic strategy and potentially replace current clinical treatment methods.

Analysis of Food Tech Startups: A Case Study Utilizing the ERIS Model (푸드테크 스타트업 현황 분석 및 ERIS 모델 기반 성공 사례연구)

  • Sunhee Seo;Yeeun Park;Jae yeong Choi
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.4
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    • pp.161-182
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    • 2024
  • The study analyzed the rapidly growing food tech startup in South Korea, focusing on industry classification, core technological domains, investment stages, and growth trajectories. Utilizing the ERIS model, two innovative food tech startups, MyChef and CatchTable, were examined as case studies. Results revealed food tech startups are focusing on information technology and smart distribution technology-oriented solutions rather than traditional food production. This study also found that robotics and AI integration were key technology areas. Analyzing the emergence of food tech startups, investment stages, and cumulative investment amounts based on founding years revealed a trend of scaling operations through rounds of funding, especially after securing SERIES A and B funding. The period between 2014 and 2018 saw a dense concentration of food tech startup establishments, likely influenced by favorable conditions for technological innovation amid the Fourth Industrial Revolution. The high rate of strategic mergers and acquisitions and bankruptcy can be interpreted as the complexity inherent in the food tech industry. The case study of MyChef, which grew into HMR manufacturing, and Wad(CatchTable), which expanded into a restaurant reservation platform, derived the entrepreneurs, resources, industry, and strategic factors that served as success factors for food tech startups. This study has practical implications in that it provides entrepreneurs, investors, and policymakers in the food tech industry with insight and direction to develop strategies in line with market trends and technological changes and promote sustainable growth.

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Influence analysis of Internet buzz to corporate performance : Individual stock price prediction using sentiment analysis of online news (온라인 언급이 기업 성과에 미치는 영향 분석 : 뉴스 감성분석을 통한 기업별 주가 예측)

  • Jeong, Ji Seon;Kim, Dong Sung;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.37-51
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    • 2015
  • Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

A Study on the Influence of IT Education Service Quality on Educational Satisfaction, Work Application Intention, and Recommendation Intention: Focusing on the Moderating Effects of Learner Position and Participation Motivation (IT교육 서비스품질이 교육만족도, 현업적용의도 및 추천의도에 미치는 영향에 관한 연구: 학습자 직위 및 참여동기의 조절효과를 중심으로)

  • Kang, Ryeo-Eun;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.169-196
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    • 2017
  • The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

A Study on Analysis of consumer perception of YouTube advertising using text mining (텍스트 마이닝을 활용한 Youtube 광고에 대한 소비자 인식 분석)

  • Eum, Seong-Won
    • Management & Information Systems Review
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    • v.39 no.2
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    • pp.181-193
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    • 2020
  • This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.