• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.141-154
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• 2014

It is widely confirmed that online retailers can obtain crucial resources and greater growth potential by depending on the external web portal sites as it is explained in resource dependence theory. Nevertheless, recent studies show that the effect of dependence may not always be beneficial for firms and stress the importance of finding relevant contingent factors. In this study, we identify and suggest that firms' age and niche width strategy, whether generalist or specialist, are contributing factors on moderating the positive relationship between resource dependence and firm growth. To test our hypotheses based on the theory, we have collected monthly web traffic data of online retailers and portals from March 2000 and July 2008. The empirical results lend support to our theory of the firm age having a negative interaction effect on web traffic dependence. Moreover, results verified that positive effect of depending on the portals may become greater if the online retailer is a specialist in terms of niche width.

• Broadcasting and Media Magazine
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• v.17 no.3
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• pp.24-39
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• 2012

2011년 3월 11일 일본 혼슈 센타이 동쪽 179Km 해역에서 발생한 규모 9.0의 지진에 의한 쓰나미로 동북부 지역에 엄청난 피해가 발생함에 따라 우리나라에서도 지진을 비롯한 각종 대규모 자연재해 상황 하에서 재난방송에 대한 체계를 전반적으로 재점검해야 한다는 의견이 나오고 있다. 지금까지 우리는 재난이 발생하면 TV나 라디오 등 전통적인 매체에 의존하고 있으며 실제 이러한 매체는 지금까지 국민들에게 신속하게 재난정보를 알리는 중요하고도 충실한 역할을 담당해 오고 있다. 그러나 지난해 일본의 쓰나미와 같이 인간의 능력으로 감당하기 힘든 대규모 재난이 발생하였을 경우 이러한 전통적인 재난 방송 매체만으론 역 부족이 될 수 있고. 실제로 일본에서 효과를 나타낸 것은 인터넷 전화(VoIP)와 SNS(Social Network Service) 등 뉴미디어로 구글, 페이스북과 국내의 NHN, 다음 등은 실종자 정보와 피난처 정보를 제공하고 피해자의 안위를 확인할 수 있는 서비스를 하는 등 필요한 정보를 실시간으로 알리는 새로운 매체로 큰 역할을 했다는 평가를 받았다. 본 고에서는 뉴미디어를 재난방송 전달 매체로 활용하기 위해 현재 운영되고 있는 재난방송 체계 및 시스템의 조사를 통해 개선되어야 할 사항을 도출하고 활용 가능한 뉴미디어 현황 조사를 통해 재난방송 시스템에 적용할 수 있는 방안을 살펴보고 외국의 재난방송 운영 사례를 참고하여 새로운 전달체계 모델의 정립과 이를 위한 법적, 제도적 강화 방안을 제시하였다.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.97-108
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• 2019

In a situation where production of short-term income forestry products has been stagnant or decreased in recent years, the government or related agencies are trying to promote consumption of short-term income forest products. While consumer sentiment studies on short-term income forestry are being conducted as part of efforts to encourage consumption, most of the studies rely solely on a survey-based method. In the information age, consumer sentiment toward consumer goods is reflected mostly on social networking sites due to the spread of the Internet. It is necessary to avoid relying solely on a survey-based method in existing research and directly analyze social networking sites that reflect consumers' wishes. In response, this study identified consumer preferences for major short-term income forest products through social big data analyses and used the results to establish strategies for promoting the sale of short-term income forest products. This paper is different from previous research using only a survey-based method, and it uses SNS to understand consumer preferences. The results of this study are expected to directly help the government or related agencies promote consumption of short-term income forest products and, ultimately, help improve forest-related income and promote healthy forest condition.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.425-440
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• 2012

As the scale of the internet grows, the amount of subjective data increases. Thus, A need to classify automatically subjective data arises. Sentiment classification is a classification of subjective data by various types of sentiments. The sentiment classification researches have been studied focused on NLP(Natural Language Processing) and sentiment word dictionary. The former sentiment classification researches have two critical problems. First, the performance of morpheme analysis in NLP have fallen short of expectations. Second, it is not easy to choose sentiment words and determine how much a word has a sentiment. To solve these problems, this paper suggests a combination of using web-scale data and a statistical approach to sentiment classification. The proposed method of this paper is using statistics of words from web-scale data, rather than finding a meaning of a word. This approach differs from the former researches depended on NLP algorithms, it focuses on data. Hadoop and MapReduce will be used to handle web-scale data.

• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.1-22
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• 2009

As Internet shopping is getting popular, "trust" has become an important factor for customers to select websites and have repurchase intention. "Trust" has been developed from uni-dimensional concept to multi-dimensional concept in e-Commerce area. From the multi-dimensional viewpoint, this study is to investigate the processes to build trust for online stores. For this purpose, this study classifies the concept of trust into cue-based trust and experience-based trust, and then investigates their relationship in online stores. This study also identifies factors that explain cue-based trust and experience-based trust. The result from questionnaire survey distinguished cue-based trust from experience-based trust and both trust concepts are correlated each other. Second, cue-based trust is explained by perceived size, perceived reputation, and return policy, while experience-based trust is done by navigation, information usefulness and interactivity.

• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.723-731
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• 2005

Wide spread deployment of infrastructure WLANs has made Wi Fi an integral part of today's Internet access technology. Despite its crucial role in affecting end to end performance, past research has focused on MAC protocol enhancement, analysis and simulation based performance evaluation without sufficient consideration for modeling inaccuracies stemming from inter layer dependencies, including physical layer diversity, that significantly impact performance. We take a fresh look at IEEE 802.11 WLANs, and using experiment, simulation, and analysis demonstrate its surprisingly agile performance traits. Contention based MAC throughput degrades gracefully under congested conditions, enabled by physical layer channel diversity that reduces the effective level of MAC contention. In contrast, fairness and jitter significantly degrade at a critical offered load. This duality obviates the need for link layer flow control for throughput improvement but necessitates traffic control for fairness and QoS. We use experimentation and simulation in a complementary fashion, pointing out performance characteristics where they agree and differ.

• Food Science and Industry
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• v.54 no.3
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• pp.124-131
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• 2021

In the 4th industrial revolution, Artificial Intelligence (AI), big data, Internet of Things (IoT) are already around us, making our society hyper-connected and blurring the lines between the digital and biological spheres. We witness drastic changes not only in the food industry, but also in economy, society and our life as a whole. Technologies bring industrial reorganization and greater changes at the system level and the food industry is not exceptional. Human demand for foods continues to grow and the very nature of the food industry remains unchanged, but its production, distribution and marketing face unprecedent innovations. Passing through the global pandemic, the food industry has been evolved into 'contact-free', as the safety become our top priority. Amid the gradual shift to technology-oriented society, the smarter food safety management skills and tools are being adopted in many countries exerting greater efforts to enhance traceability and to upgrade AI-powered safety management system.

• Journal of Digital Contents Society
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• v.13 no.4
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• pp.501-516
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• 2012

The purpose of this study is to explore the fundamental nature and meanings of the experiences of university students with regard to their smartphone usage in order to prevent smartphone addiction and provide guidelines to develop effective interventions. Nine university students who were currently enrolled in an university located in a Korean province participated in this study. In-depth interviews were conducted from June of 2012 to July of 2012, and data were analyzed using Colaizzi's phenomenological qualitative method. As a results, five theme and 40 subthemes of experiences of problematic smartphone usage were identified. Those themes include 1) a desperate try to connect with others(exposing oneself without appropriate self-protection, seeking emotional comfort, hurt and mistrust); 2) excessive use of smartphone and loss of self-control(more smartphone usage over computer/over-immersion/excessive usage/habituation, loss of self-control); 3) psychological difficulties(excessive attachment and dependence, separation anxiety, clingingness, reduced patience) ; 4) threats to daily functioning (changes in priorities, regressed independent daily functioning, irregular daily patterns, health problems, interruptions from free messenger, academic difficulties); 5) potential for recovery(conflictual feelings and doubts over smartphone usage, importance of interpersonal(face-to-face) communications, willingness to cut down the use, hope for recovery). This study provided suggestions for the prevention effort against smartphone addiction.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.53-59
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• 2022

After the 3rd level autonomous driving vehicle, the 4th and 5th level of autonomous driving technology is trying to maintain the optimal condition of the passengers as well as the perfect driving of the vehicle. However current autonomous driving technology is too dependent on visual information such as LiDAR and front camera, so it is difficult to fully autonomously drive on roads other than designated roads. Therefore this paper proposes a Braking Strength Calculation System (BSCS), in which a vehicle classifies road conditions using data other than visual information and calculates optimal braking strength according to road conditions and driving conditions. The BSCS consists of RCDM (Road Condition Definition Module), which classifies road conditions based on KNN algorithm, and BSCM (Braking Strength Calculation Module), which calculates optimal braking strength while driving based on current driving conditions and road conditions. As a result of the experiment in this paper, it was possible to find the most suitable number of Ks for the KNN algorithm, and it was proved that the RCDM proposed in this paper is more accurate than the unsupervised K-means algorithm. By using not only visual information but also vibration data applied to the suspension, the BSCS of the paper can make the braking of autonomous vehicles smoother in various environments where visual information is limited.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.23-32
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• 2019

Objectives: Insomnia is not only the most common sleep-related disorder, but also is one of the most important. Knowledge of the comorbidities of insomnia is essential for proper treatment including pharmacological and non-pharmacological methods to prevent disease chronification. This study aimed to determine sleep clinic patients' knowledge of insomnia. Methods: This study recruited 44 patients (24 males and 20 females; mean age $54.11{\pm}16.30years$) from the sleep clinic at National Center for Mental Health. All subjects were asked to complete a self-report questionnaire about their reasons for visiting a sleep clinic and about their knowledge of treatment and comorbidities of insomnia. Results: The reasons for visiting the sleep clinic were insomnia symptoms of daytime sleepiness, irregular sleeping time, nightmares, snoring, and sleep apnea, in that order. Of the responders, 72.7% had a comorbidity of insomnia, and 22.7% showed high-risk alcohol use. In addition, 70.5% of responders chose pharmacological treatment of insomnia as the first option and reported collection of information about treatment of insomnia mainly from the internet and medical staff. More than half (52.3%) of the respondents reported that they had never heard about non-pharmacological treatments of insomnia such as cognitive behavioral treatment (CBT-I) or light therapy. The response rate about comorbidities of varied, with 75% of responders reporting knowledge of the relation between insomnia and depression, but only 38.6% stating awareness of the relation between insomnia and alcohol use disorder. Of the total responders, 68.2% were worried about hypnotics for insomnia treatment, and 70% were concerned about drug dependence. Conclusion: This study showed that patients at a sleep clinic had limited knowledge about insomnia. It is necessary to develop standardized insomnia treatment guidelines and educational handbooks for those suffering from insomnia. In addition, evaluation of alcohol use disorders is essential in the initial assessment of sleep disorders.