• Information Systems Review
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• v.17 no.2
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• pp.193-218
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• 2015

The purpose of this study is to investigate the effects of closed-type SNS use (i.e., Naver Band) on the perception and behavior of the Korean Army soldiers. In contrast to open-type SNS (e.g., Facebook or Twitter), Naver Band is an online communication service system mostly based on confined offline social network. Therefore, it increases communication between acquaintances who have previously formed relationships. Although the Korean Army recently began to use Naver Band as a method of communication between soldiers, their parents/acquaintance, and Army commanders (or leaders), little research has been done about how this use directly affects army soldiers. Hence, applying the motivation opportunity ability theory of behavior, this study examines how enjoyment (Motivational factor), social ties (Opportunity factor), and social intelligence (Ability factor) affect soldiers' belongingness to their organization and organizational citizenship behavior (OCB). We also hypothesize that army soldiers' belongingness and OCB may enhance their individual performance. Survey results show that enjoyment, social ties, and social intelligence increase army soldiers' belongingness, which leads to OCB. Also, enhanced OCB increases individual performance. However, the effect of enjoyment and social ties on soldiers' OCB is non-significant and soldiers' belongingness does not have influence on individual performance. Theoretical and practical implications are presented.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.

• Journal of the International Relations & Interdisciplinary Education
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• v.3 no.1
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• pp.51-75
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• 2023

Relying on disciplinary competitions to enhance college students' innovation and entrepreneurship is one of the specific paths to explore the reform of innovation and entrepreneurship education in colleges and universities. This paper conducts an empirical study on the practice of disciplinary competitions among Chinese university students, the problems of innovation and entrepreneurship education in Chinese universities and the impact of disciplinary competitions on innovation and entrepreneurship among Chinese university students, using university students in Chinese universities as the respondents. The data collected online and offline were analysed using SPSS26 statistical software. The results of the analysis show that Chinese university students show a high level of interest in innovation and entrepreneurship competitions and that there are some differences in the level of interest in innovation and entrepreneurship competitions among university students of different academic levels. More than half of Chinese university students have participated in innovation and entrepreneurship competitions and the initiative of participating in innovation and entrepreneurship competitions varies by grade. The biggest problem facing innovation and entrepreneurship education in schools is the lack of professional innovation and entrepreneurship teachers, followed by the lack of guidance on innovation and entrepreneurship-related policies, and the unreasonable reward system, which makes teachers and students less motivated to innovate and entrepreneurship. Through one-dimensional linear regression analysis, it is found that the degree of attention to innovation and entrepreneurship among college students affects college students' entrepreneurial awareness and entrepreneurial practice; the degree of initiative of college students' innovation and entrepreneurship competition affects college students' entrepreneurial effect; and the degree of initiative of college students' innovation and entrepreneurship competition affects college students' entrepreneurial practice.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.1-21
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• 2022

Entrepreneurship has been emphasized in social and national importance. However, survival rate of domestic startups is relatively low. Therefore, it is urgent to come up with a plan to increase the survival rate by improving the satisfaction level of early start-ups. In this study, we investigated the effect of start-up motivation, start-up competence, and start-up support policies of early start-up companies on start-up satisfaction and the moderating effect of social support. Startup motivation were divided into economic motivation and self-actualization motivation in detail. Start-up competence was divided into experience competency and marketing competency in detail. The start-up support policy was divided into start-up fund support and start-up consulting support. An empirical analysis was conducted by receiving online and offline questionnaires from 250 managers of early start-up companies within 7 years of founding. As a result, economic motivation, self-actualization motivation, experience competency, marketing competency, and start-up fund support had a significant positive (+) effect on start-up satisfaction. However, start-up consulting support did not have a significant effect. In addition, the size of the influence on startup Satisfaction was in the order of self-actualization motivation, experience competency, marketing competency, startup fund support, and economic motivation. The moderating effect of social support was found in economic motivation, self-actualization motivation, and experience competency. However, the moderating effect of marketing competency, start-up fund support, and start-up consulting support was not tested. Through the research results, the academic implications that self-actualization motivation and experience competency are key factors in enhancing start-up satisfaction were suggested. In addition, practical implications were suggested that it is necessary to improve the effectiveness of entrepreneurship education programs and entrepreneurship consulting support systems that can maximize the self-realization and experience capabilities of early entrepreneurs.

• Archives of design research
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• v.20 no.3 s.71
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• pp.315-324
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• 2007

The fast development of the information technology makes Korea one of the most advanced countries in information communication in the world in a short period of time. However, the gap between the aged and the young has been seriously increased. Those who are less than 10% of the older adults are using the internet at present. It means the elderly has many difficulties in using the internet because of their physical and cognitive differences. The purpose of this study is that the aged can easily achieve and use information by developing a guidelines for the Korean typography in the web interface. A literature search was conducted on the web interface design guidelines for older adults. These guidelines were classified by interface component and the study subjects needed for the Korean internet environment were selected. The subjects are a more comfortably readable typeface according to the sizes, a proper text size of Gulim and Batang, a more comfortably readable leading size, the appropriate letter spacing, the proper line length of body, the suitable size proportion between a title and a body, and a more comfortably readable text alignment. Survey questions were made and these Questions were improved after the pretest. Both online and offline survey programs were written and the aged and the young were tested with these programs. The result of this survey shows that there are satisfaction differences between the aged and the young in the readability and legibility of the web contents. Therefore these universal guidelines to be used in the Korean typographical environment for the future aged population were specified. It is expected that this study will be used as basic data for the universal web interface where the older adults can easily use and acquire information.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.167-184
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• 2020

This study analyzed the effects of information orientation and technology commercialization ability on technological performance of corporate workers. Information Orientation consisted of information technology capability, information management ability, information behavior and value, and technology commercialization capability consisted of productization capability, production capability, and marketing capability as sub-variables, and technology accumulation capacity was used as a coordinating variable. An empirical analysis was performed on 349 online and offline questionnaires collected from corporate employees. Analysis results using SPSS v22.0 and Process macro v3.4 First, information orientation and technical performance were found to have a significant effect.In addition, information orientation had a significant effect on technology commercialization capability. The magnitude of the influence on the productive capacity and the productive capacity in the variable of competency was in the order of information technology ability, information management ability, information behavior and value, but the influence on marketing capability was different from the previous results. Information management ability and information technology ability were in order. Second, the product commercialization capability, production capability, and marketing ability of technology commercialization ability had a significant effect on technology performance independently of information orientation. Third, the information technology ability and information management ability had a significant influence on the technical performance, but the indirect effect through the commercialization ability and marketing ability in information behavior and value was significant, the indirect effect of transit was not significant. Fourth, only the interaction terms of production capacity and technology accumulation capacity were significant among the sub-variables of technology commercialization capacity, and technology accumulation capacity, commercialization capacity, and marketing ability were not significant. Therefore, the relationship between productive capacity and technological performance can be interpreted as lower in firms with high technology accumulating ability than in lower firms, subsequent studies will require the introduction of other independent variables, models through the introduction of parameters and control variables.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.69-79
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• 2022

The purpose of this study is to monitor the pesticide residues in frozen fruits and vegetables distributed and sold in online and offline markets in Korea. For the study, 107 samples of 34 types of frozen fruits and vegetables were examined, and a total of 341 pesticide residues were analyzed by using multiclass pesticide multi-residue methods of the Korean Food Code. As a result, pesticide residues were detected from 16 of 64 frozen fruits samples and 15 of 43 frozen vegetables samples. Conclusively, residues were detected from 31 samples in total, showing a detection rate of 29.0%. Specifically, pyridaben exceeded the Maximum Residue Limits (MRLs) based on the Positive list system (PLS) in one of the frozen radish leaves, and the violation rate was 0.9%. Detection on frozen fruits and vegetables was made 23 times for 11 types and 36 times for 21 types. In total, 28 types of pesticide residues were detected 59 times. Fungicides were detected the most in frozen fruits, while insecticides were detected the most in frozen vegetables. The most detected pesticides were the insecticide, acaricide chlorfenapyr (5) and the fungicide boscalid (5). Chlorfenapyr was detected only in frozen vegetables, and boscalid was detected in frozen fruits except one.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.