• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.45-60
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• 2023

In this study, we analyzed the influence of middle-aged office workers' entrepreneurial competency and entrepreneurial opportunity recognition on entrepreneurial intention by mediating entrepreneurial opportunity evaluation. Sub-variables of entrepreneurial competency were classified into prior knowledge, positive attitude, and social network. For the empirical analysis of this study, an online survey using Naver Office was conducted for about 15 days (February 6, 2023 - February 20, 2023) targeting office workers across the country who are interested in starting a business, and a total of 262 copies were collected and missing values. For 250 copies excluding 12 copies, SPSS Ver.24.0 and PROCESS MACRO Model 4.0 were used for empirical analysis. The results of the analysis are as follows: First, the higher the prior knowledge of the founder's individual competency, social network, and entrepreneurial opportunity recognition, the higher the entrepreneurial opportunity evaluation and entrepreneurial intention. On the other hand, it was found that the positive attitude among entrepreneurs' individual competencies did not affect entrepreneurship opportunity evaluation and entrepreneurial intention. In addition, the magnitude of the influence on entrepreneurial opportunity evaluation and entrepreneurial intention was in the order of entrepreneurial opportunity recognition, prior knowledge, and social network. This is because the positive attitude of middle-aged office workers towards start-up has a negative image of start-up due to the shrinking start-up environment due to COVID-19, fear of failure due to lack of preparation for start-up, and successive cases of start-up failure due to cognitive bias errors due to overconfidence. implying that there is Second, it was found that the evaluation of entrepreneurship opportunities had a significant positive (+) effect on entrepreneurial intention in a situation where the entrepreneur's individual competency and entrepreneurial opportunity recognition were controlled. Third, the startup opportunity evaluation was shown to mediate between the prior knowledge of the entrepreneur's individual competency, social network and entrepreneurial opportunity recognition, and entrepreneurial intention, but it did not mediate between positive attitude and entrepreneurial intention. Fourth, among the factors influencing entrepreneurial opportunity evaluation and entrepreneurial intention, entrepreneurial opportunity recognition was found to be larger than founder's individual competency, confirming the importance of entrepreneurial opportunity recognition. Fifth, it was found that prior knowledge and network, which are individual capabilities of the founder, affect the evaluation of entrepreneurial opportunities and entrepreneurial intention, so that strengthening entrepreneurship education to recognize the importance of cultivating prior entrepreneurial knowledge and experience can revitalize middle-aged office workers' entrepreneurship. confirmed.

• Journal of Agricultural Extension & Community Development
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• v.8 no.1
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• pp.107-119
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• 2001

As the information gap between rural and urban area, and between men and women has been widening, the Rural Development Administration(RDA) has initiated the women farmers information project from 2000. The aims of this project are; 1) to facilitate women farmers' computer and information application in agriculture and income generating activities, and 2) to make them to be leaders to popularize computer application in rural area and agricultural sector. For these, RDA has provided not only PC, software, computer training but also the post support of extension educator to target group. This paper focused on evaluating the effect of the project, clarifying the related variables with the effect, and providing suggestions to enhance the effect. The data were gathered from 310 target women farmers and 166 extension educators in charge of the project all over the country by mailing survey with questionnaire. The main findings of this study were as follows; 1) The level of computer application of the target group was improved drastically, 2) As their self-assessment, they could improve psychological fear on the computer, recognition about information, and attitude to seek information, 3) This project was helpful for them in terms of information gathering and farm(or income generating activities) management, 4) They tried to disseminate the benefit of computer application to neighbors, so that the neighbors' interest in computer and attendance of computer training were improved, 5) Variables such as the computer training hours, the number of interaction with extension educator, formal schooling and farming history were significantly related to the project's effect. To enhance the project's effect the following strategies should be carried out; 1) The period of the computer training course should be standardized and the subjects should attend to the computer training course for the standardized period. 2) Through continuous interaction with the subjects, the extension educator should support them to use computer well and to overcome some difficulties as a beginner. 3) In selecting the subjects, the priority should be given to the person who graduated high school at least. 4) The subjects should focus on using management software, gathering useful information for their business, and selling their products directly to the consumer. 5) So as to enhance the abilities mentioned above, RDA should strengthen learning opportunities through on-line training and providing educational software, besides of existing off-line training.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.137-146
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• 2022

The use of RPA (Robotic Process Automation) has been recently reviewed in various industries, but it seems that it is not being applied to companies faster than ever expected. In this study, three perceived risk factors affecting the acceptance conflict and acceptance intention of RPA technology were proposed and the effects of RPA on acceptance conflict and acceptance intention were investigated using RPA experienced people, gender and ICT industries as control variables. For the research, online survey was conducted targeting office workers and analyzed the results by using SPSS 22.0 and AMOS 22.0. As a result, it was found that among the three perceived risk factors, concern about introduction failure, employment insecurity, and execution errors, employment insecurity and execution errors did not affect the acceptance conflict and acceptance intention of RPA. This research shows that concerns over the introduction failure affected the acceptance conflict and acceptance intention. In addition, the acceptance conflict was judged as a factor of the mediation effect of the acceptance intention. From the perspective of companies that want to apply RPA, the theoretical and practical implications of business management are meaningful in that they can identify and respond to particularly important factors among perceived risks.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Management & Information Systems Review
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• v.35 no.1
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• pp.273-286
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• 2016

This study investigated the information contents of KOSPI200 Options for intraday big market movement by using minute by minute data. The major findings are summarized as follows; First, big market movement occurred more frequently during 9:00~10:00 and 14:00~14:50. These phenomena reflect market unstability just after opening and near closing. Second, VKSOPI is most closely associated with extreme changes such as KOSPI200 jumps. Third, VKOSPI is showed more predictive power with negative KOSPI200 jumps than KOSPI200 jumps. Fourth, VKOSPI showed predictive power for the positive and negative jumps up to 30 minutes before the jumps occurs. The purpose of this study is to explore the most recent topics in the field of finance, research on market microstructure. This study is an important contribution to investigate intraday information comprehensively in terms of market microstructure effects using the 15-year long-term and the high-frequency data(minute by minute). The results of this study are expected to contribute to detect intraday true jumps, proactive development of market risk indicators, risk management, derivatives investment strategy.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.25-49
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• 2009

Advances in technology have resulted in the emergence of new information systems. The convergence of IT and manufacturing sectors has blurred the boundaries among industries. Also, such convergence has become established as a paradigm to build a new area. Especially the convergence of broadcasting and telecommunication, notably in the case of IPTV (Internet Protocol Television), is among the most salient examples of its kind in recent years as a major case of disruptive technology innovation. Despite its much fanfare, such convergence, however, has not fulfilled the expectation; it has not produced positive economic effects while negatively affecting the growth of IPIV. Stakeholders in and around IPIV including telecommunication companies, broadcasting corporations, and government bodies wish to gain control of IPTV under their wings. IPTV has drifted in the midst of conflicts among the stakeholders in and around IPTV, particularly telecommunication and broadcasting organizations in a broad sense. Our empirical research intends to deal with how audiences accept IPTV and how firms provide IPTV services to utilize their resources. Three research questions in this paper include, first, whether Technology Acceptance Model (TAM) can sufficiently explain the acceptance of IPTV as an information system. The second question concerns with empirically testing the playful aspect of IPTV to increase its audience acceptance. Last, but not least, this paper deals with how firms can efficiently and effectively allocate their limited resources to increase IPTV viewers. To answer those three main questions of our study, we collect data from 197 current subscribers of high speed internet service and/or cable/satellite television. Empirical results show that 'perceived usefulness (PU) $\rightarrow$ Intention to use' and 'perceived ease of use (PEU) $\rightarrow$ Intention to use' are significant. Also, 'perceived ease of use' is significantly related to 'perceived usefulness.' Perceived ease of handling IPTV without much effort can positively influence the perceived value of IPTV. In this regard, engineers and designers of IPTV should pay more attention to the user-friendly interface of IPTV. In addition, 'perceived playfulness (PP)' of IPTV is positively related to 'intention to use'. Flow, fun and entertainment have recently gained greater attention in the research concerned with information systems. Such attention is due to the changing features of information systems in recent years that combine the functional and leisure attributes. These results give practical implications to the design of IPTV that reflects not just leisure but also functional elements. This paper also investigates the relationship between 'perceived ease of use (PEU)' and 'perceived playfulness (PP).' PEU is positively related to pp. Audiences without fear can be attracted more easily to the user-friendly IPTV, thereby perceiving the fun and entertainment with ease. Practical implications from this finding are that, to attract more interest and involvement from the audience, IPTV needs to be designed with similar or even more user friendly interface. Of the factors related to 'intention to use', 'perceived usefulness (PU)' and 'perceived ease of use (PEU)' have greater impacts than 'perceived playfulness (PP).' Between PU and PEU, their impacts on 'intention to use' are not significantly different statistically. Managerial implications of this finding are that firms in preparation for the launch of IPTV service should prioritize the functions and interface of IPTV. This empirical paper also provides further insight into the ways in which firms can strategically allocate their limited resources so as to appeal to viewers, both current and potential, of IPTV.

• Management & Information Systems Review
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• v.34 no.2
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• pp.131-149
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• 2015

Recently many organizations have engaged in widespread restructuring as well as more flexible usage of labor in an attempt to cut costs and to increase profit. As a result of lays offs resulting from frequent restructuring, many people no longer consider their jobs as permanent positions. many employees have an increased feeling of job insecurity. There structuring and following downsizing have created an uncertain environment within creased fear offer ther job losses. therefore the study of job insecurity is significant. especially To understand the relationship between job security and union-relation behaviors on the industrial relations. The purpose of this study suggested the strategies to company and union. The purpose of this study is to examine how the union-relation behaviors are influenced by the job security. This study built a exploratory model that there is causal relationship of job security to union commitment, dual commitment, and labor related behaviors. For the verification of this study model, the regression analysis was applied to the surveys of 236 members of union that are located in Busan, Gyeongnam, Ulsan, and Pohang. The result of this research shows that the job insecurity is strongly related to the union commitment and union related behaviors. According to the research, the effect that the job security affects union commitment and union related behaviors are positive. With the research outputs, we have discussed about the academic and pragmatic viewpoint. We proposed comprehensive model to verify how the job insecurity affects the union-related behaviors, and objectively analyzed the model. The research result was opposite to what the existing theories have said that high job insecurity derives high union-related behaviors. This result is meaningful because it is concerned with the social issues-present situation of Korean company, low-employment, unstable employment and so on. Moreover, this research may contribute to expand the aspect of academic research on job insecurity as there are few research conducted in korea. This research also suggests the realistic alternative of union-related behaviors because it is proved that job security can contribute to innovation activities. Also, this research implies that the matter of job insecurity is the basic need of organizational individual and presents that job security is not a notion but the alternative by using of the positional stability and situational control power. The limitation of this research is that it is only utilized the cross-sectional study. To remedy the cross-sectional study, vertical, and serial method of research is needed. And there is no enough sample to secure more comprehensive data as the targets of the research is limited to Busan and Gyeongnam regions. Finally, the measurement tool for job security is needed to be suitably modified to by the South Korea's economic, linguistic, and cultural situation.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Yeungnam Medical Science
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• v.7 no.2
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• pp.67-77
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• 1990

This study was intended to analyse the relation between the psychic traumatic experience and the psychological health of the aged. The authors carried out this study by means of the combined anxiety-depression scale(CADS) and the preadolescence traumatic experience scale(PTES) with 278 aged men and women residing in Taegu from September to October 1988. The results were as follows : 1. Based on the scores avaluated by CADS, the scores of the both groups showed that comparative group was accounted for $40.15{\pm}6.19$, while the experimental group for $57.75{\pm}6.37$, which showed significantly higher score in the experimental group(p<0.001). 2. The experimental group showed significantly higher early experience score than the comparative group in the dietary difficulty, alcoholism among family members, disunion between husband and wife, trouble between mother and children, early mother loss, parent's indifference and unwanted birth(p<0.001). 3. The experimental group showed higher early experience score than the comparative group by sex, age, marital status and grown location(p<0.001). 4. When the subjects were included in the unemployed and in the middle or low classes and their parents were engaged in agriculture and commercial business and believing in buddhism or non-religion, showed higher experience score (p<0.001).