• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Information Systems Review
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• v.25 no.2
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• pp.77-101
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• 2023

Due to COVID-19, paid virtual live-stream concerts have emerged as an alternative format and a new revenue model for in-person live concerts. Despite the increasing scholarly and practical interest in how participants experience paid virtual live-stream concerts, few studies examined participants' consumption and participation experiences. Thus, this study aims to provide insights into consumers' virtual live-stream concert experience by employing social representations theory (SRT). We explore the features of paid virtual live-stream concerts based on the C-P-N-D (Content-Platform-Network-Device) framework and the consumers' cognitive and affective perception. To this end, an SRT-based core-periphery analysis was conducted based on 239 responses to the open-ended survey questions. The results show that network-and device-level features of virtual live concerts and participants' overall perception are presented as core elements of paid virtual live-stream concerts, whereas content- and platform-level features are peripheral elements. This finding provides an in-depth understanding of the emergence of paid virtual live-stream concerts as an alternative concert format, thereby providing an invaluable understanding of a virtual live concert experience and theoretical and practical insights.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.199-216
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• 2024

This research examines the factors influencing consumer purchase intentions in e-commerce live streaming, set against the backdrop of the internet celebrity economy. The investigation serves as a pivotal inquiry into the dynamics of this economy, striving to uncover the extent of internet celebrities' influence, particularly in terms of their economic impact. Employing the Emotional Behavioral Cognitive (ABC) attitude theory and the Stimulus Organism Response (S-O-R) theory as foundational frameworks, this study scrutinizes internet celebrity live streaming sales. It incorporates direct observations and leverages existing scholarly work to devise a tailored measurement scale and questionnaire. From this, a research model and hypotheses are developed, leading to the establishment of an empirical model. This empirical model is instrumental in statistically analyzing how e-commerce live streaming, within the internet celebrity economy context, shapes consumer purchase intentions. By integrating theoretical insights and empirical findings, the research elucidates the strategic dimensions and consumer behavior aspects in digital commerce. It enhances understanding of how internet celebrity influence intersects with consumer purchasing processes. Overall, this study contributes to the academic discourse on digital marketing and consumer behavior, providing a nuanced perspective on the mechanisms through which internet celebrities affect e-commerce. It offers valuable implications for marketers, strategists, and policymakers aiming to navigate the complex landscape of the internet celebrity economy.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Informatization Policy
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• v.31 no.1
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• pp.83-99
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• 2024

This study seeks to shed light on the importance of "advancing administrative computer systems" for research administration efficiency, building upon prior literature, and aims at extending the scholarly discussion on the efficiency of research administration itself. To this end, two research questions were addressed. First, this research explores how research administrators perceive the advocated "advancement of administrative computer systems" in achieving research administration efficiency. Second, it investigates how external bureaucratic control affects burnout among administrative personnel engaged in research administration, and how burnout impacts the research-administration relationship, trust, and ultimately performance. The analysis of interviews and surveys yielded several results. For one, through the analysis of interviews conducted in the field of government-funded research institutions, it was found that "advancing computer systems" is met with practical concerns and skepticism, while also recognized as having the potential to contribute to the efficiency of research administration. Furthermore, it became evident that complex issues are intertwined. From a contrasting standpoint opposing computer advancement, the view that institutional regulations and cultural efficiency should take precedence over technology appears valid and raises a crucial point for consideration. On the other hand, regression analysis related to burnout shows empirical evidence that increased control by central government bureaucrats over administrative staff in government-funded research institutions leads to higher levels of burnout. Such elevated burnout is shown to have detrimental effects on trust between researchers and administrative personnel, as well as on overall performance. Through these discussions, we aim to stimulate academic and government interest in research administration efficiency.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.51-60
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• 2003

In the radical char]go of the business environments that the existing facilities can not guarantee the business-frosts anymore, enterprises have been importing ERP system. In Korea, Sam-sung Electronics did it for the first tin in the latter half of 1994 and other enterprises succeeded. Currently, government and public enterprises as well as most of the large enterprises are employing ERP system to sharpen the competitiveness and to win the business transparency. On the other hand, it is harder for small and medium enterprises shaded by the large enterprises to be well-equipped with information system such as ERP, because they have already suffered from chronic financial difficulties and shortage of many resources. Most of all, they prefer the short-term project that does not need much tine for them to make decisions and to carry out fully. Grounded on the above factors, in this work, I suggest the suitable ERP model for the small and medium enterprises and the successful importing process of ERP, which is derived from the previous researches made by other masters' thesis. If necessary information and human resources are interchanged pertinently between local education institute and small and medium enterprise, the latter could not only deal with the confronted difficulties successfully inside and outside but attain the goal of being proficient in up-to-minute high technology. Besides, giving the students the opportunity of researching into the practice of the business they have not ever known, local universities could help their students accumulate knowledges and acquire ideas which could not be achieved in pure academic studies. When the above-mentioned procedure is over, the students might get the intellectual faculty to ponder on the future more concretely and enter a profession more carefully. In the result, we would raise up the percentage of the employment among the graduates. And active participation of university professors is the last important factor that assists the small and medium enterprises for introducing ERP system successfully. Their scholarly attainments play an important role in strengthening local economy and make the business competitiveness balanced between the capital and the local economy.

• Journal of the Daesoon Academy of Sciences
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• v.27
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• pp.201-243
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• 2016

This paper analyzes the research trends from 358 scholarly articles published in the Journal of Daesoon Academy of Sciences from the first published journal in 1996 to the most recent journal published on the 25^th of 2015 and proposes ideas for improvement. First of all, "The Journal of Daesoon Academy of Sciences" does not meet the standards required by the National Research Foundation, falling short of the most important conditions for the registration such as the periodicity and punctuality expected from academic journals. Furthermore, in terms of the Bibliometrical analysis, the number of articles published by the journal is decreasing and the consistency, with regards to rules and principles regulating publication details and bibliography formats, is nonexistent. Although various authors seemed to be meeting these criteria on the surface, the ratio of co-authored articles is too small. Securing researchers specializing in Daesoon Thought for expanding the size of the journal is important, but it is also important to diversify the research topics through exchanging ideas among researchers from various organizations. Here are some ideas for the improvement of the Journal of Daesoon Academy of Sciences: First, in order to meet the standards for punctuality and periodicity, it would be best to publish the journal twice a year with 12 to 15 articles. Second, the journal must become searchable through the creation of a database. Third, the key words and abstracts of articles must be written in Korean and English to facilitate the sharing of articles among researchers. Fourth, the journal must have a diverse and outstanding editorial board which takes into account the geographical situations of its board members. Fifth, the Journal must include articles on relevant topics that reflect the core topics of the Daesoon Thought and other studies. Sixth, articles must have a front page that contains bibliographical items to convey information to the reader. Seventh, it is essential that the journal have a clear publication date detailing the year, month, and day as well as a standard numbering scheme (i.e, Vol. and no).

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Korean Journal of Social Welfare
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• v.59 no.4
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• pp.35-61
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• 2007

This study examines the determinants of employment and wage of new college graduates by using Youth Panel Data(2003-2005) of the Work Information Center, and seeks assignments for mitigating unemployment and wage disparities of new college graduates. Results are summarized as follows. First, an analysis of the determinants of employment shows that the Kyunggi Inchon district in school locations, higher school records, and qualification certificates positively affect the employment rate, while the private college group in the non-capital area negatively affects the employment rate. Second, an analysis of determinants of standard employment demonstrates that the Kyunggi Inchon district in school locations, higher school records, qualification certificates, and the major group of medical science, pharmacy, nursing science and health science, and the major group of education positively affect the employment rate, while the private college group in the non-capital area, the junior college groups in the capital and non-capital areas negatively affect the employment rate. Third, an analysis of determinants of nonstandard employment shows that the junior college graduation in scholarly attainments, the junior college groups in the capital and non-capital areas positively affect the employment rate, while the private college group in the non-capital area negatively affects the employment rate. Fourth, an analysis of the determinants of wages demonstrates that male in sex, the older in ages, the major group of medical science, pharmacy, nursing science and health science, and the major group of education positively affect the wages, while nonstandard employment, Kyunggi Inchon and Cholla districts in school locations negatively affect the wages. These results suggest several implications. First, college education should be reformed to cultivate professional manpower who are required by industries. Second, alternative measures to mitigate sex discrimination in labor markets should be prepared. Third, the process of attaining qualification certificates should be reformed in order that it is actually connected to the abilities of work performances and the improvement of productivity. Fourth, a locally balanced development must be realized through the decentralization of industries. Fifth a systematic and comprehensive program need to be prepared to promote the employment of new college graduates.

• Korean Journal of Child Education & Care
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• v.19 no.2
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• pp.177-196
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• 2019

Objective: This study aims to analyze research trends related to software education for young children, focusing on studies published in Korea from 2016 to 2019 March. Methods: A total of 26 research publications on software education for young children, searched from Korea Citation Index and Research Information Sharing Service were identified for the analysis. The trend in these publications was classified and examined respectively by publication dates, types of publications, and the fields of study. To investigate a means of research, the analysis included key topics, types of research methods, and characteristics of the study variables. Results: The results of the analysis show that the number of publications on the topic of software education for young children has increased over the three years, of which most were published as a scholarly journal article. Among the 26 research studies analyzed, 16 (61.5%) are related to the field of early childhood education or child studies. Key topics and target subjects of the most research include the curriculum development of software education for young children or the effectiveness of software education on 4- and 5-year-old children. Most of the analyzed studies are experimental research designs or in the form of literature reviews. The most frequently studied research variable is young children's cognitive characteristics. For the studies that employ educational programs, the use of a physical computing environment is prevalent, and the most frequently used robot as a programming tool is "Albert". The duration of the program implementation varies, ranging from 5 weeks to 48 weeks. In the analyzed research studies, computational thinking is conceptualized as a problem-solving skill that can be improved by software education, and assessed by individual instruments measuring sub-factors of computational thinking. Conclusion/Implications: The present study reveals that, although the number of research publications in software education for young children has increased, the overall sufficiency of the accumulated research data and a variety of research methods are still lacking. An increased interest in software education for young children and more research activities in this area are needed to develop and implement developmentally appropriate software education programs in early childhood settings.