• International Journal of Contents
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• v.17 no.1
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• Proceedings of the KWS Conference
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• 2000.10a
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• pp.13-18
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• 2000

Welding is critical technique for the joining of materials in the nation's major Manufacturing industries. Since 1998, leaders in welding industry have defined a vision of the issues and opportunities that it will face in 2020. In developing this vision document, more than 25 senior managers and respected experts from various segments of the welding community met to begin a dialog about the future of the welding industry. They were brought together to develop a long-range business plan for their industry that would identify how it would meet the needs of manufacturers, of the marketplace, and of society in 2020. In essence, these decision makers created an ideal vision of the state of their industry in 20 years, and the strategy to reach it. Welding is a precise, reliable, and cost-effective, method for joining materials. No other technique is as widely used by manufacturers to join metals and alloys efficiently. Most of the familiar objects in modern society, form buildings and bridges, to vehicles, computers, and medical devices, could not be produced without the use of welding. Despite the importance of welding to the manufacturing industry, the leaders in this area felt that welding was not appreciated as much as it should be from the society. The welding industry consists of the “users” of welding techniques as well as the companies, universities and other organizations that industry look for improvements in their operations by 2020, and should find their interest addressed in this document. A major economic impact study co sponsored by AWS and EWI and supported by US Navy, State of Ohio, US Department of Commerce, and major companies was kicked off. This two-year study will determine the economic impact of welding on the United States economy. The objective of this study is to break a paradigm about welding-those of us who are heavily involved in welding, believe strongly that much of our gross domestic product is directly dependent on welding. Furthermore, continued advances in the field of welding are necessary to achieving further increases in productivity that makes our economy strong. Yet, despite intuition, anecdotal information, and fragmented analyses, the completing quantitative information that would proved the justification for strategic actions to further develop this critical field is not currently available.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.127-137
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• 2010

A Widget platform is acknowledged to be a next generation intelligent platform that is well suited to Web 2.0 and mobile convergence environments. With prospects of growth, examining users' perceptions of current widgets can be a valuable source of information in setting directions for Widget's future development. This study identifies user interface factors that affect widget usability and investigates a strategic approach to promoting the use of widgets by analyzing user's "intention to use" in connection with the identified interface factors. The experimental results show the consistency, intuition, minimal action, and personalization have a positive(+) effect on perceived ease of use and that personalization and design have a causal effect on perceived enjoyment. Inaddition, perceived ease of use has an influence on perceived enjoyment that, inturn, has a direct influence on intention to use. On the other hand, the hypothesis that perceived ease of use has a direct effect on intention to use was rejected.

• Journal of Distribution Science
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• v.11 no.6
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• pp.59-65
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• 2013

Purpose - Studies of mechanism as a competitive strategy, a relatively new field in the study of strategic management research, has recently drawn the attention of the business management scholars. The literature has so far proposed the subjective-based view, environment-based view, and the resource-based view in its analyses of firm management. Hence, it is highly likely for the firm management to be reasonably thought of as a combination of and interaction among the three key elements of subject, environment, and resources this is the mechanism-based view (MBV). It is reasonable to consider firm management to be the combination of and interaction among the three key elements of subject, environment, and resources. The overall dynamic process that integrates these three elements and creates functional harmony is identified as the mechanism, the principle of firm management. Much of the extant literatures on MBV has mainly focused on case studies, a qualitative approach prone to subjectivity of the researcher, although the intuition from the study may lead to meaningful insights into a firm-specific mechanism. This study's focus is also on case analysis, but it still attempts a quantitative approach in order to reach a scientific and systematic understanding of the MBV. Research design, data, and methodology - I used both a qualitative and quantitative approach to a single model, given the complexity of the innovation processes. I conducted in-depth interviews with POSCO employees-20 from general management, two from human resources, eight from information technology, five from finance and accounting, and five from production and logistics management. Once the innovative events were selected, the interview results were double-checked by the interviewees themselves to ensure the accuracy of the answers recorded. Based on the interview, I then conducted statistical validation using the survey results as well. Results - This study analyzes the building process of innovation and the effect of the mechanism pattern on innovation by examining the case of POSCO, which has survived over the past 21 years. I apply a new analytical tool to study mechanism innovation types, perform a new classification, and describe the interrelationships among the mechanism factors. This process allows me to see how the "Subject"factor interacts with the other factors. I found that, in the innovation process of the adoption stage, Subject had a mediating effect but that the mediating effect of resource and performance was smaller than the effect of Subject on performance alone. During the implementation stage, the mediating effect of Subject increased. Conclusion - Therefore, I have confirmed that the subject utilizes resources reasonably and efficiently. I have also advanced mechanism studies: whereas the field's research methods have been largely confined to single case studies, I have used both qualitative and quantitative methods to examine the relationships among mechanisms.

• Journal of Distribution Science
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• v.13 no.7
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• pp.63-71
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• 2015

Purpose - The characteristics of the modern management environment in Korea clearly involve the limitations of knowledge management, globalization, changes in industrial structures, polarization of the economy, consumption, and education, and the demand for creative management. To achieve a continuous competitive advantage for individuals as well as organizations, Wisdom Management can be said to be a paradigm for the current environment. The Research is an alternative to environmental management in the early study of the need to conceptualize the theoretical approach to wisdom management. In other words, it presents a new management paradigm for a business environment of uncertainty and unpredictability. Furthermore, it aims to propose Wisdom Management as an alternative in the modern management environment as well as a topic of discourse. Its purpose is to provide basic knowledge to people who study and practice in this field to strengthen the competitiveness of individuals and companies. Research design, data, and methodology - This paper first provides six characteristics of the current management environment at home and abroad. It then attempts to emphasize the necessity of wisdom based on such characteristics by classifying wisdom according to recent management study research. This allows the derivation of definitions of wisdom management, suggesting its components and properties. Results - The six characteristics of the modern business environment are: 1) limits of knowledge, 2) intensifying globalized competition, 3) changes in industry structure - IoT (Internet of all Things) trend, 4) serious polarization and social unrest diffusion, 5) personal and organizational competitiveness creativity requirements, and 6) domestic special national and social situations. Therefore, accordingly, wisdom can be defined and classified as: wisdom that offers potential integration beyond knowledge, practicing and maintaining knowledge wisdom as an efficient strategy for an organization wisdom as a decision-making process that addresses ambivalence wisdom as the pursuit of common goods based on ethics; and, wisdom as creativity that involves intuition and insight. This paper attempts to define Wisdom Management in accordance with these definitions of wisdom. Wisdom Management is a management system that is awareof the current environment given in the multidimensional perspective, achieves the efficiency of the organization and the goals of common good through an uncertain decision-making process, based on the organization of individual and organizational knowledge, and the internal experiences and resources. Wisdom Management components include human beings, virtue, knowledge, creativity, and ambivalent thinking. Its properties include intentionality, self-destructiveness, creative and ethical reflexivity, complexity, insight, unpredictability, ambivalence, and wholeness. Conclusions - Since all organizations face the limitations of their environment, crises, and opportunities, applying wisdom in management to develop as Wisdom Management can be an inevitable alternative to the uncertainties of the management environment faced by modern society. The conceptualization of Wisdom Management forms a valuable context to further advance knowledge management theory into practice. It is also a cornerstone of strategic management and can provide insight into its potential for success and implementation.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.