• Korean Journal of Logic
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• v.17 no.2
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• pp.253-287
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• 2014

In First-Order Logic the English expressions, 'any', 'every', 'all', and 'each' are treated on a par but have different meanings in the natural language usages. Especially the expression 'any' is typically used only in the negative contexts, which linguists have paid attention to and attempted to provide an adequate explanation of. I shall show that the explanations so far mainly from linguists are not satisfactory and revive the philosophical insights concerning the logical features of 'any' provided by Zeno Vendler in 1962. I shall claim that the expression 'any' has what Vendler calls the 'freedom of choice' as its primary meaning and denotes what Kit Fine calls an 'arbitrary object'. It will be shown that the logical features of 'any' are manifested more evidently in the analysis of the Korean expression 'amwu'. I believe that this analysis has significant philosophical implications. As an instance I shall show that we can take a fresh perspective on the problem which involves the universal generalization rule and the preface paradox.

• Journal of Distribution Science
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• v.11 no.5
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• pp.63-76
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• 2013

Purpose - For the past several decades, behavioral economics or behavioral decision theory has undergone rapid development. This study provides a critical review of the development of behavioral economics with a focus on what are deemed to be core theories in the field. Starting from the utility function proposed by Daniel Bernoulli in the 18th century, the development history of utility functions until the emergence of the prospect theory is thoroughly reviewed. Some of the experimental results violating the traditionally assumed utility function and supporting the prospect theory value function are summarized. The most representative principles of rational choice are transitivity, independence from irrelevant alternatives (IIA), and regularity. The development of behavioral economics has been triggered by finding counter-examples to these principles. Some of the choice behaviors discussed in this study as counter-examples to the traditional theories of rational choice are the St. Petersburg paradox; the Allais paradox; gambling behavior; and the various context effects including the similarity effect, attraction effect, and the compromise effect. The Elimination-by-Aspects (EBA) model, which was proposed as an explanation for the similarity effect, is discussed in detail as well. Based on the literature review and further analysis, this study summarizes the relationship between the context effects, prospect theory, and EBA model. Research design, data, and methodology - This study provides an extensive literature review on several important theories in the field of behavioral decision theory and adds some critical comments to the theories and the relationships among them. This study first reviews the development of utility functions. Daniel Bernoulli introduced the concept of utility function to solve the St. Petersburg paradox. In the mid-20th century, Herbert Simon proposed the "satisficing" heuristic and presented a value function with a shape different from traditional utility functions. This study highlights the strengths and weaknesses of several utility functions proposed until the emergence of the prospect theory value function. Results - This study posits that prospect theory and EBA model are the two most important theories in the field of behavioral decision theory. They can explain various choice behaviors that traditional utility maximization analysis has been unable to. The application of these models to various fields is further increasing nowadays. This study explains how prospect theory and the EBA model can be used to explain the context effects. Conclusions - The traditional economic theory relies on a single variable called "utility" in explaining consumer choice. However, this study argues that, in investigating consumer choice, several other variables should also be considered. These are the similarity among alternatives, an alternative's prototypicality within the category, the dominance relationship between alternatives, and the reference point in evaluating alternatives. Due to the development of behavioral economics, we are now closer to a more complete understanding of consumer choice behavior than in the past when we had only a single tool called utility.

• Journal of Science Education
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• v.38 no.3
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• pp.569-584
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• 2014

The Purpose of this study was an analysis of high school student's understanding level about concepts of special relativity through in-depth interview. The 8 participants were 10th grade students in H high school in Ulsan city, who were interviewed and analyzed in the results of the interview about basic concepts of special relativity using achievement checklist in 6 situations(principle of constancy of light velocity, principle of relativity, relativity of simultaneity, garage paradox, rocket paradox). As results of the checklist, the participants showed high achievement in the content level of simple phenomena and simple concepts related to special relativity. But they showed low achievement in the concept level for fundamental understanding of special relativity. As results of the interview, it was found that the participants decided the order of events depending on their intuition and had a difficulty to apply the coordinate system to real situation, even though they mathematically understood it. In addition, some participants who could not understand the inertial coordinate system explained paradoxes of relativity depending on their intuition and had learner's chaos. Finally, though high school students usually being in formal operational stage, some students had difficulty to draw phenomena of space and time in two dimensional plane.

• The Journal of Industrial Distribution & Business
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• v.8 no.7
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• pp.39-49
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• 2017

Purpose - There are common factors both in Technology Readiness and Acceptance Model and Technology Paradox Theory which can be put together and made in one unified model. The unified model can provide the following merits. First, the unified model is simple but contains factors of the models. Second, the unified model can clarify the process of technology acceptance of common consumers. Third, the unified model can provide the opportunities to analyze the negative sides of new technology, thus find ways to improve the level of acceptance by general consumers. Research design, data, and methodology - The 450 questionnaires were handed out to people around Seoul and 421 were collected. Except insincere and wrong-marked ones, 402 were used to analyze. SPSS program was used to analyze. Factor analysis, regression analysis was conducted to test the hypotheses. Results - By analyzing sub-factors of both models and binding the common factors in one category, we accomplish one model. And we tested the model by empirical method. The results show that the results from the unified model are almost same as the results from the two models. In other words, the unified model works. Conclusions - Explaining one state of affair by two different method is in some sense distracting attention. By devising a new model including factors of both models, we can explain the affair more straightforward and efficiently. At first the technology acceptance model was devised to explain the technology users in an organization and the following tests and revised models were for the similar purposes. However, as on-lone activities including contracts have been expanded and become important, consumers as the technology uses have emerged as first factor to consider. In accordance models to explain this situation has been suggested. The model suggested in this research is one of the models but it has the following merits. That is, it is simple but has strong explanation power, it can clarify the process of technology acceptance of common consumers by containing negative sides of consumer conception, and thus, it can provide the opportunities to analyze the negative sides of new technology, also find ways to improve the level of acceptance by general consumers.

• Wind and Structures
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• v.9 no.3
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• pp.179-191
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• 2006

Parent wind data are often acknowledged to fit a Weibull probability distribution, implying that wind epoch maxima should fall into the domain of attraction of the Gumbel (Type I) extreme value distribution. However, observations of wind epoch maxima are not fitted well by this distribution and a Generalised Extreme Value (GEV) analysis leading to a Type III fit empirically appears to be better. Thus there is an apparent paradox. The reasons why advocates of the GEV approach seem to prefer it are briefly summarised. This paper gives a detailed analysis of the errors involved when the GEV is fitted to epoch maxima of Weibull origin. It is shown that the results in terms of the shape parameter are an artefact of these errors. The errors are unavoidable with the present sample sizes. If proper significance tests are applied, then the null hypothesis of a Type I fit, as predicted by theory, will almost always be retained. The GEV leads to an unacceptable ambiguity in defining design loads. For these reasons, it is concluded that the GEV approach does not seem to be a sensible option.

• Health Policy and Management
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• v.30 no.4
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• pp.493-504
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• 2020

Background: There have been many studies on the associations between body mass index (BMI) and cognitive function. However, no study has ever compared the associations across the methods of categorizing BMI. In this study, we aimed to fill the gap in the previous studies and examine whether the obesity paradox is valid in the risk of cognitive function. Methods: Of the 10,254 people aged 45 and older from the Korean Longitudinal Study of Ageing from 2006 to 2016, 8,970 people were finalized as the study population. The dependent variable was whether a person has a normal cognitive function or not, and the independent variables of interest were BMI categorized by the World Health Organization Western Pacific Regional Office (WHO-WPRO) method, the WHO method, and a 10-group method. Covariates included sociodemographic factors, health behavior factors, and health status factors. A generalized linear mixed model analysis with a logit link was used. Results: In the adjusted model with all covariates, first, in the case of BMI categories of the WHO-WPRO method, underweight (odds ratio [OR], 1.16; 95% confidence interval [CI], 1.15-1.17), overweight (OR, 1.36; 95% CI, 1.35-1.36), and obese (OR, 1.34; 95% CI, 1.33-1.34) groups were more likely to have a normal cognitive function than a normal-weight group. Next, in the case of BMI categories of the WHO method, compared to a normal-weight group, underweight (OR, 1.15; 95% CI, 1.14-1.16) and overweight (OR, 1.06; 95% CI, 1.06-1.07) groups were more likely to have a normal cognitive function; however, obese (OR, 0.62; 95% CI, 0.61-0.63) group was less likely to have it. Lastly, in the case of the 10-group method, as BMI increased, the likelihood to have a normal cognitive function changed like a wave, reaching a global top at group-7 (26.5 kg/㎡ ≤ BMI <28.0 kg/㎡). Conclusion: The associations between BMI and cognitive function differed according to how BMI was categorized among people aged 45 and older in Korea, which suggests that cognitive function may be positively associated with BMI in some categories of BMI but negatively in its other categories. Health policies to reduce cognitive impairment need to consider this association between BMI and cognitive function.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.159-179
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• 2024

Based on the case of collaboration between large companies and startups, this study suggests the importance of establishing mutual cooperation and trust relationships for the success of open innovation strategy from the perspective of cooperative game theory. It also provides implications for how this can be implemented. Due to information asymmetry and differences in organizational culture and decision-making structures between large companies and startups, collaboration is likely to proceed in the form of non-cooperative games among players in general open innovation, leading to the paradox of open innovation, which lowers the degree of innovation. Accordingly, this study conducted a case study on collaboration between large company 'G' and startup 'S' based on the research question "How did we successfully promote open innovation through cooperative game-type collaboration?" The study found that successful open innovation requires (1) setting clear collaboration goals to solve the organizational problem between large companies and startups, (2) supporting human resources for qualitative growth of startups to solve reliability problems, (3) leading to strategic investment and joint promotion of new projects to solve the profit distribution problem. This study is significant in that it contributes to expanding the discussion of the success factors of open innovation to the importance of interaction and strategic judgment considering the organizational culture and decision-making structure among players, and empirically confirming the success conditions of open innovation from the perspective of cooperative game theory.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.845-852
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• 2018

Mayer-Schönberger and Cukier(2013) explain why big data is important for our life, while showing many cases in which analysis of big data has great significance for our life and raising intriguing issues on the analysis of big data. The two authors claim that correlation is in many ways practically far more efficient and versatile in the analysis of big data than causality. Moreover, they claim that causality could be abandoned since analysis and prediction founded on correlation must prevail. I critically examine the two authors' accounts of causality and correlation. First, I criticize that corelation is sufficient for our analysis of data and our prediction founded on the analysis. I point out their misunderstanding of the distinction between correlation and causality. I show that spurious correlation misleads our decision while analyzing Simpson paradox. Second, I criticize not only that causality is more inefficient in the analysis of big data than correlation, but also that there is no mathematical theory for causality. I introduce the mathematical theories of causality founded on structural equation theory, and show that causality has great significance for the analysis of big data.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.235-241
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• 2020

Many studies have tried to explain the privacy paradox but reported conflicting results; Some of them found connection between privacy concerns and information disclosure, while others did not. This study examines the role of interaction privacy controls (mainly friend lists and privacy settings) as a moderating variable that has the potential to affect the relationship in the SNS context. The reason for this is that most users use interactive privacy controls to create their own social environment before conducting SNS activities, so the relationship between privacy concerns and information disclosure may vary depending on the degree of use of interactive privacy controls. The study collected data using survey method, analyzed the moderating effect of use of interaction privacy controls using hierarchical multiple regression analysis, and as a result, found that effect. Therefore, the degree of use of interactive privacy controls may be an important contingent variable that needs to be considered in a study examining the privacy paradox in SNS context.

• International Commerce and Information Review
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• v.14 no.2
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• pp.271-293
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• 2012

As service industry became more important, many of studies have been done on the role of service. Such studies has been researched focusing on the relationship between the service intensity in the economy and a country's productivity. Baumal(1967) suggested that service growth in economy would bring about decrease in productivity. However, the economy of developed countries encounter with the productivity growth as their economy grows, which phenomenon called Baumol's paradox. Oulton (1999, 2001) find out the reason of Baumol's paradox in a forward and backward chain effects. So, this paper is aimed at verifying the theory of Oulton (1999, 2001) for 13 OECD countries using panel data analysis. We find out that the intermediate knowledge-intensive service inputs cause a multifactor productivity growth.