Abstract & Downloadable Links


Network Structure Effects in Incumbency Advantage (with Jeho Lee and Jaeyong Song, Strategic Management Journal, 2016)

The literature on network effects has implicitly assumed that an increase in the size of the installed base magnifies network effects, which is a source of incumbency advantage. We argue that the overemphasis on this relationship has resulted in controversy and confusion in the literature, where the role of social networks remains largely unaddressed. By developing computational models of network effects with various network structures, we show that social distance in a customer network plays a moderating role that strengthens or weakens the relationship between the installed base and network effects, which in turn affects the durability of incumbency advantage. When the average social distance between members in a customer network is large, the incumbency advantage will not be amplified, and an entrant with an incompatible product or service may find ways into the market. On the other hand, when the average social distance is small, early entry with a growing installed base will magnify incumbency advantage.

Much of prior work on platform competition has focused on the winner-take-all possibilities on the demand side, while ignoring supply-side dynamics. The key to the latter is R&D investment for developing new complementary products or services with quality and features that appeal to customers. Thus far, little is known about how this supply side hinders or facilitates the winner-take-all processes. We develop dynamic models of platform competition by specifying the details of the missing element. Our study shows two conditions for the persistence of incompatibilities. First, we find that incompatibilities persist when external financing for R&D is not limited or when the R&D cost is relatively small. Second, the incompatibilities may persist when the benefits from the incumbent’s installed base are in a delicate balance with the benefits from the entrant’s new applications for the platform.


The Coevolution of Cooperation and Trait Distinction (with Jung-Kyoo Choi and Hang-Hyun Jo, JCNS, 2008, In Korean)

본 논문은 국지적 상호작용 하에서 행위자들간에 특성의 차이에 근거한 구별짓기가 협조적 행위의 진화에 미치는 영향을 분석한다. 이 논문에서는 이러한 구별짓기의 성향이 왜, 그리고 어떤 메커니즘을 통해서 진화해나가는지를 보이고자 시도할 것이다. 아울러 구별짓기 성향과 함께 내부인과 외부인을 향한 행동을 다르게 함으로써 어떻게 내부인에 대한 이타적 협조행동을 발생 시키는지, 더 나아가 구별짓기의 근거가 되는 행위자들의 여러 특성들(생물학적 혹은 문화적)은 어떻게 변화해 나가고 이들 특성의 변화가 구별짓기와 협조적 행동에 어떤 효과를 가져 오는지를 살펴보고자 한다. 더 나아가 본 논문에서는 구별짓기가 협조적 행위의 진화에 영향을 미치는 과정을 장/단기로 구분 함으로써 구별짓기의 효과를 보다 명확히 규명하고자 한다.

We introduce a spin model combining the majority voter model with probability p and the voter model with probability 1−p and then measure its consensus time on scale-free networks with various degree exponents γ. We find that consensus time depends on both p and γ. When all spins follow either the voter model or the majority voter model, it takes much greater time to reach consensus. On the other hand, when spins may alternate between the majority voter model and the voter model, consensus time is shortened. We find via numerical calculation that the optimized ratio to minimize consensus time is around p=0.72.

Agent-Based Approach for Revitalization Strategy of Knowledge Ecosystem (with Seungbyung Chae, Wooseop Kwak, Sun-Bin Kim, and In-mook Kim, JPSJ, 2009)

We conceptualize knowledge as an intellectual infrastructure that helps to maximize efficiency from the viewpoint of ecosystems. The knowledge ecosystem includes people and organizations that participate in the production, distribution, and consumption of this knowledge and information, as well as interactions between participants. We built the agent-based computational model of the ecosystem and induced seven key revitalization conditions from the perspective of complexity science and ecosystem management. We analyzed the effects of these conditions on the knowledge ecosystem based by the simulation of the agent-based model. Our results suggest that the proper implementation of seven revitalization conditions, focusing on the recovery of the positive feedback loop in the knowledge ecosystem, is crucial for sustainable development.

Quantitative and empirical demonstration of theMatthew effect in a study of career longevity (with Alexander M. Petersen, Woo-Sung Jung, and H. Eugene Stanley, PNAS, 2011)

The Matthew effect refers to the adage written some two-thousand years ago in the Gospel of St. Matthew: “For to all those who have, more will be given.” Even two millennia later, this idiom is used by sociologists to qualitatively describe the dynamics of individual progress and the interplay between status and reward. Quantitative studies of professional careers are traditionally limited by the difficulty in measuring progress and the lack of data on individual careers. However, in some professions, there are well-defined metrics that quantify career longevity, success, and prowess, which together contribute to the overall success rating for an individual employee. Here we demonstrate testable evidence of the age-old Matthew “rich get richer” effect, wherein the longevity and past success of an individual lead to a cumulative advantage in further developing his or her career. We develop an exactly solvable stochastic career progress model that quantitatively incorporates the Matthew effect and validate our model predictions for several competitive professions. We test our model on the careers of 400,000 scientists using data from six high-impact journals and further confirm our findings by testing the model on the careers of more than 20,000 athletes in four sports leagues. Our model highlights the importance of early career development, showing that many careers are stunted by the relative disadvantage associated with inexperience.

The Role of Noise in a Mutual Selection and Learning Model (with Yongha Kwon, Jungsoo Ahn, and Ji-Hyun Kim, JEWS, 2016)

In organizational learning and search literature, conventional wisdom holds that a moderate degree of noise helps organizations improve their performance by introducing more variation. We would like to note, however, that portrayals of most organizational structures in this line of inquiry are over simplified. We contribute to this topic by suggesting that the beneficial role of moderate noise is dependent on its relational presence in a mutual selection and learning system. By extending March’s (1991) mutual learning model, we examine the role of noise in an organization as an adaptive system, where both the organizational code and individuals can select and learn from others. We demonstrate that while a small amount of noise on the learning stage is beneficial, noise on the selection stage monotonically decreases performance. Our results indicate a need for re-examination of the role of noise in various organizational settings and structures.

The specific form of the long-term effect of exploration and exploitation on firm’s performance is still in debate both theoretically and empirically. While some view it as a monotonically increasing relation, others argue that it is an inverted U-relation. We attribute this tension to the fact that scholars applied Holland’s (1975) insights from genetic algorithms in artificial systems to organizational contexts without adequate modifications. In this study, we contribute to resolving the tension by identifying features that are unique to organizations and incorporate them in a simplified March’s (1991) model. These features can modify or disrupt the assumed relationship between exploration and long-term performance. In particular, we develop a model that treats individuals as being often (i) unable to observe others’ performances accurately, and (ii) unwilling to learn from others who hold different beliefs. The modified model shows that these two features result in a negative or an inverted u-shaped relationship, respectively, with long-term firm performance

This study tried to analyze the moderating effects of the timing of reward determination and performance standards between pay-for-performance and self-efficacy. Online experiment was performed with 352 participants collected from Amazon Mechanical Turk. It is proved that a mediating effect of self-efficacy between pay-for-performance and intrinsic motivation exists and there is a moderating effect of performance standard, while there is no significant moderating effect of reward determination timing. Performance standard was inferred to be more important moderator than the timing. In this study, we suggested the concept of the timing of reward determination and verified self-determination theory empirically. Suggested practical implication was using absolute standard would have less negative effects on employees.


This study analyzed the role of R&D cooperation in small- and medium-sized enterprises (SMEs), specifically, the mediating effects of R&D cooperation between firm size and two types of performance: technological and financial performance. In addition, we investigated how spontaneity of R&D cooperation influences the relation between firm size and R&D cooperation in the context of national R&D projects. Our empirical analysis included approximately 13,000 SME-supporting programs for three years, from 2013 to 2015. The results showed that R&D cooperation had mediating but opposite effects on the relationship between firm size and the two types of performance. While R&D cooperation had a positive effect on financial performance, it had a negative effect on technological performance. We conclude that the goal of R&D cooperation should be determined before conducting or supporting R&D cooperation in SMEs. Also, we verified that spontaneity had a moderating effect on the relationship between firm size and R&D cooperation; it strengthened the positive relation. Ours is also the only paper to analyze the effects of this variable on two types of performance at the same time. As the role of SMEs evolves, the findings of this study provide valuable information for both policy makers and researchers.

Government roles in evaluation and arrangement of R&D consortia (with Ji-Hyun Kim and Sung Joo Bae, Technological Forecasting and Social Change, 2014)

The role of government in forming and coordinating R&D consortia has often been cited in studies of the economic success of latecomer countries such as Korea and Japan. Most previous studies documented the government's efforts to provide funding. In our research about the government's role in determining the quality of innovation, we develop a computational model based on genetic algorithms. The two main aspects of government involvement explored in this study are 1) the timing of evaluation of participating firms in a consortium, and 2) the form that these consortia take. In terms of the timing of evaluation, we find that continuous evaluation is consistently superior to early evaluation. In addition, the effect of the form of the consortium depends on the timing of evaluation. An inverse pyramid arrangement, which emphasizes variation at the beginning of the innovation process, outperforms a pyramid-form arrangement only when evaluation is continuous. We identify the tension and reconciliation between diversity and selection as the force underlying the results of this study. We discuss these findings and their implications for how governments should balance diversity and selection when designing innovation systems.

Strategic R&D Budget Allocation to Achieve National Energy Policy Targets: The Case of Korea (with Jungwoo Lee)

While recent international negotiations to combat climate change have led governments around the world to invest in R&D in the energy sector, funds allocated to R&D investment have remained limited during global economic downturns and depending on national economic conditions. A systematic approach and strategic budget allocation is required to achieve various national energy policy targets. In this study, we describe the optimal investment portfolio for achieving energy policy targets in Korea based on three budget allocation criteria: past investment performance, expected future effects and additional investment risk. We outline the analytic hierarchical process by which policy target priorities are set, developing a market allocation model to analyse expected future effects and a system dynamics model to calculate the investment volume. The systematic approach suggested in this study can increase the efficiency of budget spending by helping governments makes investment decisions based on clear criteria and the results of a quantitative analysis regarding government investment in R&D.

Effect of Government energy R&D investment on sales of beneficiary firms (with Jungwoo Lee, New & Renewable Energy, 2017)

Since the late 2000s, the Korean government’s energy policy has begun to re-examine the energy industry as a new growth engine for the nation, furthering its goal of stabilizing supply and demand. The government has steadily increased R&D investment in the energy sector by promoting “low-carbon green growth” with the paradigm of national development. The purpose of this study is to find out whether government R&D investment has effect on the sales growth of beneficiaries in the energy industry. In addition, we analyze how the effects of government R&D investments differ in renewable and electricity, nuclear R&D program. Results show that the government R&D investment does not necessarily guarantee the improvement of the sales growth of beneficiary company, but are significant only in the renewable energy sector. This study concludes that there is a need to diversify investment types according to market and technology maturity.

Government R&D investment decision-making in the energy sector: LCOE foresight model reveals what regression analysis cannot (with Jungwoo Lee, Energy Strategy Review, 2018)

Governments that prioritize R&D investment, future R&D investment decision-making depends on performance-based budgeting. Governments evaluate outputs and outcomes of R&D programs regularly and budget for next year on the basis of program assessment. However, existing assessment methodology disregards long-term technology development where in sector such as the energy sector takes a long time for technologies to progress from R&D to commercialization. This paper is a comparative analysis of existing R&D assessment models and the new foresight model developed from the point of view of government. Probit and ordinary least squares (OLS) models are used to analyze the performance of projects built on past R&D investment. The foresight model, which is based on the levelized cost of electricity (LCOE), is discussed in comparison. Results of the regression analysis show that government investment in market expansion of renewable energy technologies is minimal in Korea. In contrast, the LCOE foresight model results show that renewable energy technologies are appropriate targets for government R&D investment. The foresight model should be utilized for government R&D decision-making in the energy sector because it brings to light hidden information, including learning rates and technology dynamics, which remains unaddressed when analyzing using existing R&D assessment models.

Methodology and case study of government R&D investment strategy based on value-system analysis (with Jungwoo Lee and Nagyeong An)

The Korean government has declared ’Energy Transition’ to reduce the proportion of coal and nuclear power and expand the supply of renewable energy in 2017. To achieve 20% of renewable energy by 2030, the government need to drastically increase the capacity of solar power by ten times compared to present and four to eight times for onshore wind power. However, domestic solar technology is still weaker than the leading countries such as China, and there is a concern that the local renewable energy market, which is expected to expand in the future, will be subordinated by major foreign companies. In this study, we propose a methodology for setting government R&D investment strategy based on value system analysis and present case applied to solar industry. This study suggests that investment strategy formulation methodology and practical application examples can be used as a guideline for establishing government R&D strategy for the industrial development of the national company.

Backcasting of Future Energy Service Industry based on Energy-A ICBM technology Convergence (with Jungwoo Lee)

The convergence of intelligent information technology and energy technology affects many stakeholders because it involves not only technology itself but also social, institutional and organizational changes. Therefore, it is necessary to develop a back-casting approach to create a new industry that deviates from the path dependence on the traditional energy industry. This study examines the changes in the future energy industry that intelligence information technology will bring, and then we derived the future energy service model that can satisfy the energy policy goals from the national perspective and the interests of each stakeholder at the same time. After that, we analyzed the technical prerequisites for the realization of future energy services and presented the specific configuration technology and the areas that require R&D investment at present.


Network structure reveals the pattern of legal complexity in human society: case of the Constitutional legal network (with Bokwon Lee and Kyu-Min Lee)

Complexity in nature has been broadly found not only in physical and biological but also in social and economic systems. Although complex system studies successfully contribute to understand real-world complexity, the investigation to the legal complexity has been quite limited. Here we introduce the novel approach to study complex legal systems with bringing methods of complex networks. On the basis of the bipartite relations among Constitution articles and Court decisions, we built a complex legal network and found the system shows the heterogeneous structure as generally observed in many complex social systems. By separating the legal network as different political regimes, we examine whether structural properties of the systems have been influenced as the society changes, or not. On one hand, the core structure exist in legal networks regardless of any social circumstances. On the other hand, however, with relative comparison among different networks, we could identify the characteristic structural properties of each regime’s network which would show its own identity. Our analysis would contribute to provide not only better understanding of the legal complexity for researchers but also practical guidelines in various legal and social applications

Gravity model for dyadic Olympic competitions (with Hyeseung Choi, Hyungsoo Woo, and Ji-Hyun Kim)

In the Olympic Games, professional athletes representing their nations compete regardless of economic, political and cultural differences. In this study, we apply gravity model to observe characteristics, represented by ‘distances’ among nations that directly compete against one another in the Summer Olympics. We use dyadic data consisting of medal winning nations in the Olympic Games from 1952 to 2016. To compare how the dynamics changed during and after the Cold War period, we partitioned our data into two time periods (1952–1988 and 1992–2016). Our research is distinguishable from previous studies in that we newly introduce application of gravity model in observing the dynamics of the Olympic Games. Our results show that for the entire study period, countries that engaged each other in competition in the finals of an Olympic event tend to be similar in economic size. After the Cold War, country pairs that compete more frequently tend to be similar in genetic origin.

Executive Compensation, Fat Cats, and Best Athletes (with Jerry Kim and Bruce Kogut, American Sociological Review, 2015)

Income gains in the top 1 percent are the primary cause for the rapid growth in U.S. inequality since the late 1970s. Managers and executives of firms account for a large proportion of these top earners. Chief executive officers (CEOs), in particular, have seen their compensation increase faster than the growth in firm size. We propose that changes in the macro patterns of the distribution of CEO compensation resulted from a process of diffusion within localized networks, propagating higher pay among corporate executives. We compare three possible explanations for diffusion: director board interlocks, peer groups, and educational networks. The statistical results indicate that corporate director networks facilitate social comparisons that generate the observed pay patterns. Peer and education network effects do not survive a novel endogeneity test that we execute. A key implication is that local diffusion through executive network structures partially explains the changes in macro patterns of income distribution found in the inequality data.

Information flow between stock indices (with Okyu Kwon, EPL, 2008)

Using transfer entropy, we observed the strength and direction of information flow between stock indices. We uncovered that the biggest source of information flow is America, while most receivers are in the Asia/Pacific region. According to the minimum spanning tree, the Standard and Poor’s 500 Index (GSPC) is located at the focal point of the information source for world stock markets.

We investigate the strength and the direction of information transfer in the US stock market between the composite stock price index of stock market and prices of individual stocks using the transfer entropy. Through the directionality of the information transfer, we find that individual stocks are influenced by the index of the market.

Impact of the Topology of Global MacroeconomicNetwork on the Spreading of Economic Crises (with Kyu-Min Lee, Gunn Kim, Jaesung Lee, Kwang-Il Goh, and In-mook Kim, PLoS ONE, 2011)

Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country’s role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more ‘‘globalized’’ random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises.

Global Diversification Discount and Its Discontents:A Bit of Self-selection Makes a World of Difference (with Sungyong Chang and Bruce Kogut, Strategic Management Journal, 2016)

The documented discount on globally diversified firms is often cited, but a correlation is not per se evidence that global diversification destroys firm value. Firms choose to globally diversify based on the strategies they have chosen. Conditioned on this choice, the decision to diversify globally is endogenous and self-selected. Using the same specifications save for the Heckman selection instrument, our results contradict past research that did not address endogeneity. We posit that the global premium should reflect the value of multinational operating flexibility. We use the 2008-2009 financial crisis as creating exogenous variation to permit a test for the positive change in firm valuation due to global diversification. During and after the 2008-2009 financial crisis, the premium associated with global diversification became larger and more significant than before the 2008-2009 financial crisis. The churn of subsidiaries entering and exiting countries increased during the crisis, pointing to the value of an operating flexibility to restructure the geography of the multinational network. In all, the results contradict past findings and finds evidence that operating flexibility is more valued during times of high volatility, thus generating the diversification premium.


In this paper, we examined the effect of workforce aging on company productivity. We found that an increase in the ratio of workers aged over 50 years to total workers had a negative effect on value added per worker, which was consistent with the findings of most previous studies based on European data. The results of an analysis including various classifications such as size, industry, and several financial conditions revealed that an increase in the ratio of older workers had positive effects on value added per worker in large manufacturing firms under risky or growing conditions. As the productivity of older workers may vary, future research may determine under what conditions – size, industry, region, and financial conditions – older workers contribute positively to productivity. Firms with financial troubles or those planning to downsize should be cautious to lay off older workers to improve organizational performance because these workers contribute positively to productivity under certain conditions.

A Research on the Medical Professionals’ Resistance of Telemedicine: Utilising the Delphi Study (with Woo Seok Choi, Joowoong Park, and Jin Young Brian Choi, JTT, 2018)

Introduction: Sufficient infrastructure for information and communications technology (ICT) and a well-established policy are necessary factors for smooth implementation of telemedicine. However, despite these necessary conditions being met, there are situations where telemedicine still fails to be accepted as a system due to the low receptivity of stakeholders. In this study, we analyse stakeholders’ resistance to an organization’s implementation of telemedicine. Focusing on the physicians’ interests, we propose a strategy to minimize conflicts and improve acceptance. Methods: The Delphi study involved 190 telemedicine professionals who were recommended by 485 telemedicine-related personnel in South Korea. Results: Out of 190 professionals, 60% of enrolled participants completed the final questionnaires. The stakeholders were categorized into four groups: policy-making officials, physicians, patients, and industrialists. Among these, the physicians were most opposed to the adoption of telemedicine. The main causes of such opposition were found to be the lack of a medical services delivery system and the threat of disruption for primary care clinics. Very little consensus was observed among the stakeholders, except on the following points: the need for expansion of the national health insurance budget by the government, and the need for enhancement of physicians’ professional autonomy to facilitate smooth agreements. Discussion: Our analysis on the causes of the resistance to telemedicine, carried out with the groups mentioned above, has important implications for policy-makers deriving strategies to achieve an appropriate consensus.


Analysis in correlation for the Korean stock market (with Woo-Sung Jung, Seungbyung Chae, Okyu Kwon, and Hie-Tae Moon, SPIE, 2005)

The correlation between stock price changes is useful information. Through the correlation matrix, we construct a portfolio with its minimum spanning tree. We make the minimum spanning tree of the Korean stock market, a representative emerging market, which is different from that of the mature market. It is due to the emerging market’s less abundant liquidity than the mature market. And we find the distribution of the correlation coefficient is different for several periods. As the market is developing, many changes from inside and outside the market occurs, and several parameters of the stock market network are changed. The Korean stock market is under an evolution.

Complexity and entropy density analysis of theKorean stock market (with J Brian park, Jeong Wong Lee, Hang-Hyun Jo, and Hie-Tie Moon, JCIS, 2006)

In this paper, we studied complexity and entropy density of stock market by modeling ε-machine of Korean Composition Stock Price Index (KOSPI) from year 1992 to 2003 using causal-state splitting reconstruction (CSSR) algorithm.

Temporal Evolution of the Return Distribution in the Korean Stock Market (with Seungbyung Chae, Woo-Sung Jung, and Hie-Tae Moon, JKPS, 2006)

We study the temporal evolution of the return distribution of the Korean Composite Stock Price Index (KOSPI) for the period from 1995 to 2003. The high-frequency return distribution of the KOSPI has become narrower to an exponential and finally to a Gaussian since 2000 without increasing the return interval. This crossover behavior shows that the time scale of the Korean stock market has decreased significantly since the Asian financial crisis in 1997. We have applied the Heston model with stochastic volatility to describe the exponential-to-Gaussian crossover.

Effects of Globalization in the Korean Financial Market (with Woo-Sung Jung, Okyu Kwon, and Hie-Tae Moon, JKPS, 2006)

We study the effect of globalization on the Korean market, one of the emerging markets. Some characteristics of the Korean market are different from those of the mature market according to the latest market data, and this is due to the influence of foreign markets or investors. We concentrate on the market network structures over the past two decades, with knowledge of the history of the market, and determine the globalization effect and market integration as a function of time.

Characteristics of the Korean stock market correlations (with Woo-Sung Jung, Seungbyung Chae, and Hie-Tae Moon, Physica A, 2006)

We establish in this study a network structure of the Korean stock market, one of the emerging markets, with its minimum spanning tree through the correlation matrix. Based on this analysis, it is found that the Korean stock market does not form the clusters of the business sectors or of the industry categories. When the MSCI (Morgan Stanley Capital International Inc.) index is exploited, we find that the clusters of the Korean stock market is formed. This finding implicates that the Korean market, in this context, is characteristically different from the mature markets.

Microscopic spin model for the dynamics of the return distribution of the Korean stock market index (with Seungbyung Chae, Woo-Sung Jung, and Hie-Tae Moon, Physica A, 2006)

In this paper, we studied the dynamics of the log-return distribution of the Korean Composition Stock Price Index (KOSPI) from 1992 to 2004. Based on the microscopic spin model, we found that while the index during the late 1990s showed a power-law distribution, the distribution in the early 2000s was exponential. This change in distribution shape was caused by the duration and velocity, among other parameters, of the information that flowed into the market.

Complexity analysis of the stock market (with Joongwoo Brian Park, Jeong Won Lee, Hang-Hyun Jo, and Hie-Tae Moon, Physica A, 2007)

We study the complexity of the stock market by constructing epsilon-machines of Standard and Poor’s 500 index from February 1983 to April 2006 and by measuring the statistical complexities. It is found that both the statistical complexity and the number of causal states of constructed epsilon-machines have decreased for last 20 years and that the average memory length needed to predict the future optimally has become shorter. These results support that the information is delivered to the economic agents and applied to the market prices more rapidly in year 2006 than in year 1983.

Increasing market efficiency in the stock markets (with Wooseop Kwak, Taisei Kaizoji, and In-mook Kim, EPJB, 2008)

We study the temporal evolutions of three stock markets; Standard and Poor’s 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient.

Minimum entropy density method for the time series analysis (with Jeong Won Lee, Joongwoo Brian Park, Hang-Hyun Jo, and Hie-Tae Moon, Physica A, 2009)

The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.

Return Intervals Analysis of the Korean Stock Market (with Woong Jeon, Hie-Tae Moon, Gabjin Oh, and Woo-Sung Jung, JKPS, 2010)

We analyze the return intervals in Korean stock prices. While scaling and memory effects prevail in mature markets, such as the US and Japanese markets, the Korean market does not exhibit the scaling effect, but rather the memory effect. Multiscaling behavior appears as well. Interestingly, the return interval distribution of the Korean market shows neither a stretched exponential nor an exponential distribution. We propose that the features we have found can be a distinct feature of the Korean market.

Temporal evolution into a more efficient stock market (with Taisei Kaizoji and Wooseop Kwak, Physica A, 2011)

Using the price change and the log return of 10 stock market indices, we examine the temporal evolution of the time scale. The 10 stock markets had similar properties. Their log-return time series had patterns and long-range correlations until the mid-1990s. In the 2000s, however, the long-range correlations for most markets shortened, and the patterns weakened. These phenomena were due to advances in communication infrastructure such as the Internet and internet-based trading systems, which increased the speed of information dissemination. We examined the temporal evolution of the time scale in the markets by comparing the probability density function of log returns for the 2000s with that in the 1990s and by using the minimum entropy density method.


We investigate the order parameter of the standard Ising lattice gas and driven Ising lattice gas models. The sub-block order parameter is introduced to these conserved models as an order parameter using block distribution functions. We also introduce the sub-block order parameter of damage using the block distribution functions of damage. We measure the sub-block order parameters using the Metropolis and heat-bath rates. These order parameters work well for the non-equilibrium-conserved model as well as the equilibrium-conserved model. We obtain the critical exponent of order parameter 􏰜β=1/8 for the standard Ising lattice gas and 􏰜β=1/2 for a driven Ising lattice gas using the Metropolis and heat-bath rates.

Critical behavior of the majority voter model is independent of transition rates (with Wooseop Kwak, Jang-il Sohn, and In-mook Kim, PRE, 2007)

We study the critical properties of the majority voter model by using two different transition rates: the Glauber rate and the Metropolis rate. The model with the Glauber rate has been found to be mapped to the majority voter model with noise 􏰊de Oliveira, J. Stat. Phys. 66, 273 (1992). The critical temperature and the critical exponents for the two transition rates are obtained from a Monte Carlo simulation with a finite size scaling analysis. The critical temperature is found to depend on the transition rate, but the critical exponents do not. The values of the critical exponents obtained indicate that the model belongs to the same universality class as the Ising model, regardless of the type of transition rate.

Critical behavior of the XY model on growing scale-free networks (with Wooseop Kwak, Jang-il Sohn, and In-mook Kim, PRE, 2007)

Applying the histogram reweighting method, we investigate the critical behavior of the XY model on growing scale-free networks with various degree exponents λ􏰷. For 􏰷􏰣λ is small than or equal to 3, the critical temperature diverges as it does for the Ising model on scale-free networks. For λ􏰷=8, on the other hand, we observe a second-order phase transition at finite temperature. We obtain the critical temperature Tc=3.08(􏰈2)􏰉 and the critical exponents ν′=2.62􏰈3􏰉, γ/ν′=0.127􏰈4􏰉, and β/ν′=0.442􏰈2􏰉 from a finite-size scaling analysis.

Critical behavior of the XY model on static scale-free networks (with Wooseop Kwak, Kwang-Il Goh, and In-mook Kim, EPL, 2008)

The critical behaviors of the equilibrium model on correlated and uncorrelated networks are known to differ, and the critical behavior of the XY model on correlated scale-free networks has been examined. Here, we study the XY model on uncorrelated scale-free networks with various degree exponents λ of the power law degree distribution P (k) ∼ k−λ, where the degree k is the number of neighborhood. For λ > 5, we find that the critical exponents of the XY model on uncorrelated networks are identical to those of the standard mean field. These results vary from those derived from correlated networks.

We study the critical properties of the majority voter model on three dimensions. The majority voter model belongs to the Ising universality class on two dimensions, but does not on three dimensions. We have modi􏰩ed the majority voter model by considering the di􏰨erence between the local and the global con􏰩guration energies. This modi􏰩ed majority voter model is found to belong to the same universality class as that of the Ising model on three dimensions.

We study a generalized conserved lattice gas model in two dimensions by introducing an effective temperature to the conserved lattice gas model, where the number of particles is conserved during the dynamical process. We apply Monte Carlo simulation with the Metropolis transition rate. At zero temperature we find two transition behaviors; one between the localized active states and absorbing states and the other between the localized active states and active states. With a different definition of the order parameter for the second transition behavior, we obtain the critical exponents at the transition point.

Existence of an upper critical dimension in the majority voter model (with In-mook Kim and Wooseop Kwak, PRE, 2008)

We study the critical properties of the majority voter model on d-dimensional hypercubic lattices. In two dimensions, the majority voter model belongs to the same universality class as that of the Ising model. However, the critical behaviors of the majority voter model on four dimensions do not exhibit mean-field behavior. Using the Monte Carlo simulation on d-dimensional hypercubic lattices, we obtain the critical exponents up to d=7, and find that the upper critical dimension is 6 for the majority voter model. We also confirm our results using mean-field calculation.

Magnetization is measured in experiments for both ferromagnetic and antiferromagnetic materials to investigate the magnetic properties of materials, and the susceptibility of total magnetization as a function of external field is used to determine Neel or Cueri temperatures. In the Monte Carlo simulation, it is important to define the proper order parameters to describe the spin model, where the magnetization is used as an order parameter for ferromagnetic spin model and the staggered magnetization is used as an order parameter for the antiferromagnetic spin model without geometrical frustration. However, it is difficult to define an order parameter for frustrated spin models. We perform the Monte Carlo simulation for the antiferromagnetic Heisenberg spin model using the damage spreading as an order parameter, and also perform simulation using both the magnetization and the staggered magnetization as order parameters. Then, we measure the critical temperatures and the critical exponents on three-dimensional regular lattice estimated by different order parameters, and then study the dependency of critical behaviors on different order parameters for the antiferromagnetic Heisenberg spin models.

Critical behavior of the XY model on uncorrelatedand correlated random networks (with Kwang-Il Goh, In-mook Kim, and Wooseop Kwak, NJP, 2009)

We numerically study the critical behavior of the XY model on the Erdo ̋s–Rényi random graph and a growing random network model, representing the uncorrelated and the correlated random networks, respectively. We also checked the dependence of the critical behavior on the choice of order parameters: the ordinary unweighted and the degree-weighted magnetization. On the Erdo ̋s–Rényi random network, the critical behavior of the XY model is found to be of the second order with the estimated exponents consistent with the standard mean-field theory for both order parameters. On the growing random network, on the contrary, we found that the critical behavior is not of the standard mean-field type. Rather, it exhibits behavior reminiscent of that in the infinite-order phase transition for both order parameters, such as the lack of discontinuity in specific heat and the non-divergent susceptibility at the critical point, as observed in the percolation and the Potts models on some growing network models.


Agent-based approach for generation of a money-centered star network (with Okyu Kwon, Woo-Sung Jung, and In-mook Kim, Physica A, 2008)

The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the ‘‘storage fee’’ is more crucial than ‘‘demand’’ in determining which commodity is used as a medium of exchange.

We apply Wang–Landau sampling to the continuous energy model of a protein using Simple Molecular Mechanics for Protein (SMMP). We also tried to parallelize the Wang–Landau sampling method and compare our results with previous results derived from the multicanonical and parallel tempering methods.


Last update : May 25, 2018