A network agent-based model of ethnocentrism and intergroup cooperation

Quality & Quantity - We present a network agent-based model of ethnocentrism and intergroup cooperation in which agents from two groups (majority and minority) change their communality (feeling...     

Artificial stock markets with different maturity levels: simulation of information asymmetry and herd behavior using agent-based and network models

This paper aims mainly at building artificial stock markets with different maturity levels by modeling information asymmetry and herd behavior. The developed artificial markets are multi-assets, order-driven and populated by agents having heterogeneous behaviors and information. Agents are defined by their information and their herd behavior levels. Agents trade multiple risky assets based on their wealth, their behaviors and their available information which spread among multiple behavioral networks. In a novel contribution to artificial stock markets literature, agents’ behaviors modeling is mixed with social network simulation to reproduce different degrees of information asymmetry and herd behavior based on several assortative topologies. Several simulations validated the proposed model since univariate and multivariate stylized facts were reproduced both for mature and immature stock markets. The proposed artificial stock market can be considered as a first step toward decision and simulation tools for optimal management, strategy analysis and predictions evolution of immature stock markets.     

An agent-based model of payment systems

We lay out and simulate a multi-agent, multi-period model of an RTGS payment system. At the beginning of the day, banks choose how much costly liquidity to allocate to the settlement process. Then, they use it to execute an exogenous, random stream of payment orders. If a bank's liquidity stock is depleted, payments are queued until new liquidity arrives from other banks, imposing costs on the delaying bank. We study the equilibrium level of liquidity posted in the system, performing some comparative statics and obtaining insights on the efficiency of alternative system configurations.     

A model of diffusion and implementation: An exploratory study of managerial innovation in Colombia

The focus of this paper is characterized by (1) an examination of the factors related to the “anticipation” of potential innovations in any organizational setting and (2) the identification of strategies for the diffusion and implementation of operations research/management science (OR/MS) techniques in a particular developing region. Based on the methodology used in studying change (innovation) in health care systems, a managerial innovation model incorporating four main components [the executive, the organization, the task environment of the organization and change agent(s), including the OR/MS manager and outside consultants] is developed and examined in terms of data obtained from top executives and other managers in forty industrial firms in Cali, Colombia. In the model developed the process of innovation is decomposed into the levels of; (a) attitudes and motivations of the executive, (b) “readiness” to take action, (c) action characteristics, (d) triggering cues and (e) actions taken and evaluation (feedback loop). The model was found useful for providing predictions indicating areas to which intervention and “marketing” of OR/MS strategies should be devoted. Overall, the study provides a base for comparative and longitudinal studies.     

An information diffusion model for momentum effect based on investor wealth

We propose a private information diffusion model to explain the momentum, which considers different amounts of investor wealth and uses the proportion of informed investors’ wealth to measure information diffusion speed. Different distributions of investor wealth can lead to different information diffusion processes, and the speed of information diffusion is positively correlated with the concentration of investor wealth. Our empirical results reveal the relationship between momentum return and information diffusion speed by the S&P 500 stocks in two periods of the upmarket. The results show that stocks with faster information diffusion speed gain higher time-series momentum returns, especially under short holding period strategies. These results provide new evidence for the correlation between information diffusion and the momentum effect.     

Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate

World markets are highly interlinked and local economies extensively rely on global supply and value chains. Consequently, local production disruptions, for instance caused by extreme weather events, are likely to induce indirect losses along supply chains with potentially global repercussions. These complex loss dynamics represent a challenge for comprehensive disaster risk assessments. Here, we introduce the numerical agent-based model acclimate designed to analyze the cascading of economic losses in the global supply network. Using national sectors as agents, we apply the model to study the global propagation of losses induced by stylized disasters. We find that indirect losses can become comparable in size to direct ones, but can be efficiently mitigated by warehousing and idle capacities. Consequently, a comprehensive risk assessment cannot focus solely on first-tier suppliers, but has to take the whole supply chain into account. To render the supply network climate-proof, national adaptation policies have to be complemented by international adaptation efforts. In that regard, our model can be employed to assess reasonable leverage points and to identify dynamic bottlenecks inaccessible to static analyses.     

The influence of supply network structure on firm innovation

In this study, we examine the structural characteristics of supply networks and investigate the relationship between a firm's supply network accessibility and interconnectedness and its innovation output. We also examine potential moderating effects of absorptive capacity and supply network partner innovativeness on innovation output. We hypothesize that firms will experience greater innovation output from (1) higher levels of supply network accessibility and supply network interconnectedness, (2) the interaction between the levels of these two structural characteristics, (3) the moderating role of absorptive capacity on supply network accessibility and the moderating role of supply network partner innovativeness on supply network interconnectedness. Supply network partner relationships are drawn in the context of the electronics industry using data from multiple sources. We use social network analysis to create measures for each supply network structural characteristic. Using regression techniques to test the relationship between these structural characteristics and firm innovation for a sample of 390 firms, our findings suggest that supply network accessibility has a significant association with a firm's innovation output. The results also indicate that interconnected supply networks strengthen the association between supply network accessibility and innovation output. Moreover, the influence of the two structural characteristics on innovation output can be enhanced by a firm's absorptive capacity and level of supply network partner innovativeness. By addressing the need for deeper structural analysis, this study contributes to supply chain research by accounting for the embedded nature of ties in supply networks, and showing how these structural characteristics influence the knowledge and information flows residing within a firm's supply network.     

An industrial network flow information integration model for supply chain management and intelligent transportation

Industrial network flow involves three domains: infrastructure, individual subjects of movement, and planning and control of the movement. Examples include supply chain and intelligent transportation. These traditionally isolated domains can be digitally connected to enhance their performance. Digitization of the infrastructure provides real-time data to facilitate its operation, while digitally connecting the subjects to the infrastructure allows for tailored services and support to particular subjects. Connection of both to the enterprise information systems enables adaptive control for the application (e.g. logistics) at a global optimization level. Previous results in the field cover separate aspects of planning/routing, real-time monitoring, and trip support. Toward this end, a new highway-based subject-infrastructure-enterprise (SIE) information integration model using digital connection is proposed to the field of industrial network flow control for application to intelligent transportation and supply chain management. The SIE model supports industrial network flow control in a way comparable to an adaptive control panel administering an automated material handling system. In this metaphor, the global infrastructure becomes ‘controllable’ similar to factory conveyors and automated guided vehicles. This paper presents a conceptual design substantiated with information requirements analysis. An empirical experiment at locations in New York State shows the technical feasibility of the digital connection envisioned.     

Prices,debt and market structure in an agent-based model of the financial market

We develop an agent-based model in which heterogeneous and boundedly rational agents interact by trading a risky asset at an endogenously set price. Agents are endowed with balance sheets comprising the risky asset as well as cash on the asset side and equity capital as well as debt on the liabilities side. A number of findings emerge when simulating the model: we find that the empirically observable log-normal distribution of bank balance sheet size naturally emerges and that higher levels of leverage lead to a greater inequality among agents. Furthermore, greater leverage increases the frequency of bankruptcies and systemic events. Credit frictions, which we define as the stickiness of debt adjustments, are able to explain a key difference in the relation between leverage and assets observed for different bank types. Lowering credit frictions leads to an increasingly procyclical behavior of leverage, which is typical for investment banks. Nevertheless, the impact of credit frictions on the fragility of the model financial system is complex. Lower frictions do increase the stability of the system most of the time, while systemic events become more probable. In particular, we observe an increasing frequency of severe liquidity crises that can lead to the collapse of the entire model financial system.     

The information revolution,innovation diffusion and economic growth: an examination of causal links in European countries

Quality & Quantity - Over the last 5 decades, the economic landscape in Europe has been transformed rapidly due to innovation, digitisation of the economy, and emergence of new sources of...     

An agent-based model of the observed distribution of wealth in the United States

Pareto cautiously asserted that the wealth and income distributions which bear his name are universal, basing his argument on observations of this distribution in many different types of economies. In this paper, we present an agent based model (and a scalable approximation of it) in a closely related spirit. The central feature of this model is that wealth enables an individual to secure more wealth. Specifically, the important and novel feature of this model is its ability to simultaneously produce both the Pareto distribution observed in empirical data for the top 10% of the population and the exponential distribution observed for the lower 90%. We show that the model produces these distributions of wealth when initialized with an equitable distribution. Then, using historical data, we initialize the model with US wealth shares in 1988 and show that the model tracks wealth share changes from 1988 to 2012. Simulations to 2088 project that the top 0.01% of the population will possess more than 70% of the total wealth in the economy.     

The interaction of corporate dividend policy and capital structure decisions under differential tax regimes

We develop a valuation model that integrates corporate capital structure and dividend payout policies. The resulting “extended” Miller (J Financ 32:261–297, 1977) model explicitly incorporates the different tax rates on corporate income, personal interest, dividends, and capital gains. We apply the model to ten different U.S. tax regimes since 1979 and generate several testable predictions. When the dividend tax rate exceeds the capital gains tax rate, dividend payout can partially offset value-enhancing effects of leverage. When the two rates are close, dividend payout loses its moderating influence. Using the S&P 1500 universe, we obtain empirical results that are consistent with the model’s predictions.     

A model of information diffusion with asymmetry and confidence effects in financial markets

We present a model of multi-period continuous information diffusion in financial markets. We show that price and trading volume exhibit asymmetric term structures to information flow, where the diffusion rate accelerates more slowly at short horizons than it decelerates at long horizons. Bounded rationality is modelled by an endogenous trader confidence index which declines as stock price information becomes noisier, where lower confidence translates into lower trading volume and slower price accretion. Information diffusion slows and asymmetries are accentuated as traders lose confidence in information accuracy. Our empirical findings support the model's predictions of asymmetric momentum patterns and confidence effects.     

Small samples and collateral information: An application of the hyperparameter model

When time-series and cross-section data are available for estimating a linear relationship, the data may be pooled using a number of frameworks of varying degrees of restrictiveness. One possible framework which appears not to have been exploited in previous applied econometric work, but which may have some merit especially when the number of observations in the time-series or cross-section dimension is not very large, is the hyperparameter model of Lindley-Smith (1972). Under appropriate conditions the use of this framework enables one to obtain ‘improved’ Bayesian point estimates which yield predictions with smaller mean-square-error than those from ordinary least squares. The paper uses the hyperparameter framework to estimate a Cobb-Douglas production function using U.K. cross-sectional data. A cross-validation exercise is carried out to see how much of the potential of the Bayesian method is realised in practice.     

Policy evaluation under uncertainty: An approach using subjective information

Approaches to policy analysis frequently ignore the complex, uncertain environment in which the proposals are being evaluated. An attempt is made in this article to outline a procedure which uses subjective information judgements of participants in the problem situation for including an uncertainty dimension in policy analysis. The approach is tested by way of an application to defence planning.     

网络环境下高校图书馆信息服务工作的新探索

网络环境对高校图书馆的影响及其作用。在网络环境下 ,高校图书馆信息服务工作的新探索 ,强调个性化信息服务 ,建立学科馆员制度 ,为读者提供高附加值的信息服务。     

Business model innovation in a knowledge revolution: An evolutionary theory perspective

For knowledge‐intensive industries, a need remains to increase clarity on the dynamics through which business model innovation occurs. Progress has been limited owing to complexities in these industries and to the underlying ontology of the business model concept itself. Through a conceptual methodology, our findings expose impediments to current business model theory and propose economic evolutionary theory as a useful alternative lens through which to address these limitations. This research contributes to the literature by broadening the traditional scope of the economic evolutionary view as relevant for business model innovation research and by offering a corresponding framework for future research.     

Staring at the Abyss: a neurocognitive grounded agent-based model of collective-risk social dilemma under the threat of environmental disaster

Increasingly visible climate change consequences challenge carbon-based economies worldwide. While expert knowledge on climate change percolates through political initiatives and public awareness, its translation into large-scale policy actions appears limited. Climate change consequences unequally target regions, countries and social classes, a vital issue for social cooperation. When facing an imminent ecological collapse, in which conditions can self-interested agents gain environmental awareness and settle on a sustainable path of actions when their knowledge of the imminent collapse is bounded? This cooperation emerges from the interaction between individuals and the interaction of various cognitive processes within individuals. This article develops an agent-based model for this emergence of cooperation enriched with the Agent Zero neurocognitive grounded cognitive architecture. We investigate when agents endowed with deliberative, affective and social modules can settle on actions that safeguard their environment through numerical simulations. Our results show that cooperation on sustainable actions is the strongest when the system is at the edge of collapse. Policy measures that increase the environment’s resilience become internalized by the agents and undermine awareness of the ecological catastrophe. Depending on the cognitive channels activated, agent behaviors and reactions to specific interventions significantly vary. Our analysis suggests that taking different cognitive channels, deliberative, affective, social, and others into account, significantly impact results. The complexity of agent cognition deserves more attention to assess parameter sensitivity in social simulation models.

     

R&D cooperation and unintended innovation performance: Role of appropriability regimes and sectoral characteristics

This research empirically examines the relation between R&D cooperation and unintended innovation performance. The effects of appropriability and sectoral conditions on the unintended innovation performance in the context of R&D cooperation were also tested. Binary logistic regression was used to analyze the manufacturing firms sampled from the Korea Innovation Survey (KIS) 2012. Our estimation results show that for the high-tech focal firms under strong appropriability regime, cooperation with competitors increases the likelihood of their unintended innovation performance. For the high-tech focal firms under weak appropriability regime, cooperation with customer and user firms and universities increases the likelihood of their unintended innovation performance. For the low-tech firms under strong appropriability regime, cooperation with the customer and user firms and advisory organizations increases the likelihood of unintended innovation performance. For the low-tech firms under weak appropriability regime, cooperation with competitors and government research institutes increases the likelihood of unintended innovation performance. As a whole, the significance of this paper lies in shedding a new light on approaching the innovation performance with the notion of unintended innovation performance, which is shaped by different partner types and environmental conditions.