System optimization model of adoption of a new infrastructure with multi-resource and multi-demand sites

This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, spillover effect, demand, initial investment cost, and learning rate influence the adoption of the new infrastructure technology and presents optimization results of the model in different scenarios. The main findings of the study are: from the perspective of system optimization, (1) different distances among different resource-demand pairs will result in different adoption time of a new infrastructure; (2) technological spillover among different resource-demand pairs will accelerate the adoption of a new infrastructure; (3) it is hard to say that higher demand will pull faster adoption of a new infrastructure, and the optimal time of adopting of a new infrastructure is very sensitive to its technological learning rate.     

Connecting informal networks to management of tacit knowledge

The relationship between tacit knowledge and informal networks has not been fully explored.Tacit knowledge cannot be well managed directly,because it is deeply embedded in individual actions and experiences.This study proposes an approach to managing informal networks as a new middle way to facilitate the sharing and transferring of tacit knowledge,owing to the fact that tacit knowledge is mostly shared and transferred through informal networks.To support the idea of the approach,an empirical case study of applying the approach to management of a large scientific project is also included.Our findings suggest that informal networks play essential roles for management of tacit knowledge,and thus good management of informal networks can lead to efficient sharing and transferring of tacit knowledge.     

AGENT-BASED SIMULATION FOR KANSEI ENGINEERING： TESTING A FUZZY LINEAR QUANTIFICATION METHOD IN AN ARTIFICIAL WORLD

This paper argues that agent-based simulation can be used as a way for testing Kansei Engineering methods which deal with the human reaction from sensory to mental state, that is, sensitivity, sense, sensibility, feeling, esthetics, emotion affection and intuition. A new fuzzy linear quantification method is tested in an artificial world by agent-based modeling and simulations, and the performance of the fuzzy linear method is compared with that of a genetic algorithm. The simulations can expand people＇s imagination and enhance people＇s intuition that the new fuzzy linear quantification method is effective.     

Assessing historical reliability of the agent-based model of the global energy system

This study looks at the historical reliability of the agent-based model of the global energy system. We present a mathematical framework for the agent-based model calibration and sensitivity analysis based on historical observations. Simulation consistency with the historical record is measured as a distance between two vectors of data points and inference on parameter values is done from the probability distribution of this stochastic estimate. Proposed methodology is applied to the model of the global energy system. Some model properties and limitations followed from calibration results are discussed.     

ESTABLISH A CREATIVE ENVIRONMENT FOR ROADMAPPING IN ACADEMY—FROM THE PERSPECTIVE OF I-SYSTEM METHODOLOGY

Roadmapping,originated from industry as a strategic planning tool,is attracting increasing applications in academy.Based on the recognition that roadmapping is a knowledge creation process, this paper analyzes what kind of support is needed or helpful for establishing a creative environment for roadmapping in academy and reviews various types of such support from the perspective of i-system methodology.As case studies of such support,this paper further introduces roadmapping pratices in Janpan Advanced Institute of Science and Technology.     

资源约束下绿色铝供应链网络设计多目标优化

本研究针对铝供应链中日益凸显的碳排放问题和水资源消耗问题,建立了一套决策模型框架,该框架由生命周期分析、绿色供应链网络优化模型和基于epsilon约束方法的多目标优化模型组成,同时考虑煤电、生物质发电、光伏+储能的组合等多种电力供应方式选择以及碳市场不确定性的影响,对铝供应链在多种资源约束下的多目标优化问题进行了深入分析.模型计算结果表明:经济成本和水资源消耗是一对彼此矛盾的目标;决策偏好以及碳市场不确定性会影响供应商的选择;资源约束更加严格的情况下倾向于选择低碳技术,同时产生减少水资源消耗的协同效应.高碳价下所有的帕累托解都不会选择煤电,而更多地倾向于选择光伏加储能的电力供应模式.案例研究证明了该模型在资源产业链多目标决策方面的有效性.本文提出的模型方法为环境资源约束下的资源型制造业决策提供了理论支持.     

AN AGENT—BASED SIMULATION ON MARKET CONSIDERING KNOWLEDGE TRANSITION AND SOCIAL IMPACT

In this paper, an agent-based simulation about knowledge transition associated with social impact in market is introduced. In the simulation, the genetic algorithm is used to generate the next generation products and a dynamic social impact model is used to simulate how customers are influenced by other customers. The simulation and its results not only show some features and patterns of knowledge transition, but also explore and display some phenomena of business cultures. On the basis of the innovation model of knowledge-based economy, the transition between technical knowledge and products knowledge is discussed, and a fuzzy linear quantification model which can be used to simulate the transition is introduced.     

Establish a creative environment for roadmapping in academy—From the perspective of <Emphasis Type="Italic">i</Emphasis>-system methodology

Roadmapping, originated from industry as a strategic planning tool, is attracting increasing applications in academy. Based on the recognition that roadmapping is a knowledge creation process, this paper analyzes what kind of support is needed or helpful for establishing a creative environment for roadmapping in academy and reviews various types of such support from the perspective of i-system methodology. As case studies of such support, this paper further introduces roadmapping pratices in Janpan Advanced Institute of Science and Technology.