Inventory management is considered as one of the most important factor in Supply Chain Management. However, the real-world inventory systems are complexly intertwined with related elements, it is recognized that identify the determining factor that influences the change of inventory is a complex problem. In this paper, we proposed a simulation-based combination algorithm for optimizing inventory systems. The objective is to minimize the inventory quantities while reducing opportunity loss. The inventory system is modeled and simulated, which returns the performance functions. The expectations of these functions are then estimated by an algorithm and optimal combination result is obtained. Based on the sensitivity analysis, the determining factor that influences the change of inventory is identified. The results show that proposed algorithm is powerful and effective.

Researches on leadership for corporate organizations have been not found and others, but measures to make leadership perceive to followers are not mentioned. <br> The purpose of this research is to create a model that can evaluate the recognition of leadership to build measures to recognize leadership. There are four types of leadership: instruction, empower, exchange, transformation. Of these, the transformation type and the exchange type are formalized in the Principal Agency model that generally shows the relationship between the leader and the follower of the conventional research, while the indication type and the empower type are not formalized. Modeling those two types of leadership is required to comprehensively evaluate leadership. Our final goal is to create a unified model that integrates four types of models.

© 2016 The Author.A value-centered approach to science, technology and society (STS) education illuminates the need of reflexive and relational learning through communication and public engagement. Visualization is a key to represent and compare mental models such as assumptions, background theories and value systems that tacitly shape our own understanding, interests and interactions. Yet conventional approaches including concept mapping and multi-criteria value elicitation methods often have little suggestion or implication as to how participants themselves can address and deliberate the incompatibility of their perceptions, preferences and perspectives. This study proposes Q workshop as a legitimate eliciting and deliberation technique that can be employed in pluralistic discourse, exploring systematic divergences of perspective by constructing the participant‘s self in a formative, emergent and contingent manner. For this it introduces Q mapping as a novel visualization tool for the hybridity of qualitative and quantitative methods derived from Q methodology. Q mapping is a two-factor solution that transforms the similarities in participants’ individual Q scores into distances represented in two-dimensional space, for the sake of illustrating the relative positioning and partitioning of perspectives in a schematic figure. A case study on STS education for postgraduate students demonstrates that Q workshop can play a heuristic and abductive role in providing independent illumination of distinguishable perspectives and facilitating individual and collective learning among participants, suggesting a schematic two-dimensional basis for resolving the key differences.

This paper proposes an agent-based simulation to analyze the effective resource allocation strategies for patrolling and inspection in consideration of urban network structures. A model of attackers and defenders is first formulated as "security game for urban networks." Then optimal security plans are calculated as Nash equilibria, supposing complete rationality of attackers behaviors. The "rational" security plans should be evaluated under more realistic conditions. So we provide an agent-based attacker model by addressing bounded rationality of human behaviors to support decision making under complexity and uncertainty. In particular, this paper mainly evaluates the effectiveness of security plans from the viewpoint of the structural characteristics of urban network, which can affect the route constrains for attackers. Our simulation shows the success rates of security with two types of urban networks and explains the reason why the results are generated through the investigation of attacker agents' micro behaviors in detail.

Designing a signage system in complex and large-scale facilities such as airport passenger terminals, stations or shopping malls has a significant impact on usability of the facilities. Facility managers would like to provide appropriate guidance information to facility users by using a signage system. It is difficult, however, to create the signage system designed to provide the right information to various types of users in the right place at the right timing. This paper focuses on an airport terminal and develops an agent-based model that represents the behavioral characteristics of passengers and the essential features of signs. The simulation with the model can show possible passenger behaviors and congestion situations in the facility under many different types of signage systems. As the results, we can support the managers' decision to build the signage system before it is actually implemented.

It is generally understood that manufacturers should exploit the innovation generated by users (UI: user innovation) to develop new products. UI has been observed in real world markets and the typical features of innovating users have been identified. The roles of the various communities in consumer product markets are explored as an important factor in UI. While communities foster the generation of UI and assist the diffusion of UI to the markets, it is still unclear what kind of communities managers in manufacturing firms should approach to obtain information for UI exploitation. In addition, the mechanism of UI in terms of community is also still unclear.
This paper focuses on the mechanism of UI generation and diffusion in communities by applying agent-based simulation. Based on the simulation results, we are able to recommend to managers the most appropriate communities for UI exploitation. (C) 2014 Elsevier Inc. All rights reserved.

The purposes of this paper are to build an agent-based model to explain knowledge dynamics in front office and conduct a scenario analysis for evaluating several functions of knowledge acquisition system as one of knowledge management instruments. Conventional agent-based analyses have tackled to some knowledge management problems in organizations. However they did not considered service characteristics when building their model. So we expressly model the characteristics of service co-creation processes between customers and service agents based on some findings in the field of service research. Finally our simulation with the model shows the possible changes of organizational productivity and customer satisfaction by using some scenarios, and then clarifies the reason that why the changes occurred by investigating agents' micro behaviors. © 2013 The Institute of Electrical Engineers of Japan.

Recently, a need has arisen for facsimile model construction with close correspondence to the real world for use in evaluating the effectiveness of specific policies. When constructing facsimile models requiring a large amount of data, however, parameter estimation using data fitting becomes problematic. Furthermore, there are often problems where, owing to the limitations of field research, it becomes impossible for analysts to obtain the data necessary for model construction. The paper proposes a solution to this data collection problem by using "virtual grounding" as a method for creating valid agent models. The proposed method constructs an agent model by isolating qualitative features of the real world situation that are targets for modeling at a stage where the complete dataset is not yet available, and uses standard models for which utility has been previously demonstrated. Following this construction, a number of sample participants modeled as agents repeatedly make hypothetical decision-making actions within the model environment, and the model parameters are estimated based on the results of these decisions. This paper demonstrates the utility of the virtual grounding method by using an example of modeling visitor agents to Tokyo Disney Sea.

This paper provides a computational market model with technological competitions among standards and presents simulations of various scenarios concerning standardization problems. The market model has three features: (1) economic entities such as consumers and firms are regarded as autonomous agents; (2) micro interactions among consumer agents or firm agents have essential mechanisms interpretable in real markets; and (3) consumers' preferences and firms' technologies co-affect their evolutionary behavior. In recent years, consumers have experienced various inconveniences from de facto competition based on a market mechanism. Standardization communities or committees such as the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) need to design a compatible standard or a de jure standard in a market. However, it is difficult for market designers to decide a method or timing for the standardization. Here, by introducing a novel technique used in agent-based social simulation (ABSS), which we call "scenario analysis," we aim to support such decision making. Scenario analysis provides the possible market changes that can occur following implementation of a design policy under a specific market situation and the market mechanisms that generate these market changes.

Service-oriented organizations have the properties that their main resources are the knowledge and skills of service agents, and they produce intangible outputs, while those of manufacturing organizations are tangible products. So managers in the service-oriented organizations have taken "seat-of-the-pants" approaches to evaluate their new policies for preventing productivity slump. The purpose of this paper is to model service agents and tasks in a specific service-oriented organization through a field research, and to provide helpful information from the viewpoint of creating multi-skilled agents for the managers, who wish to make an accurate policy relevant to job rotation, through agent-based social simulation (ABSS) with the model. © 2012 IEEE.

The purposes of this paper are to find users&#039;innovations in the mountain climbing product market in Japan, then to identify the attributive and structural characteristics of innovating users who develop the users&#039;innovations. It has been pointed out that manufacturers should utilize the users&#039;innovations in their new product development processes. However there have been few cases that a manufacturer actually utilized users&#039;innovations to develop a new product. This is partly because the manufacturer could not recognize the importance of utilizing the users&#039;innovations or could not find users&#039;innovations in the market. This paper shows mainly two results based on statistical analysis. First this paper shows that there exists a certain number of innovating users in the mountain climbing product market in Japan and some lead users who developed commercially successful products even though experts familiar with the market observed few innovating users. Second this paper identifies a formula to distinguish between innovating and non-innovating users. The results given in this paper provide manufactures with incentives to find and utilize users&#039;innovations in their new product development processes.

This paper examines effective knowledge-retrieval heuristics in terms of transactive memory in concurrent software development teams. We propose six knowledge-retrieval heuristics and evaluate their effectiveness in four typical situations encountered by concurrent software development teams. Agent-based social simulation suggests the following findings about effective heuristics in each situation: (1) in large teams, if team members have incomplete information about their teammates' expertise, both the minimum effort type and the risk aversion type are effective; (2) in small teams, if team members have incomplete information about their teammates' expertise, the broad retrieval type is effective; (3) in small teams with a heavy work-load, if team members have sufficient information about their teammates' expertise, the minimum effort type is effective; (4) in small teams with a light work-load, if team members have sufficient information about their teammates' expertise, both the minimum effort type and the "ask others" type are effective.

Evaluation systems for team-members have an effect on organization behavior, and their effect depends on external environmental factors and organizational characteristics. Therefore a contingency analysis of the evaluation systems under the classified situations has importance. Flaherty et al. (2007) classified into three types of sales situations. In this paper, we examine the effective evaluation systems under these three types of sales situations by agent-based social simulation. The result leads two findings: (1) the effective evaluation systems of sales organizations varies according to their respective sales situations; (2) organizational behavior under an evaluation system varies according to their respective sales situations.

In this paper we focus on some phenomena generated by lead user innovation and build a market model based on the lead user&apos;s features that are derived from the conventional studies. Then we consider market mechanism and dynamics of the market with the lead user innovation. The innovation changes a conventional market concept that consumers and firms are entities that respectively demand and supply products. It is hard for marketers and managers to comprehend the market dynamics and mechanism generated by the change of market invoked by the innovation. Our simulations with the market model show two propositions: 1) If firms take the conventional strategies based only on conventional marketing strategies and technology management, lead user innovation takes the high market share from firms&apos; products. 2) If firms focus on an innovation community as a new strategy, they can manage lead user innovation.

Balanced Score Card (BSC) is proposed as a method to translate an organization strategy into Key Performance Indicators (KPIs). How many KPIs are required for each perspective is an important research issue. It is hard to design appropriate KPIs to satisfy the required perspectives. Agent-based simulation can be an effective tool for managers' decision support about the KPIs design. In this paper, we clarify requirements for agent-based modeling for the design of KPIs. The requirements consist of defining the type and the characteristics of an organization, specifying assumptions, designing the parameters, and analyzing scenarios. The simulation satisfying the requirements can analyze effects of how KPIs are weighted in an organization under strategic questions.

Many academic people and practitioners point out that it is hard to be supported by scenario analysis methods about actual problem situations, because the identification of an agent's decision making model representing plausible behaviors is very difficult The primary purpose of this paper is to propose a method of model building for making scenario analysis methods effective options. This proposed method starts from minimum model elements, and examines whether an additional element should be introduced in terms of plausible behaviors. We give a case study of introducing visitor's preference in the theme park problem. The result of this case study suggests that the visitor's preference has a strong relationship to the phenomena which could be observed at an actual theme park.

The primary purpose of this paper is to propose a new framework for supporting market design, and to analyze standardization problems. The main features of the framework are as follows: 1) economic units such as firms or consumers are regarded as autonomous agents, 2) essential interactions among these agents in a market are considered, 3) consumers&#039; preferences and firms&#039; technologies coevolute in choices of products. We call this CAMCaT (Coevolutionary Agent-based Model for Consumers and Technologies) framework. The main target problems of this paper are standardization in market design. In recent years, a technological progress and a globalization have been intensifying competitions between standards in many markets. In these competitions, firms tend to pursuit short-term profits acquisition, and winners can get more profits than losers. Moreover a firm strains on its own standard in the competitions. As a result, many stakeholders suffer various types of inconvenience from these competitions based on a market mechanism. Therefore some problems about the standardization are noticed in many markets. It is a difficult problem how we should specify a standard. Then we would like to provide a new approach unlike conventional studies of a market structure and market dynamics. This paper builds an agent-based model using CAMCaT framework to examine some essential problems about the standardization and conducts a simulation on some scenarios that show some propositions of the standardization to verify the effectiveness and validity of the model. The result shows that this model has a high potential to support market design process.

The purpose of this paper is to provide a marketing system for supporting decision making of firms in target marketing. It is hard for firms' marketing departments to decide the target customers, since they have no past purchase data of customers when developing or launching new products. The marketing system is helpful for them to extract customers who give a higher evaluation to a product developed by them. This paper conducts some demonstrations as an example of simulations in the mobile phone market by using the system. The result shows that the system is valid and effective, since the system developed can extract customers' features based on a system user's cognition to the market.

This paper proposes guidelines to evaluate agent's internal model effectively in organizational learning. We developed an approach named Agent-based Organizational Cybernetics to describe problems in organizational learning with an agent-based model and to design some prescriptions for them. This paper focuses on four typical evaluation problems of internal model in organizational learning: (1) environmental scanning, (2) policy making, (3) coordination, and (4) task resolution. We design some guidelines for each problem, run simulations in various settings, and test the effectiveness of the guidelines.

This paper proposes Agent-based Organizational Cybernetics (AOC), which combines organizational cybernetic framework and computational organization theoretic approach, especially agent-based computational learning model. Organizational cybernetics provides a basic framework in which every organization is comprehensively described to be composed of 4 functional layers: process, coordination, adaptation and self-organization. In organizational cybernetics the difference between the overall purpose of an organization and each function of it plays an essential role especially to provide diagnosis for the organization of keeping viable. In this usage of the organizational cybernetic framework no micro-macro problem between learning of each member and that of the whole system can be seen. On the other hand, computational organization theoretic approach focuses on agents' task resolutions and bottom-up description of organizational activities. Organizational learning process described in computational organization theory mainly consists of error correcting activities by each agent and organization itself based on the agents' decision rules. Computational organization theory describes explicitly models to define detail dynamics on learning in process levels by agents. It is, however, not straightforward to describe double-loop learning as sharing internal models among agents. Though organizational cybernetic approach and computational organization theoretic one have considerably different aspects: on micro-level and on macro-level, we can combine them and build newly emergent model. Our proposed model describes the two loops of organizational learning by representing both processes of learning of internal models and resolving tasks by agents. The model can describe essentially different levels of individual learning and organizational one so as to distinguish effectively the two loops of organizational learning.

This paper proposes an agent-based simulation model for analyzing adaptive processes of organizational structures to environmental changes. The model is based on a framework of computational organization theory (COT) and performed using the method of inverse simulation with genetic algorithm. The model specifies an activity process in organization that is composed of tasks, agents and environments. The roles of agents: normal and leader, are defined based on some basic tasks of agents: recognizing tasks from environment, sharing knowledge required for processing tasks, and coordinating tasks among agents. Organizational structures are distinguished according to the configuration of the roles of agents resolving the tasks recognized. Adaptation process is represented as learning process of agents' internal models of environments. Environments are expressed as task generators and fall into 5 types. This paper shows some fundamental relationships between organizational structures and dynamically changing environments.

A formal and strict framework to deal with 'soft' games with misperception of emotions by actors is provided. The concepts of credibility and complete credibility of information are defined to examine the relations between emotions of actors and the credibility of information about behavior of the actors. The equivalence of credibility and complete credibility under inside commonality of perceptions of emotions is verified. (C) 2000 Elsevier Science Inc. Ail rights reserved.

In this paper, we propose and examine adaptive learning procedures for supporting a group of decision makers with a common set of strategies and preferences who face uncertain behaviors of "nature." First, we describe the decision situation as a hypergame situation, where each decision maker is explicitly assumed to have misperceptions about the nature's set of strategies and preferences. Then. we propose three learning procedures about the nature, each of,which consists of several activities. One of the activities is to choose "rational"' actions based on current perceptions and rationality adopted by the decision makers, while the other activities are represented by the elements of a genetic algorithm (GA) to improve current perceptions. The three learning procedures are different from each other with respect to at least one of such activities as fitness evaluation, modified crossover, and action choice, though they use the same definition for the other GA elements. Finally; we point out that examining the simulation results how to employ preference- and strategy-oriented information is critical to obtaining good performance in clarifying the nature's set of strategies and the outcomes most preferred by the nature.

Agent-based modeling shows a fruitful approach to understanding self-organizing behavior in complex social systems. The problems on self-organization have been the primary concern of systems theory. Although there have been a lot of researches studying self-organization, we would need some new way to describe a model for emergent properties and learning process. Agent-based modeling can be expected to provide some novel concept and method on learning process in complex social systems. The essential features of agent-based modeling include a learning process of the rules based on which each agent makes a decision for his next action. Genetic algorithm is a powerful tool to implement the learning process in an evolutionary manner. This paper first provides the meaning and role of system models to describe the learning process in self-organization layer. Then the essential difficulties to develop such system models are discussed. The core step in the learning process in agent-based modeling is to produce a new rule set from an old one in the previous learning phase. This correspondence is very hard to describe as some "function" between the rule sets. We should develop more effective mathematical device and concept to build system models of the learning process.

A formal model for describing the interaction stage in a meeting, particularly, persuasion and compromise by the members in a meeting, is proposed. Using the model, a sufficient condition for a meeting not to reach a deadlock is provided. The condition implies that stable emotion of members of a meeting is essential for the meeting not to reach a deadlock. (C) Elsevier Science Inc., 1998.

To give a realistic structure of perceptions that satisfies inside commonality, the concepts of stability of perceptions and complete stability of perceptions are proposed. A framework for interperception of emotions by subjects is provided to deal with the concepts. The equivalence between stability and complete stability under inside commonality of perceptions is proven. (C) Elsevier Science Inc., 1998.

We propose a method to integrate many games into one in order to analyse effectively a complex situation in which various types of games which are mutually interactive can be perceived. Applying the concept of integration of games into the theory of hypergames, we obtain the concepts of integration of hypergames and hypergames generated from a class of games. Simple examples of competitive situations are given and analysed to clarify the concepts.

In this paper, we treat strategic information exchange among subjects in a conflict that involves incompleteness of information in terms of subjects' preference and their interdependence. Then, we give two theorems that indicate senselessness of deceit. One of the theorems implies that any attempt of a subject to change another subject's preference by deceit will end in failure. The other theorem implies that deceit of a subject causes changes of preference of the subject, thus strategic information exchange cannot be effective. (C) Elsevier Science Inc., 1997