研究 / Research Topics
複雑かつ不確実であることは、課題解決のための対策が、システム全体にどのような影響を与えるかを推定することを難しくします。具体的には、電気自動車を後押ししたり、炭素税を導入したりすることが、どのように温暖化ガスの排出量に影響するのかを推定することは、社会システムの複雑さや不確実性のために困難です。
また、創造的な解決策が得られたとしても、その実現には人間のバイアスや組織慣性などのソーシャルな難しさがあります。
本研究室は、システムデザインの方法論やシステム思考的アプローチを基盤として、これらの問題に対して以下の研究テーマを設定しています。
定性的なモデルによる記述、計算機による定量的なモデル、データ解析の組み合わせにより、複雑で不確実なシステムの挙動を明らかにするシミュレーションモデルの開発。また、シミュレーションによる課題解決のアイデアの創出と評価。
創造的な課題解決策を実現するための組織のトランスフォーメーションを進める取り組み。
Complexity and uncertainty make it difficult to estimate how measures to solve a problem will affect the system as a whole. Specifically, estimating how boosting electric vehicles or introducing a carbon tax will affect greenhouse gas emissions is difficult due to the complexity and uncertainty of the social system.
Moreover, even when creative solutions are obtained, there are social difficulties in their implementation, such as human biases and organizational inertia.
Based on systems design methodologies and systems thinking approaches, our laboratory has established the following research themes to address these problems.
Development of simulation models that clarify the behavior of complex and uncertain systems through a combination of description by qualitative models, quantitative models by computers, and data analysis. Development of methodologies to create acreative solutions to problems based on the context of the system.
Efforts to promote the transformation of organizations to achieve creative solutions to problems.
複雑な挙動の予測とアイデアの評価 /
Prediction of complex systems behavior and evaluation of innovative ideas
課題解決に向けた創造的なアイデアは、それらのアイデアが社会や産業のシステムにどのような影響を与えるかによって評価されるべきです。一方で、対象のシステムの複雑さに起因する相互作用や将来の不確実性からこの影響を推定することは困難です。
このため、シミュレーションや多様な情報リソースを含むデータに基づく科学的なアプローチでシステムの挙動予測を行い、課題解決策の選定などの意思決定問題やシステム全体のデザインを支援するための研究を行います。
これまでに、海上物流の脱炭素に向けた国際規則の決定や、企業におけるプロジェクトのリソースマネジメントに関する意思決定、地方自治体の公共交通サービスの維持などに取り組み、様々な社会システムを計算機上のシミュレーションとしてモデル化するための知見を蓄積しています。
Creative ideas for solving problems should be evaluated according to the impact these ideas will have on social and industrial systems. On the other hand, it is difficult to estimate this impact due to interactions and future uncertainties caused by the complexity of the target system.
For this reason, we use simulation and data-based scientific approaches to predict system behavior in order to support decision-making problems such as the selection of solutions to problems and the design of the overall system.
So far, we have worked on international rules for decarbonizing maritime logistics, decision-making on project resource management in companies, and maintaining public transportation services in local governments, and have accumulated knowledge for modeling various social systems as computer simulations.
自動運航技術導入を加速する政策のデザイン
Policy Design for the Introduction of Automatic Operation Technology
Policy Design for the Introduction of Automatic Operation Technology
We built an industrial simulator that models the relationships among stakeholders in the maritime industry, including policy makers, shipping companies, and shipyards and manufacturers, and conducted a world-leading study to explore the combination of stakeholder decision making that will accelerate the introduction of automated vessels. The study modeled and simulated the economic feasibility and safety of 12 types of automated vessels in combination, and the impact of industrial activity on these factors. The results showed that, among the various options available, deregulation combined with subsidies for R&D and demonstration projects would accelerate the timing of the introduction of automated vessels. It is hoped that the proposed simulations can be used by policy makers and companies in their decision-making to achieve a smooth consensus-building process for the early introduction of new technologies.
Nakashima, T., Moser, B., & Hiekata, K. (2023). Accelerated adoption of maritime autonomous vessels by simulating the interplay of stakeholder decisions and learning. Technological Forecasting and Social Change, 194, 122710. https://doi.org/10.1016/J.TECHFORE.2023.122710
適切な意思決定で自動運航の実現が大きく加速 ― シミュレーションが明らかにするステークホルダーの協力の効果 ― https://www.k.u-tokyo.ac.jp/information/category/press/10269.html
ゼロエミッションデータセンターのコンセプトデザイン
Social Systems Design towards Zero Emission: Data Center Case
Social Systems Design towards Zero Emission: Data Center Case
Ichinose, Y., Hayashi, M., Nomura, S., Moser, B., & Hiekata, K. (2022). Sustainable Data Centers in Southeast Asia: Offshore, Nearshore, and Onshore Systems for Integrated Data and Power. Sustainable Cities and Society, 81, 103867. https://doi.org/10.1016/J.SCS.2022.103867
システムダイナミクスによるソフトウェア開発プロジェクトのマネジメント
A System Dynamics Approach towards Design and Management for Software Development Projects
A System Dynamics Approach towards Design and Management for Software Development Projects
Mst Taskia Khatun, Kazuo Hiekata, Yutaka Takahashi & Isaac Okada (2022). Design and management of software development projects under rework uncertainty: a study using system dynamics. Journal of Decision Systems, 1-24. https://doi.org/10.1080/12460125.2021.2023257
システムコンテクストの理解とアイデアの創出 / System Context Analysis and Ideation
専門分野横断型のシステムには唯一の最適なデザインは存在せず、トレードスペースを構築して利害関係者を超えた良いデザインポイントを探索することになります。このためには分野を超えた知識の統合が必要です。このため、知識を共有・再利用できる形で記述する方法の開発や、データからの知識発見、利害関係者間の課題解決にむけた共通認識の形成を支援することに取り組みます。また、課題解決に向けた革新的なアイデアの創出を促すため、心理的安全性の確保やバイアスによる影響低減を可能とするチームワーク環境の実現に取り組みます。
課題解決に効果的な選択肢が明らかになっても、その実現には組織慣性や認知バイアスなどさまざまな障害があります。また、立場の異なる多くの利害関係者間の合意形成も必要です。この問題を解決するため、シミュレーションモデルにより定性・定量の両面で評価された解決策を深く理解できるハンズオンワークショップの開発に取り組みます。
分野を超えた知識を共有・再利用する仕組み、専門性の異なる人々が対象システムの理解を共通化するためのシステム記述方法
システムに関する意思決定のコンテクストでの創造的かつ革新的な選択肢の創出、創造的なアイデアや課題解決方針の創出のためのチームワーク方法論
データからの課題解決や創発現象に関連するパターン(知識)の発見
There is no single optimal design for a cross-disciplinary system, and it is a matter of building trade spaces and searching for good design points across stakeholders. This requires the integration of knowledge across disciplines. To this end, we will work on developing methods to describe knowledge in a form that can be shared and reused, to discover knowledge from data, and to support the formation of a common understanding among stakeholders toward problem solving. In addition, in order to encourage the creation of innovative ideas for problem solving, we will work to create a teamwork environment that ensures psychological safety and reduces the impact of bias.
Even when effective options for problem solving are identified, there are various obstacles to their realization, such as organizational inertia and cognitive biases. It is also necessary to build consensus among many stakeholders with different positions. To solve this problem, we will work to develop a hands-on workshop that will enable in-depth understanding of solutions evaluated both qualitatively and quantitatively through simulation models.
Mechanisms for sharing and reusing knowledge across disciplines, and methods for describing systems that allow people with different expertise to share a common understanding of the target system.
Teamwork methodologies for generating creative and innovative options in the context of decision-making about the system, and for generating creative ideas and problem-solving policies
Discovery of patterns (knowledge) related to problem solving and emergent phenomena from data
複雑な社会技術システムの分析と記述 /
Analysis of Complex Social and Technological Systems
Analysis of Complex Social and Technological Systems
By connecting information technology to industry and society, people's lives have become more convenient than ever. At the same time, the complexities of the various systems and organizations that have been systematized have created many difficult problems to solve. For example, the promotion of decarbonization and the introduction of automation technology that we are working on in our laboratory require social and technological efforts.In our laboratory's approach to such problems, the research theme is to describe the context and behavior of the systems using a qualitative modeling method to deepen understanding and define ambiguous problem awareness as a solvable problem.
Chapter 2 of "Ichinose, Y., Hayashi, M., Nomura, S., Moser, B., & Hiekata, K. (2022). Sustainable Data Centers in Southeast Asia: Offshore, Nearshore, and Onshore Systems for Integrated Data and Power. Sustainable Cities and Society, 81, 103867. https://doi.org/10.1016/J.SCS.2022.103867"
チームワークの可視化:複雑なシステムの挙動の共通理解
Teamwork Environement for Understanding Systems Behaviors
Teamwork Environement for Understanding Systems Behaviors
I. Winder, D. Delaporte, S. Wanaka and K. Hiekata, "Sensing Teamwork During Multi-objective Optimization," 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), New Orleans, LA, USA, 2020, pp. 1-6, doi: 10.1109/WF-IoT48130.2020.9221086.
チームワークの可視化:コミュニケーションのパターン分析
Teamwork Visualization
Teamwork Visualization
Peng, S., Amakasu, T., Kawauchi, H., Horii, H., & Hiekata, K. (2021). Development of Method for Visualizing Behavioral States of Teams. In L. Newnes, S. Lattanzio, B. R. Moser, J. Stjepandić, & N. Wognum (Eds.), Advances in Transdisciplinary Engineering. IOS Press. https://doi.org/10.3233/ATDE210134
認知バイアス排除の取り組み:業務プロセスシミュレータを用いたサイバーセキュリティ対策ワークショップの開発
Approaches to Eliminating Cognitive Bias: Development of a Cybersecurity Workshop Using a Business Process Simulator
Approaches to Eliminating Cognitive Bias: Development of a Cybersecurity Workshop Using a Business Process Simulator
Where complex decision-making is required, such as cyber security incident response, cognitive bias may occur, To solve the problem, we developed a simulator that calculates the time and work required for response. Furthermore, through hands-on workshops using the developed simulator, we will remove the cognitive bias and motivate them to inprove their incident process.
T.kasubuchi, K. Hiekata, Propose and evaluate a workshop method to improve the security incident response process by using process simulation., 2022-SPT-48, Vol.37, pp. 1-8 ,2022
概念実証と社会実装 / Proof-of-Concept and Social Implementation
情報技術が課題解決の主要な要素である場合は、プロトタイプ開発による新しいオペレーションの概念実証も行います。
新しいオペレーションや情報システムの提案と実証
If information technology is a key element of the problem solution, we also provide proof of concept for new operations through prototype development.
Propose and demonstrate new operations and information systems
Kota Tsubouchi, Hiroyuki Yamato, Kazuo Hiekata, Innovative on-demand bus system in Japan, IET Intelligent Transportation System, 4(4), pp. 270-279, 2010.12
オンデマンド交通に関する研究
「日本一わかりやすいMaaS&CASE――ストーリーで理解する」中村 尚樹 (著) プレジデント社 第二章で紹介されています
プロジェクト紹介 / Project web page
デジタルアーカイブの構築と活用
参考:http://doi.org/10.20676/00000352