Diversity, Network Structure, and the Effectiveness of Collective Design and Innovation

多样性、网络结构以及集体设计和创新的有效性

基本信息

批准号：
1734147
负责人：
Hiroki Sayama
金额：
$ 44.1万
依托单位：
SUNY at Binghamton
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-15 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734147&HistoricalAwards=false
关键词：
Diversity Network Structure Effectiveness Collective

项目摘要

This project will investigate how the diverse knowledge, expertise and behaviors of people and their social networks can make large-scale collaborative design processes more effective and innovative. This has become a very important issue in modern society where developing successful solutions for complex problems requires collaboration among many individuals with diverse knowledge, expertise and behaviors, and where the interactions of those individuals are often complex and dynamic. The project will use multiple research methods to address this issue, combining computer simulations for idea and hypothesis generation and online experiments with human participants for idea and hypothesis testing. The project will expand knowledge about the linkage between individuals' interactions in various organizational configurations and their performance in innovation, which will be applicable to product, service, concept, policy, and/or aesthetic design tasks in a wide variety of domains.As the complexity of products and services has skyrocketed over the last several decades, collective design and innovation processes have become a necessity for the development of successful solutions for real-world problems. Such large-scale design processes typically involve individuals with diverse knowledge, expertise and behaviors, and the organizational structures under which the collective design takes place are often complex and dynamic with temporally changing non-trivial network properties. This project aims to investigate, both theoretically and experimentally, how the diversity of knowledge, expertise, and behaviors of individual members and the topological properties of organizational network structures will affect the effectiveness of design and innovation processes at collective levels. This will be accomplished through (a) theoretical agent-based network modeling and simulation, and (b) model evaluation through online laboratory experiments involving student participants with diverse majors. Modeling and simulation will investigate potential interactions between task-related diversity and large-scale organizational network structures. The predictions produced by the simulations will be evaluated through online laboratory experiments, in which participants will collaborate on several open-ended collective design tasks through a computer-mediated collaboration platform. In these experiments, the participants? task-related diversity will be measured and its distribution in the organizational network will be manipulated. The topologies of the network will also be monitored and manipulated dynamically. The successful outcome of the project will be a new "guiding principle" for configuring and manipulating task-related diversity and organizational network structures to promote effective collective design and innovation. This will bear multidisciplinary impacts on organizational science, management science, systems science, systems engineering, operations research, and network science.

该项目将研究人们及其社交网络的多样化知识、专业知识和行为如何使大规模协作设计过程更加有效和创新。这已成为现代社会中一个非常重要的问题，在现代社会中，为复杂问题开发成功的解决方案需要许多具有不同知识、专业知识和行为的个人之间的协作，并且这些个人的互动往往是复杂和动态的。该项目将使用多种研究方法来解决这个问题，结合计算机模拟来生成想法和假设，以及与人类参与者进行在线实验来测试想法和假设。该项目将扩展有关个人在各种组织配置中的互动与其创新绩效之间联系的知识，这将适用于各个领域的产品、服务、概念、政策和/或美学设计任务。过去几十年来，产品和服务的复杂性急剧上升，集体设计和创新流程已成为针对现实问题开发成功解决方案的必要条件。这种大规模的设计过程通常涉及具有不同知识、专业知识和行为的个人，并且集体设计进行的组织结构通常是复杂且动态的，具有随时间变化的重要网络属性。该项目旨在从理论上和实验上研究个体成员的知识、专业知识和行为的多样性以及组织网络结构的拓扑特性将如何影响集体层面的设计和创新过程的有效性。这将通过（a）基于理论代理的网络建模和模拟，以及（b）通过涉及不同专业的学生参与者的在线实验室实验进行模型评估来完成。建模和模拟将研究任务相关多样性和大规模组织网络结构之间的潜在相互作用。模拟产生的预测将通过在线实验室实验进行评估，参与者将通过计算机介导的协作平台就多项开放式集体设计任务进行协作。在这些实验中，参与者？与任务相关的多样性将被衡量，其在组织网络中的分布将被操纵。网络的拓扑结构也将被动态监控和操作。该项目的成功成果将成为配置和操纵与任务相关的多样性和组织网络结构的新“指导原则”，以促进有效的集体设计和创新。这将对组织科学、管理科学、系统科学、系统工程、运筹学和网络科学产生多学科影响。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Mutual-Information-based Feature Selection for Facial Emotion Recognition on Light-Weight Devices

轻型设备上基于互信息的特征选择面部情绪识别

DOI：
10.1109/ssci44817.2019.9003050
发表时间：
2019-12
期刊：
2019 IEEE Symposium Series on Computational Intelligence (SSCI
影响因子：
0
作者：
Dong, Yingjun;Sayama, Hiroki
通讯作者：
Sayama, Hiroki

Detecting Dynamic States of Temporal Networks Using Connection Series Tensors

使用连接级数张量检测时态网络的动态状态

DOI：
10.1155/2020/9649310
发表时间：
2020-07-24
期刊：
Complex.
影响因子：
0
作者：
Shun Cao;Hiroki Sayama
通讯作者：
Hiroki Sayama

Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

集体决策中的多样性和社交网络结构：基于代理的模拟的进化视角

DOI：
10.1155/2019/7591072
发表时间：
2013-11-14
期刊：
Complex.
影响因子：
0
作者：
Shelley D. Dionne;Hiroki Sayama;F. Yammarino
通讯作者：
F. Yammarino

Capturing the Production of Innovative Ideas: An Online Social Network Experiment and “Idea Geography” Visualization

捕捉创新想法的产生：在线社交网络实验和“想法地理”可视化

DOI：
10.1007/978-3-030-77517-9_20
发表时间：
2021-10
期刊：
Proceedings of the 2019 International Conference of The Computational Social Science Society of the Americas
影响因子：
0
作者：
Cao, Yiding;Dong, Yingjun;Kim, Minjun;MacLaren, Neil G.;Kulkarni, Ankita;Dionne, Shelley D.;Yammarino, Francis J.;Sayama, Hiroki
通讯作者：
Sayama, Hiroki