Using Network Science to Support Design Research: From Counting to Connecting

Parraguez, Pedro; Maier, Anja

doi:10.1007/978-3-319-33781-4_9

Cited by 7 publications

(5 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Tools from network science provides a new perspective on studying design teams, design tasks and design spaces (Adolphe et al, 2020;Leenders et al, 2016;Parraguez & Maier, 2016). To measure the design space explored by engineers during the design sessions, we created a graph to represent the entire design space produced by all the designers through the concepts they mentioned.…”

Section: Measuring Design Space Exploration With Nlp and Networkmentioning

confidence: 99%

Design process of live-action video instructions

Eriksson,

Skagert,

Ekwall

2023

Expanding the Frontiers of Design

View full text Add to dashboard Cite

show abstract

Section: Measuring Design Space Exploration With Nlp and Networkmentioning

confidence: 99%

Design process of live-action video instructions

Eriksson,

Skagert,

Ekwall

2023

Expanding the Frontiers of Design

View full text Add to dashboard Cite

show abstract

“…Efficient and effective communication is essential to the productivity of research and development teams [21] . A powerful tool for analyzing communication is network analysis [22] , which is frequently visualized using network connectivity graphs. These graphs are constructed by each individual (or role) represented by a node, with edge weights corresponding to some measure of interaction (for example mutual activity participation [23] ).…”

Section: Communication Network In Engineering Designmentioning

confidence: 99%

Analysis of Virtual Communication Within Engineering Design Teams and its Impact on Team Effectiveness

Olechowski¹,

Adolphe²,

Zande³

et al. 2021

Preprint

View full text Add to dashboard Cite

Online communication and collaboration tools are changing the way teams design products. The tools also generate a rich data source from which to study trends in communication. This paper focuses on how engineering teams utilize Slack, a popular team messaging software platform. We aim to better understand communication and coordination in product design teams via analysis of team social network dynamics, unique patterns of chat-like messaging (emoji usage), and the evolution of communication topics over time.Our study analyzes the online interactions of 32 teams, sent during a 3-month senior undergraduate product design course. These 400,000+ messages represent the team communications from 4 years of teams, with 17-20 students per team.We find that 1) Slack communications resulted in high density network maps, 2) network analysis of teams reveals that leaders have more central positions in the network, 3) strong teams have lower average centrality among members, equivalent to less public channel membership per person, 4) stronger teams use emojis at a higher rate, and 5) emojis are used most by leaders and highly connected members.These findings represent preliminary foundations for best practices in online messaging, which may lead to more effective collaboration in product design. INTRODUCTIONCommunication, key to the engineering design process, is being disrupted by new technological developments changing the ways by which teams collaborate in the classroom and the workplace. Teams worldwide are adopting online communication software for information sharing, documentation, project management, collaboration, and decision making. Slack, an online message-based communication software, has become a staple tool for student and industry engineers alike, with tens of millions of users [1] . Slack not only facilitates team messaging, but also supports a variety of project management and external integrations [2] . These software platforms unlock data for quantitative analysis of design team communication and collaboration, from which we can identify patterns of virtual communication content, timing, and organization.Previous studies have analyzed email communication of engineering teams [3] , or the use of Slack by software development teams [4,5] and Information Technology enterprises [6] . This paper focuses on student product design teams, building on previous work [7] . We analyze 400,000+ virtual interactions sent by 32 different teams over the span of three months, as they progress through the stages of product design, from ideation to alpha prototype launch.We explore the intricacies of the individual contributions and dynamics within teams through network analysis, emoji frequency analysis, and topic modelling of electronic communications. Each team, having unique communication

show abstract

“…Network science is the study of networks represented as nodes (vertices) of elements and edges (arcs) as the connections between the elements. Parraguez & Maier (2016) provided an overview of the challenges and key decisions when using network science to support design research. They advise that the first decision is to define the overall research purpose (exploratory or explanatory) and the second is to select relevant network features.…”

Section: System Architecture Modelling and Metricsmentioning

confidence: 99%

“…They advise that the first decision is to define the overall research purpose (exploratory or explanatory) and the second is to select relevant network features. In line with the Parraguez & Maier (2016) guidelines, the research study report in this article has an exploratory nature, and the network conceptualisation of complex systems is unweighted (binary) and directed to enable robustness assessment. The following sections discuss network-based metrics for modularity and robustness.…”

Section: System Architecture Modelling and Metricsmentioning

confidence: 99%

A network tool to analyse and improve robustness of system architectures

et al. 2020

View full text Add to dashboard Cite

The architecture of a system is decided at the initial stage of the design. However, the robustness of the system is not usually assessed in detail during the initial stages, and the exploration of alternative system architectures is limited due to the influence of previous designs and opinions. This article presents a novel network generator that enables the analysis of the robustness of alternative system architectures in the initial stages of design. The generator is proposed as a network tool for system architectures dictated by their configuration of source and sink components structured in a way to deliver a particular functionality. Its parameters allow exploration with theoretical patterns to define the main structure and hub structure, vary the number, size, and connectivity of hub components, define source and sink components and directionality at the hub level and adapt a redundancy threshold criterion. The methodology in this article assesses the system architecture patterns through robustness and modularity network based metrics and methods. Two naval distributed engineering system architectures are examined as the basis of reference for the simulated networks. The generator provides the capacity to create alternative complex system architecture options with identifiable patterns and key features, aiding in a broader explorative and analytical, in-depth, time and cost-efficient initial design process.

show abstract

Using Network Science to Support Design Research: From Counting to Connecting

Cited by 7 publications

References 51 publications

Design process of live-action video instructions

Design process of live-action video instructions

Analysis of Virtual Communication Within Engineering Design Teams and its Impact on Team Effectiveness

A network tool to analyse and improve robustness of system architectures

Contact Info

Product

Resources

About