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Research Papers

Understanding Communication and Collaboration in Social Product Development Through Social Network Analysis

[+] Author and Article Information
Dazhong Wu

Department of Industrial and
Manufacturing Engineering,
Pennsylvania State University,
University Park, PA 16802
e-mail: dxw279@psu.edu

David W. Rosen

The G.W. Woodruff School of
Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332
e-mail: david.rosen@me.gatech.edu

Jitesh H. Panchal

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: panchal@purdue.edu

Dirk Schaefer

Department of Mechanical Engineering,
University of Bath,
Bath BA2 7AY, UK
e-mail: d.schaefer@bath.ac.uk

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received March 7, 2014; final manuscript received October 22, 2015; published online December 10, 2015. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 16(1), 011001 (Dec 10, 2015) (10 pages) Paper No: JCISE-14-1066; doi: 10.1115/1.4031890 History: Received March 07, 2014; Revised October 22, 2015

Social media have recently been introduced into the arena of collaborative design as a new means for seamlessly gathering, processing, and sharing product design-related information. As engineering design processes are becoming increasingly distributed and collaborative, it is crucial to understand the communication and collaboration mechanism of engineers participating in such dispersed engineering processes. In particular, mapping initially disconnected design individuals and teams into an explicit social network is challenging. The objective of this paper is to propose a generic framework for investigating communication and collaboration mechanisms in social media-supported engineering design environments. Specifically, we propose an approach for measuring tie strengths in the context of distributed and collaborative design. We transform an implicit design network into an explicit and formal social network based on specific indices of tie strengths. We visualize the process of transforming customer needs to functional requirements, to design parameters, and to process variables using social network analysis (SNA). Specifically, by utilizing a specific index for tie strengths, we can quantitatively measure tie strengths in a design network. Based on the tie strengths, we can map an implicit design network into an explicit social network. Further, using the typical measures (e.g., centrality and cluster coefficient) in SNA, we can analyze the social network at both actor and systems levels and detect design communities with common design interests. We demonstrate the applicability of the framework by means of two examples. The contribution in this paper is a systematic and formal approach that helps gain new insights into communication and collaboration mechanisms in distributed and collaborative design.

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Figures

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Fig. 1

Typical information flow in engineering design processes

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Fig. 3

Geographic locations of participating students

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Fig. 4

Community detection with Clauset–Newman–Moore algorithm [35]: (a) before community detection for example 1 and (b) after community detection for example 1

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Fig. 2

Map a design network into a social network based on Adamic and Adar index scores

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Fig. 5

Community detection with Clauset–Newman–Moore algorithm [35]: (a) before community detection for example 2 and (b) after community detection for example 2

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