InnoGPS for Data-Driven Exploration of Design Opportunities and Directions: The Case of Google Driverless Car Project

Journal of Mechanical Design, 139(11), 111416 [DOI: 10.1115/1.4037680]

50 Pages Posted: 11 Jan 2018

See all articles by Jianxi Luo

Jianxi Luo

City University of Hong Kong (CityU)

Bowen Yan

Singapore University of Technology and Design (SUTD)

Kristin Wood

Singapore University of Technology and Design (SUTD)

Date Written: October 2, 2017

Abstract

Engineers and technology firms must continually explore new design opportunities and directions to sustain or thrive in technology competition. However, the related decisions are normally based on personal gut feeling or experiences. Although the analysis of user preferences and market trends may shed light on some design opportunities from a demand perspective, design opportunities are always conditioned or enabled by the technological capabilities of designers. Herein, we present a data-driven methodology for designers to analyze and identify what technologies they can design for the next, based on the principle—what a designer can currently design condition or enable what it can design next. The methodology is centered on an empirically built network map of all known technologies, whose distances are quantified using more than 5 million patent records, and various network analytics to position a designer according to the technologies that they can design, navigate technologies in the neighborhood, and identify feasible paths to far fields for novel opportunities. Furthermore, we have integrated the technology space map, and various map-based functions for designer positioning, neighborhood search, path finding, and knowledge discovery and learning, into a data-driven visual analytic system named InnoGPS. InnoGPS is a global position system (GPS) for finding innovation positions and directions in the technology space, and conceived by analogy from the GPS that we use for positioning, neighborhood search, and direction finding in the physical space.

Keywords: InnoGPS, Innovation, Data-Driven Design, Google, Driverless Car

Suggested Citation

Luo, Jianxi and Yan, Bowen and Wood, Kristin, InnoGPS for Data-Driven Exploration of Design Opportunities and Directions: The Case of Google Driverless Car Project (October 2, 2017). Journal of Mechanical Design, 139(11), 111416 [DOI: 10.1115/1.4037680], Available at SSRN: https://ssrn.com/abstract=3098411

Jianxi Luo (Contact Author)

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

HOME PAGE: http://https://www.cityu.edu.hk/stfprofile/jianxiluo.htm

Bowen Yan

Singapore University of Technology and Design (SUTD) ( email )

20 Dover Drive
Singapore, 138682
Singapore

Kristin Wood

Singapore University of Technology and Design (SUTD) ( email )

20 Dover Drive
Singapore, 138682
Singapore

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