Data-Driven Dynamic Network Modeling for Analyzing the Evolution of Product Competitions

Author:

Xie Jian1,Bi Youyi2,Sha Zhenghui3,Wang Mingxian4,Fu Yan5,Contractor Noshir6,Gong Lin1,Chen Wei7

Affiliation:

1. School of Mechanical Engineering, Beijing Institute of Technology, 5 South Zhonguancun Street, Haidian District, Beijing 100081, China

2. University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, China

3. System Integration & Design, Informatics Laboratory, University of Arkansas, 863 West Dickson Street, Fayetteville, AR 72701

4. Global Data Insight & Analytics, Ford Motor Company, Dearborn, MI 48120

5. Global Data Insight & Analytics, Ford Motor Company, Dearborn, MI 48124

6. Science of Networks in Communities, Northwestern University, Evanston, IL 60208-311

7. Integrated Design Automation Laboratory, Northwestern University, 2145 Sheridan Road, Tech A216, Evanston, IL 60208-3109

Abstract

Abstract Understanding the impact of engineering design on product competitions is imperative for product designers to better address customer needs and develop more competitive products. In this paper, we propose a dynamic network-based approach for modeling and analyzing the evolution of product competitions using multi-year buyer survey data. The product co-consideration network, formed based on the likelihood of two products being co-considered from survey data, is treated as a proxy of products’ competition relations in a market. The separate temporal exponential random graph model (STERGM) is employed as the dynamic network modeling technique to model the evolution of network as two separate processes: link formation and link dissolution. We use China’s automotive market as a case study to illustrate the implementation of the proposed approach and the benefits of dynamic network models compared to the static network modeling approach based on an exponential random graph model (ERGM). The results show that since STERGM takes preexisting competition relations into account, it provides a pathway to gain insights into why a product may maintain or lose its competitiveness over time. These driving factors include both product attributes (e.g., fuel consumption) as well as current market structures (e.g., the centralization effect). With the proposed dynamic network-based approach, the insights gained from this paper can help designers better interpret the temporal changes of product competition relations to support product design decisions.

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

Reference53 articles.

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