TY - GEN
T1 - INVESTIGATING THE EFFECT OF A BRAND FACTOR IN PRODUCT DESIGN BASED ON A DATA-DRIVEN APPROACH USING ONLINE REVIEWS
AU - Park, Seyoung
AU - Kim, Harrison
N1 - Publisher Copyright:
© 2023 American Society of Mechanical Engineers (ASME). All rights reserved.
PY - 2023
Y1 - 2023
N2 - Recently, online user-generated data has emerged as a valuable source for consumer product research. However, most studies have neglected the brand effect, although it is a significant factor in conventional market research. This paper demonstrates the importance of brands in data-driven design using online reviews. Specifically, the study utilizes game theory and suggests a game setting representing market competition. Elements of the game are determined based on online data analysis. The proposed approach consists of three stages. The first stage divides online customers into different segments and analyzes them to extract the feature importance of each brand in each segment. The importance is based on the term frequency of each feature, and it becomes the customer's partial utility for each feature. The second stage defines the specification of product candidates and calculates their costs. This study refers to real market datasets (Bill of Materials) available online. At this point, the game is all set. The final stage finds the Nash Equilibrium of the designed game and compares the optimal strategy for a product portfolio with and without brand consideration. The suggested approach was tested on smartphone reviews from Amazon. The result shows that the lack of brand consideration leads a company to choose a non-optimal product strategy, illustrating the significance of the brand factor.
AB - Recently, online user-generated data has emerged as a valuable source for consumer product research. However, most studies have neglected the brand effect, although it is a significant factor in conventional market research. This paper demonstrates the importance of brands in data-driven design using online reviews. Specifically, the study utilizes game theory and suggests a game setting representing market competition. Elements of the game are determined based on online data analysis. The proposed approach consists of three stages. The first stage divides online customers into different segments and analyzes them to extract the feature importance of each brand in each segment. The importance is based on the term frequency of each feature, and it becomes the customer's partial utility for each feature. The second stage defines the specification of product candidates and calculates their costs. This study refers to real market datasets (Bill of Materials) available online. At this point, the game is all set. The final stage finds the Nash Equilibrium of the designed game and compares the optimal strategy for a product portfolio with and without brand consideration. The suggested approach was tested on smartphone reviews from Amazon. The result shows that the lack of brand consideration leads a company to choose a non-optimal product strategy, illustrating the significance of the brand factor.
UR - http://www.scopus.com/inward/record.url?scp=85178600038&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85178600038&partnerID=8YFLogxK
U2 - 10.1115/DETC2023-114966
DO - 10.1115/DETC2023-114966
M3 - Conference contribution
AN - SCOPUS:85178600038
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 49th Design Automation Conference (DAC)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2023
Y2 - 20 August 2023 through 23 August 2023
ER -