Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market
| Date | 10 June 2019 |
| Pages | 1089-1103 |
| DOI | https://doi.org/10.1108/IMDS-08-2018-0347 |
| Published date | 10 June 2019 |
| Author | Dongha Kim,JongRoul Woo,Jungwoo Shin,Jongsu Lee,Yongdai Kim |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Can search engine data improve
accuracy of demand forecasting
for new products? Evidence from
automotive market
Dongha Kim
Department of Statistics, Seoul National University,
Seoul, Republic of Korea
JongRoul Woo
Institute for Data, Systems, and Society, Massachusetts Institute of Technology,
Cambridge, Massachusetts, USA
Jungwoo Shin
Department of Industrial and Management Systems Engineering,
Kyung Hee University, Yongin, Republic of Korea
Jongsu Lee
Technology Management, Economics and Policy Program,
Seoul National University, Seoul, Republic of Korea, and
Yongdai Kim
Department of Statistics, Seoul National University, Seoul, Republic of Korea
Abstract
Purpose –The purpose of this paper is to analyze the relationship between new product diffusion and
consumer internet search patterns using big data and to investigate whether such data can be used in
forecasting new product diffusion.
Design/methodology/approach –This research proposes a new product diffusion model based on the
Bass diffusion model by incorporating consumer internet search behavior. Actual data from search engine
queries and new vehicle sales for each vehicle class and region are used to estimate the proposed model.
Statistical analyses are used to interpret the estimated results, and the predictionperformance of the proposed
method is compared with other methods to validate the usefulness of data for internet search engine queries
in forecasting new product diffusion.
Findings –The estimated coeffic ients of the proposed mode l provide a clear interpr etation of the
relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases,
analyzing the interne t search pattern data are s ignificant to explai n new product diffusion a nd that
internet search volume hel ps to predict new product diffusion. There fore, marketing that seeks to increase
internet search volume could positively affe ct vehicle sales. In addi tion, the demand foreca sting
performance of the prop osed diffusion model is superior to those of ot her models for both long-term and
short-term predictio ns.
Research limitations/implications –As search queries have only been available since 2004, comparisons
with data from earlier years are not possible. The proposed model can be extended using other big data from
additional sources.
Originality/value –This research directly demonstrates the relationship between new product diffusion
and consumer internet search pattern and investigates whether internet search queries can be used to forecast
new product diffusion by product type and region. Based on the estimated results, increasing internet search
volume could positively affect vehicle sales across product types and regions. Because the proposed model
had the best prediction power compared with the other considered models for all cases with large margins, it
can be successfully utilized in forecasting demand for new products.
Keywords Bass diffusion model, Automotive market, Diffusion of new products, Internet search pattern,
Search engine data
Paper type Research paper
Industrial Management & Data
Systems
Vol. 119 No. 5, 2019
pp. 1089-1103
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-08-2018-0347
Received 15 August 2018
Revised 13 December 2018
Accepted 18 March 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
1089
Evidence from
automotive
market
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