Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market

Can search engine data improve accuracy of demand forecasting for new products? Evidence from... 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/approachThis 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 prediction performance 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.FindingsThe estimated coefficients of the proposed model provide a clear interpretation of the relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases, analyzing the internet search pattern data are significant to explain new product diffusion and that internet search volume helps to predict new product diffusion. Therefore, marketing that seeks to increase internet search volume could positively affect vehicle sales. In addition, the demand forecasting performance of the proposed diffusion model is superior to those of other models for both long-term and short-term predictions.Research limitations/implicationsAs 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/valueThis 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Management & Data Systems Emerald Publishing

Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market

Download PDF
15 pages

Loading next page...
 
/lp/emerald-publishing/can-search-engine-data-improve-accuracy-of-demand-forecasting-for-new-eVyScBA46J
Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0263-5577
DOI
10.1108/imds-08-2018-0347
Publisher site
See Article on Publisher Site

Abstract

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/approachThis 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 prediction performance 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.FindingsThe estimated coefficients of the proposed model provide a clear interpretation of the relationship between new product diffusion and internet search volume. In 83.62 percent of 218 cases, analyzing the internet search pattern data are significant to explain new product diffusion and that internet search volume helps to predict new product diffusion. Therefore, marketing that seeks to increase internet search volume could positively affect vehicle sales. In addition, the demand forecasting performance of the proposed diffusion model is superior to those of other models for both long-term and short-term predictions.Research limitations/implicationsAs 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/valueThis 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.

Journal

Industrial Management & Data Systems – Emerald Publishing

Published: Jun 13, 2019

Keywords: Bass diffusion model; Automotive market; Diffusion of new products; Internet search pattern; Search engine data

References

  • Understanding the role of prior product knowledge to information search: an application of process theory to the Indian market
    Awasthy, D.; Banerjee, A.; Banerjee, B.
  • Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach
    Bangwayo-Skeete, P.F.; Skeete, R.W.
  • A new product growth for model consumer durables
    Bass, F.M.
  • Internet forums as influential sources of consumer information
    Bickart, B.; Schindler, R.M.
  • Nowcasting with Google trends in an emerging market
    Carrière-Swallow, Y.; Labbé, F.
  • Mortgage default risk: new evidence from internet search queries
    Chauvet, M.; Gabriel, S.; Lutz, C.
  • Investigation of the effect of secondary market on the diffusion of innovation
    Cho, Y.; Koo, Y.
  • Predicting the present with Google trends
    Choi, H.; Varian, H.
  • Estimation of innovation diffusion models with application to a consumer durable
    Dalal, S.R.; Weerahandi, S.
  • Testing models of consumer search using data on web browsing and purchasing behavior
    De los Santos, B.; Hortaçsu, A.; Wildenbeest, M.R.
  • Forecasting German car sales using Google data and multivariate models
    Fantazzini, D.; Toktamysova, Z.
  • Detecting influenza epidemics using search engine query data
    Ginsberg, J.; Mohebbi, M.H.; Patel, R.S.; Brammer, L.; Smolinski, M.S.; Brilliant, L.
  • Predicting consumer behavior with web search
    Goel, S.; Hofman, J.M.; Lahaie, S.; Pennock, D.M.; Watts, D.J.
  • Using Google searches on the internet to monitor suicidal behavior
    Gunn, J.F.; Lester, D.
  • Analysis of new product diffusion using a four-segment trial-repeat model
    Hahn, M.; Park, S.; Krishnamurthi, L.; Zoltners, A.A.
  • Searching for the picture: forecasting UK cinema admissions using Google Trends data
    Hand, C.; Judge, G.
  • Tunnel vision: local behavioral influences on consumer decisions in product search
    Häubl, G.; Dellaert, B.G.; Donkers, B.
  • The possibility of using search traffic information to explore consumer product attitudes and forecast consumer preference
    Jun, S.P.; Park, D.H.; Yeom, J.
  • Online demand under limited consumer search
    Kim, J.B.; Albuquerque, P.; Bronnenberg, B.J.
  • Consumer search for information in the digital age: an empirical study of prepurchase search for automobiles
    Klein, L.R.; Ford, G.T.
  • The impact of online and offline information sources on automobile choice behavior
    Kulkarni, G.; Ratchford, B.T.; Kannan, P.K.
  • Forecasting new product diffusion using both patent citation and web search traffic
    Lee, W.; Choi, H.; Sohn, S.
  • When giving some away makes sense to jump-start the diffusion process
    Lehmann, D.R.; Esteban-Bravo, M.
  • Using internet search data as economic indicators
    McLaren, N.; Shanbhogue, R.
  • Diffusion of new products: empirical generalizations and managerial uses
    Mahajan, V.; Muller, E.; Bass, F.M.
  • Assisting consumers in detecting fake reviews: the role of identify information disclosure and consensus
    Munzel, A.
  • Quantifying potential tourist behavior in choice of destination using Google Trends
    Padhi, S.S.; Pati, R.K.
  • Consumer information search behavior and the Internet
    Peterson, R.A.; Merino, M.C.
  • The impact of the Internet on information search for automobiles
    Ratchford, B.T.; Lee, M.S.; Talukdar, D.
  • Estimating the dimension of a model
    Schwarz, G.E.
  • Regression shrinkage and selection via the lasso
    Tibshirani, R.
  • Forecasting private consumption: survey-based indicators vs. Google trends
    Vosen, S.; Schmidt, T.
  • Media channels and consumer purchasing decisions
    Woo, J.; Ahn, J.; Lee, J.; Koo, Y.
  • The effect of new media on consumer media usage: an empirical study in South Korea
    Woo, J.; Choi, J.Y.; Shin, J.; Lee, J.
  • Understanding consumers’ continuance intention to contribute online reviews
    Xiang, L.; Zeheng, X.; Zhang, K.Z.K.; Lee, M.K.O.
  • Forecasting Chinese tourist volume with search engine data
    Yang, X.; Pan, B.; Evans, J.A.; Lv, B.
  • Hybrid corn: an exploration in the economics of technological change
    Griliches, Z.
  • Technical change and the rate of imitation
    Mansfield, E.
  • Cross-national analysis of diffusion of consumer durable goods in Pacific Rim countries
    Takada, H.; Jain, D.
  • The digital universe of opportunities: rich data and the increasing value of the internet of things
    Turner, V.; Gantz, J.F.; Reinsel, D.; Minton, S.