{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T18:58:10Z","timestamp":1774551490700,"version":"3.50.1"},"reference-count":48,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2019,6,10]],"date-time":"2019-06-10T00:00:00Z","timestamp":1560124800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2019,6,10]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>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 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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The 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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-08-2018-0347","type":"journal-article","created":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T07:21:32Z","timestamp":1559287292000},"page":"1089-1103","source":"Crossref","is-referenced-by-count":16,"title":["Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market"],"prefix":"10.1108","volume":"119","author":[{"given":"Dongha","family":"Kim","sequence":"first","affiliation":[]},{"given":"JongRoul","family":"Woo","sequence":"additional","affiliation":[]},{"given":"Jungwoo","family":"Shin","sequence":"additional","affiliation":[]},{"given":"Jongsu","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Yongdai","family":"Kim","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020092221544759400_ref001","doi-asserted-by":"crossref","unstructured":"Akaike, H. (1998), \u201cInformation theory and an extension of the maximum likelihood principle\u201d, in Parzen, E., Tanabe, K. and Kitagawa, G. (Eds), Selected Papers of Hirotugu Akaike. Springer Series in Statistics (Perspectives in Statistics), Springer, New York, NY.","DOI":"10.1007\/978-1-4612-1694-0_15"},{"issue":"2","key":"key2020092221544759400_ref002","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1108\/13555851211218057","article-title":"Understanding the role of prior product knowledge to information search: an application of process theory to the Indian market","volume":"24","year":"2012","journal-title":"Asia Pacific Journal of Marketing and Logistics"},{"key":"key2020092221544759400_ref003","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/j.tourman.2014.07.014","article-title":"Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach","volume":"46","year":"2015","journal-title":"Tourism Management"},{"issue":"5","key":"key2020092221544759400_ref004","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1287\/mnsc.15.5.215","article-title":"A new product growth for model consumer durables","volume":"15","year":"1969","journal-title":"Management Science"},{"issue":"3","key":"key2020092221544759400_ref005","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1002\/dir.1014","article-title":"Internet forums as influential sources of consumer information","volume":"15","year":"2001","journal-title":"Journal of Interactive Marketing"},{"issue":"4","key":"key2020092221544759400_ref006","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1002\/for.1252","article-title":"Nowcasting with Google trends in an emerging market","volume":"32","year":"2013","journal-title":"Journal of Forecasting"},{"issue":"91-111","key":"key2020092221544759400_ref007","first-page":"1","article-title":"Mortgage default risk: new evidence from internet search queries","volume":"96","year":"2016","journal-title":"Journal of Urban Economics"},{"issue":"7","key":"key2020092221544759400_ref008","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1016\/j.techfore.2012.04.002","article-title":"Investigation of the effect of secondary market on the diffusion of innovation","volume":"79","year":"2012","journal-title":"Technological Forecasting and Social Change"},{"issue":"S1","key":"key2020092221544759400_ref009","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1111\/j.1475-4932.2012.00809.x","article-title":"Predicting the present with Google trends","volume":"88","year":"2012","journal-title":"Economic Record"},{"issue":"2","key":"key2020092221544759400_ref010","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00994928","article-title":"Estimation of innovation diffusion models with application to a consumer durable","volume":"6","year":"1995","journal-title":"Marketing Letters"},{"issue":"6","key":"key2020092221544759400_ref011","doi-asserted-by":"crossref","first-page":"2955","DOI":"10.1257\/aer.102.6.2955","article-title":"Testing models of consumer search using data on web browsing and purchasing behavior","volume":"102","year":"2012","journal-title":"American Economic Review"},{"key":"key2020092221544759400_ref012","volume-title":"How we Think","year":"1997"},{"key":"key2020092221544759400_ref013","volume-title":"Consumer Behavior, 8th","year":"1995"},{"key":"key2020092221544759400_ref014","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.ijpe.2015.09.010","article-title":"Forecasting German car sales using Google data and multivariate models","volume":"170","year":"2015","journal-title":"International Journal of Production Economics"},{"issue":"7232","key":"key2020092221544759400_ref015","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1038\/nature07634","article-title":"Detecting influenza epidemics using search engine query data","volume":"457","year":"2009","journal-title":"Nature"},{"issue":"41","key":"key2020092221544759400_ref016","doi-asserted-by":"crossref","first-page":"17486","DOI":"10.1073\/pnas.1005962107","article-title":"Predicting consumer behavior with web search","volume":"107","year":"2010","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"2\/3","key":"key2020092221544759400_ref017","first-page":"411","article-title":"Using Google searches on the internet to monitor suicidal behavior","volume":"148","year":"2013","journal-title":"Journal of Affective Disorders"},{"issue":"3","key":"key2020092221544759400_ref018","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1287\/mksc.13.3.224","article-title":"Analysis of new product diffusion using a four-segment trial-repeat model","volume":"13","year":"1994","journal-title":"Marketing Science"},{"key":"key2020092221544759400_ref019","volume-title":"Time Series Analysis","year":"1994"},{"issue":"11","key":"key2020092221544759400_ref020","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1080\/13504851.2011.613744","article-title":"Searching for the picture: forecasting UK cinema admissions using Google Trends data","volume":"19","year":"2012","journal-title":"Applied Economics Letters"},{"issue":"3","key":"key2020092221544759400_ref021","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1287\/mksc.1090.0525","article-title":"Tunnel vision: local behavioral influences on consumer decisions in product search","volume":"29","year":"2010","journal-title":"Marketing Science"},{"key":"key2020092221544759400_ref022","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.techfore.2013.10.021","article-title":"The possibility of using search traffic information to explore consumer product attitudes and forecast consumer preference","volume":"86","year":"2014","journal-title":"Technological Forecasting and Social Change"},{"issue":"6","key":"key2020092221544759400_ref023","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1287\/mksc.1100.0574","article-title":"Online demand under limited consumer search","volume":"29","year":"2010","journal-title":"Marketing Science"},{"issue":"3","key":"key2020092221544759400_ref024","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1002\/dir.10058","article-title":"Consumer search for information in the digital age: an empirical study of prepurchase search for automobiles","volume":"17","year":"2003","journal-title":"Journal of Interactive Marketing"},{"issue":"3","key":"key2020092221544759400_ref025","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.intmar.2012.02.001","article-title":"The impact of online and offline information sources on automobile choice behavior","volume":"26","year":"2012","journal-title":"Journal of Interactive Marketing"},{"issue":"4","key":"key2020092221544759400_ref026","first-page":"1","article-title":"Forecasting new product diffusion using both patent citation and web search traffic","volume":"13","year":"2018","journal-title":"Plos One"},{"issue":"4","key":"key2020092221544759400_ref027","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/s11002-006-7942-9","article-title":"When giving some away makes sense to jump-start the diffusion process","volume":"17","year":"2006","journal-title":"Marketing Letters"},{"issue":"2","key":"key2020092221544759400_ref028","first-page":"134","article-title":"Using internet search data as economic indicators","volume":"51","year":"2011","journal-title":"Bank of England Quarterly Bulletin"},{"issue":"3","key":"key2020092221544759400_ref029","first-page":"G79","article-title":"Diffusion of new products: empirical generalizations and managerial uses","volume":"14","year":"1995","journal-title":"Marketing Science"},{"key":"key2020092221544759400_ref030","volume-title":"Marketing of High-Technology Products and Innovations","year":"2010"},{"key":"key2020092221544759400_ref031","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.jretconser.2016.06.002","article-title":"Assisting consumers in detecting fake reviews: the role of identify information disclosure and consensus","volume":"32","year":"2016","journal-title":"Journal of Retailing and Consumer Services"},{"key":"key2020092221544759400_ref032","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.tmp.2017.07.001","article-title":"Quantifying potential tourist behavior in choice of destination using Google Trends","volume":"24","year":"2017","journal-title":"Tourism Management Perspectives"},{"issue":"2","key":"key2020092221544759400_ref033","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1002\/mar.10062","article-title":"Consumer information search behavior and the Internet","volume":"20","year":"2003","journal-title":"Psychology & Marketing"},{"issue":"2","key":"key2020092221544759400_ref034","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1509\/jmkr.40.2.193.19221","article-title":"The impact of the Internet on information search for automobiles","volume":"40","year":"2003","journal-title":"Journal of Marketing Research"},{"key":"key2020092221544759400_ref035","volume-title":"Diffusion of Innovation","year":"2003","edition":"5th ed."},{"issue":"2","key":"key2020092221544759400_ref036","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","article-title":"Estimating the dimension of a model","volume":"6","year":"1978","journal-title":"Annals of Statistics"},{"key":"key2020092221544759400_ref037","volume-title":"Click: What Millions of People are Doing Online and Why it Matters","year":"2008"},{"issue":"1","key":"key2020092221544759400_ref038","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","year":"1996","journal-title":"Journal of the Royal Statistical Society. Series B (Methodological)"},{"issue":"6","key":"key2020092221544759400_ref039","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1002\/for.1213","article-title":"Forecasting private consumption: survey-based indicators vs. Google trends","volume":"30","year":"2011","journal-title":"Journal of Forecasting"},{"issue":"8","key":"key2020092221544759400_ref040","doi-asserted-by":"crossref","first-page":"1510","DOI":"10.1108\/IMDS-02-2015-0036","article-title":"Media channels and consumer purchasing decisions","volume":"115","year":"2015","journal-title":"Industrial Management & Data Systems"},{"key":"key2020092221544759400_ref041","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.techfore.2014.09.001","article-title":"The effect of new media on consumer media usage: an empirical study in South Korea","volume":"89","year":"2014","journal-title":"Technological Forecasting and Social Change"},{"issue":"1","key":"key2020092221544759400_ref042","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1108\/IMDS-09-2016-0395","article-title":"Understanding consumers\u2019 continuance intention to contribute online reviews","volume":"118","year":"2018","journal-title":"Industrial Management & Data Systems"},{"key":"key2020092221544759400_ref043","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1016\/j.tourman.2014.07.019","article-title":"Forecasting Chinese tourist volume with search engine data","volume":"46","year":"2015","journal-title":"Tourism Management"},{"key":"key2020092221544759400_ref044","volume-title":"The Mathematical Theory of Epidemics","year":"1957"},{"issue":"4","key":"key2020092221544759400_ref045","doi-asserted-by":"crossref","first-page":"501","DOI":"10.2307\/1905380","article-title":"Hybrid corn: an exploration in the economics of technological change","volume":"25","year":"1957","journal-title":"Econometrica, Journal of the Econometric Society"},{"issue":"4","key":"key2020092221544759400_ref046","doi-asserted-by":"crossref","first-page":"741","DOI":"10.2307\/1911817","article-title":"Technical change and the rate of imitation","volume":"29","year":"1961","journal-title":"Econometrica: Journal of the Econometric Society"},{"issue":"2","key":"key2020092221544759400_ref047","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1177\/002224299105500206","article-title":"Cross-national analysis of diffusion of consumer durable goods in Pacific Rim countries","volume":"55","year":"1991","journal-title":"The Journal of Marketing"},{"key":"key2020092221544759400_ref048","unstructured":"Turner, V., Gantz, J.F., Reinsel, D. and Minton, S. (2014), \u201cThe digital universe of opportunities: rich data and the increasing value of the internet of things\u201d, available at: www.emc.com\/leadership\/digital-universe\/2014iview\/index.htm (accessed July 9, 2015)."}],"container-title":["Industrial Management &amp; Data Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IMDS-08-2018-0347\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IMDS-08-2018-0347\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:53:04Z","timestamp":1753393984000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/imds\/article\/119\/5\/1089-1103\/174522"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,10]]},"references-count":48,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2019,6,10]]}},"alternative-id":["10.1108\/IMDS-08-2018-0347"],"URL":"https:\/\/doi.org\/10.1108\/imds-08-2018-0347","relation":{},"ISSN":["0263-5577"],"issn-type":[{"value":"0263-5577","type":"print"}],"subject":[],"published":{"date-parts":[[2019,6,10]]}}}