Co-query volume as a proxy for
School of Business and Technology Management, College of Business,
Korea Advanced Institute of Science and Technology, Daejeon, South Korea
Purpose –The purpose of this paper is to utilize co-query volumes of brands as relatedness measurement to
understand the market structure and demonstrate the usefulness of brand relatedness via a real-world case.
Design/methodology/approach –Using brandrelatedness measurement obtainedusing data from Google
Trends as datainputs into a multidimensional scalingmethod, the market structureof the automobile industry
is presentedto reveal its competitivelandscape. The relatednesswith brands involved in product-harm crisis is
further incorporated in empirical modelsto estimate the influence of crisis on futuresales performance of each
brand. A representative incidentof a product-harm crisis in the automobile industry,which is the 2009 Toyota
recall, is investigated. A panel regression analysis is conducted using US and world sales data.
Findings –The use of co-query as brand relatedness measurement is validated. Results indicate that brand
relatedness with a brand under crisis is positively associated with future sales for both US and global market.
Potential presence of negative spillovers from an affected brand to innocent brands sharing common traits
such as same country of origin is shown.
Originality/value –The brandrelatedness measuredfrom co-queryvolumes is consideredas a broad concept,
which encompasses all associative relationships between two brands perceived by the consumers. Thisstudy
contributesto the literatureby clarifying the conceptof brand relatednessand proposing a measurewith readily
accessibledata. Compared to previous studiesrelying on a vast amount of onlinedata, the proposed measure is
proven to be efficient and enhance predictions about the future performance of brands ina turbulent market.
Keywords Automobile industry, Google trends, 2009 Toyota recall, Brand relatedness, Co-query,
Search query volume
Paper type Research paper
Advanced information and communication technology (ICT) devices combined with the
increased speed of the internet have enabled people to search instantaneously for
information. Consequently, the number of search queries is constantly increasing.
The query volume of Google, the leading search engine, which dominates over 80 percent of
the market (Statista, 2017), exceeded two trillion annually (Sullivan, 2016). Accordingly,
researchers and practitioners have attempted to exploit this abundant source of data in
monitoring or predicting behaviors of populations. The idea behind using search queries to
identify contemporary interests is that people frequently search for information on the
internet when they are curious or concerned about something. Indeed, findings from studies
have demonstrated that information retrieved from web search queries supplement or
outperform existing indicators in various sectors including health care (Nuit et al., 2014),
politics (Granka, 2013), and economics (Guzman, 2011).
Given that research has documented the usefulness of search-query of keywords as
proxies for user interests or preferences, we extend the use of search queries by considering
search query volumes of multiple keywords, co-queries, as an indicator of relatedness
among keywords. In fact, using co-occurrences of words is not a novel phenomenon.
Previous research has used other sources of web data such as user-generated content
(Netzer et al., 2012) or webpage results (Lee et al., 2010) to measure the association between
Industrial Management & Data
Vol. 118 No. 4, 2018
© Emerald PublishingLimited
Received 17 April 2017
Revised 25 September 2017
Accepted 28 November 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
This work was supported by Business for University Entrepreneurship Center funded by Korea Small
and Medium Business Administration (N04140205-14); and National Research Foundation of Korea
funded by the Korean Government (NRF-2015R1A2A2A04007359).