Noname manuscript No. (will be inserted by the editor) Evaluating the Use of Internet Search Volumes for Time Series Modeling of Sales in the Video Game Industry Jukka Ruohonen · Sami Hyrynsalmi the date of receipt and acceptance should be inserted later Abstract Internet search volumes have been success- JEL classification L8 Industry Studies: Services · fully adopted for time series analysis of different phe- L82 Entertainment · Media nomena. This empirical paper evaluates the feasibility of search volumes in modeling of weekly video game sales. Building on the theoretical concepts of product 1 Introduction life cycle, diffusion, and electronic word-of-mouth ad- vertisement, the empirical analysis concentrates on the In 2008 the market leader in Internet search, Google, hypothesized Granger causality between sales and search Inc., launched a web service that provided estimates volumes. By using a bivariate vector autoregression model for predicting flu trends around the world. Although with a dataset of nearly a hundred video games, only the service was later discontinued, it was strongly mo- a few games exhibit such causality to either direction. tivated by the promising time series results that were When correlations are present, these rather occur in- obtained for predicting influenza and other periodic epi- stantaneously; the current weekly amount of sales tends demics of infectious diseases (Ginsberg et al 2009; Pol- to mirror the current weekly amount of searches. Ac- green et al 2008). While the evaluation work has con- cording to the results, search volumes contribute only a tinued actively in biology, medicine, and health care limited additional statistical power for forecasting, how- (Gluskin et al 2014; Proulx et al 2013; Zhang et al 2015; ever. Besides this statistical limitation, the presented Zhou et al 2013), search engine time series have been evaluation reveals a number of other limitations for use increasingly adopted also for many other predictive pur- in practical marketing and advertisement foresight. In- poses, covering such different fields as economics (Dimpfl ternet search volumes continue to provide a valuable and Jank 2015; Vosen and Schmidt 2011), marketing empirical instrument, but the value should not be ex- (Du et al 2015; Rangaswamy et al 2009), ecology (Wilde aggerated for time series modeling of video game sales. and Pope 2013), political science (Reilly et al 2012), and, rather tellingly, research of scholarship and the Keywords technology diffusion · foresight · prece- popularization of science (Segev and Baram-Tsabari dence · Google trends · word-of-mouth · EWOM 2010; Vaughan and Romero-Fr´ıas2014). Although there is some prior work for modeling product sales with re- lation to Internet search data (Hu et al 2014), thus far, Jukka Ruohonen time series applications have been limited in empirical Department of Information Technology, University of Turku, research questions related to the video game industry. FI-20014 Turun yliopisto, Finland This empirical paper sets to the fill the gap. Sami Hyrynsalmi The larger background is far from being novel, of Pori Department, Tampere University of Technology, course. The so-called word-of-mouth (WOM) advertise- P.O. Box 300, Pori, Finland ment was actively researched already in the 1960s for E-mail: juanruo@utu.fi understanding the dynamics related to pioneers, early E-mail: sthyry@utu.fi adopters, latecomers, and non-adopters (Arndt 1967). In fact, in all likelihood, purchasing decisions have been 2 Jukka Ruohonen, Sami Hyrynsalmi influenced by communication and social dynamics even plication domains of Internet search volume modeling. for centuries. The historical emergence of the Inter- The addition is important in its own right. In contrast net brought a new letter E to the WOM abbrevia- to the globally occurring but seasonal influenza trends, tion, nevertheless. Online product reviews, blogs, dis- many variables in the video game industry are directly cussion boards, social media, and related characteristics controllable by the associated companies, which opens turned the scholarly attention towards specific forms of the door for theoretically more intriguing time series electronic word-of-mouth (EWOM) advertisement. Sec- modeling related to search volumes. onded by the fact that search engines continue to dom- inate the Internet-wide dissemination of information to consumers, this empirical paper approaches mass- 2 Background scale EWOM effects by evaluating whether Internet search volumes can help at predicting global video game The theoretical background can be motivated by rely- sales volumes. The theoretical background comes from ing on the so-called diffusion tradition, which has been a the classical product life cycle literature and the sta- prominent interdisciplinary scholarly branch for study- tistically oriented diffusion tradition (Burmester et al ing the evolution and propagation of different techno- 2015; Cox 1967; Dellarocas et al 2009; Chintagunta et al logical phenomena (e.g., Chintagunta et al 2009; Cor- 2009). The evaluation is based on four broad facets. tada 2013; Hewing 2011; Ruohonen et al 2015a). For The paper (1) assesses the underlying theory and the purposes of this paper, the concept of diffusion itself assumptions, (2) verifies methods, (3) evaluates data, can be loosely understood as an observable mechanism and (4) validates operational requirements for practical via which a phenomenon propagates in a population foresight (Piirainen et al 2012). The first two facets are through time, eventually reaching a saturation point approached with the concept of precedence, which is and the potential final demise. While this characteriza- also known as Granger causality.1 Namely, (a) the pri- tion provides a large amount of theoretical anchors, the mary empirical question is whether the current weekly scope is restricted against the constraints imposed by volumes of video game sales are affected by the past vol- time series modeling. For framing the theoretical back- umes of Internet searches, or the other way around. The ground against these constraints, a few preliminary re- empirical analysis further (b) evaluates the persistence marks should be made regarding the approach adopted. of the time series dynamics in the two volumes, (c) ad- dressing also the effect product launches. Following the 2.1 Approach recent time series evaluations in economics and mar- keting (Choi and Varian 2012; Dimpfl and Jank 2015; A few exploratory statistical assessments are carried Du and Kamakura 2012), these three questions are ex- out for evaluating whether the results vary across some amined with a bivariate vector autoregression (VAR) specific games, but the theoretical focus is still strictly model, using a longitudinal dataset comprised of nearly longitudinal. That is, different cross-sectional abstrac- a hundred video games. Although a brief forecast ex- tions (such as gaming platforms, genres, franchises, or periment is carried out to evaluate the fourth facet, geographic markets) are deliberately excluded from the more emphasis is placed on the evaluation of the three forthcoming theorizing and empirical analysis. questions that can be also motivated theoretically. Moreover, only two observable time series quantities With this evaluation, the paper contributes to the are used under a weekly sampling frequency: the vol- domain of video game sales modeling in general, and the ume of video game sales (S) and the volume of Google subdomain of EWOM research in particular. Besides in- searches (G). The specific word volume can be also used troducing and evaluating a new and novel source of em- for placing the paper into a specific branch in the extant pirical material for observing EWOM in the video game EWOM literature (cf. Hyrynsalmi et al 2015; King et al industry, the results presented allow also contemplating 2014). In other words, the fundamental presumption is about a few practical implications for marketing and that the mere amount, the volume of global Internet- advertisement. In a bigger interdisciplinary picture, the wide EWOM, as proxied by G, can help at predicting paper further adds the video game industry to the ap- global video game sales volumes, as measured by St. 1 In this paper, the concept of precedence is understood in Given this overall expectation, the forthcoming discus- the sense of Granger's (1988) classical exposition. While the sion derives six general conjectures for guiding the later term Granger causality is often used interchangeably, causal- empirical time series evaluation. The term conjecture ity itself is a much more problematic concept, of course { as underlines that the knowledge about search volumes is are the related concepts such as exogeneity (here see, e.g., L¨utkepohl 2005). This terminological disclaimer should be arguably still too incomplete for drawing definite con- kept in mind throughout the paper. clusions and contesting strict hypotheses. The same ap- Evaluating the Use of Internet Search Volumes for Time Series Modeling of Sales in the Video Game Industry 3 plies to methodological choices. As Choi and Varian keting, it can be crucial for correctly approximating (2012) argue, Internet search volume modeling is still the optimal timing of marketing campaigns, including an exploratory field, meaning that simple time series the increasingly relevant but typically fixed-period on- models are preferable for better understanding the ba- line advertisement \banners" (Chen et al 2016). An sic correlations and directions