We use data from a large-scale field experiment to explore what influences the effectiveness of online advertising. We find that matching an ad to website content and increasing an ad's obtrusiveness independently increase purchase intent. However, in combination, these two strategies are ineffective. Ads that match both website content and are obtrusive do worse at increasing purchase intent than ads that do only one or the other. This failure appears to be related to privacy concerns: the negative effect of combining targeting with obtrusiveness is strongest for people who refuse to give their income and for categories where privacy matters most. Our results suggest a possible explanation for the growing bifurcation in Internet advertising between highly targeted plain text ads and more visually striking but less targeted ads.
The failure of firms in the face of technological change has been a topic of intense research and debate, spawning the theory (among others) of disruptive technologies. However, the theory suffers from circular definitions, inadequate empirical evidence, and lack of a predictive model. We develop a new schema to address these limitations. The schema generates seven hypotheses and a testable model relating to platform technologies. We test this model and hypotheses with data on 36 technologies from seven markets. Contrary to extant theory, technologies that adopt a lower attack (“potentially disruptive technologies”) (1) are introduced as frequently by incumbents as by entrants, (2) are not cheaper than older technologies, and (3) rarely disrupt firms; and (4) both entrants and lower attacks significantly reduce the hazard of disruption. Moreover, technology disruption is not permanent because of multiple crossings in technology performance and numerous rival technologies coexisting without one disrupting the other. The proposed predictive model of disruption shows good out-of-sample predictive accuracy. We discuss the implications of these findings.
Automotive sales forecasts traditionally focus on predictors such as advertising, brand preference, life cycle position, retail price, and technological sophistication. The quality of the cars' design is, however, an often-neglected variable in such models. We show that incorporating objective measures of design prototypicality and design complexity in sales forecasting models improves their prediction by up to 19%. To this end, we professionally photographed the frontal designs of 28 popular models, morphed the images, and created objective prototypicality (car-to-morph Euclidian proximity) and complexity (size of a compressed image file) scores for each car. Results show that prototypical but complex car designs feel surprisingly fluent to process, and that this form of surprising fluency evokes positive gut reactions that become associated with the design and positively impact car sales. It is important to note that the effect holds for both economy (functionality oriented) and premium (identity oriented) cars, as well as when the above-mentioned traditional forecasting variables are considered. These findings are counter to a common intuition that consumers like unusual–complex designs that reflect their individuality or prototypical–simple designs that are functional.
The critical role of research and development (R&D) and advertising in the marketing strategy of the firm is well established. This paper conceptually and empirically examines why and how much the effectiveness of these two marketing instruments differs between times of economic expansions versus periods of economic contractions—and whether these results depend on the cyclicality of the industry in question. We consider a key marketing metric (market share) and a key financial metric (firm profit). Our empirical setting is 1,175 U.S. firms across a time period spanning over three decades. We find that R&D and advertising contribute to firm performance but that their effectiveness is not constant across the business cycle. Increasing advertising share in contractions has a stronger effect on profit and market share than increasing advertising share in expansions. Likewise, investments in R&D in contractions lead to higher gains in market share and profit than R&D investments in expansions, albeit only in subsequent years. If in contractions the firm faces tight budget constraints and has to choose between either maintaining R&D or advertising, our simulation results show that maintaining R&D is associated with better company performance. We find that advertising effectiveness, in general, and in contractions, in particular, is systematically moderated by the degree of cyclicality of the industry in which the firm operates. In relatively stable industries, advertising effects are small or even nonsignificant, and they do not go beyond the year the firm advertises. However, in highly cyclical industries, advertising effects are long-lasting, its total effect being 50% larger (market share) and 200% larger (profits) than in industries of average cyclicality. The effect of industry cyclicality on advertising effectiveness is especially pronounced in contractions. Collectively, these findings provide valuable and actionable insights into how firms should respond to contractions in order to grow profits and market share.