Knowledge that Transforms

Retail expansion is led by multistore firms, which often mix two organizational forms: franchised and company-owned outlets (“franchising decisions”). The authors examine whether strategic considerations in entry and expansion play a role in organizational-form decisions (e.g., franchising) in retailing. The authors utilize store count and revenues for franchised and company-owned outlets of nationwide convenience store chains in 47 geographical markets in Japan between 1984 and 2010. The empirical analyses show that strategic considerations in entry and expansion, ignored in the literature on franchising, appear to influence an organizational-form decision: firms rely more on company-owned outlets for expansion when the threat of entry from competitor firms in adjacent markets increases. The authors examine two interpretations: the convenience of quick deployment and a credible signal. Numerical analyses of a simple dynamic model of entry and franchising confirm that company-owned-outlet-based expansion arises under heightened entry threat. The simulation analysis highlights how franchising decisions in response to an elevated threat of entry may be beneficial (or harmful) for an incumbent firm, which yields key implications for firms, consumers, and policy makers.

Consumers increasingly expect brands to “pick a side” on divisive sociopolitical issues, but managers are reluctant to risk alienating customers who oppose their position. Moreover, research on identity-based consumption and negativity bias suggests that corporate political advocacy (CPA) is more likely to repel existing customers who oppose the CPA than to attract new customers who support it, implying that the net effect will be negative even if consumers overall are evenly divided in their support/opposition. In this research, the authors posit that despite this negativity bias in individual-level choice, the net effect of CPA at the market level is determined by a sorting process that benefits small-share brands and hurts large-share brands. This is because having few customers to lose and many to gain can offset the risk of the negativity bias in consumers’ identity-driven responses to CPA, potentially leading to a net influx of customers for small-share brands. Five experiments provide support for this theorizing and identify authenticity as a necessary condition for small share brands to benefit.

Marketers commonly seed information about products and brands through individuals believed to be influential on social media, which often involves enlisting micro influencers, users who have accumulated thousands as opposed to millions of followers (i.e., other users who have subscribed to see that individual’s posts). Given an abundance of micro influencers to choose from, cues that help distinguish more versus less effective influencers on social media are of increasing interest to marketers. The authors identify one such cue: the number of users the prospective influencer is following. Using a combination of real-world data analysis and controlled lab experiments, they show that following fewer others, conditional on having a substantial number of followers, has a positive effect on a social media user’s perceived influence. Further, the authors find greater perceived influence impacts engagement with the content shared in terms of other users exhibiting more favorable attitudes toward it (i.e., likes) and a greater propensity to spread it (i.e., retweets). They identify a theoretically important mechanism underlying the effect: following fewer others conveys greater autonomy, a signal of influence in the eyes of others.

Ads promising a desired change are ubiquitous in the marketplace. These ads typically include visuals of the starting and ending point of the promised change (“before/after” ads). “Progression” ads, which include intermediate steps in addition to starting and ending points, are much rarer in the marketplace. Across several consumer domains, the authors show an ad-type effect: progression ads foster spontaneous simulation of the process through which the change will happen, which makes these ads more credible and, in turn, more persuasive than before/after ads (Studies 1–3). The authors also show that impairing process simulation and high skepticism moderate the ad-type effect (Studies 4–5). Finally, they show effect reversals: if consumers focus on achieving the desired results quickly, and it is possible to do so, progression ads and the associated process simulation backfire in terms of credibility and persuasion (Studies 6–7). These findings contribute to existing research by identifying conditions under which progression ads have beneficial or disadvantageous effects. These findings have managerial implications because they run counter to current marketing practices, which favor before/after over progression ads.

In this research, the authors investigate the prevalence, robustness, and possible reasons underlying the polarity of online review distributions, with the majority of the reviews at the positive end of the rating scale, a few reviews in the midrange, and some reviews at the negative end of the scale. Compiling a large data set of online reviews—over 280 million reviews from 25 major online platforms—the authors find that most reviews on most platforms exhibit a high degree of polarity, but the platforms vary in the degree of polarity on the basis of how selective customers are in reviewing products on the platform. Using cross-platform and multimethod analyses, including secondary data, experiments, and survey data, the authors empirically confirm polarity self-selection, described as the higher tendency of consumers with extreme evaluations to provide a review as an important driver of the polarity of review distributions. In addition, they describe and demonstrate that polarity self-selection and the polarity of the review distribution reduce the informativeness of online reviews.

This research examines the psychological processes and factors that shape illness-detection versus illness-prevention health actions. Four experiments using contexts of mental health, skin cancer, and breast cancer show that illness detection evokes fear, which undermines engagement in detection behaviors. Considering detection at low (vs. high) levels of thought reduced fear and increased health persuasion. Illness prevention is driven by self-efficacy perceptions and considering prevention at high (vs. low) levels of thought increases persuasion. In further evidence of process, trait fear moderated the detection effects, and dispositional self-efficacy moderated the prevention effects. As an intervention, framing a detection action as serving illness-prevention goals increased people’s likelihood of engaging with an online breast cancer detection tool. These findings illuminate the psychology of detection as being distinct from the psychology of prevention, identify the role of fear in the consideration of health behaviors, and show contexts in which construal levels have divergent effects on health persuasion.

Free shipping promotions have become popular among online retailers. However, little is known about their influence on consumers’ purchases, return behavior, and, ultimately, firm profit. The authors propose that free shipping promotions encourage customers to make riskier purchases, leading to more product returns. They estimate the impact of these promotions on purchase incidence, high-risk and low-risk spend, and return share. The results show that free shipping promotions increase expenditure for high-risk products, expanding their share of the consumer’s market basket and thus increasing the overall return rate. This is validated in a field experiment. A field test and an online lab experiment analyze the mechanism linking free shipping and returns. The results suggest that the free shipping effect occurs through consumers’ perceptions that free shipping serves as a risk premium compensating them for potential returns and through positive affect generated by the promotion. A simulation shows that for the focal firm, free shipping promotions increase net sales volume, but higher product returns and lost shipping revenue render these promotions unprofitable.

The authors propose a new Bayesian synthetic control framework to overcome limitations of extant synthetic control methods (SCMs). The proposed Bayesian synthetic control methods (BSCMs) do not impose any restrictive constraints on the parameter space a priori. Moreover, they provide statistical inference in a straightforward manner as well as a natural mechanism to deal with the “large p, small n” and sparsity problems through Markov chain Monte Carlo procedures. Using simulations, the authors find that for a variety of data-generating processes, the proposed BSCMs almost always provide better predictive accuracy and parameter precision than extant SCMs. They demonstrate an application of the proposed BSCMs to a real-world context of a tax imposed on soda sales in Washington state in 2010. As in the simulations, the proposed models outperform extant models, as measured by predictive accuracy in the posttreatment periods. The authors find that the tax led to an increase of 5.7% in retail price and a decrease of 5.5%∼5.8% in sales. They also find that retailers in Washington overshifted the tax to consumers, leading to a pass-through rate of approximately 121%.

Are social media posts with pictures more popular than those without? Why do pictures with certain characteristics induce higher engagement than some other pictures? Using data sets of social media posts about major airlines and sport utility vehicle brands collected from Twitter and Instagram, the authors empirically examine the influence of image content on social media engagement. After accounting for selection bias on the inclusion of image content, the authors find a significant and robust positive mere presence effect of image content on user engagement in both product categories on Twitter. They also find that high-quality and professionally shot pictures consistently lead to higher engagement on both platforms for both product categories. However, the effect of colorfulness varies by product category, while the presence of human face and image–text fit can induce higher user engagement on Twitter but not on Instagram. These findings shed light on how to improve social media engagement using image content.