Explore the vast range of titles available.

Despite increasing efforts to encourage the adoption of field experiments in marketing research (e.g., Campbell 1969; Cialdini 1980; Li et al. 2015), the majority of scholars continue to rely primarily on laboratory studies (Cialdini 2009). For example, of the 50 articles published in Journal of Marketing Research in 2013, only three (6%) were based on field experiments. The goal of this article is to motivate a methodological shift in marketing research and increase the proportion of empirical findings obtained using field experiments. The author begins by making a case for field experiments and offers a description of their defining features. She then demonstrates the unique value that field experiments can offer and concludes with a discussion of key considerations that researchers should be mindful of when designing, planning, and running field experiments.

Does the consumption of ideologically congruent news on social media exacerbate polarization? I estimate the effects of social media news exposure by conducting a large field experiment randomly offering participants subscriptions to conservative or liberal news outlets on Facebook. I collect data on the causal chain of media effects: subscriptions to outlets, exposure to news on Facebook, visits to online news sites, and sharing of posts, as well as changes in political opinions and attitudes. Four main findings emerge. First, random variation in exposure to news on social media substantially affects the slant of news sites that individuals visit. Second, exposure to counter-attitudinal news decreases negative attitudes toward the opposing political party. Third, in contrast to the effect on attitudes, I find no evidence that the political leanings of news outlets affect political opinions. Fourth, Facebook’s algorithm is less likely to supply individuals with posts from counter-attitudinal outlets, conditional on individuals subscribing to them. Together, the results suggest that social media algorithms may limit exposure to counter-attitudinal news and thus increase polarization.

Firms using online advertising regularly run experiments with multiple versions of their ads since they are uncertain about which ones are most effective. During a campaign, firms try to adapt to intermediate results of their tests, optimizing what they earn while learning about their ads. Yet how should they decide what percentage of impressions to allocate to each ad? This paper answers that question, resolving the well-known “learn-and-earn” trade-off using multi-armed bandit (MAB) methods. The online advertiser’s MAB problem, however, contains particular challenges, such as a hierarchical structure (ads within a website), attributes of actions (creative elements of an ad), and batched decisions (millions of impressions at a time), that are not fully accommodated by existing MAB methods. Our approach captures how the impact of observable ad attributes on ad effectiveness differs by website in unobserved ways, and our policy generates allocations of impressions that can be used in practice. We implemented this policy in a live field experiment delivering over 750 million ad impressions in an online display campaign with a large retail bank. Over the course of two months, our policy achieved an 8% improvement in the customer acquisition rate, relative to a control policy, without any additional costs to the bank. Beyond the actual experiment, we performed counterfactual simulations to evaluate a range of alternative model specifications and allocation rules in MAB policies. Finally, we show that customer acquisition would decrease by about 10% if the firm were to optimize click-through rates instead of conversion directly, a finding that has implications for understanding the marketing funnel. Data is available at https://doi.org/10.1287/mksc.2016.1023 .

Amid growing calls for transparency and social and environmental responsibility, companies are employing different strategies to improve consumer perceptions of their brands. Some pursue internal initiatives that reduce their negative social or environmental impacts through responsible operations practices (such as paying a living wage to workers or engaging in environmentally sustainable manufacturing). Others pursue external responsibility initiatives (such as philanthropy or cause-related marketing). Through two experiments conducted in the field and complementary online experiments, we compare how transparency into these internal and external initiatives affects customer perceptions and sales. We find that transparency into both internal and external responsibility initiatives tends to dominate generic brand marketing in motivating consumer purchases, supporting the view that consumers take companies’ responsibility efforts into account in their decision making. Furthermore, the results provide converging evidence that transparency into a company’s internal responsibility practices can be at least as motivating of consumer sales as transparency into its external responsibility initiatives, incrementally increasing a consumer’s probability of purchase by 6.40% and 45.85% across our two field experiments, conducted in social and environmental domains, respectively. Our results suggest that it may be in the interest of both business and society for managers to prioritize internal responsible operations initiatives to achieve both top- and bottom-line benefits while mitigating social and environmental harms. This paper was accepted by Charles Corbett, operations management.

Observational methods often fail to accurately recover the treatment effects generated from randomized advertising experiments on Facebook. Measuring the causal effects of digital advertising remains challenging despite the availability of granular data. Unobservable factors make exposure endogenous, and advertising’s effect on outcomes tends to be small. In principle, these concerns could be addressed using randomized controlled trials (RCTs). In practice, few online ad campaigns rely on RCTs and instead use observational methods to estimate ad effects. We assess empirically whether the variation in data typically available in the advertising industry enables observational methods to recover the causal effects of online advertising. Using data from 15 U.S. advertising experiments at Facebook comprising 500 million user-experiment observations and 1.6 billion ad impressions, we contrast the experimental results to those obtained from multiple observational models. The observational methods often fail to produce the same effects as the randomized experiments, even after conditioning on extensive demographic and behavioral variables. In our setting, advances in causal inference methods do not allow us to isolate the exogenous variation needed to estimate the treatment effects. We also characterize the incremental explanatory power our data would require to enable observational methods to successfully measure advertising effects. Our findings suggest that commonly used observational approaches based on the data usually available in the industry often fail to accurately measure the true effect of advertising. The online appendix and data files are available at https://doi.org/10.1287/mksc.2018.1135 .

This natural field experiment tests the effects of purely symbolic awards on volunteer retention in a public goods context. The experiment is conducted at Wikipedia, which faces declining editor retention rates, particularly among newcomers. Randomization assures that award receipt is orthogonal to previous performance. The analysis reveals that awards have a sizeable effect on newcomer retention, which persists over the four quarters following the initial intervention. This is noteworthy for indicating that awards for volunteers can be effective even if they have no impact on the volunteers’ future career opportunities. The awards are purely symbolic, and the status increment they produce is limited to the recipients’ pseudonymous online identities in a community they have just recently joined. The results can be explained by enhanced self-identification with the community, but they are also in line with recent findings on the role of status and reputation, recognition, and evaluation potential in online communities. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2016.2540 . This paper was accepted by John List, behavioral economics .

Does \"liking\" a brand on Facebook cause a person to view it more favorably? Or is \"liking\" simply a symptom of being fond of a brand? The authors disentangle these possibilities and find evidence for the latter: brand attitudes and purchasing are predicted by consumers' preexisting fondness for brands, and these are the same regardless of when and whether consumers \"like\" brands on social media. In addition, we explore possible second-order effects by examining whether \"liking\" brands might cause consumers' friends to view that brand more favorably. When consumers see that a friend has \"liked\" a brand, they are less likely to buy the brand relative to when they learn that a friend genuinely likes the brand in the offline sense, which is a more meaningful social endorsement. Taken together, five experiments and two meta-analyses (N > 14,000) suggest that turning \"liking\" into improved brand attitudes and increased purchasing by consumers and their friends may require more than just the click of a button.

Virtually no research has examined the role of emoticons in commercial relationships, and research outside the marketing domain reports mixed findings. This article aims to resolve these mixed findings by considering that emoticon senders are often simultaneously evaluated on two fundamental dimensions, warmth and competence, and the accessibility of one dimension over the other is critically contingent on salient relationship norms (communal vs. exchange norms) in customers’ minds due to individual and situational factors. Through laboratory and field experiments, the current research shows that customers perceive service employees who use emoticons as higher in warmth but lower in competence compared to those who do not (study 1). We further demonstrate that when a service employee uses emoticons, communal-oriented (exchange-oriented) customers are more likely to infer higher warmth (lower competence) and thus to be more (less) satisfied with the service (study 2). We also examine two practically important service situations that can make a certain type of relationship norm more salient: unsatisfactory services (study 3) and employees’ extra-role services (study 4). We speculate on possible mechanisms underlying these effects and discuss theoretical and practical implications along with opportunities for future research.

In this introduction to the symposium, I first offer an overview of the spectrum of experimental methods in economics, from laboratory experiments to the field experiments that are the subject of this symposium. I then offer some thoughts about the potential gains from doing economic research using field experiments and my own mental checklist of 14 steps to improve the chances of carrying out an economics field experiment successfully.

This study employs a randomized field experiment to causally identify what type of signal is likely to complement another signal in the context of financing technology ventures. The study examines the effect of product certification by expert intermediaries, prominent customers, and social proof (that is, others’ interest in investing in a venture) on interest in investing. These three signals are primarily signals of a venture’s product, market, and investment characteristics, respectively. The study finds that signals of product certification and prominent customers, and product certification and social proof are complements. In particular, investors who were able to view the combined product certification and prominent customer signals have a 72% higher likelihood of indicating an interest in making an equity investment than those who did not receive any of the three signals. Similarly, investors who were able to view the combined product certification and social proof signals have a 65% higher likelihood of indicating an interest in investing. These results suggest that in the context of technology ventures, a signal about product characteristics is the key to unlocking the value of signals of market or investment characteristics. This paper was accepted by Gustavo Manso, finance.