Marketing Seminars 2022-2023

Cause-related marketing promotions (CMPs) have ongoing momentum in marketing, especially in fast-moving consumer goods (FMCG). Prior work studied CMPs primarily in relatively simple experimental environments. FMCG market conditions include many more alternatives, more information, and other promotions. In these settings, CMPs risk remaining unnoticed. Based on 123 brands that executed 63 CMPs in 20 FMCG categories this paper studies the role of CMPs at the point of sale. On average, CMPs run for eleven weeks and donate 3.2 percent of product price. This results in an average weekly sales lift of 5.2 percent. Under optimal conditions, the impact can more than double. According to a hierarchical Bayesian model, market complexity and lack of brand prominence diminish CMP potential. On the other hand, concurrent price promotions (PP) can compensate for these disadvantages and make CMPs more effective. Collectively, these findings suggest that consideration likelihood is a relevant driver of the attainable CMP sales lift in FMCG markets.

Consumers are increasingly subject to fees, often without knowing why they are charged. This fee growth is due partly to an increasingly complex and underregulated marketplace. In addition to annoying consumers, fees transfer wealth from consumers’ wallets to wealthy corporations and individuals. Aware of rising public concerns, many industries have adopted a la carte pricing, where consumers can choose options and associated fees. For example, at many hotels, guests can pay fees for early check-in or late check-out, for using the pool, Wi-Fi, and gym, and for breakfast. Other companies instead use all-inclusive pricing or assess mandatory fees (e.g., “resort fees”). In this talk, I first review prior research on how consumers react to different pricing models that involve fees (e.g., partitioned pricing, drip pricing). I then will present some research in progress that investigates consumers’ preference for the freedom to choose options and associated fees. We show in a series of studies involving different industries, options, and fee/additional charge structures, that consumers mis-predict how much they like optional fees. While they prefer optional fees when comparing different pricing structures (all-inclusive, mandatory fees), as they might be asked to do in a marketing research pricing survey, they dislike optional fees in consumptions contexts that involve paying for optional items that have fees associated with them. We provide some initial evidence that this happens because consumers mis-predict the pain of payment that comes with the freedom of choice..

Given the prevalence of smartphones and computers in use today, the question arises whether these devices have a similar or different influence on our cognitive processes (e.g., decision-making, reasoning, etc.). Previous studies from the field of consumer behavior found various behavioral differences between smartphone use and computer use. However, those findings have always been examined and explained independently from one another. The current research aims to explore whether there is a general mechanism underlying all of those different findings. Relying on the dual-process theory, I hypothesize that smartphone use leads to lower levels of deliberative cognitive processes than computer use. This hypothesis was examined by exploring the effect of the type of device on different features deriving from the dual-process theory, such as cognitive functioning and biased thinking. Various methods were applied to demonstrate the effect, including Bayesian multilevel meta-analysis and an experimental approach. The talk will review the findings of three studies and discuss their implications for consumers in the digital era.

A general conjecture is that successful products attain their popularity through the influence of adopters on their peers and product information disseminating over the social network. Indeed, many studies have confirmed the existence of local peer effects and contagion. But others have shown that peer influence has a marginal if any, effect on cascades of adoptions. In this work, we study this discrepancy by analyzing video games propagating over the social network of gamers on Steam, the world’s largest video game platform. A major identification problem – distinguishing homophily from peer influence – is a challenge in any peer influence study based on observational data. To overcome it, we introduce a novel method that estimates the impact of peer influence on adoption by using an unsupervised machine-learning algorithm to match product adopters to users based solely on the similarity of their past adoption. This procedure is applied to thousands of products and reveals how peer influence changes over their lifecycle, allowing us to draw general conclusions about the entire ecosystem. Results show that most products belong to one of two distinct groups, each exhibiting a characteristic temporal pattern of adoption: products that exhibit substantial peer influence; and products that do not, for which users' preferences drive adoption. Considering the reach of products in each group, surprisingly, we found that local peer effects are stronger in less popular products. Even more surprising is the fact that almost all blockbusters (products adopted by millions of users) did not exhibit substantial peer influence at any stage of their lifecycle. We suggest that the fit between product characteristics and platform users’ preferences mediates the effect. These results shed light on the discrepancy between the observed local peer effects and the lack of peer influence in adoption cascades characteristic of successful products.

Since people integrate more information into their representations when they construe a situation on a high (compared to low) level, it was hypothesized that the level of construal would also affect cross-sensory influences of visual information on other sensory perceptions. Four experiments tested this idea. In all experiments, participants were first primed with a high-level versus low-level construal mindset using a category/exemplar task. Next, the effect of construal level on taste perception was examined in three experiments: Participants sampled beverages in cups that differed in color and rated several qualities of the beverage. It was expected that color would influence beverage perception, particularly when participants were primed with a high construal level. In line with this hypothesis, it was found that participants who generated high-level categories (compared to low-level exemplars) rated sparkling water as more refreshing in a blue than in a yellow cup (Experiment 1), an energy drink as sourer in a yellow than in a blue cup (Experiment 2), and coffee as hotter in a red than in a blue cup (Experiment 3). Experiment 4 extended the effect to the Rubber Hand Illusion, which is a distorted perception of one’s body by the acceptance of a fake rubber hand. It was hypothesized that participants who generated high-level categories (compared to low-level exemplars) would show a larger Rubber Hand Illusion in three commonly used dependent variables (subjective ownership rating of the rubber hand, the proprioceptive drift from the own hand to the rubber hand, and participants’ skin conductance in response to a hammer stroke on the rubber hand). The findings replicated the Rubber Hand Illusion and additionally showed the expected moderation by construal level on the proprioceptive drift measure. Together, the findings provide evidence that a high level of construal can increase cross-sensory assimilation. Possible processes will be discussed.

Online platforms such as Amazon have become highly successful actors in their respective markets. While brands benefit from access to the immense number of customers provided by online platforms, the relationship has massive negative implications for their own online activities. Based on several experiments, the research investigates what motivates customers to choose online platforms over brand websites. The intention is to learn how brands can generate value for their websites and reclaim customers from the dominating online platforms.

Co-Authors: Kalinda Ukanwa (USC) & Bill Rand (NCSU)
The past years have witnessed growing consumer concern about the fairness implications of the widespread adoption of AI in customer relationship management (CRM). To protect consumers against bias from algorithmic service decisions, regulators have introduced legislation holding firms accountable for the fairness of their algorithmic decisions. However, regulators have yet to invest in the systematic monitoring of algorithmic fairness, with the laws typically tasking firms with the detection and elimination of algorithmic bias. The resulting lack of transparency reduces firms’ ability to manage consumer expectations, leaving it to consumers to assess the – perceived – fairness of CRM outcomes. We posit that, to this end, consumers gather information about firm actions from their immediate social network, and we build a mathematical model to characterize how beliefs of bias may propagate within the market – even if the firm is using a fair algorithm. We show that, paradoxically, the lack of algorithmic transparency may lead to a divergence between consumer perceptions and the judicial view regarding the fairness of firm actions – under certain conditions, a firm with a fair algorithm can be perceived by the population as less fair than a firm with a biased algorithm. Using agent-based modeling, we also demonstrate how a watchdog institution may help in correcting such misperceptions.
 

Top influencers have the capacity to generate billions of dollars within hours through live-streaming e-commerce. In this study, we apply a multi-method approach, incorporating text, audio, and visual analysis, to identify the distinguishing characteristics between top-tier influencers and their mid- and bottom-tier counterparts. Our preliminary examination of live-stream videos uncovers unique rhetoric styles among top influencers, including the usage of specialized jargon and metaphors, the expression of distinct sentiments in their speech, the presence of unique voice features like energy and extreme emotion, and the display of characteristic facial expressions, particularly surprise. A follow-up experiment provides empirical evidence that these unique traits exhibited by top influencers foster more favorable consumer attitudes towards the brands they endorse, in comparison to the tactics employed by influencers of other tiers. In our extensive analysis of 600 live-stream clips, we found that voice energy and focus positively correlate with sales, whereas extreme emotional expressions and an overuse of imaginative speech may hinder sales performance. This study is one of the first to utilize a multi-method approach to scrutinize content strategies within the swiftly growing live-streaming market. The findings hold substantial implications for future influencers, brands seeking effective promotion strategies, and platform companies hosting both influencers and brands.

Abstract: In offline helping interactions, help-recipients typically feel driven to reciprocate the kindness they have received, whether directly to the helper or indirectly, by helping others. This tendency facilitates future helping behavior and has clear potentials to benefit organizations and websites that seek to encourage helping or collaboration among users. Yet given that reciprocity is socially motivated, it is unclear whether it arises in online settings, where many users offer help anonymously. The present research shows that, if a help-provider discloses his or her name in online communications, the help-recipient is more likely to “repay” the favor by demonstrating prosocial behaviors in a subsequent situation, such as answering other people’s online questions, providing online product reviews, donating time or money to a charitable organization, or even recycling. The effect occurs because name-disclosure facilitates the individuation of the helper in the mind of the recipient, which in turn boosts the recipient’s prosocial tendency as an indirect means to reciprocate the help received from the online stranger. An analysis of field data and seven studies (including four preregistered studies) provide robust support for the relationship between helper name-disclosure and the help-recipient’s prosocial behavior, as well as for the proposed underlying mechanism.