Service with a Smile
Understanding and Improving Consumer Reactions to Service Bots
Noah Castelo et al.
Journal of Consumer Research, forthcoming
Abstract:
Many firms are beginning to replace customer service employees with bots, from humanoid service robots to digital chatbots. Using real human-bot interactions in lab and field settings, we study consumers' evaluations of bot-provided service. We find that service evaluations are more negative when the service provider is a bot versus a human -- even when the provided service is identical. This effect is explained by consumers' belief that service automation is motivated by firm benefits (i.e., cutting costs) at the expense of customer benefits (such as service quality). The effect is eliminated when firms share the economic surplus derived from automation with consumers through price discounts. The effect is reversed when service bots provide unambiguously superior service to human employees -- a scenario that may soon become reality. Consumers' default reactions to service bots are therefore largely negative but can be equal to or better than reactions to human service providers if firms can demonstrate how automation benefits consumers.
The Fundamental Recruitment Error: Candidate-Recruiter Discrepancy in Their Relative Valuation of Innate Talent vs. Hard Work
Xianchi Dai & Kao Si
Organization Science, forthcoming
Abstract:
Innate talent and orientation toward hard work are highly important personal attributes with respect to workers' productive capabilities. In this research, we identify a discrepancy between job candidates and recruiters in their relative valuation of these two attributes. Although innate talent is valued relatively more by job candidates than recruiters, the opposite is true for orientation toward hard work. We propose that the discrepancy is rooted in a misalignment of the fundamental motivations of the two parties in the job market. In seven studies (four preregistered), which include randomized trial experiments and quasi-experiments and use real life recruiters and job seekers (across a total of 112 industries) as participants, we provide evidence of the current effect and its underlying mechanism. Studies 1A-1C demonstrate the negative consequence of the discrepancy on job market efficiency, showing that it can lead candidates to adopt impression management strategies that lower their chance of getting the job. Studies 2A and 2B show that full-time workers consider career potential to be associated with both innate talent and hard work but position performance to be more strongly associated with hard work than innate talent. Finally, Studies 3A and 3B indicate that candidates are relatively more career-focused, whereas recruiters are relatively more position focused and that this difference in their relative focus mediates the current discrepancy. Implications of the present research for both job candidates and recruiters are discussed.
Do Incentives to Review Help the Market? Evidence from a Field Experiment on Airbnb
Andrey Fradkin & David Holtz
Marketing Science, forthcoming
Abstract:
Many online reputation systems operate by asking volunteers to write reviews for free. As a result, a large share of buyers do not review, and those who do review are self-selected. This can cause the reputation system to miss important information about seller quality. We study the extent to which a platform can improve market outcomes by attempting to increase the amount and quality of information collected by its reputation system. We do so by analyzing a randomized experiment conducted by Airbnb. In the treatment, buyers were offered a coupon to review listings that had no prior reviews. In the control, buyers were not offered any incentive to review. We find that, although the treatment induced additional reviews that were more negative on average, these reviews did not affect the number of nights sold or total revenue. Furthermore, we find that, contrary to the treatment's intended effect, Airbnb's incentivized program caused transaction quality for treated sellers to fall. We examine how the quality of the induced reviews, market conditions, and the design of Airbnb's reputation system can explain our findings.
Psychological Distance Increases Conceptual Generalization
Hadar Ram, Nira Liberman & Christian Unkelbach
Social Psychological and Personality Science, forthcoming
Abstract:
We predicted and found in three experiments that psychological distance increases conceptual generalization. We manipulated psychological distance by describing a medicine as being either domestic (proximal) or foreign (distal) and examined generalization by testing how information about initial experience (positive vs. negative) with this medicine influences evaluations of similar products. In all three experiments, and across both Israeli and German participants, we found that people generalized from experience with products that are distal (foreign) more than from proximal (domestic) products. We explain the relation between distance and generalization in terms of the accuracy-applicability trade-off inherent in generalization and discuss how it aligns with construal-level theory.
Meaning of Manual Labor Impedes Consumer Adoption of Autonomous Products
Emanuel de Bellis, Gita Venkataramani Johar & Nicola Poletti
Journal of Marketing, forthcoming
Abstract:
Technologies are becoming increasingly autonomous, able to complete tasks on behalf of consumers without human intervention. For example, robot vacuums clean the floor while cooking machines implement recipes on their own. These autonomous products free consumers from daily chores that they used to perform manually. The current research suggests that some consumers derive meaning from completing such manual tasks, and that this meaning of manual labor acts as a barrier to the adoption of autonomous products. A series of field and experimental studies show that consumers high (vs. low) in meaning of manual labor tend to evaluate autonomous products less favorably and adopt them less frequently. However, making alternative sources of meaning in life salient can serve as a remedy to increase autonomous product adoption among these consumers. One such strategy is to emphasize that the time gained through autonomous products can be used for meaningful activities, thus offsetting the detrimental effects of meaning of manual labor on autonomous product adoption. The findings indicate effective interventions for firms offering autonomous products while stressing the need to provide meaningful experiences to consumers.
Product Aesthetic Design: A Machine Learning Augmentation
Alex Burnap, John Hauser & Artem Timoshenko
Marketing Science, forthcoming
Abstract:
Aesthetics are critically important to market acceptance. In the automotive industry, an improved aesthetic design can boost sales by 30% or more. Firms invest heavily in designing and testing aesthetics. A single automotive "theme clinic" can cost more than $100,000, and hundreds are conducted annually. We propose a model to augment the commonly used aesthetic design process by predicting aesthetic scores and automatically generating innovative and appealing product designs. The model combines a probabilistic variational autoencoder (VAE) with adversarial components from generative adversarial networks (GAN) and a supervised learning component. We train and evaluate the model with data from an automotive partner -- images of 203 SUVs evaluated by targeted consumers and 180,000 high-quality unrated images. Our model predicts well the appeal of new aesthetic designs -- 43.5% improvement relative to a uniform baseline and substantial improvement over conventional machine learning models and pretrained deep neural networks. New automotive designs are generated in a controllable manner for use by design teams. We empirically verify that automatically generated designs are (1) appealing to consumers and (2) resemble designs that were introduced to the market five years after our data were collected. We provide an additional proof-of-concept application using open-source images of dining room chairs.