Do Emotions Sell? The Impact of Emotional Expressions on Sales in the Space‐Sharing Economy

Abstract

The digital technology underlying the concept of Industry 4.0 has brought new disruptive changes to the economy. As an innovative service model, the unique characteristics of the space‐sharing economy require the understanding of emotional and psychological aspects in managing such a disruptive service model. We empirically examine the impact of unstructured emotional information that service providers offer (i.e., marketer‐generated content) on the popularity and sales of services in space‐sharing platforms (e.g., Airbnb) above and beyond objective qualities such as guest ratings or the size and amenities of the properties. For this, we leverage a unique dataset of a large‐scale sample of Airbnb listings from New York City (NYC). The results of a panel analysis and a series of robustness checks reveal a curvilinear association between the affective expression of service providers and the sales of their services, that is, the effect of emotional expressions is positive at low levels, but it diminishes at high levels. To address the potential endogeneity, we use a 2SLS‐IV approach, and the results validate our findings. Moreover, we conduct a randomized experiment to further establish causal inference. This study makes valuable contributions to the literature on service operation management and the sharing economy. Our findings shed light on how operations managers and service providers can use emotional information in space‐sharing platforms. We provide practical examples to guide their actions. These insights also have implications for other platform owners and users to leverage emotional information and improve outcomes.

On-demand service platform operations management: a literature review and research agendas

“…Compared with the research using mathematical models, there are relatively few empirical studies on on-demand service platform operations management. Through our reading and sorting of the literature, we find that for empirical research with a single platform as the research object, field experiments and natural experiments are the most common empirical research methods (Sun et al, 2019a;Cui et al, 2020;Wang et al, 2020a;Huang et al, 2021;Mejia and Parker, 2021;Xu et al, 2021;Yan et al, 2021). Such studies are often based on actual data provided by large, well-known platforms.…”

“…They conducted four random field experiments among 1,801 hosts on Airbnb and found positive reviews on guest pages significantly reduced discrimination. Wang et al (2020a) leveraged a unique dataset of a large-scale sample of Airbnb listings from New York City. They empirically examined the impact of unstructured emotional information that service providers offer on the popularity and sales of services in space-sharing platforms.…”

“…They conducted four random field experiments among 1,801 hosts on Airbnb and found positive reviews on guest pages significantly reduced discrimination. Wang et al. (2020a) leveraged a unique dataset of a large-scale sample of Airbnb listings from New York City.…”

Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond

“…As disruptive technologies are mostly real world applications, combining the corresponding empirical data and analytical modeling analyses together is very useful to develop solid theories which are more scientifically sound. For instance, Wang et al (2021a) conduct an empirical study using data from Airbnb to explore how emotional expressions affect sales in the space-sharing platform. The authors also use the "2SLS-IV" approach to validate the findings.…”

How Ride‐Sharing Is Shaping Public Transit System: A Counterfactual Estimator Approach

“…2021, Hu 2021, Wang et al. 2021b). The idea that people have shared the use of assets is not new, but the advent of the Internet—together with its use of big data—has made it easier for asset owners and those seeking to use the assets to find each other through online digital sharing economy platforms.…”