Impacts of Live Chat on Refund Intention: Evidence from an Online Labor Market

Live chat plays a significant role in online labor markets, which mitigates the information asymmetry caused by the highly customized nature of service products. This study examines the impacts of live chat on refund intention in online labor markets and how these impacts are moderated by business familiarity. We collect unique archived data from a leading online labor market in Asia and hypothesize that reply speed has a negative effect on refund intention while both politeness intensity and sentiment intensity have a U-shaped effect on refund intention. In addition, these effects are proposed to be weakened by business familiarity formed by previous transaction experience. The study not only offers theoretical contributions to the online labor market literature by providing empirical insights on the impact of live chat on refund intention but also yields managerial implications for service providers and platform operators

What are Airbnb hosts advertising? A longitudinal essay in Lisbon

Purpose – Considering the importance of the content created by the host for Airbnb consumers while making purchasing decisions, this study aims to analyze how the Airbnb hosts promote their properties by revealing the predominant attributes considered by hosts when advertising them. Design/methodology/approach – The unstructured textual content of online Airbnb accommodations advertisements (property descriptions) is analyzed through a longitudinal text mining approach. This study defines a pipeline based on a topic modeling approach that allows not only to identity the most prevalent text attributes but also its distribution through time. Findings – This research identifies and characterizes the attributes most advertised over time, on about 30,000 accommodations posted monthly over two years, between 2018 and 2020. Five main topics were identified in the data reflecting only pull motivations. Noteworthy is the slight changes in properties’ descriptions topics along the two years, suggesting that ‘‘service’’ is increasingly being perceived by hosts as an important attribute of Airbnb guest experience. Originality/value – Through a text analysis, this study provides an insight into peer-to-peer accommodation on the key attributes that hosts consider in the description of their properties to leverage the attractiveness of Airbnb. In the light of existing research, which has predominantly focused on the trustworthiness and attractiveness of the Airbnb advertisement, this research differentiates by analyzing the main attributes in text over time. Given the Airbnb’s changes since its inception, a longitudinal view is relevant to clarify how hosts advertise their properties and how it evolves in the light of these changes.info:eu-repo/semantics/acceptedVersio

Text Mining of Airbnb Reviews: A holistic approach on reviewers’ opinions and topics distribution

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceThis thesis aims to perform a holistic investigation concerning how Airbnb accommodation features and hosts’ attributes influence guest’s reviews and how are the main topics distributed. A dataset containing almost 4 million reviews from major touristic cities in the world (Milan, Lisbon, Amsterdam, Toronto, San-Francisco, and Sydney) was used for the text mining analysis to uncover the reviews’ social and market norms, as well as the guests’ sentiments and topics distribution. This research uses both Mallet LDA (Latent Dirichlet Allocation) and Word2Vec methods to unveil the semantic structure and similarity between data in this study. This approach will allow hospitality providers to understand the impact of underlying factors on reviewers’ opinions for further improvement of their services. Finally, this study develops a predictive unbiased model to forecast the review’s scores, with an accuracy of 90.70%