Logistics and distribution need to be more responsive and flexible to satisfy changing and demanding customer requirements due to e-commerce and customization trends. This work focuses in particular on warehousing, with the aim of understanding how emerging business models provide companies with additional ways to acquire warehouse space or fulfillment services. To do so, this work classifies and describes traditional warehouse models. Next, on-demand warehousing is analyzed as an emerging business-to-business (B2B) model that embraces the sharing economy principle of accessing resources rather than owning them. On-demand warehousing companies operate through online platforms connecting companies who have underutilized warehouses or fulfillment capacity to other ones searching for warehousing services. On-demand warehousing enables more flexible resource acquisition, as fixed cost investments are not necessary, and lengthy negotiations are eliminated through a standardized contract between the on-demand platform and the renter. This work contributes to the literature through an improved understanding and description of the main features of on-demand warehousing, representing a starting point for further research on this topic. Future developments are needed on the analysis of the main decisions a lender of space has to make when choosing an on-demand model.
Airbnb’s reputation system and gender differences among guests: Evidence from large-scale data analysis and a controlled experiment
Sharing economy platforms are rapidly scaling up by reaching increasingly diverse demographics. However, this expansion comes with great difficulties in adequately identifying and responding to everyone’s needs. In this paper, we study gender-related behaviors of guests on the currently most prominent home-sharing platform, Airbnb. While our results confirm the efficacy of Airbnb’s reputation system, we also find that the level of trust and participation on the platform varies by gender. In particular, female solo travelers are more likely to be conscious of review sentiment and choose more often female hosts than male solo travelers. Our findings are obtained by combining exploratory data analysis with large-scale experiment and call for further studies on the usage of sharing economy platforms among subpopulations, informing and improving both policy and practice in these growing online environments.
- Award ID(s):
- 1755873
- Publication Date:
- NSF-PAR ID:
- 10148340
- Journal Name:
- Lecture notes in computer science
- ISSN:
- 0302-9743
- Sponsoring Org:
- National Science Foundation
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