Davide Proserpio

The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Peer-to-peer markets, collectively known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. The authors explore the economic impact of the sharing economy on incumbent firms by studying the case of Airbnb, a prominent platform for short-term accommodations. They analyze Airbnbs entry into the state of Texas and quantify its impact on the Texas hotel industry over the subsequent decade. In Austin, where Airbnb supply is highest, the causal impact on hotel revenue is in the 8%–10% range; moreover, the impact is nonuniform, with lower-priced hotels and hotels that do not cater to business travelers being the most affected. The impact manifests itself primarily through less aggressive hotel room pricing, benefiting all consumers, not just participants in the sharing economy. The price response is especially pronounced during periods of peak demand, such as during the South by Southwest festival, and is due to a differentiating feature of peer-to-peer platforms—enabling instantaneous supply to scale to meet demand.

Media cloud: an open cloud computing middleware for content management

Cloud computing allows accessing resources across Internet transparently: requiring no expertise in, or control over the underlying infrastructure. There is an increasing interest in sharing media files with family and friends. However, UPnP or DLNA were not designed for media distribution beyond the boundaries of a local network and manage media files through web applications can be tedious. To overcome this problem, we propose Media Cloud, a middleware for Set-top boxes for classifying, searching, and delivering media inside home network and across the cloud that interoperates with UPnP and DLNA.

Calibrating data to sensitivity in private data analysis: a platform for differentially-private analysis of weighted datasets

We present an approach to differentially private computation in which one does not scale up the magnitude of noise for challenging queries, but rather scales down the contributions of challenging records. While scaling down all records uniformly is equivalent to scaling up the noise magnitude, we show that scaling records non-uniformly can result in substantially higher accuracy by bypassing the worst-case requirements of differential privacy for the noise magnitudes. This paper details the data analysis platform wPINQ, which generalizes the Privacy Integrated Query (PINQ) to weighted datasets. Using a few simple operators (including a non-uniformly scaling Join operator) wPINQ can reproduce (and improve) several recent results on graph analysis and introduce new generalizations (e.g., counting triangles with given degrees). We also show how to integrate probabilistic inference techniques to synthesize datasets respecting more complicated (and less easily interpreted) measurements.

A workflow for differentially-private graph synthesis

We present a new workflow for differentially-private publication of graph topologies. First, we produce differentially-private measurements of interesting graph statistics using our new version of the PINQ programming language, Weighted PINQ, which is based on a generalization of differential privacy to weighted sets. Next, we show how to generate graphs that fit any set of measured graph statistics, even if they are inconsistent (due to noise), or if they are only indirectly related to actual statistics that we want our synthetic graph to preserve. We combine the answers to Weighted PINQ queries with an incremental evaluator (Markov Chain Monte Carlo (MCMC)) to synthesize graphs where the statistic of interest aligns with that of the protected graph. This paper presents our preliminary results; we show how to cast a few graph statistics (degree distribution, edge multiplicity, joint degree distribution) as queries in Weighted PINQ, and then present experimental results synthesizing graphs generated from answers to these queries.

Media Cloud: Sharing contents in the large

Cloud computing allows accessing resources across Internet transparently: requiring no expertise in, or control over the underlying infrastructure. UPnP or DLNA were not designed for media distribution beyond the boundaries of a local network. To overcome this problem, we propose Media Cloud, a home gateway service for classifying, searching and delivering media across the cloud that interoperates with UPnP and DLNA.

MobiScore: Towards Universal Credit Scoring from Mobile Phone Data

Credit is a widely used tool to finance personal and corporate projects. The risk of default has motivated lenders to use a credit scoring system, which helps them make more efficient decisions about whom to extend credit. Credit scores serve as a financial user model, and have been traditionally computed from the user’s past financial history. As a result, people without any prior financial history might be excluded from the credit system. In this paper we present MobiScore, an approach to build a model of the user’s financial risk from mobile phone usage data, which previous work has shown to convey information about e.g. personality and socioeconomic status. MobiScore could replace traditional credit scores when no financial history is available, providing credit access to currently excluded population sectors, or be used as a complementary source of information to improve traditional finance-based scores. We validate the proposed approach using real data from a telecommunications operator and a financial institution in a Latin American country, resulting in an accurate model of default comparable to traditional credit scoring techniques.

DLNA, DVB-CA and DVB-CPCM integration for commercial content management

DLNA can be considered as a good candidate for sharing user-generated contents among household networked consumer electronics. However, commercial content sharing requires a high degree of device protection that DLNA does not provides. We propose a solution supporting acquisition and post acquisition content protection by the integration of DLNA with DVB Conditional Access and DVB Content Protection & Copy Management. This article shows the design and implementation of a solution to improve commercial content management over DLNA.

The Impact of the Sharing Economy on the Hotel Industry: Evidence from Airbnb's Entry Into the Texas Market

Spurred by technological advancement, a number of decentralized peer-to-peer markets, now colloquially known as the sharing economy, have emerged as alternative suppliers of goods and services traditionally provided by long-established industries. A central question surrounding the sharing economy regards its long-term impact: will peer-to-peer platforms materialize as viable mainstream alternatives to traditional providers, or will they languish as niche markets? In this paper, we study Airbnb, a sharing economy pioneer offering short-term accommodation. Combining data from Airbnb and the Texas hotel industry, we estimate the impact of Airbnbs entry into the Texas market on hotel room revenue, and study the market response of hotels. To identify Airbnbs causal impact on hotel room revenue, we use a difference-in-differences empirical strategy that exploits the significant spatiotemporal variation in the patterns of Airbnb adoption across citylevel markets. We estimate that each 10% increase in Airbnb supply results in a 0:37% decrease in monthly hotel room revenue. In Austin, where Airbnb supply is highest, the impact on hotel revenue exceeds 10%. We find that Airbnbs impact is non-uniformly distributed, with lower-priced hotels, and hotels not catering to business travel being the most affected segments. Finally, we find that affected hotels have responded by reducing prices, an impact that benefits all consumers, not just participants in the sharing economy. Our work provides empirical evidence that the sharing economy is making inroads by successfully competing with, and acquiring market share from, incumbent firms.

A (not) NICE way to verify the openflow switch specification: formal modelling of the openflow switch using alloy

The introduction of Software Defined Networks (SDNs) is completely changing the way in which networks are built and managed. SDNs decouple data from control plane access, which makes introduction of new network functionalities significantly simpler. The philosophy of OpenFlow is a move towards centralization, where a single controller program manages the logic of switches. While centralized systems are often easier to coordinate, the likelihood of bugs is still high. Despite the existence of an OpenFlow Specification [3], it may still be possible observe unexpected behavior while adhering to this Specification. This can be due to various reasons, such as underspecification of some aspect of the protocol or a contrived sequence of events. One of the emerging techniques to verify (prove that a system satisfies its specification) standards and protocols is formal modeling. Created at some chosen level of abstraction, the purpose of a formal model is to enable precise understanding, specification, and analysis of the system. The modeling language Alloy has been noted as a tool that lends itself to modeling complex networks. In fact, it has been used in many applications [1], including the analysis of Chord [6, 7] which led to a counterexample proving the incorrectness of the protocol. The main contribution of this paper is to apply the principles of formal modeling to OpenFlow. Concretely we use model enumeration (Alloy and Alloy Analyzer [5]) to model an OpenFlow-capable switch. The aim of this project is twofold: (1) to provide a proof of correctness (or not) of the OpenFlow Switch Specification Version 1.1.0 and (2) provide researchers with a complete OpenFlow Switch module that can be used as a foundation to verify various applications or types of networks (more detail in Section 4 and our site [2]). The remainder of the paper is organized as follows. In Sec-

Extended DLNA protocol: Sharing protected pay TV contents

DLNA can be considered as a good candidate for sharing protected contents among authorized devices. There is a important penetration of DLNA certified devices, and it offers link protection. We identify problems on DLNAs link protection, DTCP-IP, and we propose to improve the authentication and key derivation mechanism. DLNA sharing can be extended to include pre and post acquisition protection content at the price of inexpensive descrambler.