/pdf/the-theory-of-industrial-organization-19bejph0ej.pdf

The Theory of Industrial Organization

This Review summarizes the simultaneous transmission of several independent spatial channels of light along optical fibres to expand the data-carrying capacity of optical communications. Recent results achieved in both multicore and multimode optical fibres are documented.

/pdf/space-division-multiplexing-in-optical-fibres-9acl86j916.pdf

Space-division multiplexing in optical fibres

http://www.cs.unibo.it/~montesi/CBD/Articoli/SurvyBigData2.pdf

Data-intensive applications, challenges, techniques and technologies: A survey on Big Data

Optical networks are undergoing significant changes, fueled by the exponential growth of traffic due to multimedia services and by the increased uncertainty in predicting the sources of this traffic due to the ever changing models of content providers over the Internet. The change has already begun: simple on-off modulation of signals, which was adequate for bit rates up to 10 Gb/s, has given way to much more sophisticated modulation schemes for 100 Gb/s and beyond. The next bottleneck is the 10-year-old division of the optical spectrum into a fixed "wavelength grid," which will no longer work for 400 Gb/s and above, heralding the need for a more flexible grid. Once both transceivers and switches become flexible, a whole new elastic optical networking paradigm is born. In this article we describe the drivers, building blocks, architecture, and enabling technologies for this new paradigm, as well as early standardization efforts.

Elastic optical networking: a new dawn for the optical layer?

The Grid 2: Blueprint for a New Computing Infrastructure

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. A central question regards the impact of these sharing economy platforms on incumbent firms. We study the case of Airbnb, specifically analyzing Airbnb’s entry into the short-term accommodation market in Texas and its impact on the incumbent hotel industry. We first explore Airbnb’s impact on hotel revenue, by using a difference- in-differences empirical strategy that exploits the significant spatiotemporal variation in the patterns of Airbnb adoption across city-level markets. We estimate that in Austin, where Airbnb supply is highest, the causal impact on hotel revenue is in the 8-10% range; moreover, the impact is non-uniformly distributed, with lower-priced hotels and those hotels not catering to business travelers being the most affected. We find that this impact materializes through less aggressive hotel room pricing, an impact that benefits all consumers, not just participants in the sharing economy. The impact on hotel prices is especially pronounced during periods of peak demand, such as SXSW. We find that by enabling supply to scale – a differentiating feature of peer-to-peer platforms – Airbnb has significantly crimped hotels’ ability to raise prices during periods of peak demand. Our work provides empirical evidence that the sharing economy is making inroads by successfully competing with, differentiating from, and acquiring market share from incumbent firms.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2872361_code1846454.pdf?abstractid=2366898&mirid=1

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 Airbnb’s 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 di...

/pdf/the-rise-of-the-sharing-economy-estimating-the-impact-of-rssa2tpbnf.pdf

Consumer reviews are now part of everyday decision-making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit review fraud on the popular review platform Yelp, using two complementary approaches and datasets. We begin by analyzing restaurant reviews that are identified by Yelp's filtering algorithm as suspicious, or fake ― and treat these as a proxy for review fraud (an assumption we provide evidence for). We present four main findings. First, roughly 16% of restaurant reviews on Yelp are filtered. These reviews tend to be more extreme (favorable or unfavorable) than other reviews, and the prevalence of suspicious reviews has grown significantly over time. Second, a restaurant is more likely to commit review fraud when its reputation is weak, i.e., when it has few reviews, or it has recently received bad reviews. Third, chain restaurants ― which benefit less from Yelp ― are also less likely to commit review fraud. Fourth, when restaurants face increased competition, they become more likely to receive unfavorable fake reviews. Using a separate dataset, we analyze businesses that were caught soliciting fake reviews through a sting conducted by Yelp. These data support our main results, and shed further light on the economic incentives behind a business's decision to leave fake reviews.

/pdf/fake-it-till-you-make-it-reputation-competition-and-yelp-1xivpkvmwt.pdf

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud†

Consumer reviews are now part of everyday decision making. Yet the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves...

/pdf/fake-it-till-you-make-it-reputation-competition-and-yelp-1u6tksja1h.pdf

Georgios Zervas

Papers

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

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

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud†

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

Optical Fiber Communication Conference