Comparing chains versus independent hotels based on international sales: an exploratory study

The globalization of tourism has recently increased the importance of foreign demand for most European destinations. Hotel chains have been long investigated from several perspectives. However, no research has verified the alleged ability of chains to attract foreign demand, while this information is highly sought after by hotel investors and owners when evaluating affiliation opportunities. The present study covers Italy. It is based on a survey of 148 branded hotels for 21 destinations and 22 brands. Adopting a new metric to compare the ability of hotels to sell abroad (Foreign market Per Available Room; FmPAR), it has been found that chain-affiliated hotels perform better than independent hotels in attracting foreign demand. This is particularly true for international chains compared to domestic ones. On the other hand, the effect is stronger in three-star hotels than in four and five-star ones, in destinations where chain penetration is low

Towards Runtime Monitoring of Node.js and Its Application to the Internet of Things

In the last years Node.js has emerged as a framework particularly suitable for implementing lightweight IoT applications, thanks to its underlying asynchronous event-driven, non blocking I/O model. However, verifying the correctness of programs with asynchronous nested callbacks is quite difficult, and, hence, runtime monitoring can be a valuable support to tackle such a complex task. Runtime monitoring is a useful software verification technique that complements static analysis and testing, but has not been yet fully explored in the context of Internet of Things (IoT) systems. Trace expressions have been successfully employed for runtime monitoring in widespread multiagent system platforms. Recently, their expressive power has been extended to allow parametric specifications on data that can be captured and monitored only at runtime. Furthermore, they can be language and system agnostic, through the notion of event domain and type. This paper investigates the use of parametric trace expressions as a first step towards runtime monitoring of programs developed in Node.js and Node-RED, a flow-based IoT programming tool built on top of Node.js. Runtime verification of such systems is a task that mostly seems to have been overlooked so far in the literature. A prototype implementing the proposed system for Node.js, in order to dynamically check with trace expressions the correct usage of API functions, is presented. The tool exploits the dynamic analysis framework Jalangi for monitoring Node.js programs and allows detection of errors that would be difficult to catch with other techniques. Furthermore, it offers a simple REST interface which can be exploited for runtime verification of Node-RED components, and, more generally, IoT devices