Swiss Municipal Data Merger Tool: Open-source Software for the Compilation of Longitudinal Municipal-level Data

Abstract The Swiss Municipal Data Merger Tool (Swiss MDMT) offers a solution to a frequent data management problem encountered when compiling longitudinal datasets involving Swiss municipalities as the observational units. Due to municipal mergers, the number of municipalities in Switzerland declined from 3,095 in 1960 to 2,202 in 2020. As a consequence, manually securing the correct spatial reference when merging historical cross-sectional data is tedious and time-consuming. To facilitate this operation, the Swiss MDMT considers mutations at the municipal level and maps municipalities of a first point in time to municipalities in a second point in time based on information provided by the Swiss Federal Statistical Office`s municipality inventory. The tool is distributed as an open-source R package and is freely available on CRAN

Tendencias internacionales sobre análisis de redes sociales

La Web 2.0 ha dado lugar a numerosas plataformas en las que las interacciones entre sus usuarios generan grandes cantidades de datos, facilmente accesibles. Entre las metodologías empleadas para analizar estos datos, el análisis de redes sociales se ha convertido en una de las más populares, aplicándose con éxito a campos de investigación muy diversos. En este capítulo introducimos algunos de los conceptos fundamentales en el análisis de redes sociales, enfocado al ámbito de la educomunicación. Todos los elementos que intervienen en este son puestos así en relieve, desde la planificación y recolección de datos a la generación y manipulación de la red, repasando las principales herramientas, indicadores y métodos que en él intevienen. Por último, ejemplificamos todo el proceso descrito con un estudio de caso relativo al debate producido en redes en torno a la nueva ley de reforma educativa

Management Responses to Online Reviews: Big Data From Social Media Platforms

User-generated content from virtual communities helps businesses develop and sustain competitive advantages, which leads to asking how firms can strategically manage that content. This research, which consists of two studies, discusses management response strategies for hotel firms to gain a competitive advantage and improve customer relationship management by leveraging big data, social media analytics, and deep learning techniques. Since negative reviews' harmful effects are greater than positive comments' contribution, firms must strategise their responses to intervene in and minimise those damages. Although current literature includes a sheer amount of research that presents effective response strategies to negative reviews, they mostly overlook an extensive classification of response strategies. The first study consists of two phases and focuses on comprehensive response strategies to only negative reviews. The first phase is explorative and presents a correlation analysis between response strategies and overall ratings of hotels. It also reveals the differences in those strategies based on hotel class, average customer rating, and region. The second phase investigates effective response strategies for increasing the subsequent ratings of returning customers using logistic regression analysis. It presents that responses involving statements of admittance of mistake(s), specific action, and direct contact requests help increase following ratings of previously dissatisfied returning customers. In addition, personalising the response for better customer relationship management is particularly difficult due to the significant variability of textual reviews with various topics. The second study examines the impact of personalised management responses to positive and negative reviews on rating growth, integrating a novel method of multi-topic matching approach with a panel data analysis. It demonstrates that (a) personalised responses improve future ratings of hotels; (b) the effect of personalised responses is stronger for luxury hotels in increasing future ratings. Lastly, practical insights are provided