Sustainable consumption behaviours in P2P accommodation platforms: an exploratory study

The Degree of Adoption of Business Intelligence in Romanian Companies—The Case of Sentiment Analysis as a Marketing Analytical Tool

The structural changes in the public communication space through the advent of the Internet and the further development of online commerce culminate today with the explosion of blockchain techniques and social networks. This communication space was quickly taken over by marketing tools, as demonstrated by the many marketing campaigns dedicated to these new communication channels. The development of online commerce and the emergence of social networks have allowed consumers to efficiently search for brands/products/services, compare them, express their point of view on them, and even give them grades. Due to the explosion of relevant data online, the changing business environment needs attention to interpret and extract relevant information. The application of sentiment analysis to public reaction in the online environment provides the researcher with how the authors of the analyzed texts (clients/beneficiaries) express themselves regarding the studied reference (product/service/organization/social theme and a feature of them). Along with the other metrics present in marketing, including digital marketing, the reports in the analysis panels of google analytics and social networks, sentiment analysis instantly provides the general and competitive context in which the product/service/theme evolves. In this article, two types of research have been conducted to highlight the benefits felt, but also the degree of knowledge, implementation, and use of sentiment analysis in online marketing analysis. One of the types of research was qualitative, carried out on 10 participants (specialists in the field of marketing), with the help of an interview guide. Qualitative research aims to find out the level of knowledge of sentiment analysis and the general degree of digitalization of Romanian companies, an indicator considered critical in the new post-pandemic business environment. The second research was quantitative and used to develop analysis by structural equations. For this, a questionnaire applied to a sample of 108 respondents was used. Through the analysis by structural equations, a conceptual model was developed that presents the main factors that are related to others and that contribute to the satisfaction of the users of the analysis of feelings for obtaining marketing data.

Analyzing Spatial Variance of Airbnb Pricing Determinants Using Multiscale GWR Approach

A sharing economy accommodation service like Airbnb, which provides trust between strangers to connect them for profiting from underutilized assets, was born and has thrived thanks to the innovations in the platform technology. Due to the unique structure of Airbnb, the pricing strategies of hosts are very different from the conventional hospitality industry. However, existing Airbnb pricing studies have limitations considering the varying scale of operation among hosts, spatial variances in pricing strategies, and crucial geographic information for estimating the influence of the pricing variables, as well as ignoring inter-city variances. In this research, we explored the spatially heterogeneous relationship between price and pricing variables using an innovative spatial approach, Multiscale Geographically Weighted Regression (MGWR). Analysis results for Airbnb listing in Log Angeles and New York in the US showed the effectiveness of MGWR regarding estimating the influence of pricing variables spatially. By revealing spatially heterogeneous and dependent relationships, this research fills gaps in Airbnb pricing research and deepens the understanding of the pricing strategies of the hosts.