Although large amounts of data are now available to companies, mere possession of these data is not sufficient, and, for better business decisions, it is necessary to perform thorough data analysis. Nowadays, Social Networks Services (SNS) have become important data sources. The rapid growth of SNS has led to their wide use in various research trends in social sciences. In the present study, we aim to enhance the current understanding of the possibilities offered by social data for brand communication analysis in the financial sector. To this end, a traditional methodology and a digital methodology are used to investigate the brand image of financial entities. The traditional methodology is the Periodic Evaluation of the Image (PEI). The digital methodology is sentiment analysis, a machine learning technique for Big Data analytics in social sciences using an algorithm developed in Python. The data are analyzed using both methodologies, and then their results are compared. The findings suggest that, while the results obtained using the method based on Big Data are consistent with the results obtained with the traditional methodology, the former method allows for an easier and faster data analysis. The limitations of the present study relate to the size of the sample, the studied sector, and the scope of reviewed literature.

In recent years, digital marketing has transformed the way in which companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the Internet has given rise to new business models based on the bidirectionality of communication between companies and Internet users. Digital marketing, new business models, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies have started to see the digital ecosystem as not only their present, but also as their future. From this long-term perspective, companies are concerned about sustainability and the growth of their business models. There are new business models on the Internet that support social causes, new platforms aimed at supporting social and sustainable projects, and digital advertising campaigns promoting sustainability. The overarching aim of this Special Issue was to analyze the development of these new strategies as well as their influence on the sustainability of digital marketing strategies. Therefore, we aimed to analyze how companies adopt these new technologies in a digital environment that is increasingly concerned with the sustainability of business models and actions on the Internet.

The uncertain economic situation that was experienced because of the global financial crisis in 2008 and the exponential growth in the use of new technologies in different industries has caused some individuals to become entrepreneurs through the development of a variety of new skills. The main objective of this research paper is to discover what factors significantly determine the degree of fulfilment of expectations for entrepreneurs who have graduated from the incubator programme. Entrepreneurs may expect that a business incubator programme is a key element for their economic development and that it provides them with skills for good image and professional recognition. From the methodological point of view, a survey technique was conducted on 100 entrepreneurs who had already graduated from different business incubator programmes in Madrid, Spain. For the data exploration phase, an Exploratory Factor Analysis was used, which made it possible to identify 10 factors. With the Multiple Linear Regression analysis, these newly created and named factors were ordered by level of importance. The main findings show that most statistically significant factors consist of variables that are related to behaviour, attitude and hard skills (trained).In turn, results demonstrate that soft skills (innate) also play a certain role for fulfilling expectations for developing a successful company. Study confirms that continuous managerial training programmes for entrepreneurs in the twenty-first century are a substantial part for obtaining new skills, knowledge, insights, experiences, and change of behaviours and attitudes of different aspects needed for successful company leadership and management.

Purpose: This empirical research aims to provide organisations with useful information on how teleworking has affected employee commuting, allowing organisations to adapt working conditions to the new social context. This research sets out to provide evidence on the behaviour of teleworkers in terms of the mode of transport chosen when commuting to work physically.Design/methodology/approach: This research is based on a survey conducted in Madrid based on a theoretical approach grounded in the theory of planned behaviour (TPB) and discrete choice models. Exploratory factor analysis (EFA) and discriminant analysis have been used to determine the variables that influence the mode of transport chosen by teleworkers when commuting in person.Findings: The results indicate the prevalence of private car use by teleworkers when working at the office, finding that attitudes and satisfaction with modes of transport significantly influence their choice. The characteristics and frequency of teleworking, however, are not significant, which indicates that teleworkers attach greater importance to their preferred mode of transport, regardless of the disadvantages.Originality/value: This research provides empirical evidence using an inductive approach to understand the challenges that organisations are facing with regard to teleworking since commuting behaviour has changed for teleworkers. This requires organisations to give significant reconsideration to the issue of commuting as an important component of working time that could condition employee satisfaction and, therefore, the retention or recruitment of talent. Furthermore, residence and mobility changes afford organisations better access for recruitment, notwithstanding urban planning implications.