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According to the national balance sheets of the most advanced economies, despite a recent sharp decline in per capita net wealth, Italian private households present a higher rate among the wealthiest and least indebted in Europe. Recently, the COVID-19 outbreak caused a new leap in households' savings worldwide, particularly in advanced economies and Italy. This study underlines that using advanced analytics tools, household saving behaviour information, and big data analytics may support data-driven decision approaches addressing the management of complex relationships in the financial arena. More specifically, using exploratory and predictive analyses based on big data analytics and machine learning, this study aims to provide extensive customer profiling in the household saving sector in Italy, supporting a data-driven decision-making approach. A profiling of household savings has been defined using the information provided by big data analysis. To proceed in this direction, the hardware and software requirements necessary to perform data processing were considered in the first phase of the study. Data collection was performed according to the so-called extract, transform, load (ETL) process. The contribution of this study lies in the results obtained in terms of data analytics over a dataset that accounts for the purchasing behaviour of almost 20 million postal savers. The clustering algorithm is highly efficient and scales well for large datasets. K-means clustering can be implemented within the MapReduce computational framework. Therefore, the overall procedure proposed here can be easily extended to big data using parallel computing and software implementing MapReduce, such as Hadoop and Spark.

The lockdowns of several countries due to COVID-19 outbreak resulted in severe economic consequences, among which was the immediate general disruption of the international supply chain, with few exceptions. This article aims to investigate whether some supply chains were resilient or not and why, using a knowledge-based approach and specifically focusing on the role played by supply chain innovation in building resilience to disruptions, thanks to knowledge preparedness. The study is motivated by two main rationales: the unique situation of a global pandemic and the absence of studies providing grounded evidences of supply chain resilience in a worst-case scenario. The research is based on the assumption that knowledge preparedness introduces logistics/supply chain innovations and enables companies to prevent, detect, and respond to unpredictable negative events. By using a large-scale sample of European firms' data from the Eurostat and a multivariate regression analysis, the authors cross-study the effects of supply chain knowledge preparedness – based on innovation type and expenditures – on the international trade of goods from January to June 2020. The results confirm that the most resilient supply chains were those that had previously introduced innovations, a factor that strengthens the knowledge preparedness of firms when faced with unforeseeable supply chain disruptions.

Taking into account the increasing importance of digitalization to characterize companies’ competitive advantages, and the contextual growing research interest in digital transformation, this paper focuses on dynamic capabilities affecting firms’ digital innovation in terms of creation of new offerings, processes or solutions by using a wide range of digital technologies. By means of quantitative research on a sample of managers of 210 firms in Italy, the study performs an ordinary least squares regression to investigate whether and how different knowledge-based capabilities support the process to develop digital innovation, taking into consideration the moderating effect of social media. Despite some limitations, essentially due to the geographical focus of the analysis, the paper contributes to better understand the effect of digitalization in the distinguishing context of the Italian companies, providing useful insights to rethink firms’ innovation models.

Digital transformation has completely changed the demand/offering interaction in the travel industry, as well as largely affecting the customer journey. In this direction, “big social data” and user-generated content have become key sources of well-timed and rich knowledge supporting data driven decision approaches addressed the managing of complex relationships. Based on this theoretical framework, the paper suggests how to apply “big social data” in the tourist experience co-design, providing an increased value for the visitors and a better decision making approach for managers. In this respect, the field analysis concentrated specifically on user-generated content regarding the Pompeii Archaeological Site (P.A.S.), to trace valuable insights for the tourist experience. Based on double stage of research – netnographic analysis and a supplementary online survey – the study aimed to detect: (a) tourist perception on the P.A.S.; (b) random chat on the part of internet users (tourists and other browsers, not necessarily visitors) on the topic of the P.A.S.; (c) the main characteristics of the P.A.S. that attract internet user attention; (d) the main topics debated by influencers/opinion leaders managing online discussions on the P.A.S. managerial and theoretical implications were investigated highlighting the main limitations of the study as well.

The internationalization of R&D activities has become crucial for small and medium-sized enterprises (SMEs) to create sources of competitive advantage. This research aims to analyze the role of social capital and information technology (IT) in enhancing knowledge sharing and innovation capabilities in the particular context of SMEs with geographically dispersed R&D teams. The study uses structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (FsQCA) to investigate data from an online survey of 265 R&D managers in Italian manufacturing SMEs with responsibility for at least one international R&D team. The results reveal the critical role of structural social capital and IT in enhancing knowledge sharing and innovation capabilities. The research contributes to existing knowledge and provides useful insights for marketers by highlighting how social capital, also in combination with IT, strengthens SMEs' competitiveness even when they operate in a mature industry.