The fast development of technologies shapes the way companies address and understand their customers’ needs, including the more and more pressing call for sustainability. If, by now, many organizations use the advantages of social media in their marketing strategies, newer technologies, such as Internet of things (IoT) wearables, are not fully used to their whole potential. Thus, we conducted two research studies—a qualitative one in the form of a focus group where eight different companies’ representatives took part, followed by a quantitative one in the form of an online questionnaire, where 84 (Small and Medium Sized Enterprises) SMEs and Large Enterprises answered. The main purpose of our research was to investigate companies’ attitudes and practices about using social media and IoT wearable technologies in developing organizational marketing strategies. The results indicate that, though there are some differences in the perception and use of social media and IoT wearables for developing marketing strategies, these differences are not marked between SMEs and Large Enterprises, but rather between micro enterprises and other companies with higher numbers of employees. Additionally, there are some differences noticed between companies operating in regional, national, or international markets.

In the context of the recent labor shortages in Eastern European countries, Romania included, companies, organizations and decision makers need to strongly address the issue of labor motivation for increasing worker performance and also for attracting the scarce labor resources. The main goal of the research is to explore new determinants of work motivation, such as regional sustainability and also individual factors related to individual expectations. Therefore, the responsive methodology used for this purpose implies a multilevel econometric modelling, in which the first level regards individuals, and the second one consists in development regions. Moreover, the role of individual factors is tested using Vroom’s theory of expectations and filling a gap in the existing literature on work motivation in developing, post-communist economies. The main findings prove that one dimension of sustainability, namely social sustainability has a significant impact on work motivation, alongside with four dimensions of individual factors. Economic and environmental sustainability have no significant impact on work motivation in the case of Romanian workers.

Artificial intelligence (AI) adoption in strategic sectors such as energy is often framed in optimistic narratives, yet its actual economic contribution remains under-quantified. This study proposes a novel, multi-stage methodology at the intersection of machine learning, statistics, and big data analytics to bridge this gap. First, we construct a media-derived AI Adoption Score using natural language processing (NLP) techniques, including dictionary-based keyword extraction, sentiment analysis, and zero-shot classification, applied to a large corpus of firm-related news and scientific publications. To enhance reliability, we introduce a Misinformation Bias Score (MBS)—developed via zero-shot classification and named entity recognition—to penalise speculative or biased reporting, yielding a credibility-adjusted adoption metric. Using these scores, we classify firms and apply a Fixed Effects Difference-in-Differences (FE DiD) econometric model to estimate the causal effect of AI adoption on turnover. Finally, we scale firm-level results to the macroeconomic level via a Leontief Input–Output model, quantifying direct, indirect, and induced contributions to GDP and employment. Results show that AI adoption in Romania’s energy sector accounts for up to 42.8% of adopter turnover, contributing 3.54% to national GDP in 2023 and yielding a net employment gain of over 65,000 jobs, despite direct labour displacement. By integrating machine learning-based text analytics, statistical causal inference, and big data-driven macroeconomic modelling, this study delivers a replicable framework for measuring credible AI adoption and its economy-wide impacts, offering valuable insights for policymakers and researchers in digital transformation, energy economics, and sustainable development.

In nowadays European context the challenges started from the severe disparities among countries, regions and socio-economic groups are increasing the pressure on both national and EU level authorities, leading to the conclusion that the current socio-economic systems have reached their limits. Thus, the social market economy (SME), “third path” which mixes the purely liberal market economy with the social economic model might be one viable solution. Historically, the model corresponds to the real economic policy of the German Federal Republic after the 1950s, thus it is sometimes called Rhine capitalism. Such a model might be both the solution for national-level European economies and for the entire Union and thus, for a successful implementation a two-step approach should be considered appropriate. Thereby, in the first stage an SME might be implemented at national level in as many as possible EU member states and in the second phase a SME might be created at the level of EU by aggregating the smaller national SMEs. Due to the fact that in a SME the weaker geographical regions and industries are encouraged so that “fair” distribution of wellbeing is reached, it is highly probable that such a socio-economic model might be the appropriate alternative to fuel a sustainable growth of the Romanian economy. Using county level data, from the National Institute of Statistics and from the National Office of the Trade Register, for the year 2015, and an aggregated index, we show that the Romanian economy is highly polarized with a few growth poles (islands) and a large number of underdeveloped units. Thus, it becomes obvious that these important disparities will hinder a future sustainable development and by consequence a clear “road-map” represented by the SME model might prove to be a viable solution for the Romanian economy.

The answer to the following question summarizes the research presented in this manuscript: “Are Romanian immigrants in the EU countries enhancing the foreign direct investment (FDI) inflows towards Romania?”, and as a consequence it makes the results of the paper a useful tool for all Romanian authorities dealing with one of the two topics: migration and foreign investments. To our knowledge, the paper provides the initial evidence supporting the hypothesis that Romanian immigrants in the EU countries can be regarded as “ambassadors” of the Romanian economy in attracting FDI (to Romania) from their adoption countries. The methodological approach relies on econometric modelling which reveals a positive and statistically significant relationship between the stock of immigrants and the number of FDI firms located in Romania and sourced from 15 EU economies, when controlling for several variables. The results could be useful both for companies and for Romanian policymakers that should target as source for potential foreign capital the economies which attract important flows of Romanian immigrants.