As part of the burgeoning research on green innovation (GI) and its influence on competitive advantage (CA), this paper examines the moderating effect of research and development (R&D) on this nexus. Our framework identifies five critical capabilities that contribute to CA, namely, firm image, labor costs, product differentiation, product quality, and market share. Using a novel bias‐correction methodology, we examined the Spanish Technological Innovation Panel (PITEC in Spanish) database from 2003 to 2016 to determine whether GI practices foster CA. Treatment‐effects analyses, including propensity score matching and fuzzy difference‐in‐differences (DiD), demonstrated that R&D expenditures have a positive moderating effect on CA when controlling for the covariates GI practices, firm age, and firm size. This research advances our understanding of the interplay between GI practices, R&D investments, and CA and, as such, has implications for decision makers aiming to create sustainable CA through GI. Our findings are also highly relevant for firms seeking to remain competitive in today's evolving business climate.

This study explores the scope of social entrepreneurship and examines how social entrepreneurship contributes to sustainable development. Using analysis and relevant comparisons, it identifies main actors in the socialenterprise ecosystem, as well as how the entrepreneurial ecosystem adapts to social enterprises. Additionally, this study reveals how social enterprise applies in the renewable energy domain and identifies its main advantages, as well as major barriers and how to overcome those barriers. Fundamentally, this study’s findings have significant implications, for academics and practitioners in the social field. It highlights the role of social entrepreneurship as a balanced approach for long-run increases in quality of life, and it follows innovative techniques and methods to meet social needs, inherently motivated by ethical factors in equality and social fairness. On the other hand, main challenges that could confront social entrepreneurship include government regulations, problems adopting advanced technology and infrastructure, external competitive threats, limited access to public funds or loans, lack of awareness and acquisition of skills and knowledge, and inadequate knowledge about social impact measurement techniques. This research also illustrates how to adapt Isenberg's model for the entrepreneurial ecosystem in the social enterprises, which shows that the evolution of social enterprises does not occur in a vacuum; rather, the growth of social enterprise ecosystems occurs through interactions and networks with various actors in different fields such as financial politics, law, and academia. Finally, we review the practical applications of social enterprises by highlighting the main benefits of RE social enterprises: energy savings, community awareness, and the creation of favorable social externalities in rural and developing areas.

This piece of work provides new findings about the effects of interactions between efforts to innovate and foreign direct investment on the results of innovation in Spanish firms. Examples of beneficial outcomes would be patents, as well as new products and processes. In addition, consideration will be given to the innovation activities that can favour from foreign direct investment in such a way as to attain innovation objectives of this sort. The source of the information used is PITEC, the Spanish Panel for Technological Innovation, together with figures from DataInvex, which contains the official statistics on foreign investment and other trade figures, provided by the Spanish Ministry of Commerce. In this study, we use logistic regression models to explain the impacts that attempts to innovate have upon the absorption of the foreign direct investment to attain the innovation outcomes. R&D expenditures, external collaboration, and public funds for innovation favour the absorption of Foreign Direct Investment to achieve beneficial outcomes from the innovation.

Many investors have relied on Bitcoin as a hedge against inflation. However, differences in inflation measurement and monetary policies across countries make it difficult to determine whether Bitcoin effectively serves as an inflation hedge. This study examined Bitcoin’s effectiveness as an inflation hedge in the United States and India using monthly data on Bitcoin returns and Consumer Price Index (CPI) changes from January 2015 to December 2024 (N = 118, after first-differencing and lag alignment). The study employed Ordinary Least Squares (OLS) models, bivariate Vector Autoregression (VAR) Granger causality tests, Bai–Perron Structural Break Analysis, Impulse Response Functions (IRFs), and Quantile Regression analyses. The findings revealed no significant relationship between CPI and Bitcoin returns in either the United States or India, providing no empirical support for the Fisher Hypothesis. However, Granger causality results showed that lagged Bitcoin returns significantly predicted future U.S. CPI values, while no such relationship was observed for India. The predictive power of the model for the U.S. was lost after October 2022 due to the crypto winter phenomenon. This indicates that Bitcoin is not used as a hedge against inflation but is rather considered a financially driven information asset, which is subject to market influences.

This paper estimates the effect of gender diversity on firm‐level environmental innovation. We use a large Spanish panel data and construct an inverse‐covariance‐weighted environmental innovation index. Identification comes from persistent within‐firm increases in women's representation, measured relative to a 2‐year rolling pre‐event baseline. Across several difference‐in‐differences estimators, a 5% increase in women's share of in‐house R&D personnel is associated with an increase in environmental innovation of 1.2–1.6 points. This corresponds to approximately 3%–4% of the sample mean and builds gradually over the years, consistent with a durable reorientation of innovation effort rather than a transient compositional change. The corresponding evidence for the overall female employment share is weaker and estimator‐sensitive. Empirical Bayes analysis shows that firms with larger internal underrepresentation of women in R&D have lower environmental innovation. The evidence suggests that the relevant margin is not simply gender diversity in the firm, but gender diversity inside the innovation‐producing core.