Browsing by Author "Al-Alawi, Alamir N."
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- Could the ‘Spinner Innovation’ and ‘Triple Helix’ Models Improve System Innovation?Publication . Figueiredo, Ronnie; Soliman, Mohammad; Al-Alawi, Alamir N.; Fatnassi, TarekAlthough several prior studies have outlined and examined models associated with knowledge and innovation in different fields, the literature lacks any solid insights combining the Triple Helix model and the Spinner Innovation model and ascertaining their relevance to innovation. This article correspondingly presents an unprecedented alternative based on two innovation models, analyzing and structuring a process to innovate in different economic sectors. In doing so, this paper seeks to explore how this integration between Spinner Innovation and Triple Helix models could have a significant influence to improve system innovation. We collected data from the Scopus database spanning the period between 2012 and 2021 to study the integration of the models. The analysis identifies how these models differ but are nevertheless of complementary importance for developing regional and national economies through combining the “helices”, the “fidgets” and the framework integrating both models and their components to system innovation.
- The Impacts of Geopolitical Risks on the Energy Sector: Micro-Level Operative Analysis in the European UnionPublication . Figueiredo, Ronnie; Soliman, Mohammad; Al-Alawi, Alamir N.; Sousa, Maria JoséEnergy prices play a crucial role in combating geopolitical risks, especially for the major suppliers of energy resources. However, energy prices display a bilateral relationship with geopolitical risks in any economy. Any hike in the price of energy stimulates geopolitical risk factors and visa-versa. The consequences adversely impact economies and bring forth international tensions. This paper bridges a gap between the influence of geopolitical risks relating to energy and international tensions by analyzing micro-level operational measures. We deploy an empirical model to predict the energy sector and possible risk factors incorporating Eurostat data on twenty-seven states, from 2011 to 2020. This study collected a different energy variable to support the multiple regression model constructed by the “blocks” (hierarchical linear regression) method. The results suggest that geopolitical risks cause adverse effects on both the energy and other corporate sectors. The future direction of this research is to estimate how statistical model relationships may assist the corporate sector, and investors, in adopting mitigating measures to control upcoming geopolitical risks due to energy risks caused by geopolitical unrest.