Partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were used to uncover the determinants of customers’ overall positive image of green hotels, which can affect behavioral intentions. A sample of 323 customers of 54 four- and five-star “green” hotels in the Sultanate of Oman were surveyed. The findings can explain the complex process shaping customers’ perceived image. The fsQCA analysis shows that the overall positive image of green hotels was driven by the interaction of two core conditions, environmental values and cognitive image, and one peripheral condition, low-carbon knowledge. Together, these factors are sufficient to form a favorable image of eco-hotels and could make a favorable affective image unnecessary. The PLS-SEM approach clarifies that this process takes place through an indirect mechanism wherein environmental values and low-carbon knowledge shape customers’ cognitive image, which then boosts the overall positive image of eco-hotels. Such comprehensive insights address the gap in the body of literature vis à vis the influence of customers’ psychological factors through cognitive and affective images. Theoretical and practical implications are examined.

Energy 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.

Although 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 purpose of this study is to investigate the impact of stress factors on entrepreneurial failure and to examine the relationship between prior entrepreneurial failure and future fear of failure. This study takes a novel approach by considering the moderating role of social support on this relationship. We employed the least squares–structural equation modeling (PLS-SEM) technique to analyze the responses of 162 failed entrepreneurs in Oman. Our findings demonstrate that stress factors in all four dimensions (managerial and planning elements, working capital, competitive environment, and growth and overexpansion) have a significant impact on entrepreneurial failure. Moreover, the results reveal that prior entrepreneurial failure is positively related to fear of failure. However, social support has a crucial moderating effect on the relationship between prior failure and present and future failure-related anxiety, reducing the influence of prior entrepreneurial failure on entrepreneurs’ fear of failure. This study contributes to the theoretical understanding of the antecedents and outcomes of entrepreneurial failure and offers practical implications for policymakers and practitioners seeking to promote entrepreneurship and reduce failure rates.