Ibrahim A. Abu-AlSondos

This study aims to determine the impact of green marketing (green perceived value), green products (green buildings), and environmental concerns on Jordanian consumers’ attitudes toward buying green buildings in Jordan. The research population includes all consumers in Amman, the capital of Jordan, who might be interested in buying such buildings. A convenience sample is used to collect data from the respondents by distributing the questionnaire among 400 consumers using Google Forms. 357 questionnaires were found valid for statistical analysis. The results of the multiple regression test showed that R equals 0.815, which indicated that green marketing and consumers’ attitudes toward buying green buildings in Jordan are positively and highly correlated, with a percentage of 81.5%. R square equals 0.664, indicating that the variation in green marketing explains 66.4% of the variance in consumers’ attitudes toward green buildings in Jordan. Moreover, the hierarchical multiple regression test showed that there is an increase in R and R2 values in the existence of product awareness as a moderating variable between green marketing and consumers’ attitudes toward buying green buildings in Jordan.

Type of the article: Research Article

Abstract
Business intelligence systems are becoming vital in Jordan’s insurance sector, driving efficiency, compliance, and data-driven decisions. This study investigates how institutional, technical, and cultural conditions influence the effectiveness of business intelligence implementation, especially in overcoming persistent data silos and fragmented legacy systems. A structured survey was conducted between September and December 2024 across major Jordanian cities, targeting BI managers, IT specialists, compliance officers, and operations analysts within insurance companies. A stratified sampling approach was used to ensure representation by firm size, BI maturity, and data silo severity, yielding 260 valid responses from 360 distributed questionnaires (72% response rate). This focus on professionals directly involved in BI implementation and evaluation ensured the relevance and depth of insights.
Partial Least Squares Structural Equation Modeling revealed that BI integration significantly reduced data silos (β = –0.482, p < 0.0001), improved operational efficiency (β = 0.413, p = 0.0003), strengthened regulatory compliance (β = 0.391, p = 0.0005), and enhanced decision-making effectiveness (β = 0.428, p < 0.0002). Mediation analysis confirmed that improved data quality partially explained BI’s impact on decision-making (β = 0.216, p = 0.0012). Moreover, the positive effects of BI were amplified in organizations with strong data-driven cultures (β = 0.183, p = 0.0026) and active top management support (β = 0.194, p = 0.0021). These findings underscore that technological solutions alone are insufficient; effective BI outcomes rely on an alignment of systems, culture, and leadership, offering critical insights for digital transformation in regulated industries.