The circular economy (CE) aims to reduce environmental degradation by ensuring the continuous use of materials and energy resources, aligning with the decarbonization agenda. However, despite the rising acceptance of CE concepts, the economic and managerial aspects remain underexplored in policy and practice. Therefore, this study seeks to bridge the knowledge–practice gap by studying how technology-driven innovation, renewable energy, and energy efficiency interact with CE principles to advance sustainable environmental connections in a detailed manner. The economic analysis of this study was conducted using two base and moderation models, utilizing global data from 78 developing and developed countries, and applying Fixed Effect, Random Effect, and Generalized Method of Moments estimates. The samples were selected based on data availability from internationally recognized databases from 2010 to 2021. The key findings suggest that technology-driven innovation and renewable energy reduce carbon emissions, whereas gross domestic product (GDP) growth and energy efficiency show no standalone positive effects. Notably, moderation effects reveal that the integration of technology with GDP promotes sustainability outcomes, but energy efficiency and renewable energy interact negatively with emissions, a contradictory result warranting further policy investigation. CE-driven innovation promotes decarbonization by striking a balance between environmental preservation, economic expansion, and technology uptake. This study emphasizes region-specific techniques and offers policy insights for combining the CE with natural capital and green GDP. It increases the knowledge of how circular business models powered by technology support sustainable growth and the shift to a circular economy.

We evaluate the efficiency of mutual fund managers of 20 different classes of management styles to identify the most efficient strategies and to propose an optimal pattern in selecting the funds by investors. We collect monthly data of 17,686 US mutual funds for a five-year period 2005–2010 to minimize the impact of survivorship bias and use Data Envelopment Analysis (DEA) model to evaluate the mutual fund performance. The set of considered inputs comprised “variance”, representing the mutual fund risk, and “turnover, expense ratio and loads indicators”, reflecting the mutual fund costs and fees. Two kinds of outputs are taken into account by our DEA model, “portfolio return” and “stochastic dominance indicators”. As a unique contribution, we state the benefits of the DEA approach in the DARA, CARA, and IARA framework, and evaluate the efficiency of mutual funds based on fund strategies as well as the performance of best mutual funds among their group. The evidence shows that the efficiency scores of technical, management, and scale are respectively 0.81, 0.921, and 0.874 for the DARA model, while the efficiency scores of two models of CARA and IARA are negligible. Also, we rank each management strategy in any model based on two methods – the number of referencing and the weighted value so that the managers of inefficient strategies must pattern the managers’ ability of reference (efficient) strategies to improve their efficiency on the fund market in future.

The Mudharabah Deposit Rate Behaviour in Relation to the Conventional Deposit Rate (Gelagat Kadar Deposit Mudharabah Berhubung dengan Kadar Deposit Konvensional)