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This study aims to examine the factors driving the adoption of carbon management accounting (CMA) and various considerations that mediate its effectiveness in accounting and disclosure practices.

This study used an exploratory, cross-sectional, quantitative design. Academics, managements/executives, professional accountants, professional auditors and researchers served as the primary units of analysis. This study used a survey method to gather data through a structured online questionnaire. The data were analyzed using descriptive statistics and partial least squares structural equation modeling (PLS-SEM).

The results revealed that the factors driving the adoption of CMA directly influence the effectiveness of CMA practices, with a significant mediating effect of regulatory and ethical aspects. Furthermore, this study revealed the difficulty of accounting, quantifying and reporting carbon emissions and revenue generation from the trading of carbon credits. This highlights the critical role of standard-setters and academics in deciding the concrete methodology to promote uniformity in carbon disclosures.

The major limitations of this study are that it considered only the perception of experts and did not study the actual practices of CMA by considering companies that have already implemented CMA. Further studies should consider this aspect to validate the results of this study. Furthermore, the findings highlight the insignificant effect of economic, environmental and social aspects in enhancing the overall effectiveness of CMA. This is because of the limited number of factors considered in the study of such metrics. To overcome this limitation, future studies should consider wider aspects to validate the outcomes of this study.

The major contribution of this study is that it serves as a base input for business organizations, academics, researchers and regulatory authorities who are working to implement CMA strategies to reduce carbon emissions and promote net-zero business practices.

The outcome of this study is unique and new, as the subject matter of this study is in the nascent stage. The outcome of this study may become a significant valid input for regulators and policymaking companies to gain knowledge about CMA practices and motivate them to integrate CMA practices as part of their sustainability initiatives.

Synthetic aperture radar (SAR) imaging is the most computational intensive algorithm and this makes its implementation challenging for real-time application. This paper aims to present the chirp-scaling algorithm (CSA) for real-time SAR applications, using advanced field programmable gate array (FPGA) processor.

A chirp signal is generated and compressed using range Doppler algorithm in MATAB for validation. Fast Fourier transform (FFT) and multiplication operations with complex data types are the major units requiring heavy computation. Therefore, hardware acceleration is proposed and implemented on NEON-FPGA processor using NE10 and CEPHES library.

The heuristic analysis of the algorithm using timing analysis and resource usage is presented. It has been observed that FFT execution time is reduced by 61% by boosting the performance of the algorithm and speed of multiplication operation has been doubled because of the optimization.

Very few literatures have presented the FPGA-based SAR imaging implementation, where analysis of windowing technique was a major interest. This is a unique approach to implement the SAR CSA using a hybrid approach of hardware–software integration on Zynq FPGA. The timing analysis propagates that it is suitable to use this model for real-time SAR applications.