ADVANCED INTERNATIONAL JOURNAL OF BANKING, ACCOUNTING AND FINANCE (AIJBAF)

NAVIGATING THE POST-PANDEMIC GREENWASHING WAVE IN ENVIRONMENTAL REPORTING: A SCOPING REVIEW ACROSS BUSINESS, MANAGEMENT AND ACCOUNTING FIELDS

Mai Farhana Mior Badrul Munir — 2025-06-01

Recent years have seen a growing number of companies promoting their environmental sustainability efforts. However, these claims are often undermined by greenwashing activities that raised concerns about the reliability of their environmental reporting. Despite the growing number of studies on greenwashing, a comprehensive review that identify, summarize and critically evaluating its underlying drivers remains limited, particularly across the fields of business, management, and accounting. Addressing this gap, the present study aims to thoroughly reviewing trends in greenwashing research and examine the emerging factors driving these activities, especially in the post-pandemic context. Using a scoping review method, twenty articles from the Scopus database between 2018 to 2023 were analyzed based on specific inclusion criteria. The findings reveal the absence of universally accepted definition of greenwashing, reflecting its diverse interpretation across disciplines. Notably, there has been a surge in greenwashing-related publications, predominantly in Q1 and Q2 journals. Furthermore, corporate governance mechanisms have emerged as significant influence shaping greenwashing activities following the COVID-19 pandemic. By synthesizing current literature, this study provides valuable insights into the governance structures shaping the greenwashing activities. Additionally, this study outlines several significant research gaps, provides a foundation for future research and emphasize the need for more in-depth research to reduce greenwashing activities in environmental reporting.

THE ROLE OF DIRECTOR NETWORK AND COMPLIANCE RISK ON TAX AVOIDANCE: EVIDENCE FROM INDONESIA

Annisa Hayatun Nazmi Burhan — 2025-06-04

Research trend on social network in the context of tax compliance has been evolving gradually. Using social network theory, we employ network centrality to investigate the role of director network and compliance risk on tax avoidance. With 1,848 firm-year observations from year 2017-2022, we found that the positive effect of the director network on tax avoidance is weaker because of the compliance risk. It highlights that firms with compliance risk may restrain firm tax avoidance. Our findings add to the body of literature on social network and tax compliance.

EVALUATING COMPETITIVENESS ACROSS PUBLICLY LISTED COMPANIES USING KEY FINANCIAL METRICS: A DATA-DRIVEN APPROACH

Choong Kai Xin — 2025-06-01

In an increasingly competitive global marketplace, assessing corporate competitiveness through financial metrics is vital for investors, analysts, and policymakers. This study proposes a structured, data-driven framework to evaluate the competitiveness of publicly listed companies using key financial indicators. Specifically, it examines revenue, earnings, net profit margin, price-to-earnings (P/E) ratio, price-to-sales (P/S) ratio, earnings per share (EPS), earnings yield (EY), and dividend yield (DY). Data were sourced from a global dataset of 9,912 firms, refined to 4,256 companies post-cleaning. The study employed benchmarking via median and interquartile range (IQR) analysis to mitigate outlier distortion, classify company performance, and enable fair cross-comparison across firm sizes and sectors. Findings highlight strong correlations between revenue and earnings, and between P/E and P/S ratios, whereas relationships among EPS, EY, and DY were weaker. Diagnostic charts and comparative analysis revealed that large-cap and mid-cap firms typically outperformed smaller firms, though no single metric could holistically define competitiveness. Only two companies—BAWAN Group and Samsung Electro-Mechanics—met the refined criteria for high competitiveness across multiple metrics. This research contributes a replicable benchmarking methodology that integrates statistical and visual analytics to support informed investment decisions. It also addresses gaps in comparative financial assessment frameworks, especially for emerging markets. Future studies are encouraged to expand the dataset temporally and sectorally to further refine the model and enhance predictive utility.