Several stakeholders, such as financial institutions, auditors, policymakers and markets, need transparent and comparable financial reporting to make effective decisions. Transparency and consistency of information will lead to improved accountability, internal discipline and governance. However, accuracy and transparency of financial reporting are compromised under conditions of crises and uncertainty. The nature of risks and disasters may differ, but if reporting standards are flexible and transparent, the adverse impact of such crisis can be moderated. Taking this aspect, Ikram ul Haq and Tahseen Anwer Arshi, authors of the first paper, "The Impact of Covid-19 on IAS 1 Presentation of Financial Statements", propose a revised financial statement structure to address the limitations of financial reporting, particularly in the context of Covid-19. The authors opine that transparency and consistency will improve the standards for financial reporting, while helping mitigate the negative impact of the risks involved and reduce the probability of anxiety and infectivity.

Financial efficiency is the most important feature for the sustenance of any firm. However, financial matrices are an outcome of operational efficiency. Since the proposal of 'factors of production' theory, economic literature has provided various methods to figure out the optimum combination of factors of production to be employed in any firm. Factor productivity theories are vastly employed to measure the operational efficiency of a firm. N S Sudesh and Saradhi Kumar Gonela, the authors of the second paper, "Measurement of Financial and Operational Efficiency: A Literature Review", have conducted a detailed and systematic review of various established methods of measuring the financial and operational efficiency of a firm.

The terms 'corporate failure' and 'financial distress' indicate the difficulty faced by firms in meeting their financial obligations; however, financial distress is a costly process preceding corporate failure. After experiencing financial distress, if a firm fails to recover, then it goes bankrupt. During the pandemic, many firms faced situations of financial distress. Considering the Indian textile sector in particular, Pooja Singh and Anindita Chakraborty, in the third paper, "Estimating Financial Distress in Textile Sector: Implication of Z-Score", examine the financial situation of textile firms using Altman's Z-score to predict the financial distress in the firms. The authors have also evaluated the significance of Z-score and its components in explaining the market value of the firms.

Anurika Vaish, Nishit Kumar Srivastava, Priyanshu Priyam Srivastava and Sarthak Sengupta, the authors of the fourth paper, "Deep Learning and Asset Allocation: A Bibliometric Analysis Using AHP Approach", feel that investing requires deep learning-based asset allocation. The authors have examined relevant studies on deep learning and asset allocation using bibliometric analysis and found the association between age and investment decisions, and based on their findings, they have proposed a ranking framework regarding preferred avenues for investment purposes.

Sireesha Mamidenna, the author of the last paper, "Special Purpose Acquisition Companies: An Overview of Their Structure and Legal Status in India", identifies the need for promoting Special Purpose Acquisition Companies (SPAC) in India and describes their current structure and legal status in the Indian context. The author opines that the current regulatory and legal frameworks in India are unsuitable for the promotion and suggests some key aspects to be brought in by the regulators, while prescribing the procedure for SPAC in India.