Editorial Board

A Refereed Monthly International Journal of Management

Measuring The Impact of Impairment of Assets on Profitability of Selected BSE and NSE Listed Companies Dr. Vineet Chouhan Associate Professor Unitedworld Institute of Management, Karnavati University, Gandhinagar, Gujarat-India Email: vcpc2008@gmail.com Corresponding author Dr. Pushpkant Shakdwipee Professor, Pacific Institute of Management Pacific Academy of Higher Education and Research University Udaipur, Rajasthan-India Email: pushpkant1976@gmail.com Abstract The AS, IAS and IFRS prescribe the procedure to be applied to ensure that the assets of an enterprise are carried at an amount not exceeding their recoverable amount. The standard defines recoverable amount as higher of net realizable value and value in use but if the book value of an asset is less than either of these amount than the asset is not impaired. These standards include only fixed assets for testing of impairment. This paper measures the Impact of Impairment of Assets in select BSE and NSE Listed companies. For this purpose a sample of all BSE and NSE listed companies were taken for the period of 9 years and out of them only 10 companies have made an impairment which is measured in the paper using statistical tool ANOVA and the analysis revealed that 2 independent variables EPS and NP are showing as accounting variables putting the impact on the impairment of the company’s assets and further the Tata Steel Ltd followed by the Oil & Natural Gas Corporations Limited have made the maximum amount of impairment during the period of the study. Keywords: Impairment, Tangible Assets, Intangible Assets, BSE and NSE listed companies. Introduction When an asset suffers impairment, its service potential is reduced. There is a need for recognition of this economic event of a reduction in service potential as a loss. If impairment loss exists, it should be debited to profit and loss account and this loss is also deducted from the carrying value of the asset in the balance sheet. The downward revised carrying value of the asset is to be depreciated over its remaining estimated life. These standards support reversal of impairment loss when the value of an impaired asset is recovered but the reversal is allowed up to the extent of the amount of impairment loss. The enterprise has to check impairment loss on assets at each balance sheet date whether there is an indication of impairment. For these indications, Internal and external factors are available to check whether the asset is impaired or not. Internal factors like obsolescence or physical damage of assets, outdated assets, plan of discontinuation or restructuring plan and decline in cash flow from an asset. External factors like decline in asset market value change in the technological, market, economic or legal environment, increase in market interest rate and another market rate of return on investment and the carrying amount of net assets exceeds its market capitalization. If there is such type of indication is available, then the enterprise is required to calculate impairment loss after estimating the recoverable amount. The revaluation of assets by an enterprise will prevent overstatement of the balance sheet but there is more subjectivity involved in the identification of impairment indicators, to reduce such subjectivity the standard’s provision being applied creatively which mislead the information of an enterprise. Creative application of provision may defeat the object of the standard. The major part of these standards is to provide improved quality of corporate financial reporting through the promotion of greater transparency in preparation and presentation of financial statement. It helps the user to take an improved economic decision because users have major information regarding that enterprise. This standard promotes the better allocation of capital and ultimately it leads to economic growth as well as greater social welfare. If these standards implemented properly, it will bring significant improvement in the quality of both balance sheet and income accounting but in the regulation of these standards, some enterprises face difficulties regarding inadequate guidance in the implementation of this standard. These standards explain that impairment should be check when there is an indication of impairment. To identify these indicators an enterprise has to consider at internal and external factors. It is problematic in some situation to find an indicator of impairment. Another problematic situation is identifying the recoverable amount from such an asset through value in use or net realizable value. For this recoverable amount expected future economic benefit from the use of the asset or dispose of an asset is very difficult to estimate because along with expected Future economic benefit, an entity has to consider an appropriate discount rate for calculation of discounted future economic benefit. It is more difficult to judge all these factors in difficult asset structure enterprise and this process is also likely to be costly as well as time-consuming. Major issues in accounting for impairment of intangible assets because intangible assets do not have physical existence but they have the ability to contribute to the earning capability of an enterprise as an Example of patent, goodwill, trademark, copyright. It is a complicated task to test the impairment of intangible asset especially when it comes to testing goodwill for impairment because goodwill cannot be separated from the enterprise owing it. Thus, this paper measures the level of Impairment of Assets of the BSE and NSE index listed companies. Reviews of Literature As the accounting standards changed towards the aim of enhancing the relevancy and transparency of financial reporting, asset impairment was one of the most controversial and significant fields in the sphere of financial accounting (Barth, 2025; Srivastava, 2025). The initial arguments that existed with regards to impairment accounting were the issues of inflated values of assets and the late reporting of asset losses (Barth, 2025; Bagna et al., 2023; Orthaus et al, 2023). The move to impairment-based standards was a radical change to the mechanical allocation of cost to the valuation-based system of accounting but this came with effects of management discretion and judgment which have been studied widely in previous literature (Västertun & Pitsinki, 2025; Chan et al., 2023; Görlitz & Dobler, 2023). Another major turning point in impairment accounting was the substitution of systematic goodwill amortization by impairment only approach. Li and Sloan (2017) present some solid arguments to support that this regulatory change especially the shift to SFAS 142 essentially changed accounting and valuation of goodwill. The goal of the standard was to increase the value relevance by removing amortization periodically and establishing an impairment test that relies on fair value (Maroun et al., 2022). But Li and Sloan (2017) show in practice that the new regime created tangible overstated balances of goodwill and untimely impairments recognition. Their results indicate that there is a high probability that managers took advantage of the discretion that was in impairment testing to delay the write-downs, and in the process, artificially inflated earnings and stock prices. More crucially, the research uncovers that the delay in the goodwill impairments was not well predicted by the investors, as inefficient interpretation of impairment-related disclosures in the market. Although much focus has been given to impairment, scholars have also highlighted that the impairment issue is far much more than the issue of goodwill to include long-lived tangible and identifiable intangibles. According to Massoud (2015), the fact that assets like buildings, land, and equipment are prone to impairment is attributable to a combination of such factors as technological obsolescence, augmented competition, regulatory, and physical damages. In his comparison of the impairment rules in GAAP and IFRS, Massoud (2015) highlights that the process of impairment recognition is complicated, which is why recoverability tests and measurement provisions must be followed before impairment losses are recognized (Hodder & Sheneman, 2022). This text emphasizes the fact that impairment is not a one-off accounting event, but a continuous assessment procedure that requires an objective and sound judgment and internal controls (Kelly & Larres, 2025). The literature developed, and its maturity saw scholars starting to investigate the place of governance structures and valuation mechanisms in the formation of impairment-related decisions. Cotter and Richardson (2002) discuss the question on whether boards of directors in their asset revaluations are more reliable than external independent appraisers. They use Australian data and discover that independent appraisers are more often used on re-evaluation of land and buildings, whereas directors re-evaluate investments, plant, equipment and identifiable intangible. This tendency is explained by the fact that the firms are using knowledge of directors that is specific to assets. Nonetheless, the research does indicate that plant and equipment revaluations conducted by independent appraisers are more effective than those conducted by the directors implying that the governance system and valuation knowledge is key in the credibility of the asset values. These results support the conclusion that not only accounting standards influence the recognition of impairments but also the organizational governance arrangements (Bonacchi et al., 2023; Mora et al., 2022). In addition to governance and reliability of valuations, scholars have also resorted to analytical and quantitative studies in the attempt to learn more about the impairment processes. Azzaz et al., (2015) also present a new model through the application of financial mathematics to the impairment accounting under the IFRS. Through the modelling of impairment events with the help of a Black-Scholes framework, they obtain explicit impairment probability, impairment expected value, and distributional characteristics of impairment losses. Their work in this field shows that impairment events may be studied with the help of stochastic valuation methods, which is a gap between accounting and financial economics. The strategy is capable of expanding the perspectives of impairment risk, especially financial instruments and equity securities, and the complexity of impairment research is increasingly becoming more sophisticated. The other literature trend emphasizes on the interrelation between impairment accounting and fair value measurement of liabilities (Hartmann, 2022; Hodder & Sheneman, 2022). Cedergren, Chen, and Chen (2019) examine the implication of debt valuation adjustments (DVA) according to SFAS 159, according to which the companies are identifying the gains or losses that may result due to the alteration in the credit risk of the companies themselves. Opponents of DVA have contended that that such gains are identified when the credit risk of a firm increases have counterintuitive effects on income. Cedergren et al. (2019) show that the unrecognized asset value (UAV) moderates this relationship. Their results indicate that at low levels of UAV, equity returns are positively related to DVA, but the relationship becomes less strong and later becomes negative as the UAV rises. This paper shows that impairment, valuation adjustments and unrecognized asset values together affect reported performance and market valuation. Conservatism and accrual processes research has also added theoretical knowledge to impairment accounting. According to Byzalov and Basu (2016), conditional conservatism forms a part and parcel of normal accrual behaviour, which is often not modeled. They argue that they are recognized by unrealized losses represented by disaggregated asset write-downs especially in small asset pools (Hodder & Sheneman, 2022). The fact that impairment recognition is a systematic form of conservatism, and not the arbitrary action of managers, is supported by their empirical evidence (Orthaus et al., 2023; Hodder & Sheneman, 2022). Furthermore, they demonstrate that the segment level and quarterly variables are incrementally informative of the firm level accruals indicating that impairment decision-making processes are affected by regular patterns of poor economic indicators and not by extraordinary events. Another issue that has been created by the shift to impairment-only accounting regimes is an issue of valuation methodology and conceptual consistency. Lander and Reinstein (2003) examine the implication of SFAS 142, stating that even though the standard enhances the matching of revenues and expenses, the standard imposes a lot of burden on accountants to choose suitable valuation models. They juxtapose discounted cash flow and remaining income methods of measuring goodwill impairment and state that failure to adopt the right model can discredit the accuracy of impairment reports (Grundmann, 2024). Their publication illuminates the conceptual and practical issues involved in the application of the impairment standards in the intricate business conditions. Some ethical issues regarding the impairment decisions have been analysed in terms of adoption of the IFRS. Giner and Pardo (2015), who research Spanish-listed firms in the period of the economic crisis, find that when managers are reporting goodwill impairment losses, their discretion is exercised, and only at opportune time. Their results show the big-bath and income-smoothing strategies and such strategies are dependent on firm size and macroeconomic conditions. The research also questions the ethical aspects of impairment-only regimes under economic pressure and when managerial interests of earnings manipulation can be higher. The regulatory analysis has been relevant in influencing the impairment practices. Hurtt, Kreuze and Langsam (1999) record heightened interest of the U.S. regulators towards disclosures that were made on impairments following claims that had been raised by the Securities and Exchange commission. Their analysis of Fortune 500 companies indicates that there is tremendous differentiation in the disclosure quality indicating that adherency to the impairment standards does not guarantee transparency and comparability. This supports the argument that disclosure quality is equal to recognition rules in explaining the usefulness of impairment information. The post-IFRS adoption research still demonstrates not completely resolved problems in impairment accounting. Coming to comment on subsequent studies, Zhuang (2016) expresses concern over the application of book-to-market ratios as an indicator of impairment, the degree of discretion of the managers in the recognition of impairment, and the interpretation of the increase in impairment recognition after the implementation of IFRS. Such issues indicate that impairment accounting is an area of controversy and dynamism, which needs more empirical research. Rezaee, Smith, and Lindbeck (1996) give early empirical evidence on the financial effects of impairment by examining 935 impairment write-downs reported by 670 companies after the enactment of SFAS 121. Their results show that impairment losses can be huge, in other instances more than reported earnings by several folds. Furthermore, the industry classification turns out to be influential on the financial effect of impairment, which highlights the industry-specific character of the effects of impairment. The literature is a composite of a complex and delicate image of asset impairment accounting. Although the introduction of impairment standards has been intended to improve the relationship by making them more relevant and transparent, empirical evidence indicates that managerial discretion, governance structures, and valuation issues, as well as macroeconomic conditions, have a substantial impact on impairment recognition and reporting. The majority of the available research is about goodwill, valuation impacts, and market responses, but little is said about the long-term effect of impairment on the profitability of firms. More than that, most of the empirical data is based on developed markets, and there is a gap in the factor of impairment behavior and its profitability in the emerging economies. It is against this background that the current study builds upon the available literature by investigating how the asset impairment affects the profitability indicators of the specific BSE and NSE listed companies. The study bridges a gap by concentrating on the Indian context under Ind AS, and it is significant to understand whether the asset impairment only re-arranges the reported earnings or it has any significant implications on business and financial performance. Research Methodology The data was gathered first form the 50 companies listed in BSE and NSE indexes. Out of the 50, only 10 companies have shown their impairment data for their Tangible and intangible’s impairment. These companies include the followings: 1. Asian Paints Ltd. 2. Bharti Airtel Ltd. 3. Coal India Ltd. 4. Hindalco Industries Ltd. 5. Larsen & Toubro Ltd. 6. Mahindra & Mahindra Ltd. 7. Oil & Natural Gas Corporations Ltd. 8. Sun Pharmaceutical Industries Ltd. 9. Tata Motors Ltd. 10. Tata Steel Ltd. The data were gathered for the period of 9 years from March 2017 to March 2025. It includes the variables such ae Impairment, NP, EPS, ROA, ROE, ROCE, CR and DER. Thus the above 10 companies were included in the further steps of the research work. The hypotheses were created and later the data were analysis using the Multiple regression and ANOVA tools using SPSS software. The results of the analysis is presented in the next part of the study. Data Analysis on Comparing Impact of Impairment on Profitability Further the impacts of impairment on the profitability of the companies were measured. The details are provided as under: Table-1: Comparing Impact of Impairment on Profitability Company Name Year Total assets Impairment of assets % of impairment Profit % of impairment Asian Paints Ltd. Mar-17 8168.69 18.59 0.22758 1262.76 1.47217 Mar-18 9040.63 14.64 0.16194 1427.33 1.02569 Mar-19 10696.3 52.45 0.49036 1769.36 2.96435 Mar-20 12559.4 52.45 0.41761 1966.64 2.66699 Mar-21 13930.2 52.45 0.37652 2051.73 2.55638 Mar-22 16398.8 52.45 0.31984 2167.31 2.42005 Mar-23 16310.3 52.45 0.32158 2723.45 1.92587 Mar-24 20554.9 52.45 0.25517 3178.15 1.65033 Mar-25 23277.1 66.07 0.28384 3053.24 2.16393 Bharti Airtel Ltd. Mar-17 187958 263.7 0.1403 2498.3 10.5552 Mar-18 205704 0 0 5053.1 0 Mar-19 233348 0 0 5826.4 0 Mar-20 244580 263.7 0.10782 3196.5 8.24965 Mar-21 265094 264 0.09959 1122.6 23.5168 Mar-22 288406 263.7 0.09143 1331.9 19.7988 Mar-23 371529 263.7 0.07098 -30002 -0.879 Mar-24 365964 263.7 0.07206 -12271 -2.1489 Mar-25 375903 0 0 5882 0 Coal India Ltd. Mar-17 106871 759.23 0.71042 15111.6 5.02414 Mar-18 113098 1184.2 1.04706 13726.6 8.62704 Mar-19 115048 0 0 14267.9 0 Mar-20 121559 0 0 9281.53 0 Mar-21 128277 0 0 7038 0 Mar-22 135969 0 0 17466.4 0 Mar-23 152356 0 0 16701.5 0 Mar-24 164476 0 0 12705.1 0 Mar-25 182826 0 0 17387 0 Hindalco Industries Ltd. Mar-17 141283 536.76 0.37992 2128.2 25.2213 Mar-18 147091 1370.46 0.93171 83.85 16.3442 Mar-19 149151 0 0 -873.04 0 Mar-20 154098 0 0 1907.44 0 Mar-21 154609 0 0 6207.96 0 Mar-22 160608 0 0 5495 0 Mar-23 177957 0 0 3763 0 Mar-24 199837 0 0 3478 0 Mar-25 233732 0 0 13724 0 Larsen & Toubro Ltd. Mar-17 173115 61.15 0.03532 4875.4 1.25426 Mar-18 198121 13.15 0.00664 4963.68 0.26492 Mar-19 197679 48.1 0.02433 5534.86 0.86904 Mar-20 220551 151.1 0.06851 6880.77 2.19598 Mar-21 253720 266.02 0.10485 8440.29 3.15179 Mar-22 288403 272.84 0.0946 10237.6 2.66508 Mar-23 318224 286.07 0.0899 10822.3 2.64333 Mar-24 326418 1023.86 0.31367 12906.9 7.93267 Mar-25 334390 286.06 0.08555 10291.1 2.7797 Mahindra & Mahindra Ltd. Mar-17 88738.6 2552.65 2.87659 4323.38 59.0429 Mar-18 95374.3 2573.56 2.69838 2595.48 99.1555 Mar-19 102076 0 0 2708.47 0 Mar-20 119306 0 0 3151.13 0 Mar-21 142734 0 0 6850.53 0 Mar-22 167820 0 0 4650.33 0 Mar-23 172002 0 0 -1348.3 0 Mar-24 173279 0 0 235.73 0 Mar-25 180840 0 0 5397.22 0 Oil & Natural Gas Corpn. Ltd. Mar-17 365520 2549.24 0.69743 26653 9.56454 Mar-18 360337 887.76 0.24637 17673 5.02327 Mar-19 390261 4273.35 1.095 12235.8 34.9249 Mar-20 496047 3096.71 0.62428 26359.1 11.7481 Mar-21 526960 2230.14 0.42321 23354.9 9.54894 Mar-22 560329 3513.19 0.62699 30509.8 11.515 Mar-23 527057 7971.67 1.51249 10523.1 75.7539 Mar-24 549893 6772.65 1.23163 20340.9 33.2957 Mar-25 592004 5574.41 0.94162 47830.1 11.6546 Sun Pharmaceutical Inds. Ltd. Mar-17 29400.8 6.49 0.02207 3879 0.16731 Mar-18 49345.1 0 0 5484.17 0 Mar-19 56137.2 0 0 5656.86 0 Mar-20 62216.6 0 0 7836.3 0 Mar-21 65552.1 0 0 2567.94 0 Mar-22 65841.1 0 0 3209.32 0 Mar-23 69555.4 0 0 4186.79 0 Mar-24 69184.9 0 0 2284.68 0 Mar-25 71873.8 0 0 3405.82 0 Tata Motors Ltd. Mar-17 230937 22.16 0.0096 14183.2 0.15624 Mar-18 239396 0 0 14153.1 0 Mar-19 279372 0 0 11100.7 0 Mar-20 288704 0 0 6063.56 0 Mar-21 343594 0 0 6813.1 0 Mar-22 322167 0 0 -28934 0 Mar-23 337976 0 0 -10975 0 Mar-24 358816 0 0 -13016 0 Mar-25 346773 0 0 -11235 0 Tata Steel Ltd. Mar-17 175100 8532.16 4.87273 3663.97 232.867 Mar-18 162572 11604.5 7.13802 -3955.5 -293.38 Mar-19 177831 5887.14 3.31052 -386.67 -1522.5 Mar-20 173560 3922.21 2.25986 -4176.2 -93.918 Mar-21 212685 4505.95 2.1186 17523.7 25.7135 Mar-22 237392 4377.52 1.84401 8873.63 49.3318 Mar-23 254185 6723.02 2.64494 984.49 682.894 Mar-24 249498 12372.6 4.959 7862.45 157.363 Mar-25 289395 12337 4.26303 41100.2 30.0169 It is clear from the above table that the data gathered have shown that the impairment is not regular activities for even the selected 10 companies during the entire period of the study of 9 years from 2017 to 2025. The details as per the above table revealed that for Asian Paints Ltd. the impact of the impairment over the assets was very less and below 0.5 percent while on profitability it was minimum at 1 percent and maximum at 2.96 percent. For Bharti Airtel limited the impact of the impairment over the assets was very less and below 0.1 percent while on profitability it was minimum at -2.1489 percent and maximum at 23.51 percent. Coal India Ltd. the impact of the impairment over the assets was very less and below 1.04 percent while on profitability it was minimum at 0 percent and maximum at 8.62 percent. Hindalco Industries Ltd. the impact of the impairment over the assets was very less and below 0.93 percent while on profitability it was minimum at 0.0 percent and maximum at 16.34 percent. Larsen & Toubro Ltd. the impact of the impairment over the assets was very less and below 0.31 percent while on profitability it was minimum at 0.26 percent and maximum at 7.93 percent. Mahindra & Mahindra Ltd. the impact of the impairment over the assets was very less and below 2.87 percent while on profitability it was minimum at 0 percent and maximum at 99.15 percent which is huge. Oil & Natural Gas Corporations Limited the impact of the impairment over the assets was very less and below 1.51 percent while on profitability it was minimum at 5.02 percent and maximum at 75.75 percent. Sun Pharmaceutical Industries Limited the impact of the impairment over the assets was very less and below 0.2 percent while on profitability it was minimum at 0 percent and maximum at 0.16 percent. Tata Motors Limited the impact of the impairment over the assets was very less and below 0.01 percent while on profitability it was minimum at 0 percent and maximum at 0.16 percent. For the last selected company Tata Steel Limited the impact of the impairment over the assets was very less and below 7.13 percent while on profitability it was minimum at -1522 percent and maximum at 682.89 percent. This means that the company Tata Steel Limited has made the maximum changes and impairment of the assets that might be due to their new mergers which had taken place during the period of the study. Measuring Impact of Impairment of Assets on Accounting Variables To measure the impact of the Impairment of Assets on Accounting Variables the data is gathered from the selected companies to identify the independent variables that put impact over the impairment, the statistical tool is used with the following hypothesis: H1(e)= Impairment of assets is significantly predicted by the accounting variables in the selected companies of India. The statistical tool multiple regressions are used to analyse the hypothesis with the SPSS software and the results are presented as under: Table-2: Result of multiple regression Variable Mean SD 1 2 3 4 5 6 7 8 Impair. 1339.35 2800.6 1 NP 5.75 7.34 −0.034 1 EPS 14.21 36.71 0.687* 0.281* 1 ROA 9.83 19.06 0.018 0.316* 0.245* 1 ROE 13.67 27.95 0.059 0.368* 0.316* 0.988* 1 ROCE 18 26.83 0.01 0.337* 0.277* 0.983* 0.981* 1 CR 1.82 1.87 0.008 0.200* 0.006 0.651* 0.615* 0.589* 1 DER 0.45 0.36 0.001 −0.549* −0.297* −0.682* −0.732* −0.702* −0.494* 1 Notes: Correlations are Pearson (1-tailed). *p < 0.05, **p < 0.01 NP = Net Profit; EPS = Earnings per Share; ROA = Return on Assets; ROE = Return on Equity; ROCE = Return on Capital Employed; CR = Current Ratio; DER = Debt–Equity Ratio. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 2 .726b .528 .517 1946.552 .056 10.346 1 87 .002 a. Dependent Variable: Impairment b. Predictors: (Constant), EPS, NP ANOVAa Model Sum of Squares df Mean Square F Sig. 2 Regression 368408609.875 2 184204304.937 48.615 .000c Residual 329648714.321 87 3789065.682 Total 698057324.196 89 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations Collinearity Statistics B Std. Error Beta Zero-order Partial Part Tol VIF 2 (Const.) 1061.652 263.742 4.025 .000 EPS 57.701 5.858 .756 9.850 .000 .687 .726 .726 .921 1.086 NP -94.245 29.300 -.247 -3.217 .002 -.034 -.326 -.237 .921 1.086 The summary of regression result revealed: Adjusted R2 value (The Accuracy of the Model) = .517 ANOVA F value (the Model Fitness Index) = 48.615 Sig. in ANOVA (Model fitness for Future) = .000c Constant = Impairment Variable Selected: BenOper_7, BenOper_3, BenOper_2, BenOper_5, BenOper_4 The results with the value of adjusted R square 51.7% reveals that for the dependent variable Impairment, 2 independent variables EPS and NP are showing as accounting variables putting the impact on the impairment of the company’s assets. The above stated that the model is found fit with the Value of ANOVA 48.615 which is significant (p<0.05). The variable EPS and Net profit is revealing as selected accounting variables, shown significant change in the level of the Impairment done by the companies. Measuring differences in Impairment as per companies To measure the differences amongst the companies, the following hypothesis is developed: H1: There is a significant difference in the Impairment of the selected companies. To measure the above hypothesis, the ANOVA analysis is conducted with the SPSS Software and the results are presented as under: Table-3: ANOVA Result for Differences in Impairment as per companies Descriptive N Mean Std. Deviation Std. Error Asian Paints Ltd. 9 46.00 17.274 5.758 Bharti Airtel Ltd. 9 175.83 131.875 43.958 Coal India Ltd. 9 215.94 441.461 147.154 Hindalco Industries Ltd. 9 211.91 469.322 156.441 Larsen & Toubro Ltd. 9 267.59 304.500 101.500 Mahindra & Mahindra Ltd. 9 569.58 1130.235 376.745 Oil & Natural Gas Corporations Ltd. 9 4096.57 2288.760 762.920 Sun Pharmaceutical Industry Ltd. 9 .72 2.163 .721 Sun Pharmaceutical Industry Ltd. 9 2.46 7.387 2.462 Tata Steel Ltd. 9 7806.89 3516.435 1172.145 Total 90 1339.35 2800.596 295.209 ANOVA Sum of Squares df Mean Square F Sig. Between Groups 542802996.027 9 60311444.003 31.077 .000 Within Groups 155254328.169 80 1940679.102 Total 698057324.196 89 The above results revealed that there is a significant difference in the impairment of the assets conducted by the selected companies as F31.077 is significant (P<0.05). Further, the mean value analysis revealed that the company Tata Steel Ltd followed by the Oil & Natural Gas Corporations Limited have made the maximum amount of impairment during the period of the study. Conclusion This study examined the impact of asset impairment on the profitability of selected BSE and NSE listed companies, focusing on key financial performance indicators such as Net Profit, EPS, ROA, ROE, and ROCE. The Asset impairment shows a strong positive association with Profitability of the company and its EPS, indicating that impairment recognition may coincide with earnings adjustments or restructuring phases. The relationship between impairment and profitability ratios (ROA, ROE, ROCE) is generally weak or insignificant, suggesting limited direct operational impact. Overall, the results suggest that asset impairment primarily affects accounting-based earnings measures rather than core operational profitability. The result of the study revealed that the companies like Bharti Airtel Ltd., Sun Pharmaceutical Industries Ltd. and Tata Motors Ltd. are not at all making their tangible assets impaired while the companies like Coal India Ltd., Hindalco Industries Ltd., Mahindra & Mahindra Ltd., Oil & Natural Gas Corporations Ltd. have only made impairment in their tangible assets for 2 years out of 9 years of the study, but as a major company showing the direction of Indian economy, they must provide the data of their impairment. Further, the mean value analysis revealed that the company Tata Steel Ltd followed by the Oil & Natural Gas Corporations Limited have made the maximum amount of impairment during the period of the study. Managers should treat impairment as a financial reporting and transparency tool, not merely as a negative signal. The Strategic impairment recognition can improve earnings quality and balance sheet credibility. References • Azzaz, J., Loisel, S. & Thérond, PE. 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