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This study aims to determine whether the financial ecosystem is reliable for evaluating a company’s financial performance at various lifecycle stages or whether value-based performance metrics like Economic Value Added (EVA) are the most comprehensive indicators regardless of the company’s lifecycle stage. The evaluation will analyse the importance of value-based and accounting performance benchmarks (EVA, Return on Capital Employed, Return on Equity and Earnings per Share) in creating shareholder value, as measured by market value added, throughout the company’s lifecycle.

This study is based on a robust empirical analysis of 228 Indian firms listed on the National Stock Exchange Nifty 500 Index from 2006 to 2023. By considering firms of different sizes and ages, the authors aim to capture and analyse any distinct impact across various stages of their lifecycles. Using quantile regression for analysis equips the authors to effectively address extreme events such as the 2008 global financial crisis and the COVID-19 pandemic, making the method particularly suitable for conditionally distributed samples based on size and age.

The research reveals that various performance indicators are crucial at different stages of a company’s lifecycle for generating wealth for shareholders. However, considering the significance of the EVA measure, it is recommended that policymakers standardize the calculation of EVA and mandate its disclosure.

The authors comprehensively analysed the economic value addition relative to a company’s size and age, going beyond previous studies that focused solely on specific size categories. This offers managers valuable insights into aligning business performance measures with the various stages of the business lifecycle.

The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.

A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.

The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.

The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.

The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.