Mohini Yadav - Academia.edu (original) (raw)

Papers by Mohini Yadav

Ramanujan International Journal of Business and Research

This study is divided into two parts. Part A attempts to study the relationship between HR functi... more This study is divided into two parts. Part A attempts to study the relationship between HR functions, employee engagement and post-crisis organisational recoverability during the COVID-19 crisis through quantitative methods. Part B adopts a qualitative thematic analysis approach to gain insights into the HR enablers that contribute towards its crisis-preparedness. The independent variables were (a) HR functions (HR communication, HR support, HR collaboration, HR agility, HR anticipation of crisis) and (b) employee engagement and the dependent variable was organisational recoverability as perceived by the employees. The study adopts a dual approach of gaining the employee perspective as well as HR perspective of ten organisations operating in the national capital region of Delhi, India. Causal survey design was adopted to gain employee perspective through analysis of quantitative data. In the second phase of the study, HR managers of the same ten organisations were interviewed to gain insights into HR function enablers during COVID-19. The quantitative data was subjected to machine learning analysis (Rstudio, Random Forest) & qualitative data was analysed through content analysis. Employee engagement and three functions of HR-HR support, HR agility, & HR anticipation of crisis emerged as predictors for organisational recoverability. The emerging themes from content analysis of qualitative interviews were-HR empowerment, knowledge management and learning systems. These three emerged as HR enablers. The study has implications for organisation science research in a post crisis scenario.

International Journal of Innovative Knowledge Concepts, 2019

Journal of Management Research and Analysis, 2019

Failure in the timely adjustment of the reserve levels based on reasonable anticipation of future... more Failure in the timely adjustment of the reserve levels based on reasonable anticipation of future conditions was turned out to be the major drawback of the Allowance for Loan and Lease Losses (ALLL) accounting standard during the great recession of 2007-2008. 1 The major issue during the time of crisis was that the unfavorable economic conditions was not taken into consideration for the calculations of losses under the ALLL method. Because of that reserves were not adjusted for the expected losses in the future. In 2011, The OCC (Office of the Comptroller of the Currency) and Fed (US Federal Reserve) anticipated that the allowances in the industry would increase by 30% to 50%. 2 But since the expectations of the economy has changed drastically since then, many economist have predicted that the increase in the industry allowances would not be significant. Keefe, Bruyette & Woods, Inc., an investment banking firm headquartered in New York City predicted in September 2015 that the median increase in ALLL for small and mid-size bank will be meagre 3%. 2 After the great recession, Financial Accounting Standards Board (FASB) reviewed how financial institutions are estimating the losses in the ALLL calculation. Various weaknesses in the existing incurred loss model (ALLL) were exposed, which included complexity and delay in recognition of credit losses. At the time of review, The FASB and the International Accounting Standards Board (IASB) discussed and proposed many approaches to correct the damage. Ultimately the final resolution was to make a new accounting standard altogether that should accelerate recognition of credit losses and CECL come into the picture. CECL requires the estimation of expected losses over the life of the loans, and is forward looking approach to make the allowances by giving consideration to the future economic outlooks and the life of the loan. The major expectation of the FASB while introducing this new standard-CECL is that it will improve the liquidity, stability and financial reporting of the financial institutions, and will necessitate the timey recording of credit losses on loans. After much discussions and review, the Financial Accounting Standards Board finally issued 'Measurement of Credit Losses on Financial Instruments' in June 2016, 3 which contained the methodology for the current expected credit losses (CECL) for estimating allowances for credit losses loans and other financial instruments. As per the CECL methodology, financial institutions requires a determination of the expected amount to be collected on a portfolio of originated loans from day one till the entire life of the loan. The day one CECL allowance would be equal to the difference between the originated loan amount and expected loan amount to be collected over the life of the loan.

A sentiment analysis, a form of artificial intelligence, is a technique which uses natural langua... more A sentiment analysis, a form of artificial intelligence, is a technique which uses natural language processing (NLP) to ascertain the opinions and emotional tone of the user written content on the online platform. It can be used in any form ranging from determining the sentiments of consumer’s reviews, employee’s feedback, and their social presence for effective marketing of their products and services. Through this article we wish to analyse the existing literature in sentiment analysis field to ascertain it usefulness in the marketing activities

Ramanujan International Journal of Business and Research

This study is divided into two parts. Part A attempts to study the relationship between HR functi... more This study is divided into two parts. Part A attempts to study the relationship between HR functions, employee engagement and post-crisis organisational recoverability during the COVID-19 crisis through quantitative methods. Part B adopts a qualitative thematic analysis approach to gain insights into the HR enablers that contribute towards its crisis-preparedness. The independent variables were (a) HR functions (HR communication, HR support, HR collaboration, HR agility, HR anticipation of crisis) and (b) employee engagement and the dependent variable was organisational recoverability as perceived by the employees. The study adopts a dual approach of gaining the employee perspective as well as HR perspective of ten organisations operating in the national capital region of Delhi, India. Causal survey design was adopted to gain employee perspective through analysis of quantitative data. In the second phase of the study, HR managers of the same ten organisations were interviewed to gain insights into HR function enablers during COVID-19. The quantitative data was subjected to machine learning analysis (Rstudio, Random Forest) & qualitative data was analysed through content analysis. Employee engagement and three functions of HR-HR support, HR agility, & HR anticipation of crisis emerged as predictors for organisational recoverability. The emerging themes from content analysis of qualitative interviews were-HR empowerment, knowledge management and learning systems. These three emerged as HR enablers. The study has implications for organisation science research in a post crisis scenario.

International Journal of Innovative Knowledge Concepts, 2019

Journal of Management Research and Analysis, 2019

Failure in the timely adjustment of the reserve levels based on reasonable anticipation of future... more Failure in the timely adjustment of the reserve levels based on reasonable anticipation of future conditions was turned out to be the major drawback of the Allowance for Loan and Lease Losses (ALLL) accounting standard during the great recession of 2007-2008. 1 The major issue during the time of crisis was that the unfavorable economic conditions was not taken into consideration for the calculations of losses under the ALLL method. Because of that reserves were not adjusted for the expected losses in the future. In 2011, The OCC (Office of the Comptroller of the Currency) and Fed (US Federal Reserve) anticipated that the allowances in the industry would increase by 30% to 50%. 2 But since the expectations of the economy has changed drastically since then, many economist have predicted that the increase in the industry allowances would not be significant. Keefe, Bruyette & Woods, Inc., an investment banking firm headquartered in New York City predicted in September 2015 that the median increase in ALLL for small and mid-size bank will be meagre 3%. 2 After the great recession, Financial Accounting Standards Board (FASB) reviewed how financial institutions are estimating the losses in the ALLL calculation. Various weaknesses in the existing incurred loss model (ALLL) were exposed, which included complexity and delay in recognition of credit losses. At the time of review, The FASB and the International Accounting Standards Board (IASB) discussed and proposed many approaches to correct the damage. Ultimately the final resolution was to make a new accounting standard altogether that should accelerate recognition of credit losses and CECL come into the picture. CECL requires the estimation of expected losses over the life of the loans, and is forward looking approach to make the allowances by giving consideration to the future economic outlooks and the life of the loan. The major expectation of the FASB while introducing this new standard-CECL is that it will improve the liquidity, stability and financial reporting of the financial institutions, and will necessitate the timey recording of credit losses on loans. After much discussions and review, the Financial Accounting Standards Board finally issued 'Measurement of Credit Losses on Financial Instruments' in June 2016, 3 which contained the methodology for the current expected credit losses (CECL) for estimating allowances for credit losses loans and other financial instruments. As per the CECL methodology, financial institutions requires a determination of the expected amount to be collected on a portfolio of originated loans from day one till the entire life of the loan. The day one CECL allowance would be equal to the difference between the originated loan amount and expected loan amount to be collected over the life of the loan.

A sentiment analysis, a form of artificial intelligence, is a technique which uses natural langua... more A sentiment analysis, a form of artificial intelligence, is a technique which uses natural language processing (NLP) to ascertain the opinions and emotional tone of the user written content on the online platform. It can be used in any form ranging from determining the sentiments of consumer’s reviews, employee’s feedback, and their social presence for effective marketing of their products and services. Through this article we wish to analyse the existing literature in sentiment analysis field to ascertain it usefulness in the marketing activities