Theme: TRENDS IN MANAGEMENT & HR IN THE PRESENT SCENARIO
Guest Editor: Dr. Amit Sharma , Dr. Sharad Patil, Dr. Tarun Goma, Dr Divyshikha, Dr Rajanai H Pillai, Dr Rupa Adarsh, Dr Vikrant Rehani
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1. THE INFLUENCE OF DIGITIZATION ON TALENT ACQUISITION AND RETENTION STRATEGIES
Authors: ADHEER A. GOYAL, Dr. S MD SHAKIR ALI, Dr. MEENA SHARMA, Dr. INDU MAJUMDAR, SWATI A. GOYAL, Dr. SHRIRAM JOSHI and Dr. TEJASVINI PARALKAR
Abstract
The profound shift towards digitalization within companies demands comprehensive restructuring across all aspects of the organization. This study examines how the adoption of digital technologies impacts strategies for managing talent. By analyzing the factors influencing the attraction and retention of skilled individuals, we aim to explore potential variations in resource allocation among companies. Our research focuses on a sample of 314 Indian companies actively engaged in digital transformation endeavours. Data pertaining to these organizations were collected through a questionnaire distributed to their managerial staff. To evaluate the assumptions of our model, we utilized structural equation modelling as the statistical approach. The findings substantiate the hypotheses posited by our model, underscoring the role of digital transformation in shaping talent management practices and bolstering efforts to attract and retain talent.
Keywords: Digital metamorphosis, Skillful resource oversight, Digital readiness gauge, attracting skilled personnel, Retaining top talents.
2. FACTORS IMPACTING LEVERAGE AND PROFITABILITY IN FIRMS
Authors: Dr. NISHI MALHOTRA
Abstract
The research study evaluates the impact of various variables, such as profitability, bankruptcy costs, tangibility, and managerial ownership, on a company's capital structure. Moreover, its objective is to assess the influence of (ESG Score) sustainable initiatives and corporate governance on the firm's profitability and capital structure. According to the study, there is a positive relationship between tangible assets that a firm has and the leverage levels of firms. At the same time, the higher bankruptcy costs lead to a lower level of debt. Furthermore, it suggests that Return on Equity (ROE) positively impacts the Return on Assets (ROA), while debt negatively impacts the ROE. Data for the study was collected in 2 parts. In the first part for identifying the factors impacting the capital structure the data was collected through the 5-point likert scale and for the analysis of the impact of various factors on capital structure, data was collected from Bloomberg for the period 2019-2022. The principal component analysis was used to identify the factors impacting the capital structure and the dynamic panel random effects model was used to identify the impact of various factors on the leverage and capital structure of the firm. The study substantiates that the inclusion of female independent directors on the board of management leads to enhanced earnings per share (EPS). Additionally, the research study validates that sustainable ESG (Environment, Society, and Governance) initiatives positively impact a firm’s profitability. Conversely, it validates the negative impact of the debt on the profitability of the firm.
Keywords: Capital structure, Corporate Governance, ESG
3. A FRAMEWORK FOR PREVENTING ACCIDENTS DUE TO HUMAN ERROR IN OIL AND GAS DRILLING OPERATIONS OF KUWAIT
Authors: MANI KUMAR DEVARAPALLI and TOTAKURA BANGAR RAJU
Abstract
Drilling operations in The Oil and Gas industry are highly prone to accidents for various reasons, and human error is one of the prime reasons. These accidents cause tremendous losses to human life and the environment, apart from organizations. Kuwait is a leading country in terms of oil and gas exploration. The country has a potential catastrophe owing to its oil and gas drilling operations. This study attempts to develop a framework for preventing accidents caused by human error. Considering the HFACS framework, ten working personnel from the oil and gas fields were interviewed for feedback on the various preventive measures required. Based on the interviews, coding was performed using Maxqda software, and a framework was proposed to prevent further accidents in Kuwait's oil and gas industry. This study could help various stakeholders in Kuwait develop a better safety management system for oil and gas drilling operations personnel
Keywords: Accidents, Human errors, prevention, HFACS, Safety
4. MACHINE LEARNING FOR CREDIT DEFAULT PREDICTION IN SMES: A STUDY FROM EMERGING ECONOMY
Authors: NAVEEN KUMAR K, PAVITHA N and ASHUTOSH KASHYAP
Abstract
Credit default prediction is a crucial task for financial institutions as they aim to minimize future losses associated with credit risk. Statistical models and machine learning (ML) algorithms have become prevalent in the field of credit risk modeling. This study compares and contrasts five different ML algorithms- Random Forest (RF), Adaptive Boosting (AdaBoosting), Gradient Boosting (GB), XGBoosting (XGB), and Linear Discriminant Analysis (LDA) - to predict the credit default risk of SMEs in an emerging market economy. The study provides a step-by-step model development approach and evaluates the performance of each model using various performance evaluation metrics, including accuracy, precision, recall, F1-Score, and Area Under Receiver Operating Characteristics (AUROC) curve. The feature importance of different models is also analyzed to draw inferences. The results show that RF outperforms other models in terms of accuracy, AUROC, and F1-Score. The findings of this study can help financial institutions in making more informed decisions regarding credit default prediction in emerging market economies.
Keywords: Credit default prediction, machine learning algorithms, emerging market economy, performance evaluation metrics, feature importance.