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This paper analyzes citations from the first 20 volumes of Advances in Management Accounting using Google Scholar in April and May, 2013.

This study assesses the success of the first 20 volumes of Advances in Management Accounting using citation analysis. Four citation metrics are used. The four citation metrics are: (1) total citations since year of publication until April and May, 2013, (2) citations per author since year of publication until April and May, 2013, (3) citations per year since year of publication until April and May, 2013, and (4) citations per author per year since year of publication until April and May, 2013.

The top 20 authors for each citation metric, the top 20 faculties for each citation metric, and the top 20 doctoral programs for each citation metric are determined. Furthermore, the top 20 articles are determined using two citation metrics and the H-index for Advances in Management Accounting is computed.

Potential doctoral students, current doctoral students, “new” Ph.D.s with an interest in management accounting, current management accounting faculty, department chairs, deans, other administrators, journal editors, and journal publishers will find these results informative.

Today, firm performance must be measured not only on traditional metrics but also on those that reflect the changing imperatives and new metric knowledge. Thus, the focus of managers, investors, and researchers is shifting from rubrics like sales and profitability to growth as a more appropriate measure of firm performance. We aim to highlight the effects that growth of a firm can have on the level of its systematic risk. Using a sample of 203 firms across nine industries taken from the Indian manufacturing sector for a period of 17 years (1998–2014), we develop and test a panel vector autoregressive (VAR) model to analyze the causal relationship between growth aspects and systematic risk of firms. Results depict that a growth option available to firms increase their level of systematic risk and the risk decreases when firms start chasing this growth by increasing their assets in place. Sustainable growth rate, which depicts the growth potential of firms, plays an important role in reducing the level of systematic risk. The findings of this chapter are relevant to managers who think that growth is always beneficial.

Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to online mode. The introduction of the online P2P lending industry is in its nascent stage of growth. As this industry is relatively new, understanding user experience, sentiments, and emotions would be helpful for the industry to innovate as per customer requirements.

Purpose: To explore the patterns in the sentiments expressed by users of ‘Cashkumar’ based on Google reviews.

Methodology: Sentiments have been analysed using user experience in risk, cost, ease of use, and loan processing time. Python application was used for sentiment analysis of Google reviews.

Findings: The sentiment analysis results showed that the average sentiment score was 0.7144, which indicates that the user sentiment towards ‘Cashkumar’ is positive. The reviews reflect that the users, especially borrowers were satisfied with the platform’s services and happy with loan processing time. The other factors – ease of use, cost, and risk – were not given much importance by users. Both lenders and borrowers faced a few issues, but the results of the lender’s sentiment analysis could not be generalised due to a smaller number of posted reviews.

Purpose: Worldwide economies have been shattered by the alarming increase in Non-Performing Assets (NPAs) in Banking Sector. In India, the rise in NPA levels gives a clear insight into the health of industry and state. This study aims to determine how NPAs in India impact the profitability of eight banks chosen from the public and private sectors; specifically: Punjab National Bank (PNB), Bank of India (BOI), UCO Bank, Punjab and Sind Bank (PSB), HDFC Bank, Axis Bank, ICICI Bank, and Yes Bank; during the period 2009/2010 to 2017/2018.

Design/methodology/approach: The study utilised IBM SPSS version 20 application to carry out our statistical analysis of measures of central location (mean and median), measures of dispersion (standard deviation), to carry out the Kolmogorov–Smirnov test to check the normality of data, the Mann–Whitney U test (for two groups) for median comparison between private and public sector banks and the Kruskal–Wallis test (for more than two groups) for median comparison for more than two banks. p ≤0.01 and p ≤0.05 were the two-tailed significance level used for determining the significance of all statistical tests.

Findings: Trend analysis and statistical tests show that the trend in public sector banks to have NPAs is higher compared to private sector banks, and losses arising from NPA impact the banks’ profitability.

Practical implications: It is apparent that NPAs are a large threat to banks in India as it reflects the state of the Indian economy. The growth of the economic cycle is predominantly dependent on the smooth and profitable functioning of private and public sector banks. This current study focusses on and compares the impact of NPAs on the profitability of public and private sector banks. NPAs have grown exponentially more in the case of public sector banks than private sector banks, which has affected the former banks’ financial health and performance. Increases in the level of NPAs adversely affect the working style and long-term stability of public and private sector banks in the economy.

Social Implications: NPAs have a negative influence on the profitability of the banks as well as on the economic growth of the country too. However, it is recommended that management in the banking sector, particularly the public banks, should use various preventive and recovery strategies to reduce the risk of failure and to keep track of NPAs to stay safe.

Originality/value: This study aims to determine how NPAs in India impact the profitability of eight banks chosen from the public and private sectors; specifically: PNB, BOI, UCO Bank, PSB, HDFC Bank, Axis Bank, ICICI Bank, and Yes Bank; during the period 2009/2010 to 2017/2018.

Purpose of This Chapter:

This perspective seeks to assert that India was (and is) a great civilization and is on its way to further greatness in the year 2047 (the 100^th year of India’s independence), provided some challenges are confronted in the earnest – both at the managerial and societal levels.

Design / Methodology / Approach:

The chapter adopts a simplistic review of literature-cum-personal analysis-based approach. Sources ranging from journals and newspapers to websites have been employed to arrive at an informed opinion on the theme.

Findings:

The chapter advocates for concerted action on the fronts of employee welfare, adoption of the latest digital technologies, improving inter- and intra-team communication, upgrading the skills of employees, promoting innovation and employment of women in decent jobs with robust wage and social security structures to tackle the new-age management challenges.

Research Limitations:

In the wake of the absence of empirical research and lack of quantifiable data on the new-age management challenges, it is difficult to ascertain the exact nature of the relationship of the same with Target 2047.

Practical Implications:

The chapter projects certain strengths, weaknesses, opportunities, and threats (SWOT) that are both internal and external to the country’s socioeconomic makeup. The same would assist the new-age managers to be better prepared for upcoming challenges and roadblocks to India’s Goal 2047.

Originality:

This chapter is one of the earliest attempts at linking the seemingly unrelated concepts of new-age management challenges and India’s quest to become a developed country by 2047.

Background: Human resource management (HRM) is the tactical method for a business enterprise’s optimistic and systemic administration. This study aims to identify the common and major triggering attributes and the knowledge gap between HRM and an organisation’s employee attrition rate.

Method: The employee Attrition Case Study Dataset used is an anecdotal data set that tries to figure out relevant variables that determine employee behavioural aspects towards attrition. This study investigates why attrition occurs, the major triggering attributes for employee turnover, and how it might be anticipated to employ artificial intelligence (AI) to avert corporate losses.

Results: Employees’ monthly income, age, average monthly hours, distance from home, total working years, years at the company, per cent of salary hike, number of companies worked, stock options level, job role and other factors are taken into consideration. A feature importance extraction framework was devised to investigate the various dormant factors. The findings also show feasible hypotheses that help enhance employee engagement, reinvent the worker dynamic, and higher levels of risk decrease attrition rate.

Implications: Employees’ monthly income, age, average monthly hours, distance from home, etc., are all major variables in employee attrition in the Indian IT business. This research adds to the theory development of behavioural elements in people analytics based on AI.

Purpose: Can we predict employee attrition through employee behavioural patterns advancement using AI tools.