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Through this case, participants will be able to:

▪ understand the different approaches to preparing operating budgets;

▪ classify the costs based on traceability to its cost centres;

▪ understand the difference in budget preparation and its analysis under different cost centres;

▪ put together the required information, identify the format and prepare major operating budgets; and

▪ evaluate operating budgets and give suggestions to the company based on budget analysis.

This case is about a manufacturing company that is going to introduce a budgeting system. It highlights the process of information collecting from key employees for budget preparation. This case also deals with various decisions to be made during the implementation of the new system such as the context of budgets, cost units and sequence of budgets.This case will help students to enhance their understanding of the operating budgets. The students will able to visualize the difficulty faced by companies to implement a new system.

This case is applicable in the courses such as Master of Business Administration, Master of Commerce or other postgraduate studies. This can also be discussed in professional courses such as Chartered Accountants, Certified Management Accountants, Company Secretaries, Institute of Cost and Works Accountants of India and Chartered Financial Analysts.

Teaching Notes are available for educators only.

CSS 1: Accounting and Finance.

This paper aims to revisit the theme of fiscal-monetary coordination in a general equilibrium setup that allows for unconventional monetary policy, monetary policy transmission and developing country characteristics.

This paper uses a calibrated new Keynesian dynamic stochastic general equilibrium (DSGE) model to study fiscal-monetary interaction.

Debt sits at the center of monetary-fiscal interaction. Under high-debt conditions, the inflation-output trade-off rises with an increase in the strictness with which monetary policy targets inflation, undermining the standard prescription of strict inflation targeting. At the same time, the transmission of monetary policy is also impeded, due to which unconventional monetary policy becomes more appropriate. The need for coordination among the policies gets enhanced in the presence of borrowing cost channel. While the presence of borrowing cost channel increases the need for policy coordination regardless of the debt situation, features like higher share of non-Ricardian households and weaker monetary policy transmission affect monetary-fiscal interaction to a greater extent under high-debt environment.

First, this paper uses inflation-output trade-off as a metric, to analyze fiscal-monetary interaction. Second, this paper considers the impact of developing country characteristics (such as a higher share of non-Ricardian households, impeded monetary policy transmission and supply constraints/borrowing cost channel) on fiscal-monetary interaction. Third, the DSGE model developed in this paper incorporates open market operations that could shed light on the role of unconventional monetary policy in the presence of high fiscal deficit and debt, which is particularly relevant in the current context of the COVID-19 pandemic. Fourth, the model also permits an investigation into monetary policy transmission under different debt regimes.

Ghee, anhydrous milk fat, is chemically highly complex in nature. The authentication and characterization of edible fats and oils by routine chemical methods are highly laborious and time consuming. Fourier transform-mid-infrared (FT-MIR) spectroscopy has emerged as a predominant analytical tool in the study of edible fats/oils. However, sufficient attention has not been paid so far to spectral characterization of milk fat obtained from cow and buffalo milk. The purpose of this paper is to fill this void.

Ghee samples were prepared from cow and buffalo milk by the direct cream method. From each type of milk (cow and buffalo), 35 samples of ghee were prepared; thus, in total, 70 samples of ghee were obtained for the study. For assigning absorption bands in the IR spectrum, spectra of cow and buffalo ghee samples were acquired in the MIR region (4,000-650 cm⁻¹).

In FT-MIR spectra of ghee, 14 peaks were obtained at different positions and with varying intensities. They were at 3,005, 2,922, 2,853, 1,744, 1,466, 1,418, 1,377, 1,236, 1,161, 1,114, 1,098, 966, 870 and 721 cm⁻¹ for cow and buffalo ghee with almost equal intensity of absorption.

The finding of this study will be useful for characterization and authentication of ghee.

Application of IR spectral bands of ghee in the MIR region using a FT-infrared spectrometer to monitor the quality of ghee is suggested.

Need of the Study: Artificial intelligence (AI) can be regarded as a big leap in the case of technological advancement. Developments in AI have profound implications for economic sectors and on the societal level. In contemporary times, AI is applied widely in assisting organisations in informing managerial decisions, organisational goals, and business strategies. One can very well witness the interest of human resource (HR) professionals in the implementation of AI for the formulation of HR policies and future frameworks. In the past few years, various research works have been carried out on how these two critical branches can be combined for bringing out the best in human resource management (HRM). The fundamental explanation for this is found in every organisation’s most important management aim is employee retention and elevation.

Purpose: In this direction, this chapter will try to analyse the probability of employees leaving the company, the key drivers behind it, recommendations or strategies that can be implemented in improving employee retention, elevation predictions with the help of different features of machine learning, and the possibility of some other techniques other than key performance indicators (KPI), and rating and training score in this field.

Methodology: The goal will be achieved with the help of implementing machine learning-based classification tools and an ensemble learning approach to the data set of the corporate sector.

Findings: Machine learning techniques can be utilised to develop reliable models to find different factors for elevation and employee attrition.

The agri-food industry is experiencing a revolutionary shift due to the introduction of Industry 4.0 technologies to improve efficiency, transparency and sustainability. The importance of agri-food supply chains (AFSC) in promoting sustainability is expanding as the globe struggles with issues including resource scarcity, climate change and population growth. In order to better understand how Industry 4.0 might improve sustainability in a world that is changing quickly, this work aims to focus on identifying various sustainability assessment factors influencing AFSC to increase overall sustainability, minimize resource consumption, cut waste and streamline operations.

Important sustainability assessment factors are identified from the past academic literature and are then validated using the fuzzy-Delphi method. A method called decision-making trial and evaluation laboratory (DEMATEL) is used to examine and analyze structural models with complex causal linkages. The results are then validated using sensitivity analysis.

The factors that emerged as the highest ranked for evaluating the sustainability of Industry 4.0 in AFSC are market competitiveness, and knowledge and skill development, followed by resource efficiency. Industry 4.0 technologies are essential for increasing the marketability of agricultural products because of the major implications of market competitiveness. The significance of knowledge and skill development draws attention to Industry 4.0’s contribution to the promotion of chances for farmers and agricultural employees to increase their capability.

By outlining the nexus between Industry 4.0 technologies and sustainability, the study presents a comprehensive framework that would be relevant for researchers, policymakers and industry stakeholders who want to leverage Industry 4.0 technology to build more sustainable AFSC in the future. The study findings can help the farmers or producers make sensible choices that adhere to sustainability standards and guarantee long-term financial viability.

The originality of this work lies in the identification of sustainability assessment factors especially for AFSC in the era of digitalization which has not been discussed previously.

Principles of Management, in particular, the topics of planning, organizing, leading, controlling, human resource management, and operations management.

The case will be helpful to undergraduate and graduate business school students for learning the subject, Principles of Management.

Vikas Jha, the newly appointed executive producer and CEO of Magic Films, is a troubled man today. At 29, he is also an unusually tired man to lead this social enterprise presently focussing on producing and distributing short films that carry a strong social message. A whole set of problems is plaguing this start up leaving Vikas totally clueless about the future course of action! The case dwells on the challenges of a film production start-up and provides an opportunity for readers to explore creative solutions to management problems.

Critical thinking, creative thinking, communication skills and leadership ability are some of the liberal arts outcomes that the case study attempts to deliver. In addition, it enables students to apply their knowledge and understanding of key principles of management in solving the case problems. Thus, the case also provides transfer ability as an important learning outcome.

Teaching notes. Additional material with respect to film production can be helpful to the students in appreciating the finer aspects of this case, which deals with filmmaking. In this direction, helpful links to useful resources are mentioned in the case study.

This paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates the influence of several exogenous variables on the WCM efficiency.

WCM efficiency was calculated using BCC input-oriented DEA model. Further, the panel data fixed effect model was used on a sample of 1391 Indian manufacturing firms spread across nine industries, covering the period from 2008 to 2019.

Firstly, the WCM efficiency of Indian manufacturing industries has been stable over the analysis period. Secondly, the capacity to generate internal resources, size, age, productivity, gross domestic product and interest rate significantly influence WCM efficiency.

First, the selected study period has observed various economic uncertainties including demonetization and recession, so the scenario might differ in normal conditions or country-wise. Second, the findings might not be generalizable to the developed economies, since the current study sample belongs to a developing economy, which further provides scope for comparative study.

An efficient model for managing the working capital comprising most vital determinants could enhance the firms' valuation and goodwill. Also, this study would be helpful for financial executives, manufacturers, policymakers, investors, researchers and other stakeholders.

This study estimates the industry-wise WCM efficiency of the Indian manufacturing sector and suggests measures to the concerned parties on areas to focus on and provide evidence on the estimated relationships of firm-level and macroeconomic determinants with WCM efficiency.

The purpose of this paper is to empirically investigate the relationship between working capital management (WCM) efficiency and exogenous variables of the Indian manufacturing sector along with its sub-industries that are involved in export activities.

Panel regression (fixed effects) was used on a sample of 563 Indian manufacturing firms involved in export activities, covering a time period from 2008 to 2018.

Industry-wise results showed a significant relation of leverage, net fixed asset ratio, profitability, asset turnover ratio, total asset growth rate and productivity with cash conversion cycle (CCC).

Firstly, having taken a sample from a developing economy, the results of our study may be generalizable only among developing contexts. Secondly, the time period taken in this study (2008–2018) has witnessed several economic fluctuations such as recession and demonetization which might differ for the firms or countries in normal conditions.

An improved working capital model could advance the firms' performance by reducing the CCC of the firm, thereby creating efficiency in WCM. In addition, the results of this study could be helpful for many stakeholders such as working capital managers, debt holders, investors, financial consultants and others for monitoring the firms.

This study contributes to the existing literature in the relation between WCM efficiency and exogenous variables of the Indian manufacturing firms engaged in the export activities. Moreover, this study is one of the few research studies to investigate this relationship among Indian export firms in different industries, thus filling the gap in similar work done in other countries.

This study aims to analyze the dynamic performance of aerostatic thrust bearing for different geometries of recess. Different geometries of recess of equal recess area, i.e. circular, elliptical, rectangular and annular, have been considered in analysis. The work also analyzes the influence of tilt angle on the performance of thrust bearing. To compute the unknown pressure field, the Reynolds equation governing the flow of compressible lubricant (air) has been solved using finite element formulation. Further, separate finite element formulations have been carried out to compute fluid film stiffness and damping coefficients directly. This method provides quick computation of stiffness and damping coefficients of aerostatic thrust bearing than the usual approach.

As the Reynolds equation governing the flow of compressible lubricant is nonlinear partial differential equation, the computation of the stiffness and damping coefficient follows an iterative procedure. It requires a lot of computational energy. Therefore, in the present work, a novel technique based on finite element formulation is suggested to compute air film stiffness and damping coefficient in aerostatic thrust bearing.

A novel technique based on finite element formulation is illustrated to simulate the performance of tilted pad aerostatic thrust bearing. On the basis of simulated results, following key conclusions may be drawn. The static and dynamic performance of a circular aerostatic tilted thrust pad bearing is significantly affected with a change in the value of tilt parameter and the shape of the recess.

Implications are as follows: direct computation of air film damping coefficient is performed without perturbation method in finite element method (FEM); influence of tilt on aerostatic thrust bearing is studied; influence of recess shape on aerostatic thrust bearing is observed; and finite element formulation of aerostatic thrust bearing is performed.

The present work will be quite useful for bearing designer and academicians.