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Technical education plays an important role in the development of a country in this age of knowledge economy. Indian technical education system is facing many opportunities and challenges, one of which is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative efficiency and ranking of a set of private engineering colleges under multi-criteria environment.

To cater to the increasing need of technical manpower, a very large number of private engineering colleges have been established in the state of West Bengal of eastern India within a very short period. Uniform and acceptable quality of the graduates from many of these private engineering colleges is a concern today and therefore the need for performance evaluation and ranking of these colleges is paramount. For the proposed framework a comparatively new multiple criteria decision-making tool, multiple objective optimization on the basis of simple ratio analysis (MOOSRA) is applied for performance evaluation of eight private engineering colleges taking into account some selected criteria. The subjective weights of the criteria are determined using fuzzy analytic hierarchy process (AHP).

For the analysis, the required data have been provided by the management of the colleges for the academic year of 2011-2012. Based on request of the management identities of these institutes are not disclosed. The institutes are considered as anonymous institute and coded as A, B, C, D, E, F, G and H, respectively. The result of the study reveals that E is the best and the ranking the authors get is in the order of E > F > A > H > D > C > G > B. The result shows that composite performance scores of institutions A, E and F are above the mean performance score value. Therefore these three institutions can be considered as the benchmark or peer group for the remaining five institutions which lie below the mean line of the performance score value.

This paper provides a comprehensive yet detailed methodology for performance evaluation of academic institutions. The novelty in the approach is that fuzzy AHP and MOOSRA are being used as a benchmarking technique in a simple methodology which is generic in nature. It is one of the few studies that evaluate the performance of technical institutions in India.

Due to liberalization, privatization and globalization, the need of competent technical manpower at an economical cost is increasing rapidly. Many foreign multinationals are focusing on India for employable talents. Many technical institutions with cutting edge technologies and leading edge techniques are being set up by foreign collaboration, national and private initiatives. The objective of this study is to propose a model for performance evaluation and benchmarking of Indian technical institutions from perspective of all stakeholders.

For the proposed framework, a multiple criteria decision‐making tool, distance‐based approach (DBA) methodology is applied for performance evaluation of seven Indian technical institutions taking into account some selected criteria like, faculty strength (FS), student intake (SI), number of PhD awarded (PhD), number of patents applied for (patent), the campus area in acres (CA) and tuition fee per semester in rupees (TF). Consulting the experts in various fields with the help of certain questionnaire and aggregating their views by conducting ameliorated nominal group technique session, we select these evaluation criteria. The subjective weights of the criteria are determined using analytic hierarchy process (AHP). For the analysis, the required data are collected from annual report published by Ministry of Human Resource and Development (MHRD) for the year of 2007‐08.

In this paper, we have chosen seven centrally funded technical institutions for study and the institutions are coded as A, B, C, D, E, F and G. The result of the study reveals that A is the best and F is the worst. The ranking we get is in the order of A≽B≽E≽C≽G≽D≽F. From the result it is understood that A can be considered as benchmark for B, C and E (which form the second group) and this second group can be considered as an improvement target for the rest. At the end a holistic technical education system model (HTESM) is proposed.

This paper is one of the few studies that evaluate the performance of technical institutions in India. The novelty in the approach is that DBA and AHP are being used as a benchmarking technique in a simple methodology which is generic in nature.

The case explores information technology (IT) company Mindtree’s journey of 20 years from the time it was founded in 1999 to be different from others, and how it became a target for acquisition by an Indian diversified conglomerate in 2019. It offers insights into developing organizational culture and values in an organization, threats faced by a company when promoters dilute their shareholding, and the strategies followed by the acquirer and the target firm. It also deals with the challenges in the acquisition of a knowledge service digital firm. After working through the case and assignment questions, students will be able to: identify the circumstances under which a company can become a target for hostile takeover; describe motivations of the acquirer firm in an acquisition; distinguish between acquisition and hostile takeover, and discuss salient features of Securities and Exchange Board of India (substantial acquisition of shares and takeover) regulations, 2011; list the defenses a target firm can adopt to ward off hostile acquirer; explore strategies followed by acquirer and target firms; analyze important ingredients of organization culture, and importance of cultural congruence in an acquisition; and discuss challenges faced by an acquirer in India, namely, legal, retention of clients and key people in the target firm particularly in hostile environment.

The case explores how ten IT professionals founded mid-tier IT services company Mindtree in 1999 in Bengaluru, India (home to Infosys and Wipro) to be different from others – by inserting themselves at a higher level in the value chain, being philanthropic as a part of broader business strategy to attract a certain kind of employee and customer. It developed a culture of equality, consideration and respect. Its attrition rate of 12 to 13 per cent was significantly lower than the Industries. Mindtree crossed annual revenue of US$1bn for FY 2019 and was growing at twice the industry’s growth rate. The most attractive part was that its proportion of revenue from digital services was about 50 per cent as compared to 25-35 per cent of other services vendors. With time, the share of promoters/founders declined and increased one investor’s shareholding of V. G. Siddhartha and his related entities. In early March 2019, the promoters’ stake was 13.32 per cent while Siddhartha had 20.32 per cent. Larsen and Toubro (L&T) one of India’s conglomerate entered into a share purchase agreement on March 18, 2019 with Siddhartha to acquire his 20.32 per cent stake. Immediately, L&T asked its broker to purchase up to 15 per cent of share capital of Mindtree at a price not exceeding INR 980 per share (each share of face value INR 10). This would trigger an open offer by L&T to purchase additional 31 per cent shares of Mindtree. The action of hostile takeover bid by L&T evoked emotional criticism from Mindtree founders. Mindtree efforts to defend itself could not materialize. L&T’s stake crossed 26 per cent on May 16, 2019. After Indian regulator SEBI’s approval, L&T’s open offer to buy shares from Mindtree shareholders commenced on June 17, 2019. The case examines motivation of the acquirer firm particularly when it is a conglomerate, and how a well-performing company became a target for hostile takeover. It looks at vulnerabilities of a target firm, and defensive steps a firm can take to fence itself against such takeover. The case also explores how organizational culture is built in a people-oriented business, namely, digital services, and what role it plays in a merger of two firms.

The case is suited for postgraduate students of management, as well as those undergoing executive courses in management.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

The learning outcomes of this paper are as follows: to understand the language of accounting, to interpret financial statements to understand beyond what’s reported and to predict the financial health of a company before it is too late.

The case revolves around the Indian coffee retail giant - Café Coffee Day (hereafter, CCD). Coffee Day Global Limited of which CCD is a part, is the largest producer of Arabica beans in India. The case goes on to discuss the life and profile of VG Siddhartha (hereafter, VGS), whose leadership and farsightedness made coffee a household name in India, traditionally a tea-drinking country. Within just a year or two after its Initial Public Offering in November 2015, the company’s financial and legal troubles began to surface. The worst blow came when VGS, the 60-year-old founder and CEO committed suicide on July 29, 2019. His group’s mounting debt and impending doom had propelled him to take his own life. Today, the future of CCD remains hanging in the balance, with creditors ready and willing to take the firm into bankruptcy.

Under-graduates and above.

Teaching notes are available for educators only.

CSS 1: Accounting and Finance.

Marketing.

Post Graduate.

Rajiv Bapna and Pradeep Bapna co-founded Allied Electronics & Magnetics Limited (widely known as Amkette) in the year 1985 for the production of floppy diskettes in India. By the year 1995, Amkette was the largest selling floppy diskette brand in India. With the advent of new technology in storage media sale of floppy diskette observed a constant decline. By the end of year 2004, floppy diskettes completely vanished from the market. Amkette anticipated the changes in the computer peripherals market and introduced a wide range of products in storage media, wireless and wired peripherals, accessories and digital lifestyle products. After the launch of Evo TV on June 2012, Amkette was hopeful for a major success in digital lifestyle segment. Evo TV, a connected TV device, allowed consumers to use smart apps on their television sets and was a cost-effective substitute to Smart TVs. Amkette was betting very high on Evo TV for revenue generation and market development.

Following are the learning outcomes: to review the product life cycle of technology products, to understand evolving customers’ expectations and behavior, to assess the adoption process of innovative products and to explore the challenges associated with innovative products for market development.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 8: Marketing.

For the first time in a decade, a new form of pneumonia virus, coronavirus, COVID-19, appeared in Wuhan, China. To date, it has affected millions of people, killed thousands and resulted in thousands of deaths around the world. To stop the spread of this virus, isolate the infected people. Computed tomography (CT) imaging is very accurate in revealing the details of the lungs and allows oncologists to detect COVID. However, the analysis of CT scans, which can include hundreds of images, may cause delays in hospitals. The use of artificial intelligence (AI) in radiology could help to COVID-19-positive cancer in this manner is the main purpose of the work.

CT scans are a medical imaging procedure that gives a three-dimensional (3D) representation of the lungs for clinical purposes. The volumetric 3D data sets can be regarded as axial, coronal and transverse data sets. By using AI, we can diagnose the virus presence.

The paper discusses the use of an AI for COVID-19, and CT classification issue and vaccination details of COVID-19 have been detailed in this paper.

Originality of the work is, all the data can be collected genuinely and did research work doneown methodology.

Computed tomography (CT) scan can provide valuable information in the diagnosis of lung diseases. To detect the location of the cancerous lung nodules, this work uses novel deep learning methods. The majority of the early investigations used CT, magnetic resonance and mammography imaging. Using appropriate procedures, the professional doctor in this sector analyses these images to discover and diagnose the various degrees of lung cancer. All of the methods used to discover and detect cancer illnesses are time-consuming, expensive and stressful for the patients. To address all of these issues, appropriate deep learning approaches for analyzing these medical images, which included CT scan images, were utilized.

Radiologists currently employ chest CT scans to detect lung cancer at an early stage. In certain situations, radiologists' perception plays a critical role in identifying lung melanoma which is incorrectly detected. Deep learning is a new, capable and influential approach for predicting medical images. In this paper, the authors employed deep transfer learning algorithms for intelligent classification of lung nodules. Convolutional neural networks (VGG16, VGG19, MobileNet and DenseNet169) are used to constrain the input and output layers of a chest CT scan image dataset.

The collection includes normal chest CT scan pictures as well as images from two kinds of lung cancer, squamous and adenocarcinoma impacted chest CT scan images. According to the confusion matrix results, the VGG16 transfer learning technique has the highest accuracy in lung cancer classification with 91.28% accuracy, followed by VGG19 with 89.39%, MobileNet with 85.60% and DenseNet169 with 83.71% accuracy, which is analyzed using Google Collaborator.

The proposed approach using VGG16 maximizes the classification accuracy when compared to VGG19, MobileNet and DenseNet169. The results are validated by computing the confusion matrix for each network type.

The COVID-19 pandemic has led to a huge loss of human life worldwide and presents an unprecedented challenge to public health, food systems and the world of work. Tens of millions of people are at risk of falling into extreme poverty due to loss of their carriers. Mainly, the people who work in public places are impacted due to this decease. The frontline warriors such as doctors, health workers, sweepers and policemen showed their effort to reduce the spreading of the virus. In this paper gives the detailed view of how the corona virus evaluated and how it spread from one person to another person and how we prevent this virus. The purpose of the paper, detailed about the diagnosis of the virus in the human body. There are some tests associated to know the presence of virus in our body; these are nose test, chest scan and CT scan of lungs.

Molecular analysis methods such as antibody or enzyme tests are used to assess whether the infection is present. The most common lancing techniques include using a cotton swab is in the back of the neck. Then hands over the sample to the doctor for examination. Polymerase chain reaction (PCR) is performed on the sample. This test screens for viral DNA. A CO19 PCR test can detect unique SARS-2 gene products. If one of these genes is ignored, it will return as an invalid result This test is useful only for patients who are already suffering from COVID-19. You cannot know if anyone has the infection, and they cannot say for sure whether they ever did. Serological tests are particularly useful for detecting cases of infection with mild or no symptom.

In this paper, the different tests provided to diagnosis the virus and the prevention measures to be taken to prevent the virus from spreading from one person to another are explained.

This work presents the original contribution and information of the COVID-19 pandemic.

Aluminium metal matrix composites are used in automotive and aerospace industries because of their high performance and weight reduction benefits. The current investigation aims to focus on the development of the stir cast aluminium-boron carbide composites with enhanced mechanical and tribological properties.

The aluminium-boron carbide composites are produced by stir casting process. Aluminium alloy A356 is chosen as the matrix material and three sets of composites are produced with different weight fractions of boron carbide particles. Higher particle size (63 µm) of boron carbide is chosen as the reinforcement material. Aluminium-boron carbide composites are tested for mechanical and tribological properties. The effect of process parameters like load, speed and percentage of reinforcement on the wear rate are studied using the pin-on-disc method. The interaction of the process parameters with the wear rate is analysed by DesignExpert software using RSM methodology and desirability analysis. The coded levels for parameters for independent variables used in the experimental design are arranged according to the central composite design. The worn surface of the pin is examined using a scanning electron microscope. The phases and reaction products of the composites are identified by X-ray diffraction (XRD) analysis.

Aluminium-boron carbide composites reveal better mechanical properties compared to monolithic aluminium alloys. Mechanical properties improved with the addition of strontium-based master alloy Al10Sr. The ultimate tensile strength, hardness and compressive strength increase with an increase in the reinforcement content. The wettability of the boron carbide particles in the matrix improved with the addition of potassium flurotitanate to the melt. Uniform dispersion of particles into the alloy during melting is facilitated by the addition of magnesium. Wear resistance is optimal at 8 per cent of boron carbide with a load 20 N and sliding speed of 348 RPM. The wear rate is optimized by the numerical optimization method using desirability analysis. The amount of wear is less in Al-B₄C composites when compared to unreinforced aluminium alloy. The wear rate increases with an increase in load and decreases with the sliding speed. The wear resistance increases with an increase in the weight fraction of the boron carbide particles.

The produced Al-B₄C composites can retain properties at high temperature. It is used in nuclear and automotive products owing its high specific strength and stiffness. The main applications are neutron absorbers, armour plates, high-performance bicycles, brake pads, sand blasting nozzles and pump seals.

Al/B₄C composites have good potential in the development of wear-resistant products.

The purpose of this study is to help the researchers, public, industries and government to realize the tremendous trends to improve the power quality of both sources and load side.

The work carried out in the Facts device and power quality issues.

Maintaining the quality of electric power is always a challenging task. The effect of power electronics devices leads to improper power quality. The use of FACTS devices is preferably the best approach to treat power-quality-related problems. Usually, all FACTS devices are constructed to operate on the side of either the source side or the load.

This paper explores a broad comprehensive study of various types of power quality problems and classification of FACTS devices with its recent developments. Furthermore unified power quality conditioner (UPQC) is particularly reviewed to highlight the advantages over other compensating devices. An exhaustive study of literature has been carried out and most significant concepts are presented