Search results

As the move from the business incubator loomed, Abdul Khan had to decide where his business should relocate to. ACEES Group LLC, a small consulting firm, had grown from three friends working out of Abdul Khan’s house to a 20-person firm generating more than a million dollars in revenue within five years. This growth had necessitated the need for a larger and more prominent place. Although Abdul knew he did not want to renew the lease at the incubator, and he did not want to move his business too far from its current location, but the decision he had to make was whether ACEES Group should lease a commercial place or buy its own property. He was particularly torn because the real estate prices had fallen considerably, and were now on the mend and interest rates were still low.

The primary source of materials in the case was an interview with the owner (pseudo name: Abdul Khan). The owner wishes to remain anonymous. The financial statements of the firm produced in the case have been modified by a fixed factor so as to disguise the actual numbers but not materially alter the information in any fashion. Other secondary sources of materials include information about the business incubator program, the MBE certification and its benefits through the State of Florida, real estate and lease rates in Central Florida and other economic information.

This case is primarily intended for undergraduate students taking a course in entrepreneurship, real estate investments or financial management, with emphasis on real estate valuation, cash flow forecasting and/or valuation of business. Students should be familiar with time value of money concepts, understand the concept of NPV and IRR, and preferably be comfortable in the use of Excel. This instructor manual provides all calculations of space needs analysis, and discounted cash flow analysis for lease vs buy analysis. A few suggestions to discuss qualitative aspects of this decision making are also included.

Document retrieval has become a hot research topic over the past few years, and has been paid more attention in browsing and synthesizing information from different documents. The purpose of this paper is to develop an effective document retrieval method, which focuses on reducing the time needed for the navigator to evoke the whole document based on contents, themes and concepts of documents.

This paper introduces an incremental learning approach for text categorization using Monarch Butterfly optimization–FireFly optimization based Neural Network (MB–FF based NN). Initially, the feature extraction is carried out on the pre-processed data using Term Frequency–Inverse Document Frequency (TF–IDF) and holoentropy to find the keywords of the document. Then, cluster-based indexing is performed using MB–FF algorithm, and finally, by matching process with the modified Bhattacharya distance measure, the document retrieval is done. In MB–FF based NN, the weights in the NN are chosen using MB–FF algorithm.

The effectiveness of the proposed MB–FF based NN is proven with an improved precision value of 0.8769, recall value of 0.7957, F-measure of 0.8143 and accuracy of 0.7815, respectively.

The experimental results show that the proposed MB–FF based NN is useful to companies, which have a large workforce across the country.

The case aims to understand and analyse the capital structure decisions made by a profit-making, growing organisation which aimed to be India’s premier airline and the market leader. The company that had pursued a high debt policy, to take advantage of the financial leverage that it would get, was now facing problems in an operating environment that proved to be challenging. A decline in operating profit, coupled with high-interest costs and an uncertain environment with cutthroat competition, had caused the company to plunge into losses. Attempts to deleverage by equity infusion were proving to be difficult. The case can be used in MBA, Executive Education and doctoral programmes. The learning objectives of this case are: to analyse the capital structure of the company, to interpret the relationship between financial leverage and risk, to assess the pecking order theory, to analyse the nuances of the aviation sector and the factors influencing the profitability of the companies in the aviation industry, to estimate the risks and the rewards associated with foreign currency loans, to evaluate the magnifying impact of the financial leverage and to propose deleveraging methods like sale and leaseback, debt conversion to equity and devise a revival strategy for the company.

The case discusses the dilemma faced by Naresh Goyal, promoter and chairman of Jet Airways (India) Limited. At the initial stage, Jet Airways, like many other companies in its growth phase, relied on borrowed funds to meet its investment needs. However, over-reliance on borrowed funds with just one equity infusion resulted in a high leverage ratio and an aggressive capital structure. Moreover, the company operated in a sector that was highly regulated, with competition that was cutthroat and a cost structure that was volatile. A high operating risk, coupled with high financial leverage, pushed the company into incurring losses. Having run out of cash, Jet Airways eventually defaulted on loan repayments to its lenders. Facing the eventuality of losing control of the company to lenders or to a strategic investor, Goyal was trying to figure out a way to save the company from insolvency and liquidation. It was becoming increasingly difficult for Goyal to keep Jet Airways, the company he had nurtured like a baby, airborne.

The case can be taught in both online and offline modes of delivery in a 90-minute session. Post-covid, the delivery mode of classes has changed. In online sessions, it may be a challenging task to ensure student participation.

Teaching notes are available for educators only.

CSS 1: Accounting and Finance.

This paper aims to measure outcome quality in banks in India and to make a comparative assessment of its influence on customer service quality perceptions. Though both functional quality (i.e. how service is delivered) and outcome quality (i.e. what is delivered) are important aspects of service quality, it is the functional quality which has primarily been the focus of past studies.

The data used in the study are based on a survey of bank customers located in Delhi and National Capital Region. Using the exploratory factor analysis and confirmatory factor analysis, validity and dimensionality of the multi-item functional and outcome quality scales used in the study were assessed. A structural model of relationships of functional and outcome quality with overall service quality was tested through use of the structural equation modeling (SEM) approach.

The study finds outcome quality as being a significant and major determinant of customer service quality perceptions in banks. Inclusion of outcome quality in the analysis is, moreover, found to be helpful in capturing more exhaustively the variations present in customer overall service quality perceptions.

Both the functional and outcome quality in the study have been measured through scales adapted from past studies. But the same have not been found able to fully capture variations in customer service quality perceptions. More psychometrically sound scales to measure functional and outcome quality are needed. Studies in both the developing and developed countries and additional service sectors are called for to increase the generalizability of the study findings. Furthermore, nomological validity of the outcome quality scale needs to be investigated by relating it with other anent constructs, such as customer satisfaction and their behavioral intentions.

Instead of simply remaining preoccupied with functional quality, i.e. process or how part of service delivery, bank management also needs to gauze customer outcome quality perceptions (i.e. what the customers think they are eventually getting out of their transactions with the service provider) and exercise due care to see that customers in fact are getting the core banking tasks performed for which they approach the banks in the first instance.

Present study is first of its kind in investigating role of outcome quality in banking services sector in the context of an emerging market like India. Use of SEM for analyzing both the measurement and structural models constitutes another noteworthy feature of the study.

Board meeting was in full swing as an important announcement had been made by Manish Jain, MD FinMen Advisors Pvt. Ltd. ‘We need to get 5,000 clients by 2023’. Management board members look at each other in wonder as they have only 500 clients in 2018. ‘That's a herculean task’, says a board member, ‘Besides, the clients’ fees are reducing in our business'. Manish interrupts to suggest that it is precisely the reason they want to enhance their client base. But the board members were still not convinced. Their questions revolved around whether they are equipped enough in terms of resources and infrastructure to reach to the number suggested by Manish. There were issues in the processes and systems of the company, there were issues in employees taking onus of leading certain verticals in the company, there were no branding exercise in terms of increasing awareness about the company. On the whole, in order to reach 5,000 clients, a total revamp of processes, systems and training employees needed to be given huge emphasis. But does the company have money for revamping all these issues? ‘I don't care’, says Manish, ‘Any client in any industry looking for credit ratings should be our client’. As Manish moves out of the board room, he says to himself that he was well aware of the facts questioned by the board members. But as a person ready to take up challenge and enjoy the perils of it, Manish was not ready to reconsider any of the points raised by the members. He thought whatever has to be done, has to be done to achieve targets set by him. However, sitting in his office and thinking about the future, Manish was still on the same dilemmic question as any employee in his company: how does he achieve the figure of 5,000 clients by 2023?

Rapid product/process realization and enterprise integration have been identified among the major imperatives for enabling the next generation manufacturing paradigm. This paper proposes a virtual factory modeling approach to support these imperatives. A virtual factory is defined as an integrated simulation model of major subsystems in a factory that considers the factory as a whole and provides an advanced decision support capability. It seeks to go beyond the typical modeling of one sub‐system at a time, such as the manufacturing model, the business process model and/or the communication network model developed individually and in isolation. A basic virtual factory model of a semi‐conductor backend factory has been developed for concept demonstration. Application examples are used to demonstrate the integration between business processes and manufacturing system performance. Future work will move further towards the development of the complete virtual factory and its industry applications.

This case study aims to understand the criticalities of hiring in a knowledge-based start-up; the various ways of retaining talent in a knowledge-based start-up; the competency requirements of human resource professionals in start-up organizations; the trade-off between business profitability and the R&D drive of the company; and the various organizational structures available for a knowledge-based start-up.

Ayush Jain, a first-generation entrepreneur, is facing a challenge with his start-up, TechShlok. TechShlok is an IT solution provider with its headquarters in Jaipur, India. The company is doing very well and is able to achieve many accolades. As the company grows in business and employee strength, it is facing talent acquisition and retention challenges. Ayush is in a fix to solve the talent issue and retain the key talent of the organization.

The case can be taught in a Human Resource Management course, including “talent management” and “human resource planning”. The case may be taught at upper undergraduate levels. It can also be taught in courses of entrepreneurship and knowledge-based start-ups.

Teaching notes are available for educators only.

CSS 11: Strategy.

Research in the domain of behavioral finance has proven that investors demonstrate irrational behavior while making investment decisions. In a similar domain, the primary objective of this research is to prioritize the behavioral biases that influence cryptocurrency investors' investment decisions in the Indian context.

A fuzzy analytic hierarchy process (F-AHP) was used to prioritize the behavioral factors impacting cryptocurrency investors' investment decisions. Overconfidence and optimism, anchoring, representativeness, information availability, herding, regret aversion, and loss aversion are among the primary biases evaluated in the present study.

The findings suggested that the two most important influential criteria were herding and regret aversion, with loss aversion and information availability being the least influential criteria. Opinions of family, friends, and colleagues about investment in cryptocurrency, the sale of cryptocurrencies that have increased in value, the avoidance of selling currencies that have decreased in value, the agony of holding losing cryptocurrencies for too long rather than selling winning cryptocurrencies too soon, and the purchase of cryptocurrencies that have fallen significantly from their all-time high are the most important sub-criteria.

This survey only covered active cryptocurrency participants. Additionally, the study was limited to individual crypto investors in one country, India, with a sample size of 467 participants. Although the sample size is appropriate, a larger sample size might reflect the more realistic scenario of the Indian crypto market.

The study is relevant to individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, market regulators, and society at large.

To the best of the authors' knowledge, no prior research has attempted to explain how the overall importance of various criteria and sub-criteria related to behavioral factors that influence the decision-making process of crypto retail investors can be assessed and how the priority of focus can be established, particularly in the Indian context.