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This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

The learning outcomes are as follows: Understand the concept and characteristics of Bottom of Pyramid (BoP) markets; understand the concept and characteristics of frugal innovations; understand the Design Thinking approach to product design and how it might be useful to develop frugal innovations for BoP markets.

The case details the journey of a group of students at a premier engineering college in India. The group aimed to develop and implement a social innovation that addressed a serious and important health issue – menstrual hygiene practices among urban slum dwellers in India. The case begins with how a chance visit to an NGO inspired a pair of students to take up this issue, how the project unfolded at their college, the challenges faced in their journey and, finally, an outcome that was only a partial success. It raises important questions of challenges that are specific to bottom of pyramid markets in emerging economies. The case can provide a context for discussions on approaching frugal innovations from a Design Thinking perspective.

This case can be used in social innovation courses/modules at an undergraduate or graduate level in social innovation and social entrepreneurship courses. The case is best positioned towards the beginning of the course as an overview of the process of Social Innovation, and to discuss the relevance of concepts of BoP markets and frugal innovation.

Teaching Notes are available for educators only.

CSS 7: Management Science.

The purpose of this paper is to investigate the relationship between dividend policy and the life cycle of firms in India. In addition, this study intends to examine the variation in dividend behaviour over the life cycle of a firm. The study anticipates that a firm's dividend behaviour varies over its life cycle.

To scrutinize the validity of the proposition, the authors classify 1968 non-financial industrial firms listed at Bombay Stock Exchange (BSE) into growth, mature and stagnant firms over the period 2000–20. Additionally, to check the robustness of the results, they use an array of techniques such as analysis of variance, pooled ordinary least squares, fixed effects models and random effects models.

The empirical findings suggest that dividend behaviour varies over a firm's life cycle. Specifically, stagnant firms are paying significantly higher dividends than growth firms. Mature firms are paying significantly higher dividends than growth firms. The results are consistent after controlling the effects of firm's size, profitability, leverage, operating risk, systematic risk and growth opportunities.

The findings are useful for corporate decision makers in establishing an appropriate dividend policy conditional on firms' life cycle stage and for shareholders in making investment decisions.

The relation between dividend policy and firm life cycle has not been examined before in the context of Indian stock market. Thus, this research bridges this gap in the literature.

The purpose of this paper is to study the various solutions and recommendations provided by researchers in applying the blockchain concept to different problems in aviation industry. It will discuss and highlight the specific approaches that leverages blockchain to mitigate the automatic dependent surveillance-broadcast (ADS-B) security issues. Furthermore, it introduces an innovative design and method to secure ADS-B data using a tamper-resistant distributed public ledger of authenticated flight plans and validates the position and other parameters of the associated aircraft identifier against the flight paths/routes that are stored in the blockchain ledger.

ADS-B is the key technology that is mandated by Federal Aviation Administration in USA by 2020. However, ADS-B data is neither encrypted nor authenticated. This paper proposes a novel solution using blockchain to secure the ADS-B data communications and in-depth analysis of existing solutions covering the following aspects: classification of various possible attacks on ADS-B. Presents various solutions proposed by different researchers regarding use of blockchain in aviation industry. Discuss a new solution to secure ADS-B using blockchain. Discuss the high-level architectural framework of the proposed and patented solution. Finally, presents the conclusions and future work scope.

While the main intention of this paper is to bring together all the existing solutions using blockchain to secure aviation and ADS-B data at one place, the proposed novel solution could contribute to maintaining security and privacy for aircrafts flying in the airspace at any point in time. Continuously securing the ADS-B data transmissions based upon the filed flight plans in real time can provide a mechanism to identify spoofed aircraft messages and communicate the same to ground stations for authentication of existence of such a malicious aircraft. Thus, this solution also differs from all the existing ones.

As aviation industry is in its infancy stage in implementing blockchain-based solutions, practical implementation of the proposed concept might take longer.

This paper is a comprehensive survey and review paper. To the best of the authors’ knowledge, this is the first of its kind that presents various use cases for usage of blockchain in aviation industry along with a detailed review of existing proposed or implemented solutions using blockchain to secure ADS-B data. This can serve as an invaluable reference for the future researchers on this topic in both industry and academia.

This research study aims to design a novel risk-managed time-series momentum approach. The present study also examines the time-series momentum effect in the Indian equity market. Apart from this, the study also proposes a novel risk-managed time-series momentum approach.

The study considers the adjusted monthly closing prices of the stocks listed on the Bombay Stock Exchange from January 1996 to December 2020 to formulate long-short portfolios. Newey–West t statistics were used to test the significance of momentum returns. The present research has considered standard risk factors, i.e. market, size and value, to evaluate the risk-adjusted performance of time-series momentum portfolios.

The present research reports a substantial absolute momentum effect in the Indian equity market. However, absolute momentum strategies are exposed to occasional severe losses. The proposed time-series momentum approach not only yields 2.5 times higher return than the standard time-series momentum approach but also causes substantial enhancement in downside risks and higher-order moments.

The study's outcomes offer valuable insights for professional investors, capital market regulators and asset management companies.

This study is one of the pioneers attempting to test the time-series momentum effect in emerging economies. Besides, current research contributes to the escalating literature on risk-managed momentum by suggesting a novel revised time-series momentum approach.

The purpose of this paper is to evaluate the value of internship as a function of the disparity between the initial expectation from the internship and its actual experience. The perceived internship experience has been evaluated through the expectation confirmation theory (ECT).

A sample of 106 students pursuing Master of Business Administration in a business school in India were administered a questionnaire to assess their expectations and experience before and after the internship. The self-designed questionnaire based on review of extant literature on internship included items related to supervisor–intern exchanges, significance of prior classroom academic preparation, prior work experience and perceived learning value. Students’ assessment scores on the internship project were taken as the outcome variable.

Pre- and post-analysis of perceived internship value indicated a positive expectation disconfirmation. The result indicates that “Positive Expectation Disconfirmation” has a significant direct relationship with overall satisfaction with internship. Structural equation modeling further revealed that perceived quality of the supervisor–intern exchange has a significant relationship with perceived internship value. Perceived significance of classroom academic preparation has a weak negative relationship with both perceived internship value and internship performance. Perceived internship value has a weak positive relationship with internship performance.

It is first time an attempt has been made to look into the issue of internship from the ECT.

This study aims to measure the level of public awareness about the threat of the emerging coronavirus (COVID-19) pandemic among the Omani population. It also aims to investigate the mediating effect of the Omanis’ attitudes and behaviors with underlying conditions of COVID-19.

A cross-sectional study was conducted to collect data via an online survey of Omani citizens and residents from various geographic areas in Oman, 305 responses were received. SPSS and partial least square-structural equation modeling were used for data analysis.

The study revealed that public awareness regarding the COVID-19 pandemic was significantly influenced by people’s perceived risk, information source and health-related knowledge. Further, preventive behavior during the disease spread has a significant direct and indirect impact on their awareness. However, an insignificant mediation effect of public attitude was found between the source of information and public awareness.

This study is limited by the scarcity of related literature in the Omani context. It is recommended that future research complete an in-depth study of public awareness regarding COVID-19, using other constructs and/or other data collection techniques.

This research will provide governmental health authorities and policymakers with a guideline to establish more efficient pandemic containment strategies to control public behavior toward the COVID-19 pandemic and curb viral prevalence.

This research will help in improving prevention measures against COVID-19 are recommended to be more educated through a more effective mechanism to raise public attitude regarding pandemic prevalence positively.

The originality of this research can be drawn from key findings that indicate that people overall gained knowledge about how to deal with the COVID-19 pandemic and the accuracy of information significantly impacts public awareness.

From a pedagogical point, the case may fulfill following objectives: First, to understand Vodafone’s position in the current environment. Does the environment present the elements that are necessary for them to thrive (as analyzed using a PESTEL framework)? Second, to understand the resources needed to build competitive advantage in an emerging market context (as analyzed using the Porter five forces model); and third, to understand the competitive challenges of conducting business in a highly (and sometimes capriciously) regulated industry.

The Indian Telecommunication sector is one of the fastest growing industries in the world. There are nine telecom operators who are pioneering this growth; however, five private companies: Bharti, Idea, Reliance, Aircel and Vodafone make up 78.86 per cent of the market. These five companies have the opportunity to increase their market share by expanding the services provided to rural India; however, the Indian Tax Authorities have caused some hesitation. Aside from being known as heavy handed and unpredictable, the authorities have also demanded that Vodafone pay them billions in taxes. These court cases have challenged the way that other telecom operators look at investing. The arrival of Reliance Jio as a new player in the Indian wireless space with deep pockets has not helped the already fierce competitive landscape. Reliance Jio is forcing all wireless companies including Vodafone to reevaluate their India strategy.

This case could be used in both MBA and executive education programs.

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CSS 11: Strategy.

This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum industry.

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) is initially used to identify key barriers as reported in extant literature. The decision-making trial and evaluation laboratory (DEMATEL) technique is then used to discover the interrelationships between the barriers, which are then prioritised, based on three criteria (time, cost and relative importance) using complex proportional assessment (COPRAS) and multi-objective optimisation method by ratio analysis (MOORA). The Delphi method is used to obtain and analyse data from 10 petroleum experts who work at various petroleum facilities in India.

The findings provide practical insights for management and accident data analysts to use ML techniques when analysing large amounts of data. The analysis of barriers will help organisations focus resources on the most significant obstacles to overcome barriers to adopt ML as the primary tool for accident data analysis, which can save time, money and enable the exploration of valuable insights from the data.

This is the first study to use a hybrid three-phase methodology and consult with domain experts in the petroleum industry to rank and analyse the relationship between these barriers.