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The purpose is to derive the most effective place in the air for an aerial robot, viz., drone to use as an alternative communication system during disasters.

In this technology-driven era, various concepts are becoming the area of interest for multiple researchers. Drone technology is also one of them. The researchers, with interest in drones, are therefore trying to understand the various uses of employing drones in diverse applications which are mind-boggling, starting from civil applications (viz., an inspection of power lines, counting wildlife, delivering medical supplies to inaccessible regions, forest fire detection, and landslide measurement) to military applications (viz., real-time monitoring, surveillance, patrolling, and demining). However, one area where its usage is still to be exploited in many countries is using drones as a relay when communication lines are disrupted due to natural calamities. This will be particularly helpful in rescuing the affected people as the aerial node will enable them to communicate to the rescue team using mobiles/ordinary landline telephones even when regular communication towers are destroyed due to disastrous natural calamities, for example, tsunamis, earthquakes, and floods. Various algorithms, namely, water filling algorithm, advanced water filling algorithm, equal power distribution algorithm, and particle swarm optimization, were therefore studied and analyzed using simulation in addition to various path loss models to realize the desired place for an aerial robot, viz., drone in the air, which will eventually be used as an alternative communication system for badly hit ground users due to any disaster.

It was found that the effective combination of the water filling algorithm and particle swarm optimization algorithm may be done to place the drone in the air to increase the overall throughput of the affected ground users.

The research is original. None of the parts of this research paper has been published anywhere.

The purpose is to design a system in which drones can control traffic most effectively using a deep learning algorithm.

Drones have now started entry into each facet of life. The entry of drones has made them a subject of great relevance in the present technological era. The span of drones is, however, very broad due to various kinds of usages leading to different types of drones. Out of the many usages, one usage which is presently being widely researched is traffic monitoring as traffic monitoring can hover over a particular area. This paper specifically brings out the basic algorithm You Look Only Once (YOLO) which may be used for identifying the vehicles. Consequently, using deep learning YOLO algorithm, identification of vehicles will, therefore, help in easy regulation of traffic in streetlights, avoiding accidents, finding out the culprit drivers due to which traffic jam would have taken place and recognition of a pattern of traffic at various timings of the day, thereby announcing the same through radio (namely, Frequency Modulation (FM)) channels, so that people can take the route which is the least jammed.

The study found that the object(s) detected by the deep learning algorithm is almost the same as if seen from a naked eye from the top view. This led to the conclusion that the drones may be used for traffic monitoring, in the days to come, which was not the case earlier.

The main research content and key algorithm have been introduced. The research is original. None of the parts of this research paper has been published anywhere.

Marketing, strategy, and integrated marketing communication.

The case is suitable for analysis in an MBA level marketing communication course where the theories of hierarchy of effects (HoE) models, push vs pull strategies as well as positioning strategies can be introduced. The case is suitable for analysis in an MBA level marketing course for the module on marketing communications/advertising and promotions.

Sanjay, the regional head of PepsiCo India (eastern region), had been tasked with the preparation of a support plan for a new communication campaign of Mountain Dew, a yellow-coloured drink in PepsiCo's soft-drink portfolio. He had attended a meeting at the headquarters where he had been briefed on the new national campaign roll-out for Mountain Dew – for the first time with celebrity association. While Mountain Dew had been growing its market share in other regions of the Indian market, the Eastern region had been unresponsive to the mass media image building campaigns. During the meeting, the various aspects of Mountain Dew's performance were discussed and Sanjay was asked to prepare a support plan for the national campaign that will help to increase revenues and market share of the brand in the Eastern region.

To understand the complexities of differential impact of integrated nation-wide communications on various segments of the market due to cultural variations, to understand the role of push strategy vs pull strategy in marketing communications, to understand the role of consistency in image between the trade and consumers perception, to understand the impact of celebrity endorsements, an introduction to the HoE communication models and their applications, to understand limitations of the HoE and Think-Feel-Do models in objective setting and understanding the uses of alternative models, to build a communication plan based on pull vs push strategy.

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

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

The case study is designed to help students understand how the “growth at all costs” attitude can lead to compromised corporate governance in a start-up leading to disastrous implications for all the stakeholders. This case study aims to make students understand the components of the fraud triangle, the impact of financial fraud on various stakeholders, the role of venture capitalist (VC) investors and the importance of good corporate governance in start-ups. The case study presents an excellent opportunity for students to discuss the consequences of ignoring good governance in the pursuit of growth in a start-up. After analyzing the case study, the students shall be able to explain the concept of the fraud triangle and to be able to identify the motivation, opportunity and rationalization of financial irregularities in a start-up; analyze the impact of financial irregularities on various stakeholders; comprehend the business model of VCs and evaluate its influence on VC-funded start-ups; and appraise the importance of good corporate governance in start-ups.

The case study revolves around the confession of financial irregularities made by one of the cofounders of GoMechanic, a start-up headquartered in Gurugram, India. On January 18, 2023, Amit Bhasin confessed to financial irregularities in the company’s financial statements, leading to laying off 70% of the workforce of the company. GoMechanic had earlier raised close to US$62m [1] from maverick global investors including Sequoia Capital, Tiger Global, Orios Venture Partners and Chiratae Ventures, and was negotiating to raise Series D financing from the Japanese multinational SoftBank with aspirations to be a unicorn (start-up with a valuation of over $1bn). The confession led to a debate about the consequences of the “growth at all cost” culture being followed by start-ups as well as VCs. GoMechanic was not an isolated instance of a lack of governance in the start-ups. The confession had consequences not only for the GoMechanic but for the entire start-up ecosystem of India, which was the third largest in the world. Bhasin stated that the founders take full responsibility for the situation, and they were working on a plan which was most viable under the circumstances. However, it was not going to be easy to regain the confidence of the investors.

The case study is best suited for senior undergraduate- and graduate-level business school students and in executive education programs in courses such as corporate governance and ethics, private equity and entrepreneurial finance.

Teaching notes are available for educators only.

CSS 1: Accounting and finance

Reality television is a dynamic, profit-making platform that occupies prime-time slots on the television almost all over the world. Despite its immense popularity and influence, it has received little attention in the extant literature and almost none in terms of its impact on celebrity repositioning. This study aims at examining the relationship between the film stars as brands and the impact of the platform of reality television in repositioning these celebrities in the Indian context.

Through extensive literature review and qualitative interviews, the paper expounds that reality television provides an opportunity to celebrities to successfully reposition themselves at crucial junctures in their career. The framework to study this repositioning has been adopted from the work of Chris Simms and Paul Trott (2007) who created it to study the brand repositioning of various consumer goods.

The literature establishes celebrities as brands. This study provides evidence that brand repositioning through reality television is possible for these celebrity brands. The symbolic and functional repositioning of these celebrities is presented through thematic content analysis.

The study provides a useful framework to understand celebrity brand repositioning through reality TV. It can also be replicated to understand the repositioning of a wide variety of celebrities other than film-stars such as sportspersons, social media influencers and politicians.

The paper contributes to the need of expanding the corpus of Indian reality television and explains how Indian celebrities reposition themselves through reality television.

The purpose of this exploratory study is to highlight the stages in the relationship which eventually lead to an integrated logistics alliance.

The stages involved in the evolutionary process have been explained with the help of concepts of mental models and knowledge-related asymmetries. The study has been justified by applying multiple case research design which involves examples of successful logistics alliances.

The analysis using case study approach provides a detailed overview how third-party logistics providers develop successful relationships with different industry firms over a period of time which eventually lead to innovations benefiting both the partners.

In the paper, a qualitative case study methodology has been adopted which is limited in nature when compared to quantitative approach. Nevertheless, the multiple cases discussed in the paper involve organizations from diverse sectors thus providing a holistic perspective and adding value to the current strategic alliance literature.

The complete understanding of the concepts discussed in this paper will help companies revisit their business strategies and identify areas of improvements in their current engagement practices with third-party logistics providers.

Many a time, relationships fail to develop into an alliance and research related to the attributes causing these failures might be limited. In the past, though many papers have talked about strategic alliances between third-party logistics providers and customers, little has been discussed about how such relationships evolve into successful strategic alliances.

This study aims to explore the effects of responsible international investment in a least developed country (LDC) on ethics and corruption in the local industry. While investment growth in least developed countries (LDCs) is essential to meet the United Nations Sustainable Development Goals, international investment in LDCs poses challenges, including corruption. The authors explore perspectives from relevant stakeholders on the influence, if any, on an LDC’s banking sector, of investment in the LDC by a multinational bank with an environmental, social and governance focus – using a case study of Standard Chartered Bank (SCB) in Nepal.

The authors conducted thematic analysis on: focus groups with current and former SCB Nepal management; semi-structured interviews with Nepal banking regulator representatives; senior staff from SCB global divisions; and management of other commercial banks in Nepal.

Knowledge transfer, organisational enablers and constructive international competition contributed to the dissemination of best practices within the Nepal banking sector, supporting the notion of beneficial spill-over effects of multinationals on LDC host countries.

Practical insights will aid LDC governments, international businesses, investment funds and donor organisations seeking to invest in/assist LDCs with economic development.

To the best of the authors’ knowledge, this may be the first case study on ethics and anti-corruption practices of a multinational bank in a LDC. Through a practice-driven focus, the authors provide “on-the-ground” insights to better understand the complex nature of corruption.

The objective of this paper is to investigate the effect of working capital efficiency (WCE) and its components on the composite financial performance of a sample of Indian firms.

Our sample includes 796 non-financial listed firms from 2015–16 to 2021–22. Sample firms’ profitability, liquidity, solvency, cash flow management, and financial and operational leverage have been used to classify them into companies with high composite financial performance (HCFP) and with low composite financial performance (LCFP) by using K-Means Clustering technique. A composite financial performance score (CFPS) of 1 has been assigned to HCFP and 0 to LCFP. We have used logistic regression models with fixed effect to estimate the effect of cash conversion cycle (CCC) and its components, i.e. inventory days, accounts receivable days and accounts payable days on CFPS in the presence of control variables such as growth, leverage, firm size, and age.

The study finds that CCC and inventory days are inversely associated with CFPS. This finding shows that the firms’ WCE leads to superior financial performance on a composite basis.

The research findings are based on samples drawn from the population of the listed Indian non-financial companies. Since the operation, financial practices, working capital policies, and management styles of firms vary greatly among nations, the results of this study should be extended to firms in other countries after taking into account the degree of resemblance to the sample firms.

The findings of this study hold significant value for industry practitioners, as they provide guidance in determining the optimal allocation of funds for working capital and devising strategies for effectively managing inventory levels, credit sales, and vendor payments in order to increase the overall value of the company. This study aims to help investors in building their investment portfolios by identifying companies with superior composite financial performance. Investors can enhance the construction of their investment portfolios by strategically selecting companies that demonstrate superior overall performance.

The results of our study will help companies improve their WCM strategies to enhance their overall value, and their significance increases manifold during economic downturns. Business firms that perform well by efficiently managing their working capital have a multiplier effect on the economy and society at large in the form of GDP contribution, labor income, taxes to the government, investment in capital assets, and payments to suppliers.

To understand the impact of WCE on firms’ performance, the extant working capital literature focuses on some specific characteristics such as profitability, valuation, solvency, and liquidity. The limitation of employing a single parameter is its inability to present the comprehensive performance evaluation of firms. This study is among the earliest studies that focus on the holistic evaluation of WCE's impact on the composite performance of a company.