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An investor is expected to analyze the market risk while investing in equity stocks. This is because the investor has to choose a portfolio which maximizes the return with a minimum risk. The mean-variance approach by Markowitz (1952) is a dominant method of portfolio optimization, which uses variance as a risk measure. The purpose of this paper is to replace this risk measure with modified expected shortfall, defined by Jadhav et al. (2013).

Modified expected shortfall introduced by Jadhav et al. (2013) is found to be a coherent risk measure under univariate and multivariate elliptical distributions. This paper presents an approach of portfolio optimization based on mean-modified expected shortfall for the elliptical family of distributions.

It is proved that the modified expected shortfall of a portfolio can be represented in the form of expected return and standard deviation of the portfolio return and modified expected shortfall of standard elliptical distribution. The authors also establish that the optimum portfolio through mean-modified expected shortfall approach exists and is located within the efficient frontier of the mean-variance portfolio. The results have been empirically illustrated using returns from stocks listed in National Stock Exchange of India, Shanghai Stock Exchange of China, London Stock Exchange of the UK and New York Stock Exchange of the USA for the period February 2005-June 2018. The results are found to be consistent across all the four stock markets.

The mean-modified expected shortfall portfolio approach presented in this paper is new and is a natural extension of the Markowitz’s mean-variance and mean-expected shortfall portfolio optimization discussed by Deng et al. (2009).

This chapter looks at a number of diverse elements that led to the rise of the digital banking industry. In this age of rapid digitisation, today's bank transactions and activities are mostly done on mobile phones or other smart devices instead of going back and forth between a traditional branch lobby. With more and more customers seeking banking services accessible around the clock from the palm of their hand, based on the numerous experiential data digital platforms have accumulated for many years in the field and other places, traditional financial institutions will have no way but to break open their thinking about how to deliver those services to think. Governments and their regulators are beginning to see the potential risks posed by the new digital banking technology and want consumer protection, competition put under even stricter conditions for players as well and system stability all guaranteed. Above all, it is evidence of something people cannot ignore: the sharp upward trend of cybersecurity risk in recent years. The advent of digitalisation eliminated any excuse for storing sensitive financial data without the most modern cyber defences. Then, at a further level, financial tech start-ups come up like crocuses in spring while Bigtech companies all over the globe are jumping into banking. Both cooperation opportunities and competitive challenges await traditional banks. However, bank customers' changing demographics (millennials and GenZ) are the most vivid examples as they age, together with global universal financial inclusion trends, bringing about social and economic challenges.

The metaverse marks the beginning in a new era of digital interaction and innovation, having a significant impact on a variety of established sectors, including banking. This chapter exposes readers to the principles of data wrangling, laying the groundwork for comprehending its significance. It also looks at the specific issues presented by Metaverse Banking data, which includes a wide range of data kinds. To ensure consistency and practical relevance, these data must be processed in real time, whether for individuals or organizations. This chapter then transitions to unleash the power of data (which forms the lifeblood of Metaverse Banking), followed by a detailed explanation of advanced data-wrangling techniques and integration with Artificial Intelligence and machine learning. It showcases case studies illustrating how effective data wrangling has helped drive Metaverse Banking platforms by utilising real-world use cases that show the best practices of metaverse entities for a more customer-centric experience. This chapter also explores future trends, expecting the evolution of technologies for data wrangling and their possible repercussions. It further delves into regulatory considerations the nascent industry faces. This chapter underscores the need for a planned strategy in data management and provides suggestions along with best practices to guide stakeholders towards placing metaverse banks based on data. As the metaverse continues to expand and change, wrangling data will remain how banks can win on this digital frontier by keeping themselves nimble, safe and consumer-friendly in an ever more virtual world.

The purpose of this study is to provide a broad understanding of the pre-completion stage and subsequent abandonment of mergers and acquisitions (M&As).

A total of 117 peer-reviewed, English language articles published in scholarly journals were considered in the review. The approach includes a descriptive evaluation of the literature, coupled with content analysis. The paper uses both positivist and constructivist approaches to qualitative research. The analysis is conducted with the help of R programming and Gephi visualization software. The authors organize the work around the event of outcome/closure of deal proposal.

It is found that earlier studies sampled on domestic M&As in developed economies (DEs). However, the interest of scholars has increased in cross-border deals and emerging economies (EEs) in the last decade. Various factors interact and facilitate the completion/abandonment of good and bad deals. The authors find that complex non-linear relationships exist, and there is a need for studies with other classification techniques focusing on predictive accuracy.

The literature review is limited to articles available to the researcher using search terms related to M&A completion/termination. The databases accessed were: ProQuest, Scopus and Web of Science. However, backward snowballing was performed to avoid the omission of relevant articles.

The findings and subsequent discussions familiarize researchers and practitioners with an overview of research undertaken in the field of M&A abandonment. The authors find voids within the literature and suggest future research agendas.

As the COVID-19 epidemic ravages the world in the fourth industrial revolution era, the manufacturing sector faces its worst situation in a century. Lean philosophy, renowned as a “warrior philosophy,” can be an able rescuer to these industries. This study aims to identify the hurdles to lean strategy implementation and conduct an analysis to provide cognizance to policymakers, practitioners and decision-makers.

This study aims to identify the obstacles that obstruct lean implementation into seven primary barriers/components, with the fuzzy DEMATEL approach being used to evaluate the critical factors as well as the cause and effect factors among them. Expert opinions are sought to obtain the relevant data for evaluation purposes.

The results reveal that a firm should focus on firm cultural conflict scenario, resources–responses incapability, improve on suppliers’ attitude and execute a proper planning and logistics equation to alleviate the hindrances of implementing lean. As these causal factors influence the effect factors, namely, top management vision, management–employee relationship and human resource building, focusing on them automatically improves the effect factors; thus, the surge to overcome resistance to lean implementation is alleviated.

This research aids in identifying and analyzing lean implementation issues in the manufacturing and industrial sectors. The observations, results and insights drawn can act as a guiding force to rupture the resistance envelope covering the domain of lean implementation and possibly reinstating industries to survive and excel in the business post-COVID era.

This research introduces barriers to lean implementation in a unique way, as it articulates all sections of an industry and group the barriers based on the classification. It further prioritizes the barriers for their importance in the Indian industrial scenario. This would help the industry professionals and managers access the barriers and generate insight on how and where to start implementing lean.

This paper aims to review the recent advances in processing and utilization of Madhuca longifolia flowers to address its potential as an industrial ingredient.

The paper analyzes the harvesting practices of flowers and recent works on the value addition.

Mahua flowers are rich source of natural sugars (glucose, fructose, sucrose, etc.) and hence are deliberately used for liquor production by tribal besides various food products, namely, Mahua ladoo, barfi, kheer, sweet puri and as grain staple. Mahuain medicine has been curing people since ages such as in rakhtpitta, diarrhoea and skin diseases and as aphrodisiac, galactagogue, carminative, antihelmenthic, antibacterial and antioxidant. Mahua candy, cake, ready to serve beverages, toffee, squash, ladoo, bars, etc. have been developed as value-added products. However, such a wonderful nature’s gift remains underused due to post harvest spoilage.

Improvement in storage facilities and processing of flowers after harvesting and drying will lead to enhanced availability of flowers for industrial purposes for food, feed and fodder. More value-added products can be prepared by the preparation of flower-juice concentrate, as well as efforts are made to produce powder from the flowers.

Post-harvest spoilage of Mahua flowers due to improper collection and handling practices, and filthy storage conditions is the major limitation of Mahua flowers to be used as a potential industrial ingredient. An improvement in collection, handling and pre-processing practices can diversify its use from liquor production to various value-added and functional food products at an industrial scale.