Search results

While Blockchain can serve us, Bitcoin threatens our survival. If Bitcoin is assumed to be a country, it will rank 38th globally for energy consumption. With 90.2 metric million tonnes of carbon dioxide, Bitcoin mining and trading has emerged as an environmental threat. The current study investigates how the trading-specific variables, the prices of Crypto Index and Ethereum, affect bitcoin-based energy consumption. Also, the role of mining-specific variables is analyzed.

The study uses monthly data from various sources collected from December 2018 to January 2023. The authors used the Autoregressive Distributed Lag (ARDL) Model to determine the short- and long-term relationships between variables. This study uses the Theory of Green Marketing and the Theory of Cross Elasticity of Demand as a theoretical lens.

The findings show that escalating crypto market index and Ethereum prices with a one-month lag increases bitcoin-specific electricity consumption and carbon emissions. Green investors may shift to cryptocurrencies based on consensus other than of Proof-of-Work. Ethereum behaves like a substitute for Bitcoin, reflected by the long-term positive relationship between Bitcoin's energy consumption and Ethereum prices.

The study analyses how the crypto market index and Ethereum price affect bitcoin-based energy use. The relationships identified are substantiated by the literature to provide suggestions to green investors and policymakers to mitigate the harmful impact of Bitcoin's colossal energy consumption on the natural environment.

The purpose of this paper is to examine if the announcement of corporate power purchase agreements (PPAs) induce significant effects on the electricity buyers' stock returns.

This is an event study based on the Fama French Five Factor Model which uses several significance tests and robust regression approaches.

The announced closing of corporate PPAs induces significant positive abnormal stock returns. This announcement effect is even more pronounced in case of virtual PPAs.

To the best of the author‘s knowledge, this study is the first which explictly investigates the announcement effects of corporate PPAs, which are closed between the owner of the renewable energy asset and the institutional end consumer. In addition, this study extends the event study approach by robust regression methods.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

The coronavirus (COVID-19) is the worst pandemic in recent memory in terms of its economic and social impacts. Deadly second wave of COVID-19 in India shook the country and reshaped the ways organizations functions and societies behave. Medical infrastructure was unaffordable and unsupportive which created high distress in the Indian society, especially for poor. At this juncture, some pharmaceutical firms made a unique social investment when they reduced price of drugs used to treat COVID-19 patients. This study aims to examine how the market and the society respond to the price reduction announcement during the psychological distress of COVID-19.

Market reactions have been analyzed by conducting an event study on stock market data and visual analytics-based sentiment analysis on Twitter data.

Overall, this study finds positive abnormal returns on the day and around the day of event. Interestingly, this study finds that returns during the time of high distress are significantly higher. Sentiment analysis conveys that net sentiment is favorable to the pharmaceutical firms around the day of event and it sustains more during the time of high distress.

This study is unique in contributing to the business and industrial management literature by highlighting market reactions to social responsibility of business during the time of psychological distress in emerging economies.

This paper aims to propose an alternative method to measure idiosyncratic volatility and test whether the idiosyncratic volatility puzzle holds in commodity futures markets.

This paper proposes a partially new measure of idiosyncratic volatility in commodity futures markets based on the Schwartz and Smith (2000) short-term/long-term model. This model enables us to capture systematic risks of commodity futures markets in a parsimonious way.

Using a sample of futures contracts for 20 commodities from 1973 to 2022, this paper demonstrates that idiosyncratic volatility is more significant than systematic volatility in commodity futures markets, and that the idiosyncratic volatility puzzle does not hold in these markets. This paper also performs robustness tests to investigate whether the puzzle holds during subsample periods when commodity markets are more volatile and find consistent results. This study highlights the differences between commodity futures markets and equity markets and emphasizes the importance of investigating idiosyncratic volatility in commodity futures markets.

The contributions of this paper are threefold. First, this paper contributes to the literature by focusing on the idiosyncratic volatility of commodity futures returns. Second, this paper constructs a partially new measure of idiosyncratic volatility in commodity futures markets. Finally, this paper also contributes to the literature on the idiosyncratic volatility puzzle and demonstrates that the puzzle may not exist in commodity futures markets.

This study reviews existing cryptocurrency research to provide answers to three puzzles in the literature. First, is cryptocurrency more like gold (i.e., a commodity) or should it be classified as a new financial asset? Second, can we apply our knowledge of the traditional capital market to the emerging cryptocurrency market? Third, what might be the future of cryptocurrency?

Bibliometric analysis is used to assess 2,098 finance-related cryptocurrency publications from the Web of Science (WoS) Core Collection database from January 2009 to April 2022. Three key research streams are identified, namely, (1) cryptocurrency features, (2) behaviour of the cryptocurrency market and (3) blockchain implications.

First, cryptocurrency should be viewed and regulated as a new asset class rather than a currency or a new commodity. While it can provide diversification benefits to the portfolio, cryptocurrency cannot work as a safe haven asset. Second, crypto markets are typically inefficient. Asset bubbles exist and are exacerbated by behavioural finance factors. Third, cryptocurrency demonstrates increasing potential as a medium of exchange and store of value.

Extant review papers primarily study one or two particular research topics, overlooking the interaction between topics. The few existing systematic literature reviews in this area typically have a narrow focus on trend identification. This study is the first study to provide a comprehensive review of all financial-related studies on cryptocurrency, synthesising the research findings from 2,098 publications to answer three cryptocurrency puzzles.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

This chapter examines the potential of solar energy for the development of sustainable tourism in Croatia. Tourism is an important economic activity in the Croatian economy due to the mild climate and many sunny days. Solar energy photovoltaic and thermal systems can help to support sustainable tourism, as well as increase employment and cooperation between local and national governments. This study compares best practices in solar energy for the Mediterranean countries of Italy, Spain, Cyprus, and Greece. The Mediterranean Basin is a strategic development area for the European Union, and solar energy will help to maintain its stability and high-quality standards of living.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

The learning outcomes of this case study are to understand the business model canvas and value propositions and apply advanced business innovation tools in electric vehicle business models; evaluate the current cargo vehicle scenarios at national and global levels and draw out the possibilities and costs for a new player; extrapolate the future scenario of the cargo economy, its electrification and positioning in a business-to-business (B2B) and business-to-customer (B2C) segment, especially for a developing economy; and improve the student’s ability to get organisational buy-in and execute new business models.

LoadExx is a fully electrified electric cargo service focusing on logistics in Kolkata, a metropolitan city in the eastern part of the country. The service of LoadExx commenced in January 2021 in the B2B segment after overcoming its then issues of driver hesitancy and customer anxiety and financial issues to adopt electrified cargo systems. The conundrum faced by LoadExx in its commencement thus had been solved under the able guidance of its owner Amit Arora. The case study was positioned four months after the commencement of LoadExx. To gain market power and traction, Arora and his team came up with the idea of market expansion. However, the current conundrum was whether LoadExx would enter the B2C segment in its current location or expand with the same business model to other parts of the country. The expansion was to be implemented in the immediate future to retain its rarity and reduce the imitability of the business model of LoadExx. This case study details the logistics and market operations of the cargo sector, especially electric cargo, in a developing economy, especially India. A teaching note supplementing the “Cracking the conundrum of e-cargo logistics: curious case of LoadExx” case study has been provided.

This case study is designed for undergraduate and postgraduate students and senior management professionals in executive education programmes undertaking courses in logistics management and supply chain operations and related cargo logistics courses. This case study denotes integrating key processes from end-users and gaining the trust of drivers, thereby showing the perspective of the plight and conundrums of a cargo aggregator working in the B2C segment. This case study could be used to discuss concepts related to not-for-profit firms, aggregators, policymakers and think tanks.

Teaching notes are available for educators only.

CSS 9: Operations and logistics.