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This paper aims to study the ongoing and emerging technological changes in the global energy sector from the frequently neglected perspective of their potential destructive impact on the Russian economy.

Having reviewed existing global energy forecasts made by reputable multilateral and national government agencies, major energy corporations and specialised consulting firms, the authors noticed that most of them are by and large based on the extrapolation of conventional long-term trends depicting gradual growth of fossil fuels’ demand and catching-up supply. Unlike this approach, the paper focuses on the possible cases when conventional trends are broken, supply–demand imbalances become huge and the situation in the global energy markets is rapidly and dramatically changing with severe consequences for the Russian economy, seriously dependent on fossil fuels exports. Revealing these stress scenarios and major drivers leading to their realisation are in the focus of the research. Based on the Social, Technological, Economic, Environmental, Political, Values (analytical framework) (STEEPV) approach, the authors start from analysing various combinations of factors capable to launch stress scenarios for the Russian economy. Formulating concrete stress scenarios and assessing their negative impact on the Russian economy constitute the next step of the analysis. In conclusion, the paper underlines the urgency to integrate stress analysis related to global energy trends into the Russian national systems of technology foresight and strategic planning, which are now in the early stages of development.

The analysis of global energy market trends and various combinations of related economic, political, technological and ecological factors allowed to formulate four stress scenarios particularly painful for the Russian economy. They include the currently developing scenario “Collapse of oil prices”, and three potential ones: “Gas abundance”, “Radical de-carbonisation” and “Hydrogen economy”. One of the most important conclusions of the paper is that technology-related drivers are playing the leading role in stress scenario realisation, but it is usually a specific combination of other drivers (interlacing with technology-related factors) that could trigger the launch a particular scenario.

This study’s approach is based on the assumption that Russia’s dependence on hydrocarbons exports as one of the main structural characteristics of the Russian economy will remain intact. However, for the long-term perspective, this assumption might not hold true. So, new research will be needed to review the stress scenarios within the context of radical diversification of the Russian economy.

This paper suggests a number of practical steps aimed at introducing stress analysis as one of the key functions within the energy-related sectoral components of the Russian national systems of technology forecasting and strategic planning.

The novelty of this paper is determined both by the subject of the analysis and approach taken to reveal it. In contrast to most of research in this area, the main focus has been moved from the opportunities and potential benefits of contemporary technology-related global energy shifts to their possible negative impact on the national economy. Another important original feature of the approach is that existing global energy forecasts are used only as a background for core analysis centred around the cases when conventional energy trends are broken.

Stresses the importance of forecasting in essential supply industries such as the gas industry with regard to storing the product. Examines some of the problems encountered in this area and how they are dealt with.

The chapter discusses global trends in the world oil and gas sector and their impact on the Russian hydrocarbon market. The key short-term risks for the Russian Federation are the following: the high dependence of the industry on the equipment of foreign suppliers and oilfield service companies. Possible threats associated with these factors may materialise against the backdrop of the geopolitical crisis of early 2022. Long-term trends include a global green transition with a peak in hydrocarbon consumption in 2030–2040 and a phase-out of oil and gas as a primary energy source. Simultaneously, the given industry is going to face gradual metamorphosis in terms of the types of wells being developed, which might require more science-intensive and high-tech approaches.

There is evidence in the literature suggesting the usage of performance measurement framework (PMF) has a positive impact on organisational performance. This is in line with resource based view (RBV) theory, which argues attaining competitive advantage through internal resources and capabilities. In this regard, PMF can be viewed as a “resource” that can be explored in enabling organisational performance. This paper is aimed at developing PMF for the oil and gas supply chain (SC) as a resource and strategic capability.

Drawing on RBV theory, a questionnaire survey was designed based on prior literature review and exploratory interview with five SC experts. Following this, the questionnaires were distributed to 550 companies in the UK and 120 companies in Malaysia, which resulted in 15% overall response rate.

This study presents the prevalence of performance measures (PM) for the oil and gas industry based on the level of importance. It also reveals the impact of the usage of PMF on overall organisational performance. In addition, it identifies the challenges in managing SC performance and factors to be considered in choosing PM.

This study identifies the challenges in managing SC performance and establishes distinctive factors to consider when choosing PM in the oil and gas SC.

The chapter considers the significance of the oil and gas industry for the Russian economy. The authors analyze the current state of the oil and gas industry, their specific weight in the structure of Russian GDP, and tax revenues from this industry to the Russian budget that was estimated. We give scenario analysis that considers the problems that the Russian economy may face because of the sanctions, the price fluctuations at the commodity market, and the crisis phenomena in the world economy. The chapter points out that localization of technology production and development of technologies for offshore oil and gas production in the Arctic zone may become an incentive to further ensure import substitution for Russia. At present, the experience of Arctic defense enterprises in the production of equipment for oil and gas production and processing is becoming increasingly popular. The chapter elaborates the most significant examples of the creation of new industries in the Arctic zone, the prospects of seismic exploration on the Arctic shelf, and that localization of production capacities and service bases will allow obtaining a multiplicative incentive for a qualitatively new industrial and infrastructure development of the northern territories. Also, we provide an assessment of the development of liquefied natural gas (LNG) industry, which makes economically attractive use of natural gas on a regional level as LNG opens the way to fuel high-power needs and to long-distance transport.

The purpose of this paper is to examine the impact of oil price shocks on capital spending in relation to the following firm characteristics: firm size, debt ratio, growth prospects, earnings and key sectors of the oil and gas industry.

To examine the impact of oil price changes on each of the sample firm’s capital spending, the authors utilize a vector autoregressive (VAR) framework which requires that the oil price and the firm’s capital spending series are stationary. The authors employ the Augmented Dickey–Fuller (ADF) procedure to test if these series are stationary in levels or in their first difference. Since the results show that the ADF values for adjusted oil price and for all but one capital spending series are stationary, the authors perform VAR analysis using the level data.

The impulse response results show that there is a positive relationship between oil price shocks and capital spending by the oil and gas firms. In other words, the oil and gas firms reduce (increase) capital spending when oil prices fall (rise). The responses are highest around q3. Additionally, the responses are stronger for the exploration and production, drilling, and oil services firms, and weaker for the refining firms (oil majors). Also, the small, low-earnings and low p/e firms exhibit the highest responses to oil price shocks. The impulse response results for the debt quartiles are inconclusive.

The findings shed light into the impact of oil price shocks on capital spending in relation to firm characteristics. The impulse response results that capital spending of the E&P, drilling and oil services firms, and the small firms in general, have a higher positive impact of oil shocks lend support to the argument that these firms more likely reduce capital spending because of financial constraints in the capital markets. A higher positive response by the low return on assets firms indicates that firms with low earnings and cash flow problems are more likely to reduce their capital spending when oil price drops. With regard to growth prospects, it appears that shocks in oil price dampen the outlook for the low p/e firms, which leads to a cut in their capital spending. On the other hand, the high p/e firms seem to rely more on their growth prospects and downplay the adverse impact of oil price shocks.

Unlike previous studies in this area, the study focuses on firm-level data in detail, uses quarterly data and uses firm-specific variables that explain impact of oil price shocks on capital spending in oil and gas industry.

The purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market.

Using principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices.

Natural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model.

Significant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil.

As per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

Iran as an energy‐rich country faces many challenges in the optimal utilization of its vast resources. High rates of population and economic growth, a generous subsidies program, and poor resource management have contributed to rapidly growing energy consumption and high energy intensity over the past decades. The continuing trend of rising energy consumption will bring about new challenges as it will shrink oil export revenues, restraining economic activities. This calls for a study to explore alternative scenarios for the utilization of energy resources in Iran. The purpose of this paper is to model demand for energy in Iran and develop two business‐as‐usual and efficiency scenarios for the period 2005‐2030.

The authors use a techno‐economic or end‐use approach to model energy demand in Iran for different types of energy uses and energy carriers in all sectors of the economy and forecast it under two scenarios: business as usual (BAU) and efficiency.

Iran has a huge potential for energy savings. Specifically, under the efficiency scenario, Iran will be able to reduce its energy consumption 40 percent by 2030.The energy intensity can also be reduced by about 60 percent to a level lower than the world average today.

The paper presents a comprehensive study that models the Iranian energy demand in different sectors of the economy, using data at different aggregation levels and a techno‐economic end‐use approach to illuminate the future of energy demand under alternative scenarios.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.