Benchmarking energy use of iron and steel industry: a data envelopment analysis

Limited Demand or Unreliable Supply? A Bibliometric Review and Computational Text Analysis of Research on Energy Policy in India

Although India has made significant progress towards the sustainable development goal on energy (SDG 7), further policy innovations are essential for closing the gap, addressing geographic disparities, and harnessing energy for transformative change. Research can support this process by creating policy-relevant knowledge regarding the energy transition, but there is no systematic account of the literature pertaining to energy policy in India to map the research area and suggest key avenues for future research. In this study, I conduct a bibliometric review and computational text analysis of over 2700 publications to identify the key themes, geographies, and public policy concepts (not) examined in the research on energy policy in India. I find that: (i) the literature is dominated by topics in energy supply and less attention is paid to demand-side management, energy efficiency, and electricity distribution; (ii) existing studies have hardly examined subnational policy (-making), especially in the case of eastern and north-eastern India; and (iii) research on both analysis for policy and analysis of policy is limited. I conclude that the current foci lack the breadth and depth necessary for supporting the Indian energy transition and urge scholars to diversify the thematic, geographic, and conceptual engagement in future research.

Energy Intensity of Steel Manufactured Utilising EAF Technology as a Function of Investments Made: The Case of the Steel Industry in Poland

The production of steel in the world is dominated by two types of technologies: BF + BOF (the blast furnace and basic oxygen furnace, also known as integrated steel plants) and EAF (the electric arc furnace). The BF + BOF process uses a lot of natural resources (iron ore is a feedstock for steel production) and fossil fuels. As a result, these steel mills have a significantly negative impact on the environment. In turn, EAF technology is characterised by very low direct emissions and very high indirect emissions. The raw material for steel production is steel scrap, the processing of which is highly energy-consuming. This paper analyses the energy intensity of steel production in Poland as a function of investments made in the steel industry in the years 2000–2019. Statistical data on steel production in the EAF process in Poland (which represents an approximately 50% share of the steel produced, as the rest is produced utilising the BF + BOF process) was used. Slight fluctuations are caused by the periodic switching of technology for economic or technical reasons. The hypothesis stating that there is a relationship between the volume of steel production utilising the EAF process and the energy consumption of the process, which is influenced by investments, was formulated. Econometric modelling was used as the research method and three models were constructed: (1) a two-factor power model; (2) a linear two-factor model; and (3) a linear one-factor model. Our findings show that the correlation is negative, that is, along with the increase in technological investments in electric steel plants in Poland, a decrease in the energy consumption of steel produced in electric furnaces was noted during the analysed period.

The dynamics of Indian energy mix: a two-phase analysis

Purpose

The Indian power sector is dominated by coal. Environmental awareness and advances in techno-economic front have led to a slow but steady shift towards greener alternatives. The distributions of both fossil fuel resources and renewable energy potential are not uniform across the states. Paper attempts to answer how the states are performing in the sector and how the renewable energy and conventional resources are affecting the dynamics.

Design/methodology/approach

The authors employ a two-stage data envelopment analysis (DEA) to rank the performance of Indian states in the power sector. Multi-stage analysis opens up the DEA black-box through disaggregating power sector in two logical sub-sectors. The performance is evaluated from the point-of-view of policy formulating and implementing agencies. Further, an econometric analysis using seemingly unrelated regression equations (SURE) is conducted to estimate the determinants of total and industrial per-capita electricity consumption.

Findings

Efficiency scores obtained from the first phase of analysis happens to be a significant explanatory variable for power consumption. The growth in electricity consumption, which is necessary for economic wellbeing, is positively affected by both renewable and non-renewable sources; but conventional sources have a larger impact on per-capita consumption. Yet, the share of renewables in the energy mix has positive elasticity. Hence, the findings are encouraging, because development in storage technologies, falling costs and policy interventions are poised to give further impetus to renewable sources.

Originality/value

The study is one of the very few where entire spectrum of the Indian power sector is evaluated from efficiency perspective. Further, the second phase analysis gives additional relevant insights on the sector.

Determinants of material footprint in BRICS countries: an empirical analysis

This paper explores the relationship between renewable energy consumption, urbanization, human capital, trade, natural resources, and material footprint for BRICS countries from 1990 to 2016. We apply the cross-sectional dependency test to check the correlation among the cross-section. Then, we use the second-generation panel test like CADF and CIPS to check the stationary in the series. After that, we go for the panel cointegration test, i.e., Pedroni and Westerlund panel cointegration, to know the long-run relationship of the variables. The test results reject the null hypothesis of no cointegration among the variables and accept cointegration. The long-run results indicate that economic growth, natural resources, renewable energy, and urbanization have reduced the environmental quality for BRICS countries in case of material footprint employed to measure environmental degradation. However, foreign trade and human capital improve environmental quality. Based on the empirical results, the study recommended some important policy suggestions to achieve sustainable development in BRICS countries.

Benchmarking the practices of flexibility with maturity models and frameworks of organizational capabilities

Purpose

Organizational capabilities are crucial to achieve the objectives. A plethora of maturity models is available to guide organizational capabilities that create a perplexing situation about what stuff to improve and what to leave. Therefore, a unified maturity model addressing a wide range of capabilities is a necessity. This paper establishes that a flexibility maturity model is an unified model containing the operational, strategic and human capabilities.

Design/methodology/approach

This paper does a comparative analysis/benchmarking studies of different maturity models/frameworks widely used in the information technology (IT) sector with respect to the flexibility maturity model to establish its comprehensiveness and application in the organization to handle multiple goals.

Findings

This study confirms that the flexibility maturity model has the crucial elements of all the maturity models. If the organizations use the flexibility maturity model, they can avoid the burden of complying with multiple ones and become objective-driven rather than compliance-driven.

Research limitations/implications

The maturity models used in information technology sectors are used. This work will inspire other maturity models to adopt flexibility phenomena.

Practical implications

The comparative analysis will give confidence in application of flexibility framework. The business environment and strategic options across organizations are inherently different that the flexibility maturity model well handles.

Social implications

A choice is put to an organization to see the comparison tables produced in this paper and choose the right framework according to the prevailing business situation.

Originality/value

This is the first study that makes a conclusion based on comparative benchmarking of existing maturity models.

Analyzing the Lean Six Sigma enabled organizational performance to enhance operational efficiency

Purpose

The aim of this analysis is to review the Indian manufacturing organizations practicing Lean Six Sigma (LSS) tools/techniques with an objective of monitoring the performance of an organization and to develop recommendation for strategies to benchmark organizational operational efficiency.

Design/methodology/approach

This study offers insights of the LSS performance measurement aspects of the Indian manufacturing organizations based on Data envelopment analysis (DEA) approach. The five inputs and two outputs are considered on the basis of literature review and discussed with the practitioners.

Findings

In this analysis, the relative efficiency score of 18 Indian manufacturing organizations has been determined in order to assist evaluation of the impact of monetary investment on the outputs. The present analysis not only investigates the optimum level of input variables but also lays down a significant observation that an organization having higher profit and inventory turnover ratio is not necessarily an efficient organization.

Practical implications

The results assist to determine the best practice units, potential source of inefficiency and deliver beneficial data for the consistent enhancement of the operational efficiency. The DEA results assist managers and decision makers to derive appropriate strategies to enhance their performance with reference to the efficient organization and to regard it as their role model.

Originality/value

This analysis renders a DEA based framework of LSS practicing Indian manufacturing organizations. The framework is unique in terms of its input-outputs variable selection and measurement procedure.

Direct and indirect impacts of high-tech industry development on CO2 emissions: empirical evidence from China

Vigorously developing high-tech industry has been considered to be an effective way to coordinate economic growth with excessive carbon dioxide (CO₂) emissions. However, previous studies have not explored the heterogeneous impacts of high-tech industry on CO₂ emissions in regions with different levels of high-tech industry development, and not distinguished the direct and indirect impacts. Based on STIRPAT model, this study investigates the impacts of high-tech industry development on CO₂ emissions in China between 2005 and 2016. Adopting the K-medians cluster method, effects in regions with high, middle, and low levels of high-tech industry development are considered. Indirect effects of high-tech industry development on CO₂ emissions by affecting industry structure upgrades and economic growth are explored. Empirical results illustrate a positive U-shaped nonlinear link between the level of high-tech industry development and CO₂ emissions at the national level and regional (high, middle, and low) level. In terms of indirect impacts, high-tech industry development attenuates the reduction of CO₂ emissions due to industry structure upgrades, and promotes economic growth to increase CO₂ emissions slightly. The indirect impact intensity gradually decreases as the level of high-tech industry development decreases across three regions. Reasonable implications of our findings are proposed.

Measuring performance of government-supported drug warehouses using DEA to improve quality of drug distribution

Purpose

Drug warehouses (DWs) play a crucial role in drug distribution of government-supported healthcare supply chain as it controls both the cost and responsiveness of the logistics activities. The current study proposes a methodology using data envelopment analysis (DEA) to estimate the performance along different dimensions and was applied to 30 government-supported DWs.

Design/methodology/approach

This study employs DEA to evaluate the performance and relative technical efficiency of DWs. In this research, four inputs and six outputs are identified based on intensive literature review and discussion with all stakeholders of DWs. The inputs are warehouse storage capacity, temperature-controlled storage capacity, number of skilled employees and operational cost, while the outputs are fill rate, number of generic drugs, volume of drugs, consumption points, inventory turns ratio and time efficiency.

Findings

Results show that 30% DWs operate at the most productive scale size with 100% efficiency level while 47% DWs have a significant possibility for further enhancement in productive efficiency and 23% DWs should diminish their operational size to increase their productivity level. It was also found that achieving 100% operational productivity along warehouse space capacity needs significant effort, whereas other three inputs, namely temperature-controlled capacity, number of skilled employees and operational cost, require comparatively less effort. Similarly, it was observed that the performance along the fill rate and time efficiency is satisfactory, whereas the performance along other fours output variables (i.e. number of generic drugs, volume of drugs, consumption points and inventory turns ratio) needs to be improved.

Practical implications

The findings offer insights on the inputs and outputs that significantly contribute to efficiencies so that inefficient DWs can focus on these factors.

Originality/value

Although many issues related to DEA have been widely researched and reported, but no literature has been found for analysis of DWs in general and government-supported DWs specifically to find out efficiencies for supply chain performance improvement.