Changes in Energy Sector Strategies: A Literature Review
Bibliographic record
Abstract
Sustainable development (SD) can indicate the direction of the development of modern organizations’ transition and transformation strategies in the energy sector. Currently, in most countries, the main challenge for the energy sector’s strategies is to deal with energy security. The implementation of SD induces changes both in strategy and technology. The strategies are based on the technological transition toward renewable energy sources (RES). The aim of this paper is to explore business management literature dedicated to the transformation and transition strategies in the energy sector. The adopted methods are a systematic literature review (SLR) accompanied by a classical literature review (CLR) in Scopus database exploration. A literature review is developed in VOSviewer software and keyword co-occurrences analysis allowed to identify the main changes of direction in energy sector transformation strategies. The literature was explored by the 26 queries which resulted with 11 bibliometric maps. The analysis of the bibliometric maps was a challenge due to the cross-disciplinary strategic directions of development presented in indexed publications in the Scopus database. The identification of the changes in energy sector strategies is important because of its reliance on depleting resources and natural environment degradation. As a result of this paper, there is a visible shift of the trend in explored scientific publication from not only technological-based solutions but also towards managerial and organizational practices to achieve sustainability in the energy sector. This paper, besides the results, presents the theoretical contribution and managerial recommendations for business practices and addresses future research avenues. There are discussed implications of the presented analysis for further research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.021 | 0.029 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".