Although several research studies have adopted specific energy consumption (SEC) as an indicator of the progress of improved energy efficiency, publications are scarce on critical assessments when using SEC. Given the increasing importance of monitoring improved industrial energy efficiency and the rising popularity of SEC as an energy key performance indicator (e-KPI), an in-depth analysis and problematization on the pros and cons of using SEC would appear to be needed. The aim of this article is to analyse SEC critically in relation to industrial energy efficiency. By using SEC in the pulp and paper industry as an example, the results of this exploratory study show that although SEC is often used as an e-KPI in industry, the comparison is not always straightforward. Challenges emanate from a lack of information about how SEC is calculated. It is likely that SEC is an optimal e-KPI within the same study, when all deployed SECs are calculated in the same way, and with the same underlying assumptions. However, before comparing SEC with other studies, it is recommended that the assumptions on which calculations are based should be scrutinized in order to ensure the validity of the comparisons. The paper remains an important contribution in addition to the available handbooks.

The energy efficiency gap is known as the difference between optimal level of energy efficiency and the actual level of achieved energy efficiency. Energy management has proven to further close the energy efficiency gap. Energy management may differ depending on whether it concerns a large, energy-intensive company or small and medium-sized enterprises (SMEs). SMEs are of high interest since they form a large share of the economy today. For SMEs, a lighter form of energy management, in the form of energy efficiency network participation, has proven to deliver sound energy efficiency impact, while for larger, energy-intensive firms, a certified energy management system may be more suitable. However, various barriers inhibit adoption of energy efficiency measures. While there is an array of research on barriers to and driving forces for energy efficiency in general, research on barriers to, and driving forces for, energy management is rare, one exception being a study of energy-intensive pulp and paper mills. This holds even more so for industrial SMEs. This paper aims to identify the barriers to, and drivers for, energy management in manufacturing SMEs. Results of this explorative study show that the top four barriers to energy management are lack of time/other priorities, non-energy-related working tasks are prioritized higher, slim organization, and lack of internal expert competences, i.e., mainly organizational barriers. The top four drivers for energy management are to reduce production waste, participation in energy efficiency networks, cost reduction from lower energy use, and commitment from top management. Furthermore, results show that energy management among the studied SMEs seems to not be as mature, even though the companies participated in an energy management capacity building program in the form of energy efficiency networks, which, in turn, shows a still largely untapped potential in the societal aim to reduce the energy efficiency and management gaps. The main contribution of this paper is a first novel attempt to explore barriers to, and drivers for, energy management among SMEs.

Purpose: This study aims to develop a maturity model to assess manufacturing companies’ adoption of digital technologies for energy efficiency and to formulate strategies to facilitate progress toward higher maturity levels. To achieve this goal, the study will identify and analyze the challenges inherent in the adoption and implementation of digital technologies for energy efficiency. Design/methodology/approach: This study used a mixed methodology, combining analysis of the literature for building a maturity model and a questionnaire for validating the model and developing strategies for advancing maturity. The questionnaire was answered by 101 Swedish manufacturing companies. Findings: The findings reveal that the aluminum industries and iron and steel industries exhibit higher maturity levels in adopting digital technologies. Most companies are intermediate adopters utilizing core technologies such as the Internet of things, cloud and big data for energy use monitoring, analysis and reporting. A smaller subset of companies, identified as leading adopters, reached the highest maturity level, integrating artificial intelligence, predictive analytics and machine learning into their energy management systems to optimize both production and energy use. A key challenge identified is the “lack of knowledge” regarding the adoption and implementation of these technologies. Research limitations/implications: It is essential to emphasize that the developed maturity model does not prioritize the adoption of multiple types of digital technologies. From a maturity standpoint, what truly matters is how effectively the information obtained from digital technologies is utilized in energy efficiency and energy management work to create knowledge and, thus, add value to the organization. Practical implications: The maturity model and the strategies for advancing maturity related to the adoption of digital technology for energy efficiency are designed to be applicable to all types of manufacturing industries regardless of what sector or country the company is active in. The model can also be used by academia or other actors interested in evaluating the maturity level for the adoption of digital technologies for energy efficiency in companies in the manufacturing industry. The developed strategies offer guidance on determining which activities to undertake within the organization based on its current level of maturity. Originality/value: This study’s main contributions are: (1) the maturity model to assess digital technology adoption for energy efficiency, (2) a set of strategies to advance maturity in adoption and (3) empirical investigation of maturity levels in the adoption of digital technologies for energy efficiency in 101 Swedish manufacturing companies.

Energy efficiency is essential for climate change mitigation. Energy management, shaped by both technical artefacts and social constructions, can overcome barriers and achieve greater emission reductions than technology-focused approaches alone. Nine social constructions of energy management emphasize the need for a broader view that includes operations, processes, and knowledge creation and diffusion. By adopting these strategies, corporations and policymakers can substantially reduce industrial energy use and emissions. We estimate that effective energy management policies and voluntary initiatives could cut at least 5% of global industrial fossil CO₂ emissions.