Setting up Energy Efficiency Management in Companies: Preliminary Lessons Learned from the Petroleum Industry

Abstract

In the era of expensive energy carriers and care for the climate, companies are keen to take action towards bolstering energy efficiency. Businesses often lack data on actual energy consumption to date, are rarely equipped with adequate analytical tools, and do not have the know-how regarding the transition itself. Developing energy efficiency management (EEM) for a given enterprise requires many steps, which ultimately unleash analytical potential and seamlessly integrate the EEM framework with the business model of a given company. This study scrutinizes and formalizes a reference process of pilot EEM implementation that involves external business partners in a multi-facility organization. The process is tailored to the specificity of the company’s operations as well as its technical and management capabilities regarding energy efficiency. The proposed approach, phased in time and involving multiple stakeholders, should be especially useful for practitioners running EEM-related projects characterized by uncertain and changing requirements.

The role of LightGBM model in management efficiency enhancement of listed agricultural companies

“…The literature [8] suggested that enterprise management efficiency enhancement can effectively drive labor productivity growth by promoting the upgrading of enterprise product quality. The literature [9] argues that management is also an important resource allocation tool for firms, and firms with high managerial efficiency prefer to hire higher-skilled employees, introduce more advanced technology and production equipment, and invest more in technological innovation, which has an important contribution to the enhancement of firm performance. The literature [10] argues that differences in management efficiency, represented by management culture, management team, and management model, are likely to be important causes of heterogeneity among firms in terms of corporate performance enhancement.…”

Lessons Learned from Developing an Industry 4.0 Mobile Process Management System Supported by Artificial Intelligence

“…Research and Development (R&D) projects are characterised by their complexity and interdependence (Gawin and Marcinkowski, 2020;Liu, Luo, Geng, and Yao, 2021). These projects are the response to the highly competitive market and the demand for innovative products and services (Awan, Muneer, and Abbas, 2013;Falkowski-Gilski and Uhl, 2020).…”