Keywords Environmental management; Environmental management systems; Financial performance; Organizational performance; ISO 9001

Increased industrial energy efficiency (EE) has become one of the main environmental actions to mitigate carbon dioxide (CO₂) emissions, contributing also to industrial competitiveness, with several implications on the production system and cost management. Unfortunately, literature is currently lacking empirical evidence on the impact of energy efficiency solutions on production. Thus, this work primarily aims at investigating the economic and production-related influence on the reduction in industrial energy consumption, considering the cross-cutting technologies HVAC, motors, lighting systems and air compressor systems. The analysis is performed using data from previous studies that characterized the main EE measures for the cross-cutting technologies. Four logistic models were built to understand how costs and production influence energy efficiency across such cross-cutting technologies. In this way, motivating industries to implement measures to reduce electrical consumption, offering an economic cost–benefit analysis and optimizing industry processes so that the reduction in electricity consumption adds to industrial energy efficiency were the aims of this study. The results of this work show through the adjusted indicators that senior management is mainly responsible for energy savings. The operational measures of each piece of equipment can be oriented in the industry towards a specific maintenance process for each technology, becoming an active procedure in industrial productions to obtain EE. Additionally, maintenance planning and control is essential to the reliability of the reduced energy consumption of cross-cutting technologies. This article concludes with managerial implications and suggestions for future research in this field.

The main objective of this paper is to verify which economic and cultural-industrial factors influence the diffusion of ISO/TS 16949 certificates in the world. The use of multiple regression models for certification data is not new, the characterisation and quantification of the factors influencing the diffusion of ISO/TS16949 have not yet been addressed in other studies. In addition, the use of social and governmental factors makes this work more applicable to managers and decision makers. Data were collected from the ISO Survey, World Bank and Global Competitiveness Index. Twenty countries were assessed. China, Republic of Korea, India, USA and Germany were the ones with the highest number of ISO/TS 16949 certifications. The factor that most influenced the diffusion of ISO/TS 16949 was the Global Competitiveness Index. The influence was observed in the models for thirteen countries, followed by IDH. Other factors that showed influence in the of ISO/TS 16949 were: GDP_pc, Total Reserve, Foreign Direct Investment, Corruption Perceptions Index, Combating Corruption, ISO9001 (n–1) and ISO9001. Briefly, this study has several implications for the academy and industry, with the proposal of new concepts, guidelines and implementation on the factors that assist in ISO/TS 16949 certification in the world.

The industrial energetic efficiency (EE) is recognized as one of the main factors for the reduction of gas emissions that cause the greenhouse effect and for the improvement of the industrial competiveness. Within this context, many papers of the international literature have proposed different indicators of industrial, economic and environmental behavior, so as to promote the EE inside the industries. However, such proposals do not generally check the result of the joint work for more than one indicator in the organizations, making more global analysis more difficult related to EE. This paper aims to check which environmental, economic and industrial practices indicators influence the EE of the industries. The data have been collected from the framework developed by Trianni et al. (2014), that analysed the main energetic efficiency measures for the technologies: motors, lighting, compressed air and HVAC systems (heating, ventilation and air conditioning). A logistic regression model has been adjusted for understand the relationship the economic, environmental and productive practices behavior on the energetic efficiency. Results suggest that a healthy workplace enables investments in equipment and machinery, allowing the EE inside the industries.