In this paper, the relationship between operations strategy and performance through flexibility as a moderating variable is analysed within the service setting of engineering consulting firms in Spain. A framework for service strategy dimensions is suggested while manufacturing flexibility dimensions are applied to service operations considering necessary adaptations. A path analysis model is applied in order to enhance the understanding of interactions. This research proves that service operations strategy has a significant positive and direct effect on service delivery performance. The fact that is especially relevant is that flexibility plays a more intense moderating role for efficiency performance measures than for customer satisfaction performance measures.

In this paper, a model for determining innovation degree in service industries is presented. Such a model is developed under the knowledge‐based theory lens. So, knowledge flows and knowledge integration capabilities of the organisation’s members are considered as crucial for the innovation processes to be successfully implemented. The model is tested in a sample of engineering consulting firms of Spain. Main results point out the strong explanatory power of innovation intensity with knowledge theory‐based models. Final conclusions consider knowledge management policies as the main impellers of service innovation.

Understanding the relationships among CO₂ emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relationships amongst the three aforementioned indicators in G20 countries using an adaptive neuro-fuzzy inference system (ANFIS) model in the period from 1962 to 2016. In this regard, the ANFIS model has been used with prediction models using real data to predict CO₂ emissions based on two important input indicators, energy consumption and economic growth. This study made use of the fuzzy rules through ANFIS to generalize the relationships of the input and output indicators in order to make a prediction of CO₂ emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO₂ emissions based on energy consumption and economic growth. The direction of the interrelationship is highly important from the economic and energy policy-making perspectives for this international forum, as G20 countries are primarily focused on the governance of the global economy.