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The purpose of this paper is to identify the most appropriate multidisciplinary data sources related with energy optimization decision support as well as the related methodologies, tools and techniques for data capturing and processing for each of them.

A review is conducted on the state-of-play of decision support systems for energy optimization, focussing on the municipal sector, followed by an identification of the most appropriate multidisciplinary data sources related with energy optimization decision support. An innovative methodology is outlined to integrate semantically modeled data from multiple sources, to assist city authorities in energy management.

City authorities need to lead relevant actions toward energy-efficient neighborhoods. Although there are more and more energy and other related data available at the city level, there are no established methods and tools integrating and analyzing them in a smart way, with the purpose to support the decision-making process on energy use optimization.

A novel multidimensional approach is proposed, using semantic technologies to integrate data from multiple sources, to assist city authorities to produce short-term energy plans in an integrated, transparent and comprehensive way.

The purpose of this paper is to investigate the efforts undertaken by the Gulf Cooperation Council (GCC) countries in deploying renewable energy (RE), in terms of capacity assessments, research and development activities, and current and planned projects. The paper also aims to investigate the drivers and barriers for the diffusion of RE technologies in the GCC.

The paper provides a literature‐based study on the status of the RE sector in the GCC, including capacities, projects, policies and frameworks in the GCC, in addition to an analysis of the main drivers and barriers to RE deployment arising from the literature.

The results of this paper illustrate growing interest in renewable energy in the GCC countries at the R&D and project implementation level.

The paper contributes by the provision of the latest knowledge on the status of the RE sector in the GCC and by highlighting the most significant drivers fuelling RE deployment, as well as the barriers currently hindering the greater diffusion of RE technologies in the region.

The purpose of this paper is to explore the associations between food literacy, consumer profiling and purchasing behaviour in a sample of Italian consumers.

Participants (N = 194) completed an online survey including personal data, two questionnaires on purchase behaviour and food consumption, the General Trust Scale (GTS), a questionnaire assessing individual chronotype and two scales about food literacy: one investigating nutritional knowledge (short food literacy questionnaire, SFLQ) and the other focussing on procedural skills (self-perceived food literacy scale, SPFL). Associations between food literacy, consumer profiling and purchase behaviour were analysed with linear regression models.

Participants with specific education in nutrition reported higher scores in food literacy. The final score of food literacy was predicted by a greater attention to nutritional content and nutritional properties of products. Women paid more attention to nutritional properties than men, and they obtained higher scores in SFLQ. Evening types obtained lower scores in SFPL compared to intermediate and morning chronotypes. Body mass index (BMI) was negatively correlated to SPFL score, while it was associated with the easy availability of a product, so that obese (BMI ≥ 30) subjects considered the easy availability of a product more important compared to non-obese ones (BMI < 30).

This study investigates the influence of personal and psychometric variables of consumer profiling on food literacy and consequently on purchase behaviour, paving the way for implementing healthier food consumption policies. These findings reinforce the primacy of specific education in building healthy eating habits.