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In a panel of European countries, we analyse paper products, sawnwood and wood panels consumption data. With this object, we use a classical demand model where national consumption depends on real GDP and real prices. In contrast to previous panel estimations in the literature, we highlight non-stationarity time series which can lead to spurious regressions. We explicitly take into account the issue by using recent panel cointegration techniques. Cointegration is present for printing paper and fibreboard, though less clear cut for other products. Then we estimate demand elasticities and find that GDP elasticities are significantly lower than estimates from the literature. Finally, we simulate the implications of modified demand elasticities by using a partial equilibrium model of the forest sector. For most products, changes in elasticities would lead to lower projected demand and lower prices over a 20-year time horizon. Lower demand for solid wood and wood fibre would lead to less tensions with fuel wood- and wood-based chemical markets. In a context of rising interest for renewable bio-based products, updated long-term demand models contribute to the analysis of the forest sector’s sustainability. [ABSTRACT FROM AUTHOR]

The paper aimed to analyze the main trends in tourism demand in the top European countries in terms of tourist arrivals, overnight stays, tourism intensity, receipts, receipts/arrival, receipts/inhabitant. The correlation coefficient and regression function were used to analyze the relationship between tourist arrivals and tourism receipts. The top visited countries in Europe registered 377.8 million international tourist arrivals in 2015, by 17.07 % more than 322.7 million in the year 2007. Their market share in the EU international tourist arrivals was 78.8 % and at the world level 31.55 %. The decreasing order of these countries based on their market share in the EU tourist arrivals is: France, Spain, Italy, Germany, United Kingdom, Austria, Greece, Poland, Netherlands, Croatia and Portugal. These countries contributed by USD 302.2 Billion to the EU receipts coming from tourism, representing 80.2 % of the EU receipts. In 2015, all these 11 countries registered 2,035 million overnight stays, representing 86.5 % of the total overnight stays in the EU. Based on this indicator, the decreasing order of these countries is: Spain, France, Italy, Germany, United Kingdom, Austria, Netherlands, Greece, Croatia, Poland and Portugal. The number of overnight stays/inhabitant, reflecting tourism intensity, varied between 16.9 in Croatia and 1.9 in Poland. While the receipts/tourist arrival varied between USD 1,323 in United Kingdom, and USD 532 in France, the receipts per overnight stay varied between Euro 88 in Germany and Euro 194 in Portugal, and the receipts/inhabitant varied between Euro 248 in Poland and Euro 1,909 in Austria. The correlation coefficient, the coefficient of determination and the regression equations attested that between the number of international tourist arrivals and tourism receipts is a positive strong correlation in case of United Kingdom and Croatia. In case of Greece and Germany it was found a moderate positive correlation, while in case of Austria, France, Italy, Netherlands, Poland, Portugal and Spain it was noticed a weak correlation. Therefore, the number of tourist arrivals reflects an increased tourism demand, but it can't entirely explain the growth of tourism receipts, which are determined by many other factors. [ABSTRACT FROM AUTHOR]

This article analyzes the effect of exporting activity on the innovative performances of firms in France, Germany, Italy, Spain, and UK. It argues that the positive effect of exporting on innovation usually found in the literature varies according to the specific destinations of exports, and it identifies two dimensions along which export destinations might differ: the level of foreign technological spillovers available to exporting firms (the technological learning effect) and the type of foreign demand that exporting firms are able to access (the foreign demand effect). The empirical analysis, which takes advantage of firm-level information about the export destinations of exporters, shows that while the technological learning effect increases mainly the incentives to introduce brand new product innovations, the foreign demand effect fosters the adoption of process innovations. [ABSTRACT FROM AUTHOR]

Purpose-This study aims to examine the management of food supply chains in complex and volatile business environments, where the sustainability requirements of customers and legislation are increasing. This challenging situation gives rise to the question as to how a logistics company can achieve and sustain competitive advantage through environmentally-oriented sustainability. Design/methodology/approach-This empirical study gathers insights on emerging practices in European food service supply chains from two parallel Delphi surveys conducted with 145 industry experts from 27 countries. The long-term industry expectations of a leading provider in food service logistics are compared with an industry-wide external panel. The questions were designed to understand how managers perceive the emerging domain of sustainability in supply chains. Findings-Environmentally oriented sustainability will remain a key driver of success in the field. However, after applying the dominant logic concept for analyzing results, it becomes apparent that managers have to continuously challenge internal existing expectations to translate an emerging domain into strategy. We show how the senior management team under investigation was challenged in its dominant logic and how it tried to overcome this situation during strategy development. Originality/value-The study shows how managers perceive and cope with the emerging domain of environmentally oriented sustainability, how they translate it into strategy, and utilize resources for creating customer value. The research supports managers in adapting to new competitive environments. Furthermore, the study contributes by visualizing the dominant logic of a firm and the approach of top management for adjustment. [ABSTRACT FROM AUTHOR]

The building sector accounts for one third of the global energy consumption and it is expected to grow in the next decades. This evidence leads researchers, engineers and architects to develop innovative technologies based on renewable energies and to enhance the thermal performance of building envelopes. In this context, the potential applicability and further energy performance analysis of these technologies when implemented into different building typologies and climate conditions are not easily comparable. Although massive information is available in data sources, the lack of standardized methods for data gathering and the non-public availability makes the comparative analyses more difficult. These facts limit the benchmarking of different building energy demand parameters such as space heating, cooling, air conditioning, domestic hot water, lighting and electric appliances. Therefore, the first objective of this study consists in providing a review about the common typologies of residential buildings in Europe from the main data sources. This study contains specific details on their architecture, building envelope, floor space and insulation properties. The second objective consists in performing a cross-country comparison in terms of energy demand for the applications with higher energy requirements in the residential building sector (heating and domestic hot water), as well as their related CO2 emissions. The approach of this comparative analysis is based on the residential building typology developed in TABULA/EPISCOPE projects. This comparative study provides a reference scenario in terms of energy demand and CO2 emissions for residential buildings and allows to evaluate the potential implementation of new supply energy technologies in hot, temperate and cold climate regions. From this study it was also concluded that there is a necessity of a free access database which could gather and classify reliable energy data in buildings. [ABSTRACT FROM AUTHOR]