Investigaciones financiadas por la Unión Europea (OpenAire) - Europar Batasunak finantzatutako ikerketak (OpenAire)

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Open Access
Consumers' willingness to pay for health claims during the COVID-19 pandemic: a moderated mediation analysis
(Elsevier, 2023) Bou Fakhreddine, Lara; García Martínez, Marian; Sánchez García, Mercedes; Schnettler, Berta; Gestión de Empresas; Enpresen Kudeaketa
The COVID-19 pandemic has posed a substantial threat to people's lives and raised health concerns. This research explores the mediating role of consumers' attitudes towards health claims in the relationship between consumers' interest in health claims and their willingness to pay (WTP) for health claims in extra virgin olive oil (EVOO). Additionally, we examine the moderation effect of COVID-19 risk perception in the relationship between consumers' interest in and attitudes towards health claims. Data were collected through an online survey in three countries: Spain, the UK and Chile. Findings confirm the mediating role of consumers' attitudes towards health claims. Furthermore, the relationship between consumers' interest and their attitudes towards health claims was stronger when COVID-19 risk perception was higher.
Open Access
Energy-socio-economic-environmental modelling for the EU energy and post-COVID-19 transitions
(Elsevier, 2022) Cazcarro, Ignacio; García-Gusano, Diego; Iribarren, Diego; Linares, Pedro; Romero, José Carlos; Arocena Garro, Pablo; Arto, Iñaki; Banacloche, Santacruz; Lechón, Yolanda; Miguel, Luis Javier; Zafrilla, Jorge; López, Luis Antonio; Langarita, Raquel; Cadarso, María Angeles; Enpresen Kudeaketa; Institute for Advanced Research in Business and Economics - INARBE; Gestión de Empresas
Relevant energy questions have arisen because of the COVID-19 pandemic. The pandemic shock leads to emissions' reductions consistent with the rates of decrease required to achieve the Paris Agreement goals. Those unforeseen drastic reductions in emissions are temporary as long as they do not involve structural changes. However, the COVID-19 consequences and the subsequent policy response will affect the economy for decades. Focusing on the EU, this discussion article argues how recovery plans are an opportunity to deepen the way towards a low-carbon economy, improving at the same time employment, health, and equity and the role of modelling tools. Long-term alignment with the low-carbon path and the development of a resilient transition towards renewable sources should guide instruments and policies, conditioning aid to energy-intensive sectors such as transport, tourism, and the automotive industry. However, the potential dangers of short-termism and carbon leakage persist. The current energy-socio-economic-environmental modelling tools are precious to widen the scope and deal with these complex problems. The scientific community has to assess disparate, non-equilibrium, and non-ordinary scenarios, such as sectors and countries lockdowns, drastic changes in con sumption patterns, significant investments in renewable energies, and disruptive technologies and incorporate uncertainty analysis. All these instruments will evaluate the cost-effectiveness of decarbonization options and potential consequences on employment, income distribution, and vulnerability.
Open Access
The interplay between health claims and sensory attributes in determining consumers’ purchase intentions for extra virgin olive oil
(Elsevier, 2023) Bou Fakhreddine, Lara; Sánchez García, Mercedes; Gestión de Empresas; Enpresen Kudeaketa; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
A large body of literature has supported the idea that both food-intrinsic sensory attributes (e.g., taste, aroma, etc.) and food-extrinsic attributes (e.g., origin, health claims etc.) play a crucial role in consumers’ purchase intentions. However, it is still uncertain how the presence of health claims in the era of high prevalence of diseases and viruses (e.g., the COVID-19 pandemic) might impact sensory attributes, and therefore shape consumers’ purchase intentions. Thus, the aim of the study is to (i) investigate the impact of health claims presented to the consumers along with the sensory attributes on their purchasing intentions, and (ii) examine to what extent sensory attributes mediate the relationship between the presence of health claims and consumers’ purchasing intentions. For that purpose, sensory analysis of a healthy food product (extra virgin olive oil (EVOO)) was conducted to examine consumers’ interest in health claims in two scenarios: an informed scenario without health claims (n = 102) and an informed scenario with health claims (n = 105). The findings from a Structural Equation Model using STATA software suggest that the presence of health claims positively affects purchase intentions for EVOO. The sensory attributes taste and aftertaste partially mediate the relationship between the presence of health claims and consumers’ purchasing intentions. Furthermore, consumers rated the sensory attributes higher in the presence of health claims. Therefore, the food industry should focus on ways to improve consumers’ sensory and health perspectives by producing not only healthier food products with health claims but also tastier products than the ones available in the market. Moreover, food companies and marketers can make health claims more effective by targeting consumers’ preferences and developing marketing campaigns using claims that are essential for promoting extra-virgin olive oil.
Open Access
On the use of biased-randomized algorithms for solving non-smooth optimization problems
(MDPI, 2020) Juan Pérez, Ángel Alejandro; Corlu, Canan Gunes; Tordecilla, Rafael D.; Torre Martínez, Rocío de la; Ferrer, Albert; Enpresen Kudeaketa; Institute for Advanced Research in Business and Economics - INARBE; Gestión de Empresas
Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory management, it is possible to consider stock-outs generated by unexpected demands; and in manufacturing processes and project management, it is frequent that some deadlines cannot be met due to delays in critical steps of the supply chain. However, capacity-, size-, and time-related limitations are included in many optimization problems as hard constraints, while it would be usually more realistic to consider them as soft ones, i.e., they can be violated to some extent by incurring a penalty cost. Most of the times, this penalty cost will be nonlinear and even noncontinuous, which might transform the objective function into a non-smooth one. Despite its many practical applications, non-smooth optimization problems are quite challenging, especially when the underlying optimization problem is NP-hard in nature. In this paper, we propose the use of biased-randomized algorithms as an effective methodology to cope with NP-hard and non-smooth optimization problems in many practical applications. Biased-randomized algorithms extend constructive heuristics by introducing a nonuniform randomization pattern into them. Hence, they can be used to explore promising areas of the solution space without the limitations of gradient-based approaches, which assume the existence of smooth objective functions. Moreover, biased-randomized algorithms can be easily parallelized, thus employing short computing times while exploring a large number of promising regions. This paper discusses these concepts in detail, reviews existing work in different application areas, and highlights current trends and open research lines.

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