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Dark tourism is one of the tourism types that have developed in line with the expectations of tourists in recent years. One of the special interest tourism types, dark tourism is based on fears such as pain, fear, and sadness. From this point of view, dark tourism destinations include battlefields, execution scenes, areas where death is experienced firsthand, centers with horror themes, and regions where natural and technological disasters occur. The centers where dark tourism takes place are quite different from the centers where other types of tourism take place. Thus, there is also diversity in the tourist type. Among the travel motivations of Dark tourists are reasons such as experiencing the moment of death, feeling fear, respecting the past, and obtaining information. With the advancement of technology, the reach of dark tourism to tourists has also accelerated. Today, dark tourism destinations reach large masses by using various marketing strategies. With this information, the aim of this study is to examine marketing strategies within the scope of dark tourism. Within the scope of this examination, social media will be emphasized. Social media accounts of destinations based on dark tourism will be examined and data will be analyzed through content analysis. Thus, it is aimed to have a rich section within the scope of dark tourism and social media.

The purpose of this paper is to explore the specific characteristics of consumers’ lived experience in a brand museum within a luxury context. While previous research has investigated this experience through the lens of brand heritage, the unique attributes and prestigiousness of the luxury field have not yet been examined. The authors argue that these distinctive features may alter the brand heritage experience in significant ways.

To understand the dimensions of a brand heritage experience in a luxury context, the authors applied a qualitative method using reflexive introspection. Specifically, the authors used 89 reflective introspections of 29 visitors of nine different luxury brand museums.

The findings indicate that a brand heritage experience in luxury is based on four dimensions: aesthetic, authentic, scientific and mythic. The data also reveal the heterogeneous aspect of the experience, which varies according to the level of consumers’ brand familiarity as well as whether the museum visit is led by a guide or not.

The authors contribute to the literature by emphasizing a new dimension of a brand heritage experience in luxury: a mythic dimension. This study also unveils the impact of contextual factors on the brand heritage experience.

The underdevelopment of the financial sector could be one of the barriers to the deployment of renewable energies in developing countries. The purpose of this paper is therefore to analyse the effect of financial development in the deployment of renewable energies in sub-Saharan African countries.

The empirical analysis is based on a production approach and a cross-sectionally augmented autoregressive distributive lag error correction model estimate for 25 sub-Saharan African countries over the period 1990–2018. The augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators were used for the robustness analysis.

Two results emerge: financial development contributes positively to renewable energy deployment in sub-Saharan African countries in the short and long run; and fossil fuel dependence impedes significantly renewable energy deployment in the short and long run. The robustness analyses using the AMG and CCEMG methods confirm these results.

These results suggest the need for policies to support and strengthen the development of the financial sector to improve its ability to effectively finance investments in renewable energy technologies.

The originality of this paper lies in the fact that the analysis is based on a renewable energy production approach. Indeed, the level of renewable energy deployment is measured by the production and not the consumption of renewable energy, unlike other previous work. In addition, this research uses recent econometric estimation techniques that overcome the problems of cross-sectional dependence and slope heterogeneity.