Statistical Anisotropies in Gravitational Waves in Solid Inflation

Solid inflation can support a long period of anisotropic inflation. We calculate the statistical anisotropies in the scalar and tensor power spectra and their cross-correlation in anisotropic solid inflation. The tensor-scalar cross-correlation can either be positive or negative, which impacts the statistical anisotropies of the TT and TB spectra in CMB map more significantly compared with the tensor self-correlation. The tensor power spectrum contains potentially comparable contributions from quadrupole and octopole angular patterns, which is different from the power spectra of scalar, the cross-correlation or the scalar bispectrum, where the quadrupole type statistical anisotropy dominates over octopole.Comment: 30 pages, 11 figure

Memorable tourism experiences and critical outcomes among nature-based visitors: a fuzzy-set qualitative comparative analysis approach

Intense global competition for natural resources, manifesting in negative environmental externalities, has forced hospitality and tourism stakeholders to adopt strategies that may result in economic growth in tandem with environmental conservation. One such strategy is to cultivate travellers’ loyalty to the tourism destinations and encourage them to participate in environmentally friendly activities. Using the affective theory of social exchange, social identity, stimulus–organism– response, tourism consumption system and attachment theories, this study proposes and tests a configurational model that predicts the antecedents of visitors’ pro-environmental behavioural intentions (PEBIs) regarding their desire to revisit (REVI) and recommend (RECI) the services that they experienced. Fuzzy-set qualitative comparative analysis was applied to assess the effect of memorable tourism experiences, place attachment, and demographics on these outcomes. The findings revealed that multiple configurations can predict visitors’ intentions at tourist destinations. This study’s implications for theory, practice, and future research directions are also discussed

A critical assessment of a protected area conflict analysis based on secondary data in the age of datafication

Recently, a global trend towards a broader use of secondary data in social sciences has been reinforced by the COVID-19 pandemic. This evoked doubts about the validity of the results unless restrictive assessment procedures are implemented. To address this need in the field of protected area (PA) conflict analysis, we propose a three-fold approach (theory-, method-, and cross-scale simulation-driven) to assess the usefulness of the utilized state register dataset and the indicator analysis methodology for the multi-level recognition of PA conflict determinants. With the ultimate aim to inform case study selection, we processed 187 relevant indicators from the official Statistics Poland register for a Lesser Poland region. We distinguished five types of PA conflict determinants in Lesser Poland (‘urbanity’, ‘agriculture’, ‘tourism’, ‘small-scale entrepreneurship’, and ‘sprawl’) and respective groups of 15 clusters comprising local-level units. For one cluster, we juxtaposed the obtained results with secondary data from another source (Internet content) and for a specific PA (Tatra National Park). Although the reported conflict issues corresponded to the indicator-derived descriptors of the cluster, in the theory-driven phase of the assessment, the state register failed to address the key prerequisites of PA conflicts. We have demonstrated that, in crisis conditions such as COVID-19, the proposed method can serve as a proxy for a multi-level recognition of PA conflict potentials, provided that it synthesises the results of different methodological approaches, followed by in-person interviews in the selected case studies

Tackling the complexity of the pro-environmental behaviors of visitors to marine turtle sites

This empirical study improved our understanding of how to simulate visitors’ pro-environmental behavior intentions (PEBIs) during interpretive marine turtle tours in Cyprus. Complexity theory was applied as a sufficient theoretical basis of the proposed configurational model that was tested using fuzzy set Qualitative Comparative Analysis (fsQCA) as an innovative set theoretic approach. Four configurations—demographics, values, beliefs, norms and attitudes—were used to explore causal recipes leading to both high and low PEBIs scores. The findings highlighted the heterogeneity issue in predicting PEBIs, addressed by determining the positive or negative role of PEBIs indicators along with attributes of other indicators in causal recipes. The fsQCA results of four configurations suggested 12 recipes for attaining high PEBIs scores. Further insight was obtained via configurational modeling of visitors’ PEBIs during endangered species tours, which contributed to the current knowledge of tourism management in protected areas. Implications for practice and further research are discussed