The cultural tourism market has diversified and fragmented into many different niches. Previous attempts to segment cultural tourists have been largely unidimensional, failing to capture the complexity of cultural production and consumption. We employ multiple correspondence analysis to visualize the relationship between cultural consumers and attractions in a large data set (n = 12,905). This indicates that two dimensions describing the ranges between 'static' and 'dynamic' attractions and 'high-brow' and 'low brow' culture effectively discriminate different groups of arts and heritage tourists. The holiday structure itself seems to provide a context that influences the cultural consumption of actors. Thus higher levels of cultural capital are related to more accessible forms of culture, contrary to theoretical expectations. There is also evidence of the development of a cultural tourism 'travel career' with more dynamic cultural forms being characteristic of younger tourists and more high brow and static forms of culture being consumed in later life by those with higher levels of cultural capital.
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BACKGROUND: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.METHODS: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.RESULTS: We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.CONCLUSIONS: We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
We are currently in a transition moving from a linear economy grounded on economic value maximization based on material transformation to a circular economy. Core of this transition is organising value preservation from various yet interlinked perspectives. The underlying fundamental shift is to move away from mere financial value maximization towards multiple value creation (WCED, 1987; Jonker, 2014; Raworth, 2017). This implies moving from mere economic value creation, to simultaneously and in a balanced way creating ecological and social value. A parallel development supporting this transition can be observed in accounting & control. Elkington (1994) introduced the triple bottom line (TBL) concept, referring to the economic, ecological and social impact of companies. The TBL should be seen more as a conceptual way of thinking, rather than a practical innovative accounting tool to monitor and control sustainable value (Rambaud & Richard, 2015). However, it has inspired accounting & control practitioners to develop accounting tools that not only aim at economic value (‘single capital’ accounting) but also at multiple forms of capital (‘multi capital’ accounting or integrated reporting). This has led to a variety of integrated reporting platforms such as Global Reporting Initiative (GRI), International Integrated Reporting Framework (IIRC), Dow Jones Sustainable Indexes (DJSI), True Costing, Reporting 3.0, etc. These integrated reporting platforms and corresponding accounting concepts, can be seen as a fundament for management control systems focussing on multiple value creation. This leads to the following research question: How are management control systems designed in practice to drive multiple value creation?
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