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Resolving eddy currents in three dimensions with finite elements, especially in geometrically complex structures, is very time consuming. Notable additional efforts will be required, if these eddy currents are influenced by magnetic fields arising from larger parts or range over widespread regions. The purpose of this article is to present a new sub-modelling simulation technique, based on the finite-element approach. This method offers remarkable advantages for solving this type of problems.

A novel sub-modeling technique is developed for the finite-element method addressing this problem by dividing the process into two steps: firstly, a simulation of a “source”-model is carried out providing magnetic field distributions within the entire domain neglecting local eddy current effects and without modeling it in full detailed geometry. A subsequent “sub”-model comprises only the region of interest in higher resolution and is solved while being constrained with boundary conditions derived from the previous source-model. An implementation in ANSYS Mechanical is carried out with the objective to validate finite-element simulation against measurement results.

The proposed simulation technique performs robustly and time efficiently. Applying this method to an end-region of a turbogenerator allows comparisons with test data of this region for validation purposes. The comparison between measured and simulated radial flux densities shows good correspondence.

This work is novel in many aspects: a new technique for three-dimensional (3D) finite-element method using edge-elements is introduced. To the best of the authors’ knowledge, for the first time, these 3D sub-models are compared against measurement results of an electric machine with net currents. Leveraged from this work, detailed analyses of eddy current phenomena under influences of external magnetic fields can be investigated in higher detail within shorter calculation times.

The UK private finance initiative (PFI) public policy is heavily criticised. PFI contracts are highly profitable leading to incentives for PFI private-sector companies to support PFI public policy. This contested nature of PFIs requires legitimation by PFI private-sector companies, by means of impression management, in terms of the attention to and framing of PFI in PFI private-sector company annual reports. The paper aims to discuss this issue.

PFI-related annual report narratives of three UK PFI private-sector companies, over seven years and across two periods of significant change in the development of the PFI public policy, are analysed using manual content analysis.

Results suggest that PFI private-sector companies use impression management to legitimise during periods of uncertainty for PFI public policy, to alleviate concerns, to provide credibility for the policy and to legitimise the private sector’s own involvement in PFI.

While based on a sizeable database, the research is limited to the study of three PFI private-sector companies.

The portrayal of public policy in annual report narratives has not been subject to prior research. The research demonstrates how managers of PFI private-sector companies present PFI narratives in support of public policy direction that, in turn, benefits PFI private-sector companies.

This study aims to examine the relationships between tourism destination competitiveness (TDC) determinants and tourism performance. This study specifically assessed the soundness of the TDC attributes and evaluated their ability in explaining tourism performance.

The Dwyer and Kim’s (2003) destination competitiveness integrated model (IM) was used. Secondary data of 115 nations available from the Travel and Tourism Competitiveness Index (TTCI) and other international reports were also used. The hypothesised relationships were tested via partial least square-structural equation modelling (PLS-SEM).

This study confirms that the core resources, complementary condition, globalisation and tourism price significantly explain tourism performance. Results have shown differences in the competitiveness level and actual performance among nations, highlighting specific limitations of the current TDC model and TTCI report reliability.

Future study could segment the sample base on destinations characteristic and then analyse it based on smaller sub-samples of similar destinations. Moreover, drivers of destination performance in developed and less develop destinations are quite diverse.

The incorrect competitiveness ranking evaluation will affect inward investment decisions. This study framework enables policymakers to arrive at more informed decisions than merely relying on the original competitiveness rankings.

The widespread acknowledgment of the importance of competitiveness for a tourism destination's success suggests that there is a crucial need for sound benchmarking of countries’ competitive capabilities. The proposed competitiveness determinants aid the policymakers in identifying the best competitiveness and tourism performance predictors, as well as how to identify crucial factors affecting the rankings.