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Interest rate risk, i.e. the risk of changes in the interest rate term structure, is of high relevance in insurers' risk management. Due to large capital investments in interest rate sensitive assets such as bonds, interest rate risk plays a considerable role for deriving the solvency capital requirement (SCR) in the context of Solvency II. This paper seeks to address these issues.

In addition to the Solvency II standard model, the author applies the model of Gatzert and Martin for introducing a partial internal model for the market risk of bond exposures. After introducing calibration methods for short rate models, the author quantifies interest rate and credit risk for corporate and government bonds and demonstrates that the type of process can have a considerable impact despite comparable underlying input data.

The results show that, in general, the SCR for interest rate risk derived from the standard model of Solvency II tends to the SCR achieved by the short rate model from Vasicek, while the application of the Cox, Ingersoll, and Ross model leads to a lower SCR. For low‐rated bonds, the internal models approximate each other and, moreover, show a considerable underestimation of credit risk in the Solvency II model.

The aim of this paper is to assess model risk with focus on bonds in the market risk module of Solvency II regarding the underlying interest rate process and input parameters.

The study aims to investigate the comparatively under‐researched relationship between ownership structure and capital structure in an emerging market. It is also one of the first studies to apply both single and reduced‐form equation methods using a panel data approach. Design/methodology/approach – The study applies econometrics modelling using both single equation and reduces equation models for panel data.

The results demonstrate that Jordanian firms follow the same determinants of capital structure as occur in developed markets, namely: profitability, firm size, growth rate, market‐to‐book ratio, asset structure and liquidity. In addition, institutional ownership structure is found to be determined by: assets structure, business risk (BR), growth opportunities and firm size. Finally, the results reveal that assets tangibility, firm size, growth opportunities and BR are considered to be joint determinants of ownership structure and capital structure.

The practical implication of the study is that investors and managers should consider both capital structure and ownership structure when they take their investment decisions.

This is the first study of the interaction between institutional ownership and capital structure in Jordan where there are differences, as regards institutional and financial structures, relative to those in developed markets.

The purpose of this paper is to examine the role of institutional, macroeconomic, industry, and firm characteristics on the adjustment speed of corporate capital structure within the context of developing countries.

The authors considers a sample of 986 firms drawn from nine developing countries in Africa over a period of ten years (1999-2008). The study develops dynamic partial adjustment models that link capital structure adjustment speed and institutional, macroeconomic, and firm characteristics. The analysis is carried out using system Generalized Method of Moments procedure which is robust to data heterogeneity and endogeneity problems.

The paper finds that firms in developing countries do temporarily deviate from (and partially adjust to) their target capital structures. Our results also indicate that: more profitable firms tend to rapidly adjust their capital structures than less profitable firms; the effects of firm size, growth opportunities, and the gap between observed and target leverage ratios on adjustment speed are functions of how one measures capital structure; and adjustment speed tends to be faster for firms in industries that have relatively higher risk and countries with common law tradition, less developed stock markets, lower income, and weaker creditor rights protection.

Future research should focus on examination of the adjustment speed of debt maturity structure. Identification of industry-specific characteristics that affect the pace with which firms adjust their capital structure to the optimum is another possible avenue for future research.

Our findings have practical implications for corporate managers, governments, legislators, and policymakers.

The study focuses on firms in developing countries for which the literature on adjustment speed of capital structure is virtually non-existent. Furthermore, unlike previous works on capital structure, it explicitly models industry variable as one of the determinants of adjustment speed. Therefore, it contributes to the literature on capital structure and adjustment speed in general and to the literature on developing countries in particular.

Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.

The purpose of this paper is to investigate impacts of policy instruments for market penetration of renewable technologies in South Africa. Based on the current debates about renewable energy policies and the comparative advantage of the country in terms of coal resources the author set up a framework focusing on renewable energy price subsidies, carbon tax and renewable energy portfolio standard.

Using a simulation model through a linear programming approach the paper assesses impacts of those policies on fossil fuel and renewable energy sectors via business‐as‐usual and policy option scenarios. The business‐as‐usual assumes that there are not policy instruments mobilized to promote adoption and diffusion of clean technologies instead of a policy scenario where such policies are included.

The results of the analysis show that when the coal‐based resources are integrated in the simulation process, only carbon tax and renewable energy price‐based subsidies promote a transition towards a sustainable energy production, therefore reduce the associated environmental damage.

Moreover, the paper also shows that in the case of carbon tax and renewable price subsidies, emission prices should be adequately scrutinized in order to guarantee a positive economic surplus.

This study aims to validate the KAIIAE model in the public sector and analyse the interrelationships between Enablers and Results in the King Abdullah II Award for Excellence (KAIIAE) model to better understand the dynamic logic behind improving excellence results.

The methodology used is structural equation modelling (partial least squares technique), and the data were obtained from the assessment processes for the KAIIAE for 98 Jordanian public organisations.

The findings showed that the award model has proven to be a reliable and valid framework, as the criteria and sub-criteria were highly correlated. The set of Enablers was strongly related to the set of Results, and the synergies between the critical criteria confirmed the importance of leadership, strategy, and processes for the organisation's excellence results. It was found that the new significant and direct relationships between “People” and “People Results” and between “Partnerships and Resources” and both “Society Results” and “Key Results” improved the understanding and implementation of the model. There was a significant interrelationship between model criteria, excluding the relationship between “Society Results” and “Key Results”, since the government's main objective is to serve society. A new structural model for the KAIIAE with the new relationships was suggested.

This paper concentrated only on the public sector, although the excellence model has been implemented in the private sector. Features of the different types of organisations were not tested. Furthermore, the variations in size, covered fields, number of employees and provided services need to be investigated further.

Government award bodies can use these research findings to develop a new model version for public sector awards by combining a cohesive array of elements for any government organisational need or application. The study suggested adding new criteria or relationships or eliminating those that are not significant and have no impact on public sector organisations. The findings will assure the organisations' managers that the KAII excellence model criteria are highly correlated and synergised for public sector organisations. These criteria perform efficiently once they are considered and implemented in an interconnected manner rather than managing them independently, which makes up their management framework. This knowledge about the validity of the structure of the model allows public sector organisations to benefit fully from the self-assessment processes and improve the organisation's management, enhancing their faith in excellence award models.

This study has contributed to the existing literature on the reliability and validity of business excellence models as a framework for implementing, evaluating, and improving excellence, particularly in the government sector. Several important insights have emerged from this study. The relevant analysis supports a new model structure for excellence in the public sector. Among the model structure relationships, the study identified the existence of new direct relationships between enablers and results. New significant and direct relationships are added to the model that advances the implementation and understanding of the model. Moreover, it informs theory about Excellence Award implementation in developing countries within the context of Jordan – a topic that has previously received limited attention in the international business excellence literature. Since there is limited research on the suitability of implementing the KAIIEA excellence model (that is based on nine criteria of the EFQM model) in public organisations, this work suggested introducing a new modification to the model to suit the characteristics of the public sector.

The considerable prominence of the government sector has drawn attention to the excellence parameters within its organisations. Hence, a lack of studies and inadequate knowledge in the governmental management system have limited testing excellence in the public sector. This paper provides support that the excellence model (KAIIAE model that is EFQM based) is an appropriate framework by identifying direct and significant model interrelationships for the public sector based on the actual and sufficient performance of its entities so as to drive the changes of the next model generation. This is the first study that attempts to comprehend and describe the validation of the KAIIAE model in the public sector.

The purpose of this paper is to critically review the latest approaches for capturing and explaining heterogeneity in partial least squares (PLS) path modelling and to classify these into a methodological taxonomy. Furthermore, several areas for future research effort are introduced in order to stimulate ongoing development in this important research field.

Different approaches to treat heterogeneity in PLS path models are introduced, critically evaluated and classified into a methodological taxonomy. Future research directions are derived from a comparison of benefits and limitations of the procedures.

The review reveals that finite mixture‐PLS can be regarded as the most comprehensive and commonly used procedure for capturing heterogeneity within a PLS path modelling framework. However, further research is necessary to explore the capabilities and limitations of the approach.

Directions for additional research, common to most latent class detection procedures include the verification and comparison of available approaches, the handling of large data sets, the allowance of varying structures of path models, the profiling of segments and the problem of model selection.

Whereas modelling heterogeneity in covariance structure analysis has been studied for several years, research interest has only recently been devoted to the question of clustering in PLS path modelling. This is the first contribution which critically consolidates available approaches, discloses problematic aspects and addresses significant areas for future research.

This paper aims to analyze and model consumer behavior on hotel online search interest in the USA.

Discrete Fourier transform was used to analyze the periodicity of hotel search behavior in the USA by using Google Trends data. Based on the obtained frequency components, a model structure was proposed to describe the search interest. A separable nonlinear least squares algorithm was developed to fit the data.

It was found that the major dynamics of the search interest was composed of nine frequency components. The developed separable nonlinear least squares algorithm significantly reduced the number of model parameters that needed to be estimated. The fitting results indicated that the model structure could fit the data well (average error 0.575 per cent).

Knowledge of consumer behavior on online search is critical to marketing decision because search engine has become an important tool for customers to find hotels. This work is thus very useful to marketing strategy.

This research is the first work on analyzing and modeling consumer behavior on hotel online search interest.