Compliance ist gut – Vertrauen ist viel besser?! Eine Besprechung des Buches Margin of Trust. The Berkshire Business Model von Lawrence A. Cunningham and Stephanie Cuba
A review of the book Margin of Trust. The Berkshire Business Model from Lawrence A. Cunningham and Stephanie Cuba (2020).
In this study, we analyse compliance for a large sample of European companies mandatorily applying International Financial Reporting Standards (IFRS). Focusing on disclosures required by IFRS 3 Business Combinations and International Accounting Standard 36 Impairment of Assets, we find substantial non-compliance. Compliance levels are determined jointly by company- and country-level variables, indicating that accounting traditions and other country-specific factors continue to play a role despite the use of common reporting standards under IFRS. At the company level, we identify the importance of goodwill positions, prior experience with IFRS, type of auditor, the existence of audit committees, the issuance of equity shares or bonds in the reporting period or in the subsequent period, ownership structure and the financial services industry as influential factors. At the country level, the strength of the enforcement system and the size of the national stock market are associated with compliance. Both factors not only directly influence compliance but also moderate and mediate some company-level factors. Finally, national culture in the form of the strength of national traditions (‘conservation’) also influences compliance, in combination with company-level factors.
In December 2012 Russia enacted important amendments to the Federal Law titled: “On combating corruption,” which came into force on January 1, 2013. This Law established obligations for all companies in the Russian Federation to have anti-corruption compliance policies and take measures to prevent corruption.
This paper analyzes opportunities of application of the self-determination theory to the compliant behavior and describes the process of development and validation scale for measuring compliance-related causality orientations in the normative sample. Experts’ appraisals demonstrated that in clinical settings controlled causality orientation could be divided into two subscales: controlled by doctors and controlled by others subscales. Empirical data (N=246 students) supports internal consistency (Cronbach's alpha .76-.79), test-retest reliability and factor validity of the scale. All the subscales correlate with general controlled orientation subscale as well as relevant subscales of General Causality Orientation Scale. Controlled by doctors and impersonal causality orientations were negatively related to health-related quality of life. Compliance-Related Causality Orientations Scale correlated with retrospective appraisals of last episode of somatic illness (subjective interference with other domains, fear of future complications, fear of more severe illness, subjective ability to follow chosen treatment. Although testing prospective validity of the scale is a challenge for future research, the scale could be useful to study motivational factors of compliant behavior both in the normative and clinical samples.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.