Audit Tendering in the UK: A Review of Stakeholders’ Views

This study reports the results of a content analysis of the comment letters sent to the UK Financial Reporting Council (FRC), in response to its consultation document on the 2012 revisions of the UK Corporate Governance Code, concerning the proposal for mandatory audit tendering. The results indicate a general support for the FRC’s proposals with a number of key concerns related to audit quality, auditor independence and audit cost. There is also clear conflict of interests among some stakeholder groups such as audit firms and companies on one side and institutional investors on the other side. There is evidence of conflict of interest between Big 4 and non-Big 4 audit firms. Implications for future consultations and legislations are also discussed.

Exploring Auditors’ Perceptions of the Usage and Importance of Audit Information Technology

This study provides novel evidence on the extent to which auditors perceive the usage and importance of audit technology in an emerging market. It explores the types of audit technology tools used and factors influencing the use of these; it tests the association between the perceived use and importance of the tools and firm-specific/ auditor-specific characteristics. Using interviews and questionnaires from auditors at Big 4 and international non-Big 4 audit firms, the findings reflect the highly perceived importance of using audit technology in technical and administrative procedures, specifically to assess risk. We find that the perceived use and importance of audit technology is relatively higher for those in Big 4 firms, with less years of auditor experience and higher auditor technology expertise, and those in management positions. The results provide policy makers with guidance on the opportunities and challenges of using information technology in the audit process.

Detailed analysis of data from heat pumps installed via the Renewable Heat Premium Payment Scheme

The RHPP policy provided subsidies for private householders, Registered social landlords and communities to install renewable heat measures in residential properties. Eligible measures included air and ground-source heat pumps, biomass boilers and solar thermal. Around 18,000 heat pumps were installed via this scheme. DECC funded a detailed monitoring campaign, which covered 700 heat pumps (around 4% of the total). The aim of this monitoring campaign was to assess the efficiencies of the heat pumps and to estimate the carbon and bill savings and amount of renewable heat generated. Data was collected from 31/10/2013 to 31/03/2015. This report represents the analysis of this data and represents the most complete and reliable data in-situ residential heat pump performance in the UK to date.

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.