Finance & Accounting

Audit Quality Of Financial Performance Of Industrial Engineering Firms

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Assessment Type


Word Count

1500-2000 Words




4 Days

Assignment Criteria

For this assessment, students are expected to demonstrate their understanding of the extant, academic literature related to an approved, business topic.


In consultation with their lecturer, students need to decide on a business-related topic/concept. Students need to select approximately eight to twelve (8-12), but at least three (3), peer-reviewed articles or comparable sources (online resource can be accessed using ProQuest or Google Scholar) that are related to the topic (as the basis of their literature review).

In the context of their chosen topic, students need to review the articles and sources selected, i. e. read and critically analyse (compare and contrast) the literature. In doing so, students are required to discuss the key ideas/arguments put forward by authors, identify communalities/similarities, differences and conclusions drawn by different authors. Based on this analysis and discussion, students are expected to point out potential gaps in the literature that will form the basis of Assessment 2, the research proposal. 

Marking criteria of the literature review include: the quality and currency of the literature selected; the student's ability to compare and contrast author's arguments/viewpoints and identify gaps in the existing literature in the context of the chosen business topic; the demonstrated ability to use Harvard referencing. 

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Assignment Solution

Research Methodology

Research Question

From the literature review and empirical findings, the following research questions were formulated to establish the impact of the quality of the audit, i.e. size of auditor and independence of auditor on financial performance, i.e. on profit margin.

  1. Does auditor independence have any impact on the fiscal recital of industrialised engineering establishments in the UK?
  2. Does the size of auditors have any bearing on the financial recital of industrialised engineering companies in the UK?
  3. Does the gearing ratio have any effect on the financial outcomes of the engineering industry and establishments in the UK?

The research led to the following propositions:

  1. Auditor independence and profit margin are related to each other.
  2. Auditor size and profit margin are related to each other.
  3. Gearing ratio and profit margin are related to each other.

Data Sources

In this case, secondary sources were used to establish the association between the size of auditors and independence of auditor as proxies of quality of audit. Financial success and performance would be based on profit. Information for secondary data-analysis was extracted from the World Bank Database. The investigation was conducted with a sample size of fifteen industrial engineering enterprises in the UK. The period covered was ten years 2006 to 2015. A sum of 150 observations was considered for analysing and research. Information about auditor independence, auditors' size, gearing ratio, and financial performance of firms was gathered from the World Bank Database.

The main cause behind picking industrial engineering industries for this study is that audit is an essential factor for industrial engineering firms (Berg and Bruce, 2009). Most of the firms attempt to increase their earning artificially to improve their price of the share. Companies that display their annual report audited by reputed auditing firms are favoured in the share market. Thus, the influence of audit and the quality of audit on the performance of the firms should be studied. 

The specific period was studied to understand the global recession in 2009. The study also aimed at the recession in the UK. The quality of audit in the industrial engineering industry in the UK was influenced in a critical way during the recession (Creswell, 1998). The thesis implements secondary data analysis that can be traced to the Fame financial database. The data of gearing ratio, profit margin, independence of auditor and size of the audit was extracted and from the Fame finance InfoBase. 

Data Analysis – Methodology and Technique

Data were analysed and studied using statistical tools. Graphic statistics was instigated to explain factors such as gearing ratio, profit margin, independence of auditor and size of audit. The thesis is a depiction of the information. Descriptive statistics methods deal with systemising, summarising, gathering, and showing the financial figure in a proper format that is basically in terms of tables or graphs for understanding. It represents the sample data in an organised way. The statistical value that evaluates multiple statistical metrics and outlines different characteristics of data is called a statistical measure (Creswell, 2003). Quantitative data can be estimated in two types, such as measures of dispersal and measure of central propensity. The values in the estimated position are termed as measures of central propensity. There is a diverse classification of measures of central tendency. They are mean, mode, and median. The measure of disagreement among the measure of central tendency (e.g. mean, median and mode) is universally known as measures of dispersion. The different categories could be outlined as kurtosis, Skewness, standard deviation, variance, and range.  

Correlation analysis was applied to study the behaviour and association between two factors (Franklin, 2012). In this case, correlation technique helped to determine the nature of the relationship between quality of audit (size of the auditor, independence of the auditor and gearing ratio) and financial performance (i.e. profit margin) each at a time. This technique helped to display a way to determine the intensity of the association between two measures (Guba and Lincoln, 1989). The correlation technique supports to determine the gradation of differentiation in the values in an appropriate tactic. Furthermore, it could be referred to as quantifiable index as it estimates the gradation of reliance between dualistic variables. The level of correlation between two factors is considered positive if the dual values of factors are different in the one direction (Herrman, 2009). It could be inferred that the rise of a value of the factor, would influence the other value of factor to rise. The correlation between dual factors is considered negative if both the numbers of factors are different on the contrary direction. This indicates that with a rise in the value of the factor, the other value of factor diminishes (Howell, 2013). The range of the coefficient of correlation is [-1, +1]. If the value of the given coefficient of correlation is 0, the value signifies that the duo factors stand unrelated to each other.

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