Internal auditor selection using a TOPSIS/non-linear programming model

Petridis, Konstantinos; Drogalas, George; Zografidou, Eleni

doi:10.1007/s10479-019-03307-x

Cited by 25 publications

(10 citation statements)

References 68 publications

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“…Understanding business objectives and strategies and aligning them with business objectives and activities (Coetzee and Lubbe, 2014; Selim and McNamee, 1999b), as well as assessing business risks on an annual basis and in individual audit assignments (Allegrini and D’Onza, 2003; Koutoupis and Tsamis, 2009) – that is, identifying, measuring and prioritizing the negative effects for the entity – contributes to an effective risk management that follows a holistic approach at the lowest possible cost (Bowling and Rieger, 2005; Banham, 2005; Busman and Zuiden, 1998; Goodwin, 2003; Griffiths, 2006; Gupta, 2011; Lois et al , 2020; McCord, 2002; Verschoor, 2002). Therefore, the focus of internal auditors is shifted to the future (Crawford and Stein, 2002; Petridis et al , 2019) and to “high-risk” areas that must be considered as a priority when preparing the internal audit plan (Grıffıths, 2006; Hafizah, 2017; Koutoupis and Tsamis, 2009; Sarens et al , 2012). To achieve the above, internal auditors, who now play a strategic role in organizations (IIARF, 2013; Krogstad et al , 1999), are required to possess specialized knowledge in matters of control and risk management (Deloitte, 2012; Mayur and Saravanan, 2017; Zain et al , 2006).…”

Section: Introductionmentioning

confidence: 99%

Risk-based internal audit: factors related to its implementation

Lois

Drogalas

Nerantzidis

et al. 2021

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Purpose This study aims to investigate the factors associated with the implementation of risk-based internal audit (RBIA). Design/methodology/approach As a first step, a literature review of the relevant literature is performed and five potential factors related to the implementation of RBIA are identified. Based on that, this paper constructs a questionnaire survey sent out to 185 internal auditors, executives and accountants in Greece to receive 90 responses during the period of November 2019–January 2020. Multiple regression analysis is conducted to identify the factors related to the implementation of RBIA. Findings This paper shows that there is a statistically significant positive relationship between the implementation of RBIA and: the provision of risk management training, an active audit committee role and the establishment of a formalized risk management system. Practical implications The results have important implications for internal auditors, chief executive officers and accountants who wish to enhance internal audit effectiveness and the accuracy and quality of financial information. Originality/value Empirical studies on the factors related to the implementation of RBIA are rare. This is the first study to create empirical variables based on a thorough review of the relevant literature to empirically investigate the factors that are related to the implementation of RBIA in an emerging economy. By focusing on the Greek context, this study also sheds light to other countries with similar corporate governance systems, thus providing insights to settings where the Type II agency problem exists (La Porta et al., 1999).

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Section: Introductionmentioning

confidence: 99%

Risk-based internal audit: factors related to its implementation

Lois

Drogalas

Nerantzidis

et al. 2021

View full text Add to dashboard Cite

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“…They assigned weights to the responses with the decision-makers choice [ 23 ]. The main advantage of AHP is used for determining the weights on top and bottom level criteria [ 14 ]. However, the AHP method needs to be performed in comparison in pairs of criteria [ 20 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The AHP method was almost impossible to perform entirely consistent comparisons in pairs with over nine criteria, which often overcame by dividing the criteria into subcriteria and would further make the model more complex [ 20 ]. Increasing the problem’s size will lead the decision-makers to meaningless pairwise comparisons among measures [ 14 ]. The AHP method is also limited to many comparisons as it needs to perform n(n-1)/2 comparisons in pairs of criteria [ 20 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the literature, the TOPSIS method has been another broadly used MCDM approach since 2020. TOPSIS technique is straightforward to construct the problem, easily understandable, and demonstrating adequate computational efficiency, which provides a scalar value that accounts for both best and worst alternatives’ ability to measure the relative performance for each choice in a simple mathematical form [ 14 ]. The TOPSIS method allows the weighting of each criterion from the decision-maker regardless of the level [ 14 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…TOPSIS technique is straightforward to construct the problem, easily understandable, and demonstrating adequate computational efficiency, which provides a scalar value that accounts for both best and worst alternatives’ ability to measure the relative performance for each choice in a simple mathematical form [ 14 ]. The TOPSIS method allows the weighting of each criterion from the decision-maker regardless of the level [ 14 ]. The disadvantage of TOPSIS is that for the criteria for which higher values were preferred, the larger the criterion outcomes were, the greater were the preferences attached [ 38 ].…”

Section: Literature Reviewmentioning

confidence: 99%

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A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

Zhang

Yan

et al. 2022

PLoS ONE

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Background As the world’s largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Methods Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. Results The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. Conclusions The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments.

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A Hybrid Interval-Valued Intuitionistic Fuzzy Aggregation Operator-Based Algorithm for Team Member Selection of International Entrepreneurs

Hajiagha

Kandi

2021

Contributions to Management Science

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Internal auditor selection using a TOPSIS/non-linear programming model

Cited by 25 publications

References 68 publications

Risk-based internal audit: factors related to its implementation

Risk-based internal audit: factors related to its implementation

A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

A Hybrid Interval-Valued Intuitionistic Fuzzy Aggregation Operator-Based Algorithm for Team Member Selection of International Entrepreneurs

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