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could apply to evaluate the audit performance of internal auditors and optimally assign
audit tasks according to the required performance value.
could apply to evaluate the audit performance of internal auditors and optimally assign
Since these companies do not provide all the performance data of the assigned
audit tasks according to the required performance value.
personnel, to generate complete audit data for the assignment planning of senior
Since these companies do not provide all the performance data of the assigned
supervisors, this study proposes an integrated two-stage data analysis model. First, we
personnel, to generate complete audit data for the assignment planning of senior
apply random forest and machine learning regression technology to accurately estimate
supervisors, this study proposes an integrated two-stage data analysis model. First, we
and simulate the audit performance of all auditors under different tasks to predict all
apply random forest and machine learning regression technology to accurately estimate
NTU Management Review Vol. 33 No. 1 Apr. 2023
values. In the second stage, based on the predicted values of auditors’ performance, we
and simulate the audit performance of all auditors under different tasks to predict all
optimize task assignment by heuristic algorithms to avoid the infeasibility of integer
values. In the second stage, based on the predicted values of auditors’ performance, we
supervisors, this study proposes an integrated two-stage data analysis model. First, we
planning method in solving high-dimensional problems. The outcome shows that in
optimize task assignment by heuristic algorithms to avoid the infeasibility of integer
apply random forest and machine learning regression technology to accurately estimate
and simulate the audit performance of all auditors under different tasks to predict all
terms of the effectiveness, speed, and stability of assignment, Binary Differential
planning method in solving high-dimensional problems. The outcome shows that in
values. In the second stage, based on the predicted values of auditors’ performance, we
Evolution (BDE) performs better than Genetic Algorithm (GA) and Binary Particle
terms of the effectiveness, speed, and stability of assignment, Binary Differential
optimize task assignment by heuristic algorithms to avoid the infeasibility of integer
Swarm Optimization (BPSO). Therefore, we recommend BDE algorithm for auditor
planning method in solving high-dimensional problems. The outcome shows that in terms
Evolution (BDE) performs better than Genetic Algorithm (GA) and Binary Particle
of the effectiveness, speed, and stability of assignment, Binary Differential Evolution (BDE)
assignment, as the results have well demonstrated its far-better effectiveness of the
Swarm Optimization (BPSO). Therefore, we recommend BDE algorithm for auditor
performs better than Genetic Algorithm (GA) and Binary Particle Swarm Optimization
heuristic approach when compared with the conventional methods.
assignment, as the results have well demonstrated its far-better effectiveness of the
(BPSO). Therefore, we recommend BDE algorithm for auditor assignment, as the
results have well demonstrated its far-better effectiveness of the heuristic approach when
3. Findings
heuristic approach when compared with the conventional methods.
compared with the conventional methods.
3. Findings
This study aims to compare two objectives from an active performance evaluation
3. Findings
model and an integrated performance evaluation model. Objective one: the auditing
This study aims to compare two objectives from an active performance evaluation
department primarily concerns results (that is, result-oriented), with its organizational
This study aims to compare two objectives from an active performance evaluation
model and an integrated performance evaluation model. Objective one: the auditing
model and an integrated performance evaluation model. Objective one: the auditing
goal to maximize the audit performance (∑∑ ). Objective two: The auditing
department primarily concerns results (that is, result-oriented), with its organizational
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department primarily concerns results (that is, result-oriented), with its organizational
department adopts organizational learning to establish a continuous learning mode
goal to maximize the audit performance (∑∑ ). Objective two: The auditing
goal to maximize the audit performance � � �� �� Objective two: The auditing
department adopts organizational learning to establish a continuous learning mode among
among auditors to improve long-term performance (Roussy, Barbe, and Raimbault,
department adopts organizational learning to establish a continuous learning mode
auditors to improve long-term performance (Roussy, Barbe, and Raimbault, 2020; Gimbar,
2020; Gimba, Jenkins, Saucedo, and Wright, 2018; Pace, 2002). In addition to
among auditors to improve long-term performance (Roussy, Barbe, and Raimbault,
Jenkins, Saucedo, and Wright, 2018; Pace, 2002). In addition to maximizing performance
by organizational goals (∑∑ ), it promotes Audit
maximizing performance by organizational goals � appropriate tasks to auditors, which is a equation
�� �� it promotes Audit Apprenticeship, strengthens
2020; Gimba, Jenkins, Saucedo, and Wright, 2018; Pace, 2002). In addition to multi-objective
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departmental professional skills training, and assigns appropriate tasks to auditors, which
Apprenticeship, strengthens departmental professional skills training, and assigns �
maximizing performance by organizational goals (∑∑ ), it promotes Audit
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is a multi-objective equation (∑∑ �� + ∑∑ �� � � + � � �� ) .
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The results indicate that this method could prioritize important characteristics that
Apprenticeship, strengthens departmental professional skills training, and assigns
The results indicate that this method could prioritize important characteristics that
affected the performance of auditors; compared with the single-objective model, the multi-
objective model will first consider the high-performance audit portfolio, find out the audit
affected the performance of auditors; compared with the single-objective model, the
variables that improve the performance value through the overall model analysis, and
multi-objective model will first consider the high-performance audit portfolio, find out
carry out the audit task according to the level of influence between the audit variables—
the audit variables that improve the performance value
assignments to maximize conversion of audit performance values. For example, auditors through the overall model
with high audit qualifications and high professional license teaching hours are assigned
analysis, and carry out the audit task according to the level of influence between the
to audit tasks with low levels of complexity. Limiting the seniority of three people
audit variables—assignments to maximize conversion of audit performance values. For
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example, auditors with high audit qualifications and high professional license teaching
hours are assigned to audit tasks with low levels of complexity. Limiting the seniority
of three people in the audit team allows the team to have senior and junior auditors
simultaneously (∑ ≤2, ∑ ≤2, ∑ ≤2). The existence of auditors
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helps promote senior personnel's growth, leading to junior personnel's development.
Assignment methods show that audit experience, expertise, and task complexity affect
audit performance and assignments, which is a finding that echoes current research
findings (Asare and McDaniel, 1996; Tan, Ng, and Mak, 2002; Alissa et al., 2014).
Machine learning methods can improve the ability of audit-task scheduling model
in order to analyze critical factors and understand which combinations of audit
specialties or backgrounds perform best on tasks of varying complexity. When the
number of auditors and tasks solved increases to a certain number, the order of

assignment of auditing tasks could be summarized as dispatching rules. Thus, in the

future, audit supervisors will be able to follow the audit dispatch rules for task

assignment, and the encouragement of learning in organization will also have a positive

effect. For example, priority should be given to assigning auditors with professional

training experience in their job qualifications to the least complex tasks, and then