Investigating the Effect of Auditors' Behavior Biases on Decision Making and Errors within Capital Market, with Emphasis on Auditor's Personal and General Characteristics

Subject Areas : International Journal of Finance, Accounting and Economics Studies

bakhtyar  ashrafi ¹ (Ph.D Student in Accounting, Department of Management and Economics, Islamic Azad University Science and Research Branch, Tehran, Iran.)
zohre  hajiha ² (Professor and Faculty Member, Department of Accounting, Islamic Azad University East Tehran Branch, Tehran, Iran “Corresponding author”. Invited of Science and Research Branch)
reza  tehrani ³ (Professor and Faculty Member, Department of Financial Management, Tehran University, Tehran, Iran.)

Received: 2022-02-22 Accepted : 2022-05-07 Published : 2022-10-01

Keywords: Decision-making Process, Judicial Biases, mental accounting, Behavioral Biases, Behavioral Finance Theory,

Abstract :

Behavioral biases are defined as systematic errors in judgment. researchers have identified and presented a long list of types of behavioral biases. recent studies have introduced more than fifty types of known behavioral biases about investors, while many behavioral biases have not yet been clearly identified. This study used a combined quantitative and qualitative method to present the research model. Based on the capital market’s nature, accountants and auditory information is provided by an effective influence of personal decisions and market results, derived systematically by information structure and market participants’ features. Auditors’ choices are influenced by perception, judgment and decision options processes, which may affect auditing errors. The study's purpose is to investigate auditors’ different biases and decision-making factors on errors based on a cognitive approach in the capital market. The model’s objective is practical and based on a descriptive-analytical methodology. The statistical population of the study includes all certified auditors of Iran's Securities and Exchange Organization, who were provided with the researcher-made questionnaires with valid narration and reliability. The collected data were analyzed by AMOS software. The findings indicate that components of the cognitive bias are predictable by auditors’ errors based on the priority level and maximum influences, including mental accounting bias, availability bias, heuristic bias, and ambiguity aversion bias. Also, components of decision-making are predictable by auditors’ errors based on the priority level and maximum influences, including decision case, job experience, decision-making situation, and individual features.