Anchoring Bias in Strategic Business Decisions

Abstract

Cognitive biases are tendencies that cause distortions in perception, interpretation and judgment, thereby leading to a systematic deviation from rational decision-making. There are various types of cognitive biases, where the anchoring bias is the main focus of this report. Anchoring refers to how different suggestions, such as words or numbers, can affect the decision maker to make a certain decision. Biases related to anchoring is however also discussed in the theoretical framework, such as priming, framing, availability bias, confirmation bias and groupthink, since these are important in order to understand what kind of information can induce cognitive biases. By understanding the theory behind anchoring and related cognitive biases, efforts can be made in order to mitigate its effect on decision-making and thereby make more accurate decisions. This report investigates and analyzes how different information or treatment induces anchoring bias in a purchasing decision. More specifically, the aim of the report is to test whether the status or authority granted by the CEO title is a source of bias, causing erroneous conclusions and suboptimal decision-making. A case study was conducted on 42 students, where the case results was analyzed in the statistical software Stata and compared with the theoretical framework presented in order to identify if anchoring was observed. Also, the report aims to discuss how the anchoring bias and related tendencies can be overcome. To further specify, the study presents the results of regressions containing variables retrieved from participants choice between recommending one of two suppliers for a given company, as well as a motivation regarding this choice, decision time to complete the case and several answers to questions contained in a post case form. Significance is not found for the main regression concerning the effect of treatment on participants’ choice of supplier recommendation, possibly partly due to sample size. However, the coefficient for the treatment holds the expected sign, and while assuming the presence of its associated bias, regressions indicate that time may have had a mitigating effect. Also, several remarkable tendencies are found by further investigating the relationships between variables. Furthermore, reasons as to why significance is not found in the relatively small sample are discussed. Aside from the sample size itself, the fact that a large fraction of respondents selected the same supplier, regardless of whether they received treatment or not is addressed as a conceivable explanation. In examining reasons for this, a tendency of risk aversion and what is referred to as the tendency of sticking to well-known brands is discussed. Accompanying regressions regarding time related variables also indicate that confirmation bias might have been a culprit in the case. The thesis also discusses implications of observed tendencies and suggests strategic measures to be implemented.