168 More importantly, the utilization of essential judgment in inspecting unique research locations using different measures, tests, plans, and examinations are
imperative to permit an association on a considerable appreciation of a wonder (Aliyu, et al., 2014).From the on-going investigation, the actions of CEOs, project managers and stakeholders involved in decision making are viewed with regard to social forces.
Moreover, a cognitive bias is viewed as a construct that is modelled by social forces more than innate thinking of the social actors. Further, the inclusion of demographic characteristics of the sample under study indicates the importance placed on social forces in modelling daily behaviour and actions of individuals.
Another sphere of research leading to the classification of the research philosophy as positivist is related to the ultimate focus of research (Thompson, 2015). Positivist research attempts to unearth the truth about reality from an individual’s actions and behaviours in the same way that scientific research has provided guidelines about physical reality (Thompson, 2015). This investigation views the individuals under research (CEOS, Managers, and Stakeholders) objectively by dissociating the research from the actual experience of individuals. Ultimately, the above allows for measuring of the constructs under investigation independently of the social actors. Ideally, this
research attempts to explain the relationship between cognitive bias and decision making using the identified variables such as personality traits, cost overrun, over- optimism and risk; thus, a positivist approach is best suited for the study.
.
169 justification. Notably, research designs often rife with inconsistencies such as bias and insignificant results; however, this study identified and acknowledged weaknesses in the designs and followed research recommended guidelines. Distinctly, from the description presented in the research philosophies, the current study is quantitative. The
aforementioned research designed is motivated by the nature of questions this study seeks to answer, the sample size used, and the amount of objectivity intended by the researcher. In specific, the type of data collected and tests to be conducted are most fit investigated under the quantitative research design. Furthermore, a quantitative
approach is most suitable to ensure generalizability of the results (Langkos, 2014) to other spheres of knowledge where cognitive bias and decision making are under investigation. In addition, a quantitative approach allows independence of the research from the researcher’s bias which is quite common in qualitative research (Langkos, 2014). The current study is quantitative descriptive as it seeks to measure the relationship between variables and establish whether any associations exist.
Essentially, quantitative research involves the deliberate examination of phenomena by socially quantifiable information and scientific or computational methods. Quantitative research is generally driven in human sciences using statistical techniques to accumulate quantitative data. In this examination method, experts and investigators leverage numerical structures and theories that identify with the variables under scrutiny. Because the ongoing investigation is quantitative, it falls under cross- sectional research. According to Earl (2010), this type of study is adequately defined as a cross-sectional survey. In the end, the structure of quantitative research calls for descriptive and inferential statistics involving the testing of hypotheses and significant
170 differences. Another key feature is the reliance on tabulation to present results; this is evident in the analysis chapter of this study.
Even with the above strengths of the quantitative design, weaknesses still exist.
For instance, Langkos (2014) criticized the use of a quantitative design due to the tendency to misrepresent the target population under research. In this investigation, however, a thorough review of secondary sources of information serves to supplement the results of the investigation on cognitive bias and decision making in Megaprojects.
Moreover, the systematic nature of the quantitative approach guarantees meaningful results.
Notably, the personal experiences of the CEOs, Managers, and Stakeholders of mega projects cannot be investigated as this requires a qualitative approach. Despite that, the ongoing study posed questions and hypotheses that are best answered and explained by methods encapsulated in the quantitative research design. Moreover, similar studies investigating one or two of the variables under scrutiny in this paper opted to use a quantitative approach. Andrić, et al.(2019) used a mixed research approach, however, they noted that the quantitative approach was best suited to investigate cost overrun and its relationship with other variables such as cost
performance in Mega infrastructure projects. Another similar study by (Esa, et al., 2016) also adopted a quantitative approach to measure the relationship between cost overrun and behavioral biases.
The aforementioned examples demonstrate the accreditation of the research design by other scholars investigating cognitive bias and decision making or related variables. Even with the above justifications for using a quantitative research design, there still exist limitations on the part of quantitative research. For instance, faults
171 individual quantitative studies for being subject to bias; instead, he recommends using a quantitative meta-analysis technique where the results of multiple quantitative studies are synthesized to generate knowledge. Moreover, Hallion and Ruscio (2011) claimed that many quantitative studies fail to answer their research questions or meet their objectives, thus, the use of a meta-analysis is recommended.
Nonetheless, an examination of the research questions posed in the on-going investigation indicates that a quantitative approach is best suited for the investigation.
Thompson (2015) claimed that since a positivist approach views individuals objectively, then quantitative approaches are required as they are less susceptible to subjectivity as compared to qualitative methods. Further, the adoption of quantitative research methods helps to ensure the results are valid and reliable in contrast to qualitative research methods that may at times forego reliability for more validity (Thompson, 2015). Additionally, given the fact that size of mega projects is also measured numerically, it will be prudent to adopt a quantitative study so as to make it easier to analyse numeric data. Due the above justifications and type of philosophy used, the researcher decided to use quantitative as opposed to qualitative methodology.