The primary research instrument in this investigation is the questionnaire. For this research, the questionnaire was selected deliberately due to the number of
respondents’ data ought to be collected from and the intrinsic features of the research described in preceding sections. Moreover, the questionnaire is known for allowing the collection of quantifiable data that can be easily analysed. This investigation
acknowledges that questionnaires may be misleading if the formulation of the questions is not free of error. Further, questionnaires remain susceptible to bias on the part of the research especially in the formulation of questions and administration of the instrument.
Therefore, the data collected from the questionnaire is analysed for consistency, common bias and reliability to ensure that ultimately only meaningful inferences are made. In addition, the questions are simplified and clarified to ensure respondents
176 understand the context of the questions and avoid misinterpretation that could affect the quality of this research.
The data required to answer questions related to the demography of the
individuals, their personality types, how they approach different decision scenarios and the level of knowledge they had on the existence of cognitive bias. Demographic
variables gathered in the questionnaire were gender, culture, company size, job position, and work experience. Other four main variables are defined from the questionnaire data for further statistical tests. “Cost decision making in mega projects” coded as DM1 in this study is the first main variable; it attempts to inquire whether overall decision making has an influence on project cost. “Risk decision-making” coded as RM in this study is aimed at measuring whether risk decision making is a key component of mega projects. In essence, the variable aims to quantify whether mega projects are inherently characterized by risk decision making. The third variable is linked to cognitive bias, thus, 12 personality traits linked to different individuals are investigated alongside decision making to determine if there is a significant relationship and if there is, what does it mean? In specific, the influence of the identified personality traits linked to cognitive biases is checked against cost overrun and overall decision making. The final variable is related to optimism and decision making. Evidently, over optimism is closely linked to cognitive biases, thus, its influence on overall decision making in mega
projects in investigated.
5.7.1 Types of Questions
According to research, the questions posed from a questionnaire can be
developed from existing questionnaires especially from similar studies or adopting them directly (Dillman, 2017; Fink, 2003). The on-going investigation incorporates this
177 strategy to ensure the questions are consistent with broad research in the field. Even though, the questions are based on existing studies they are adjusted to fit the role of the investigation. According to Fink(2003) scholars who develop their own research
questions achieve a level of flexibility that is useful in contextualizing and
conceptualizing the research constructs under investigation. The questionnaire adopted for the on-going study is primarily composed of closed questions. According to
Dillman(2017) close ended questions are difficult to interpret as they restrict
respondents’ responses to a specific set of outcomes. In this study, they are based on the 5-point Likert scale. In the end, the respondents are expected to give ratings based on the questions. Even with the claim that closed questions are difficult to interpret, their analysis is quite straightforward as soon as they are coded. On the other hand, open ended questions giving participants freedom to explain their responses are easy to interpret but difficult to analyses as a lot of information is usually collected from them.
The design of the questions also takes into account recommendations by scholars to organize them consistently for different ratings throughout the questionnaire to avoid confusion. Questions collecting demographic data are also closed to help frame the research to a specific group of individuals (project managers), the range of their work experience, the number of employees in their organizations, gender and cultural background.
5.7.2 Measurements
Different types of data exist for quantitative and qualitative studies. Quantitative research is usually founded on two basic data types; (1) categorical data and (2)
numerical data. The latter is associated with actual counting and the number of
responses or participants supporting a specific construct while the latter is based on the
178 classifying responses into sets with innate similar features (Blumberg, et al., 2008).
Categorical data can further be classified in nominal data and ordinal data. Nominal data is related to the incidence of responses to questions on a specific construct while ordinal data is related to the rank or order of priority of strength of the responses (Saunders, et al., 2016). On the other hand, numerical data into interval and ratio data based on whether the comparative difference between the data can be computed (Blumberg, et al., 2008; Saunders, et al., 2016). The differences can be computed for ratio data and not for interval data. The subsets of the interval and ratio data are continuous and discrete data which is related to whether a construct can take a specific value within a range (Blumberg, et al., 2008). Discrete data takes specific values within a range while continuous data does not (Blumberg, et al., 2008).
5.7.3 General Structure
The questionnaire offered to respondents in current investigation can be divided into two distinct sections. The general information section collects data on the role of the participant within an organization, their work experience, the size of the firm they work in with regard to the number of employees, the gender they identify with and their cultural background (race or ethnicity). Evidently, three spheres are examined from the general information, the demographic features of the participants, their professions and the characteristics of organization they work for.
5.7.4 Specifics
The specific part of the questionnaire comprises of questions that are crucial to meeting the objectives of the on-going investigation. The section is divided into five intuitive sections based on the constructs under investigation. The table below effectively describes the four areas of focus.
179
Construct Description
Decision-making in mega projects Participants are tasked with a five-point Likert scale assessing how they perceive the likelihood of incorporating different factors decision-making in Megaprojects.
Risk and decision-making in mega projects
Participants are tasked with a five-point Likert scale assessing how they perceive the likelihood of incorporating different factors into risk decision-making in Megaprojects.
Personality traits and cost decisions Participants are asked to respond to a five-point Likert scale on the level of agreement with statements about the interplay between personality traits and cost decisions.
Reasons for cost overrun in mega projects
This section requires participants to rate researched justifications of cost overrun in mega projects. Five factors are identified and ranked with percentages.
5.7.5 Questionnaire data coding and validation.
The data collected from the specific part of the questionnaire is coded using different weights as is common for Likert scale questions. Ultimately, the data is fed into SPPS for analysis. The coding associated with Likert responses is commonly used
180 and is known to be simple and straightforward. Even so, there are numerous challenges as important information may be missed by restricting the responses of participants to a given set. Aside from presenting the questionnaire to a pilot group of project
management students to test for validity, the questionnaire is also examined in the context of similar research studies and statistical measures such as the Cronbach’s alpha.