Defining Research Objectives and Identifying Variables

As explained in the Methodological Pluralism section of this chapter, in the complementarity approach, information gathered from the qualitative study provides

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131 a foundation for the quantitative inquiry. The quantitative analysis, also, complements the outcomes of the qualitative study. During the course of qualitative data analysis (QDA), many topics were identified that needed more investigation. In other words, to clarify certain situations, there was a need for numerical data to provide a broader insight in to the research.

The first step in conducting a quantitative survey is to design a questionnaire. This is an important task because it affects factors, such as response rate, validity and reliability of the collected data (Saunders, Lewis, & Thornhill, 2009). To design the questionnaire, the variables should be identified to be measured. A variable is ―an attribute or characteristic of the phenomenon under study that can be observed and measured‖ (Collis & Hussey, 2009, p. 188). The variables should be selected in such a way that address the research questions. It is worthwhile taking a look at the three research questions again: construction experts experienced in their projects?

Considering the research questions, it can be explained that the variables should measure three subjects: (a) the logistics awareness of respondents, (b) the process of construction logistics, and (c) the importance of logistical problems and challenges.

These three subjects should be broken down to more specific topics. This is already done in the qualitative inquiry. The QDA provides the research with detailed categories and subcategories that can be used as variables for designing the questionnaire (Figure 42).

At the beginning of the questionnaire design process, 30 topics were selected from the results of the QDA to be investigated quantitatively. The selected topics should meet two criteria: (1) to have close relationship with the research questions and the three factors indicated above and (2) to add new insight to the outcomes of the QDA.

The list of topics that were selected initially is provided in the following:

132 Logistics Translation in Farsi, Critical Materials, Estimation Methods, Material Costs, Warehousing Duration, Material Re-handling, Logistics Failure, and Environmental Conservation were taken out from the list. Also, Procurement and Contracts merged together to form a more generic topic. Finally, 21 topics were categorised under nine sections to be put in the questionnaire (Appendix four). One section was also dedicated to demographic questions. The categories, topics and variables are summarised in Appendix five.

The type of variable influences the wording of the questions. Generally, there are three types of variables (Saunders, Lewis, & Thornhill, 2009):

1. Opinion: to assess how respondents feel and think about a subject and whether what they believe is true or false.

2. Behaviour: to assess what people did in the past, do in the present and will do in the future.

3. Attribute: to assess characteristics of respondents, including personal and demographic information.

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133 Most variables in the questionnaire are of the behaviour type because the research aim is to understand the current practice of construction logistics management in the Iranian projects (Appendix five). In fact, the focus is on what people do in the projects. However, there are opinion questions to find out what participants think about issues such as waste and logistical risks. A few attribute questions were also asked at the beginning of the questionnaire to make clear the characteristics of the sample. Detailed description about each question will be provided in the next section.

After determining variables, a strategy should be set to accurately measure the variables. Measurement allows the researcher to detect and explain small differences between respondents in terms of the characteristic in question (Bryman & Bell, 2003). There are four levels of measurement (Collis & Hussey, 2009):

1. Nominal: It classifies data into qualitative categories that are usually mutually exclusive. These categories cannot be ranked.

2. Ordinal: It categorises data into levels that can be ranked. Yet, there is no meaningful difference between two levels of measurement.

3. Interval: It is a quantitative measure in which data can be ranked with questions, their wording, and the order in which they are presented (Collis & Hussey, 2009). Closed questions are more appropriate for self-administered questionnaires.

The questionnaire consisted of 86 closed questions that provided a number of answers for respondents to choose from. In some cases, there were dedicated spaces that could be used by the respondents to express their views about a particular subject. Saunders et al. (2009) highlighted six types of closed questions as: list, category, ranking, rating, quantity, and matrix. The type of each question depends on

134 the nature and purpose of that question. The types that are used in the questionnaire are list, category, and rating, defined in the following by Saunders et al. (2009):

 List questions provide the respondents with a list of responses to choose from. The respondents can consider all possible responses and choose one or more options.

 Category questions are designed in a way that the respondents can choose only one response. This type is useful when behaviour or attribute variables need to be measured.

 Rating questions records responses by using a rating device. Two famous types of rating questions are Likert and scale.

The types of the questions are shown in Appendix five. As is clear, there is a balance between the numbers of category and rating questions in the questionnaire.

In terms of wording, the researcher attempted to avoid the use of jargon to minimise the ambiguity of the questions. In the whole process of question design, the target audience were considered as people who are familiar with the construction industry and have a medium level of intelligence and knowledge. However, to avoid any confusion, clear instructions were provided for some questions. Also, wherever it was appropriate, technical terms that needed clarification were defined. It should be explained that the questionnaire was originally designed in Farsi (Appendix six) to enable respondents to answer questions in their native language. The original questionnaire was translated to English later for reference only (Appendix four).

After designing questions, the questionnaire layout should be set. Considering the advice of Burns and Burns (2008), particular attention should be paid to the visual appearance of the questionnaire, because in a self administrated survey, the respondents see the actual questionnaire. It was attempted to keep the structure of the questionnaire simple and easy to complete. Normally, a questionnaire structure has four parts (Burns & Burns, 2008):

1. Introduction

2. Demographic questions 3. Body of the study

4. Expression of thanks and contact information of the researcher

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135 This research attempted to adopt the above model but owing to cultural reasons, section one and four were merged together. Hence, the questionnaire started with an introduction and expression of thanks followed by demographic and main questions.

The questions were set in a logical order in the questionnaire moving from general to specific topics. This method is usually known as funnelling (Collis & Hussey, 2009).

The questionnaire started with demographic information and this was followed by questions about logistics and supply chain knowledge. Then, based on the sequence of logistic tasks, the associated questions were put in order: scheduling, supply, transportation, and warehousing. At the end, questions were focused on more specific topics of logistics organisation, waste management and logistics risks.

Answer choices are located under the questions with plenty of white spaces between the choices and the next question (Appendix six). These spaces can be used by the respondents to add any other comment they have. In some questions, the variables were tabulated to make the answering process easier. All tables had a striped pattern to minimise the risk of confusion and mistake.