Secondary Research Methods in the Built Environment

Emmanuel Manu, Julius Akotia, Emmanuel Manu, Julius Akotia

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000351507
• Edition: 1
• Topic: Architecture
• Subtopic: Architecture General

The use of secondary data for research can offer benefits, particularly when limited resources are available for conducting research using primary methods. Researchers and students at both undergraduate and postgraduate levels, including their academic instructors, are increasingly recognising the immense opportunities in applying secondary research methods in built environment research. Advances in technology has also led to vast amounts of existing datasets that can be utilized for secondary research. This textbook provides a systematic guide on how to apply secondary research methods in the built environment, including their various underpinning methodologies. It provides guidance on the secondary research process, benefits, and drawbacks of applying secondary research methods, how to source for secondary data, ethical considerations, and the various secondary research methods that can be applied in built environment research. The book incorporates chapters dealing with qualitative secondary analysis, systematic literature reviews, legal analysis, bibliometric and scientometric analysis, literature-based discovery, and meta-analysis.

Secondary Research Methods in the Built Environment is an ideal research book for undergraduate and postgraduate students in construction management, construction project management, quantity surveying, construction law and dispute resolution, real estate and property management, building services engineering, architecture, and civil engineering.

1 Introduction to secondary research methods in the built environment

Emmanuel Manu and Julius Akotia

Introduction

Secondary research methods involve the analysis of data that already exists or has already been created. This is in contrast to primary research, which is based on principles of the scientific method (Driscoll, 2011) where researchers learn more about the world by collecting measurable data first-hand. In recent years, the use of secondary research methods has grown exponentially across various disciplines, including in the built environment. This growth has been attributed to technological advances (Johnston, 2014) and the vast amounts of secondary data that is now available and easily accessible for research as a result. Researchers and students at both undergraduate and postgraduate levels across various built environment disciplines, including their academic instructors, are increasingly recognising and exploiting the immense opportunities in conducting secondary research. However, for the inexperienced secondary researcher, some of the issues with which they are confronted include clarifications to questions such as: what exactly is secondary research? What types of secondary research methods are available, and how can these methods be applied robustly in built environment research? This is hardly surprising as issues relating to secondary research can be confusing for experienced researchers who are unfamiliar with secondary research methods, let alone the novice researcher. This situation has been complicated by the sometimes differing views and varying terminologies that are used to describe different secondary research methods. Terminologies, such as secondary data analysis, qualitative secondary analysis (QSA), qualitative secondary research, meta-analysis, and meta-synthesis, abound in the literature without clarity on how all these fit within the domain of secondary research methods.

Therefore, in this introductory chapter, the aim is to create a context for the rest of this book by evaluating what constitutes secondary research, the secondary research process, secondary research designs and the benefits and drawbacks of applying secondary research methods in built environment research. To conclude, an overview of the various chapters that are included in this book has been presented.

What is secondary research?

Secondary research involves the use of data that already exists rather than what would be obtained from first-hand sources, using primary methods such as questionnaires, interviews, focus groups, observations, and the like. Johnston (2014, p. 619) who used the term “secondary data analysis” defined this as “the analysis of data that [were] collected by someone else for another primary purpose”.

There are subtle differences in perspectives as to what constitutes secondary research. In some discussions the re-analysis of data from previous primary research is emphasised, suggesting that all forms of secondary research will utilise data that have emerged from a primary research study, which have been analysed and published in academic literature, but are then being re-analysed. However, in the definition offered by Johnston (2014), the term “analysis” is used rather than “re-analysis”, an indication perhaps that the data for secondary analysis might be in its raw state but would still have come into existence for a different purpose. Whilst some secondary methods are focused on the re-analysis of published findings from primary research (e.g. systematic literature reviews (SLRs) and meta-analysis), confining secondary research to only the use of such methods is a narrow perspective. This is because there are other established secondary research methods such as the QSA that involve the re-use of archived, original (pre-existing) qualitative data (e.g. interview transcripts) to answer new research questions. The raw qualitative data would have been archived in their original, pre-analysed, and unpublished form and, hence, their re-use as secondary data is a case of re-purposing the original data. With this practice, the existing unanalysed and archived, raw data are re-used as opposed to re-analysing the published results from a previous analysis of the same data.

Johnston (2014) also emphasised in his definition that the existing data should have been collected by someone else rather than the secondary researcher. This relationship between the secondary researcher and how the existing data came about has also featured in other discussions on secondary research. Church (2001), for instance, emphasised that in secondary data analysis, individuals that were not involved in data collection are responsible for analysing the data, unlike in primary research where individuals that collect the data are also responsible for analysing it. This suggests that secondary research will always involve the use of data that have been collected by someone else, which is mostly the case. However, it is important to clarify also that secondary research can involve the re-use of existing raw data that had previously been collected by the same individuals, although for a different purpose than their re-use to explore new research questions (Ruggiano and Perry, 2019).

From a much broader perspective, secondary research can also extend beyond the re-use or re-analysis of data from previous primary research, although the purpose of the data’s existence should be different from the purpose of their present use in research. Secondary research can encompass the analysis of existing datasets that might not have come about from primary research (Doolan et al., 2017). Doolan et al. (2017), whose work was done from a medical research perspective, emphasised that existing datasets for secondary research can also be derived from other sources such as hospital charts, academic course records, quality improvement records, news media, or social media. What is clear from the various perspectives is that secondary research: (1) involves the use of pre-existing datasets, and (2) these datasets should have come into existence for purposes that are different from the purpose of their use in the secondary research. This view is consistent with the meaning of the term “secondary” in secondary research, which refers to the use of pre-existing data for secondary analysis. The term indicates only that the data are being used for research purposes beyond the specific need that prompted their original gathering or its generation (Stewart and Kamins, 1993).

The term “research” refers to the application of a systematic approach to study and generate new facts and conclusions about a subject of interest. Put together, a broader definition of “secondary research” is the study of specific problems to generate new facts and conclusions through analysis of pre-existing data or information that was originally created for a different reason or purpose.

It is from this broader perspective of secondary research that the rest of this book has been compiled. Based on this broader perspective, it should be emphasised once again that the pre-existing data or information may or may not have come about from primary research but should still meet the requirement of existing for a different purpose than their use in secondary research. The systematic approach that should be applied when conducting secondary research requires that a clear, logical, transparent, and verifiable process is followed.

Secondary research process

Despite the increase in the use of secondary research methods, there is still limited guidance on what this process should entail (Doolan et al., 2017), and practical case examples that outline the process and techniques required to carry out secondary research effectively are lacking, particularly within the context of the built environment. However, it should be clarified that one of the main features that differentiates the secondary research process from the primary research process relates to data collection and analysis as shown in Table 1.1.

Table 1.1 Comparison of secondary data and primary data research processes

Secondary research	Primary research
Establish gaps in the research and formulate research questions using existing literature	Establish gaps in the research and formulate research questions using existing literature
Undertake a detailed literature review	Undertake a detailed literature review
Identify, select, and evaluate the existing datasets	Develop data collection instruments and protocol and collect data
Undertake secondary data analysis	Undertake primary data analysis
Discuss, interpret, and disseminate findings from the research	Discuss, interpret, and disseminate findings from the research

Source: Adapted from Doolan et al. (2017) and Johnston (2014).

The steps involved in the secondary research process are discussed briefly below.

Establish gaps in the research and formulate research questions

Just like with primary research, it is important that secondary research commences with a literature review to establish the research gaps, and research question(s) or hypotheses. Clearly defined research question(s) or hypotheses will be crucial in establishing whether the study will fit well with any existing dataset (Smith, 2008).

Undertake literature review

At this stage of the secondary research process, literature will need to be reviewed to examine the current and past thoughts and issues in the area of interest (Johnson, 2014). This is still the case even when the secondary method to be used involves the re-analysis of published academic literature as secondary data e.g. a systematic literature review.

Identify, select, and evaluate the existing datasets

It is important to ascertain whether the existing dataset can address the research question of the secondary study (Long-Sutehall et al., 2010; Johnson, 2014). If the datasets are from previous primary research, it is essential that the purpose for which they were collected originally – the data collection techniques and instruments used and the participants from which the data were collected – are all established as part of the evaluation (Smith, 2008).

Undertake secondary data analysis and disseminate findings

Data analysis forms an integral aspect of any research methodology. It is essential that the analysis and the interpretation of the findings are undertaken in the same way as the methods used for the primary data research (Long-Sutehall et al., 2010).

Secondary research designs

Just as in primary research, secondary research designs can be either quantitative, qualitative, or a mixture of both strategies of inquiry (qualitative and quantitative) as shown in Figure 1.1. Qualitative secondary research designs can be based on either the re-analysis of published results or the analysis of existing qualitative datasets. Largan and Morris (2019, p. 14) defined qualitative secondary research as “a systematic approach to the use of existing data to provide ways of understanding that may be additional to or different from the data’s original purpose”. There are various qualitative, secondary research methods. Those that are based on the re-analysis of published academic literature include SLRs or meta-synthesis, state-of-the-art reviews and scoping reviews. SLRs have been discussed in detail in Chapter 5, Chapter 6, Chapter 7 of this book. Qualitative secondary research can also be based on designs that involve the analysis of existing raw qualitative datasets rather than the published results from a previous analysis. A typical example of such a design is the QSA, which involves the use of pre-existing qualitative data from primary research to develop new social scientific or methodological understandings (Heaton, 2008; Irwin, 2013). According to Johnston (2014), using QSA contributes to scientific knowledge by offering alternative theoretical or conceptual perspectives on previously collected and archived qualitative data. QSA has been discussed in detail in Chapter 4 of this book.

Figure 1.1 Secondary research designs.

Source: Original.

There are other qualitative designs like legal research that arguably straddle between the primary and secondary research domain, depending on whether the sources of data used for the analysis are regarded as primary or secondary sources of the law. For example, the analysis of legal trends and principles using secondary sources of law, such as law reports, legal commentaries, and other literature about law, will constitute a form of secondary qualitative research. The secondary dimension of legal research, and more specifically doctrinal legal research, has been discussed in detail in Chapter 8 of this book.

Similarly, on the quantitative secondary research side, designs can involve the re-analysis of published academic literature or the analysis of pre-existing quantitative datasets. A typical example of a quantitative secondary research design that is based on published results is quantitative secondary analysis, which is a quantitative form of systematic review that is commonly referred to as meta-analysis research. This is a very well-established secondary research design in which statistical approaches are used to combine quantitative research findings from multiple empirical studies to increase the analytical power owing to the combined effect of sample sizes from the various studies. Church (2001) described meta-analysis as the quantitative combination of statistical information from multiple studies on a given phenomenon. Meta-analysis has been applied in Chapter 15 of this book.

Another secondary design that is more quantitative in nature and which is growing in popularity in the built environment is bibliometric research. Bibliometric researc...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• List of Figures
• List of tables
• List of boxes
• List of contributors
• Preface
• 1 Introduction to secondary research methods in the built environment
• 2 Identifying and sourcing data for secondary research
• 3 Ethical considerations in the use of secondary data for built environment research
• 4 Qualitative secondary analysis (QSA) as a research methodology
• 5 Evaluation of systematic literature reviews in built environment research: what are we doing and how can we improve?
• 6 When does published literature constitute data for secondary research and how should the data be analysed?
• 7 A systematic literature review evaluating sustainable energy growth in Qatar using the PICO model
• 8 Understanding legal research in the built environment
• 9 Applying science mapping in built environment research
• 10 Bibliometric analysis for reviewing published studies in the built environment
• 11 Scientometric review and analysis: a case example of smart buildings and smart cities
• 12 Analysis of BIM-FM integration using a science mapping approach
• 13 Trends in recycled concrete research: a bibliometric analysis
• 14 Using literature-based discovery in built environment research
• 15 Combining study findings by using multiple literature review techniques and meta-analysis: a mixed-methods approach
• 16 Analysing secondary data to understand the socio-technical complexities of construction-design decision-making
• Appendix A: Chapter 14: computation of cosine similarity for shared terms
• Appendix B: Chapter 14: computation of cosine similarity for all terms
• Index