Case Study Research

Based on the research aims and objectives, the findings from the literature review, the collaboration with the sponsor, and the philosophical worldview, it was decided that the best way to achieve the research aim was through the use of case studies.

Yin (2014) has a twofold definition for a case study:

“A case study is an empirical enquiry that investigates a contemporary phenomenon (the “case”) in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident

A case study inquiry copes with the technically distinctive situation where there will be many more variables of interest than data points, and as one result relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result benefits from the prior development of theoretical propositions to guide data collection and analysis.”

Case studies are in-depth studies that typically utilise data from multiple methods and sources [Yin, 2014; Proverbs and Gameson, 2008]. Multiple sources of evidence allow triangulation to be used as a data analysis method, where data and findings from different sources converge to reach the same conclusion [Yin, 2014; Proverbs and Gameson, 2008, Fellows and Liu, 2008]. The benefit of triangulation is that convergent findings from multiple sources of evidence lead to greater confidence in the findings, because the data from one source are corroborated and supported by the data from other sources.

The use of case studies as an approach to inquiry is very well aligned with the postpositivistic paradigm, due to the preference for natural settings, the minimal control over parameters, and for the collection of data from multiple sources. The reasons for choosing to conduct case study research were also motivated by the aims and context of the research problem. Yin (2014) describes the conditions under which various research methods might

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be adopted, advising that the case study method is best suited for research questions that seek to answer “how” and “why” questions for contemporary problems for which there is no control over events. This research concerns the energy and thermal performance of existing buildings, and therefore concerns contemporary events. There is also no desire to control the factors which influence energy and thermal performance within buildings, because to control them would create an unnatural situation and the data would not be objective or representative of real building use or real performance. The research also seeks to answer “how” and “why” questions in addition to “what”, “where”, “how many”, “how much” questions. The aim is to determine not only how much energy is used, but also why that much energy is used, not only if overheating occurs, but also why it may or may not occur, and not only how the fabric performs well, but also why it performs as such. The aim is not simply to quantify energy and thermal performance, but to delve deeper into the causes, in order to make suggestions to the manufacturer on how to improve their product.

Another reason why case study research is so suited to the research aims and objectives is the complexity of the problem. There are hundreds of interacting variables that influence energy use and thermal performance in buildings, which are context dependent: the same building in another location would perform differently, a different building in the same location would perform differently, and the same building with different occupants would perform differently. The energy and thermal performance of a building is a function of the fabric, the systems, the location, the weather, the occupants, and the interaction between these factors; to change any of these would change the performance in some way. It is not straightforward to separate these factors and how they interact, to rank them, and to focus on only one issue in isolation from the rest. Nor were there any reliable data or evidence that there should be a focus on a particular aspect of performance to the exclusion of others. Therefore, it was deemed best to investigate the whole system.

Yin (2014) explains that case study research:

"benefits from the prior development of theoretical propositions to guide data collection and analysis.”

The findings from the literature allowed the creation of theoretical propositions that helped guide the inquiry. For instance, the literature shows that there is potential for increased quality and repeatability in products manufactured offsite compared to on site, and therefore it could be hypothesised that this increased quality could result in improved fabric performance because there are less fabric defects. The literature also shows that the risk of overheating is greater in thermally lightweight buildings, particularly in cities and especially in London; and given that buildings are thermally lightweight and often located in cities, it

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could be hypothesised that they overheat at some point during the year. However, there was no clear evidence specific to buildings to formulate hypotheses, only theoretical propositions (which were used to help formulate the research questions outlined in Chapter 1.5).

While the research was to be conducted in natural settings, the approach is experimental, where aim is for researcher to be separate from the subject, to be impartial, objective and to not directly influence the results. The research design used was based on the experimental approach, it was approximately linear and separated into distinct stages (Figure 3.1).

Figure 3.1: The research process - Linear experimental

3.3 Data

Case study research requires in-depth knowledge about each case, therefore it typically involves the collection of data from multiple methods.

The methods chosen were based on the data required to answer the aims and objectives. Many parameters can give insights into building performance, but it was only practical to collect data from a limited number of parameters. The data chosen for collection and the

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reasons for their selection are summarised in Table 3.1. This data will give insight into the energy and thermal performance of the buildings in use, and the design, manufacture and construction of light-gauge steel modular buildings. With this dataset, the focus is on technical changes that could be made to the design, manufacture and construction of the modular buildings to improve energy and thermal performance in use.

Table 3.1: Data selected for collection and the reasons for selection

Data collected Reason for collection

Internal temperature  To understand the thermal behaviour of a building

 To calculate the occurrence of overheating

Relative humidity  Primarily collected because the sensors measured temperature and

humidity

 To understand the internal environment of a building: too dry or too

humid are both unwanted

External temperature  To understand the thermal behaviour of a building

 To calculate comfort temperatures for overheating analyses

Electricity consumption  To understand how occupants use buildings

 To understand electric space heating use

 To calculate internal gains within a building

Window opening  To understand how occupant use buildings, specifically occupant

controlled natural ventilation

 To identify the occurrence of simultaneous space heating and

window opening

Fabric air leakage rate  To understand the thermal behaviour of the building

 To identify faulty design, materials or workmanship

Ventilation system flow rates

 To quantify ventilation rates

 To identify faulty design, materials or workmanship

Infrared thermographic images

 To investigate thermal performance of the facade

 To identify faulty design, materials or workmanship

construction details (e.g. AutoCAD drawings, design and construction details, compliance test results

photos, observations, site measurements,

information from informal conversations)

 To understand design, manufacture and construction of the buildings

 To quantify thermal performance of the fabric design

 To identify faults with design, manufacture and construction

 To understand how buildings are used by occupants and operated by

managers

 To understand design constraints

 To garner any additional information that may be pertinent to the

project

Weather conditions  To understand the impact that weather has on the thermal behaviour

of the buildings

 To create an EnergyPlus weather file for simulations (not presented

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