Qualitative And Quantitative Method Of Research

Nature of research in the field of built environment

Quantitative and qualitative research in the built environment: application of ``mixed'' research approach

A discipline or profession is established by developing a body of knowledge which is unique ± that body of knowledge is produced through research. Construction and the built environment (BE) draw on a wide variety of established subjects/disciplines, including natural sciences, social sciences, engineering and management. These are then applied to the particular BE context and requirements (Fellows and Liu, 1997). Only by the use of appropriate methodologies and methods of research applied with rigour can the body of knowledge for BE be established and advanced with confidence. The approach adopted in this paper is to outline the process of research in BE, to undertake initial discussion on epistemological issues, to discuss types of research methods available within the field and appropriate data analysis techniques available. Conclusions are then drawn from this body of evidence and discussion.

Dilanthi Amaratunga David Baldry Marjan Sarshar and Rita Newton The authors Dilanthi Amaratunga is a Research Fellow, David Baldry is a Lecturer, Marjan Sarshar is a Director, Construct IT and Rita Newton is a Lecturer, all at the School of Construction and Property Management, The University of Salford, Salford, UK. Keywords Research, Methodology, Qualitative techniques, Quantitative techniques Abstract

Research and research methods

Built environment research consists of cognitive and affective, as well as behavioural, components. Existing built environment research utilises either strong qualitative or, more often, strong quantitative methodologies. Aims to discuss some of the philosophical issues that would be considered when undertaking academic research into the built environment. Considers the available research options or paradigms and suggests ways in which a researcher can make an informed and sensible decision as to how to proceed. The main dimensions of the debate about the relative characteristics and merits of quantitative and qualitative methodology are outlined, developing the argument that the use of a single methodology often fails to explore all of these components. The use of a mixed methods approach is suggested to counteract this weakness and to enhance research into the built environment.

Although research is important in both business and academic activities, there is no consensus in the literature on how it should be defined. One reason for this is that research means different things to different people. However, from the many different definitions offered there appears to be agreement that: . research is a process of enquiry and investigation; . it is systematic and methodical; and . research increases knowledge. Research studies in BE have been criticised for their anecdotal approach when interpreting real world phenomena. In this sense, it is argued that the clear definition of a research strategy is a fundamental and necessary requirement for a sound empirical study in such a field. BE research has reached a stage that demands the validation of its heuristic principles within different ``real world''

Electronic access The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0043-8022.htm

This paper was initially presented at the 1st International Postgraduate Conference organised by the School of Construction and Property Management at the University of Salford, March 2001.

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considered when choosing an appropriate research methodology, with the topic to be researched and the specific research question being primary drivers (Remenyi et al., 1998). The starting point in research into BE is to focus clearly on the fact that the ultimate purpose is to add something of value to the body of accumulated BE knowledge. This means that an unanswered question or unsolved problem will be identified and studied and that the researcher will attempt to produce a suitable answer to the question or a solution to the problem. Therefore, a discussion of philosophy is essential before embarking on a research project.

situations in order to refine and integrate them. Buckley et al. (1975) suggest that an operational definition of research requires the satisfaction of the conditions that: . it be an orderly investigation of a defined problem; . appropriate scientific methods be used; . adequate and representative evidence be gathered; . logical reasoning, uncoloured by bias, be employed in drawing conclusions on the basis of the evidence; . the researcher be able to demonstrate or prove the validity or reasonableness of their conclusions; . the cumulative results of research in a given area yield general principles or laws that may be applied with confidence under similar conditions in the future.

Schools of thought Philosophers of science and methodologists have been engaged in a long-standing epistemological debate about how best to conduct research. This debate has centred on the relative value of two fundamentally different and competing schools of thought or inquiry paradigms. Logical positivism uses quantitative and experimental methods to test hypothetical-deductive generalisations. Among the major implications of this approach is the need for independence of the observer from the subject being observed, and the need to formulate hypotheses for subsequent verification. Positivism searches for causal explanations and fundamental laws, and generally reduces the whole to simplest possible elements in order to facilitate analysis (Easterby-Smith, 1991; Remenyi et al., 1998). Phenomenological (interpretive science) inquiry uses qualitative and naturalistic approaches to inductively and

Research is conducted in the spirit of inquiry, which relies on facts, experience and data, concepts and constructs, hypotheses and conjectures, and principles and laws. Table I illustrates how together these concepts of research form a symbolic and rational system of inquiry (abstracted from Buckley et al., 1975; cited in Then, 1996). Additionally, they constitute the language of research, enabling precision in the use of words and communication among those concerned. Before suggesting some guidelines for BE research, it is useful to define research methodology and to put the issue of research and its methodologies into perspective. Research methodology refers to the procedural framework within which the research is conducted (Remenyi et al., 1998). There are many factors to be Table I Basic elements of scientific research methodology Laws

Verified hypotheses; used to assert a predictable association among variables; can be empirical or theoretical

Principles

A principle is a law or general truth which provides a guide to thought or action

Hypotheses

Formal propositions which, though untested, are amenable to testing; usually expressed in causal terms

Conjectures

Informal propositions which are not stated in a testable form, nor is a causal relationship known or even necessarily implied

Concepts and constructs

Concepts are inventions of the human mind to provide a means for organising and understanding observations; they perform a number of functions, all of which are designed to form logical and systematic relationships among data

Facts

Something that exists, a phenomenon that is true or generally held to be true

Data

The collection of facts, achieved either through direct observations or through garnering from records; observation is the process by which facts become data

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adhered to prescribed canons of either logical positivism or phenomenology but whether one has made sensible methods decisions, given the purpose of the study, the questions being investigated, and the resources available (Then, 1996). Therefore it is crucial to know about the methodological paradigms debate in order to appreciate why methods decisions can be highly controversial. The paradigm of choices recognises that different methods are appropriate for different situations. Table IV provides a pragmatic view of a summary of some of the strengths and weaknesses of the two research paradigms (adapted from Easterby-Smith, 1991).

holistically understand human experience in context-specific settings. This approach tries to understand and explain a phenomenon, rather than search for external causes or fundamental laws (Easterby-Smith, 1991; Remenyi et al., 1998). This picture is set out in Table II (Silverman, 1998). The interpretive science/phenomenological approach also rejects the positivists' beliefs which centre on atomism ± that the objects of experience are atomic, independent events. This concept is central to the notion of deducticism, which claims that generalisations can be made from a finite set of events in the past to predict future events. The use of regularities to ground generalisations and causations is rejected by phenomenologists. Causation does not refer to regularity between separate things or events but about what an object is likely to and what it can do, and only derivatively what it will do in any particular situation. The goal of BE research under the phenomenological doctrine is therefore the development of theories through explanatory methods rather than through the creation of generalisations. Easterby-Smith (1991) summarised the main differences between the positivist and the phenomenological viewpoints similar to Table III. In research design, therefore, the issue then becomes not whether one has uniformly

Quantitative and qualitative methodology as research traditions Research may be categorised into two distinct types: qualitative and quantitative, according to the above schools of thought. The former concentrates on words and observations to express reality and attempts to describe people in natural situations. In contrast, the quantitative approach grows out of a strong academic tradition that places considerable trust in numbers that represent opinions or concepts. Over the past 15 years, the debate over the relative virtues of quantitative and qualitative methodologies has gained considerable impetus. While the exact constitution of the two methodologies varies somewhat from author to author or is defined with varying degrees of specificity, there is substantial agreement about the fundamental antinomies and their practical implications for the conduct of research.

Table II Two schools of science Approach

Concepts

Methods

Positivism

Social structure Social facts

Quantitative Hypothesis testing

Interpretive science (phenomenological)

Social construction Meanings

Qualitative Hypothesis generation

Table III Key features of positivist and realism paradigm and the chosen mixed approach Theme

Positivist paradigm

Realism paradigm

Basic beliefs

The world is external and objective Observer is independent Science is value-free

The world is socially constructed and subjective Observer is part of what is observed Science is driven by human interests

Researcher should

Focus on facts Look for causality and fundamental laws Reduce phenomena to simplest elements Formulate hypotheses and test them

Focus on meanings Try to understand what is happening Look at the totality of each situation Develop ideas through induction from data

Preferred method in the Operationalising concepts so that they can Using multiple methods to establish different views of the phenomena research be measured Small samples investigated in depth or over Taking large samples time

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Table IV Comparison of strengths and weaknesses Theme

Strengths

Weaknesses

Positivist (quantitative paradigm)

The methods used tend to be rather They can provide wide coverage of the inflexible and artificial range of situations They are not very effective in They can be fast and economical understanding processes or the Where statistics are aggregated from large significance that people attach to actions samples, they may be of considerable They are not very helpful in generating relevance to policy decisions theories Because they focus on what is, or what has been recently, they make it hard for policy makers to infer what changes and actions should take place in the future

Phenomenological (qualitative paradigm)

Data-gathering methods seen more as Data collection can be tedious and require natural than artificial more resources Ability to look at change processes over Analysis and interpretation of data may be time more difficult Ability to understand people's meaning Harder to control the pace, progress and Ability to adjust to new issues and ideas as end-points of research process they emerge Policy makers may give low credibility to Contribute to theory generation results from qualitative approach

Choice of research strategy

Perhaps as a response to the dominance of quantitative research, some qualitative researchers such as King (1994) seem to assume a fixed preference or predefined evaluation of what is good and bad research methodology. Such normative assumptions have, of course, been around for many years and are illustrated in Table V.

From the discussion under schools of thought, it is apparent that both qualitative and quantitative methods involve differing strengths and weaknesses. McGrath (1982) in his study of research choices makes it clear that there are no ideal solutions, only a series of compromises. Patton (1990) expresses the same view: ``research, like diplomacy, is the art of the possible''. This quote by Patton is perhaps a very poignant guide to any researcher contemplating the most appropriate avenue of successfully completing a sizable piece of research study. According to Yin (1994), research strategy should be chosen as a function of the research situation. Each research strategy has its own specific approach to collect and analyse empirical data, and therefore each strategy has its own advantages and disadvantages. Although each strategy has its own characteristics, there are overlapping areas, which bring complexity to the process of strategy selection. In order to avoid gross misfits between the desired outcome and the chosen strategy, Yin (1994) stresses that the type of question posed; the control over actual behavioural elements; and the degree of focus on historical or contemporary events; are the conditions which should

Table V Claimed features of qualitative and quantitative method Quantitative

Qualitative

Inquiry from the outside Underpinned by a completely different set of epistemological foundations from those in qualitative research Are simply different ways to the same end? Involves the following of various states of the scientific research The results are said to be ``hard generalisable data''

Inquiry from the inside An attempt to take account of differences between people Aimed at flexibility and lack of structure, in order to allow theory and concepts to proceed in tandem The results are said to be, through theoretical generalisation, ``deep, rich and meaningful'' Inductive ± where propositions may develop not only from practice, or literature review, but also from ideas themselves An approach to the study of the social world, which seeks to describe and analyse the culture and behaviour of humans and their groups from the point of view of those being studied

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Qualitative research: meanings or practices

provide the grounds for strategy choice. Table VI depicts the outcome of the intersection between most common research strategies and the three conditions identified above. Galliers (1992) (cited in Remenyi et al., 1998) provides a list of approaches or tactics. Table VII summarises this list according to the general philosophical base underpinning the different research tactics. It is important to note that most research tactics listed in the table can be used, at least to some extent, as either positivistic (quantitative) or phenomenological (qualitative) devices.

Defining and justifying qualitative research It is difficult to find an unambiguous and definitive statement as to what qualitative research in BE actually is. This is primarily due to the fact that topic, theory and methodology are usually closely interrelated in qualitative research. Qualitative research is conducted through an intense and/or prolonged contact with a ``field'' or life situation. These situations are typically ``banal'' or normal, reflective of the everyday life of individuals, groups, societies, and organisations (Miles and Huberman, 1994). In some senses, all data are qualitative; they refer to issues relating to people, objects, and situations (Berg, 1989, cited in Miles and Huberman, 1994). In the BE discipline there are distinct signs of a growth in the application and acceptance of the use of qualitative approaches. What is important about well-collected qualitative data? One major feature is that they focus on naturally occurring, ordinary events in natural settings, so that there is a view on what ``real life'' is like. Another feature of qualitative data is their richness and holism, with strong potential for revealing complexity. Such data provide ``rich

Table VI Research strategies versus characteristics Form of research question

Strategy Experiment Survey

How, why Who, what, where, how many, how much Archival analysis How, why History How, why Case study How, why

Requires control Focuses on over behavioural contemporary events? events? Yes No

Yes Yes

No No No

Yes/No No Yes

Source: Yin (1994)

Table VII Research tactics and philosophical bases Research approaches Action research Case studies Ethnographic Field experiments Focus groups Forecasting research Futures research Game or role playing In-depth surveys Laboratory experiments Large-scale surveys Participant observer Scenario research Simulation and stochastic modelling

Positivistic (quantitative) Have scope to be either Have scope to be either Strictly positivistic with some room for interpretation Have scope to be either

Phenomenological (qualitative) Strictly interpretive Have scope to be either Strictly interpretivist Have scope to be either Mostly interpretivist

Have scope to be either Strictly interpretivist Mostly interpretivist

Strictly positivistic with some room for interpretation Strictly positivistic with some room for interpretation Strictly interpretivist Mostly interpretivist Strictly positivistic with some room for interpretation

Source: Galliers (1992), cited in Remenyi et al. (1998)

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descriptions'' that are vivid, nested in a real life context, and have a ring of truth. Furthermore, the fact that such qualitative data are typically collected over a sustained period makes it powerful for studying any process. Also the inherent flexibility of qualitative studies (data collection times and methods can be varied as a study proceeds) gives further confidence that what has been going on is really understood. Qualitative data, with their emphasis on people's ``lived experience'', are fundamentally well suited for locating the meanings people place on the events, processes and structures of their lives: their ``perceptions, assumptions, prejudgments, presuppositions'' (Van Manen, 1977), and for connecting these meanings to the social world around them. There are three other claims for the power of qualitative data. They have often been advocated as the best strategy for discovery, exploring a new area, developing hypotheses. In addition their strong potential for testing hypotheses is underlined on seeing whether specific predictions hold up. Further, qualitative data are useful when one needs to supplement, validate, explain, illuminate, or reinterpret quantitative data gathered from the same setting. Richards and Richards (1994) outline four major perceived constraints which have traditionally militated against the use of qualitative approaches in practice despite the excitement about their potential in theory. These are: (1) volume of data; (2) complexity of analysis; (3) details of classification record; and (4) flexibility and momentum of analysis.

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towards the development of testable hypotheses and theory which are generalisable across settings and in contrast this methodology is more concerned with how a rich, complex description of the specific situations under study will evolve. In general, quantitative philosophy could be defined as an extreme of empiricism according to which theories are not only to be justified by the extent to which they can be verified but also by an application to facts acquired. It is a branch of thought which tried to find out the origins, justifications and progress of knowledge through observation, but is considered to have meanings only in so far as they can be derived (Chalmers, 1976). Quantitative investigations look for ``distinguishing characteristics, elemental properties and empirical boundaries'' and tend to measure ``how much'' or ``how often'' (Nau, 1995). They are appropriate to examine the behavioural component of BE. A quantitative research design has always been concerned with defining an epistemological methodology for determining the truth-value of propositions and allows flexibility in the treatment of data, in terms of comparative analysis, statistical analyses, and repeatability of data collection in order to verify reliability. It can be seen that the strengths of quantitative methodologies for BE research are: . comparison and replication are allowable; . independence of the observer from the subject being observed; . subject under analysis is measured through objective methods rather than being inferred subjectively through sensation, reflection or intuition; . reliability and validity may be determined more objectively than qualitative techniques; . strong in measuring descriptive aspects of BE; . emphasises the need to formulate hypothesis for subsequent verification; . helps to search for causal explanations and fundamental laws, and generally reduces the whole to the simplest possible elements in order to facilitate analysis (Easterby-Smith, 1991)

Further, it has long been recognised that purely qualitative research may neglect the social and cultural construction of the variables studied (Richards and Richards, 1994).

Quantitative research Quantitative research designs are characterised by the assumption that human behaviour can be explained by what may be termed ``social facts'' which can be investigated by methodologies that utilise ``the deductive logic of the natural sciences'' (Horna, 1994). This process is directed

These strengths, however, are not the sole prerogative of quantitative designs. Indeed, many of the arguments for the use of 22

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quantitative research, especially in an academic environment where resources are limited, have pragmatic origins in terms of allowing large-scale data collection and analysis at a reasonable cost and effort, as well as providing statistical ``proof''. The weaknesses of such quantitative research designs lie mainly in their failure to ascertain deeper underlying meanings and explanations of BE, even when significant, reliable and valid. Quantitative research is strong in measuring variables such as a quantitative assumption regarding construction process capability in that ``processes can be reduced to a set of variables which are somehow equivalent across construction projects, persons involved and across situations'' and, if this measurement is one of the focuses of the research, then a quantitative approach may be justified. However, factors such as physiological factors, motivating factors, employees' capability, etc. are important in most of the BE research concepts. Although quantitative methods can be used to measure such factors, their appropriateness in explaining them in depth is more limited. A further weakness in quantitative approaches lies in their tendencies to take a ``snapshot'' of a situation, that is to measure variables at a specific moment in time. Some construction related aspects might be affected by temporal changes which cannot always be identified within a single quantitative study.

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in research (Yin, 1994). Triangulation is the combination of methodologies in the study of the same phenomenon. The assumption in triangulation is that the effectiveness of triangulation rests on the premise that the weaknesses in each single method will be compensated by the counter-balancing strengths of another. This term is occasionally taken to refer to a broad approach which combines ``multiple observers, theoretical perspectives, and methodologies'' and is frequently used interchangeably to describe research strategies that incorporate a combination of quantitative and qualitative research methods in the study of the same phenomenon. It generally denotes a reference to a combination of research methods ± thus the use of qualitative and quantitative techniques together to study the topic ± which is very powerful for gaining insights and results, and for assisting in making inferences and in drawing conclusions, as illustrated in Figure 1 (Fellows and Liu, 1997). Although the use of a single methodology has been advocated by a number of authors (for example, Miles and Huberman, 1994; Eisenhardt, 1989; Yin, 1994), many of the supporting arguments are decidedly pragmatic such as time constraints, the need to limit the scope of the study and so on. Rossman and Wilson (1991) answer the question of why link qualitative and quantitative data and consider it to be: . to enable confirmation or corroboration of each other via triangulation; . to elaborate or develop analysis, providing richer details; and . to initiate new lines of thinking through attention to surprises or paradoxes, ``turning ideas around'', providing fresh insights.

The mixed (or balanced) approach There is a strong suggestion within the research community that research, both quantitative and qualitative, is best thought of as complementary and should therefore be mixed in research of many kinds. Das (1983) states that:

Quantitative data can help with the qualitative side of a study during design by finding a representative sample and locating deviant samples, while qualitative data can help the quantitative side of the study during design by aiding with conceptual development and instrumentation. The crucial aspect in justifying a mixed methodology research design in BE is that both single methodology approaches (quantitative only and qualitative only) have strengths and weaknesses. The combination of methodologies, on the other hand, can focus on their relevant strengths. The

. . . qualitative and quantitative methodologies are not antithetic or divergent, rather they focus on the different dimensions of the same phenomenon. Sometimes, these dimensions may appear to be confluent: but even in these instances, where they apparently diverge, the underlying unity may become visible on deeper penetration . . . The situational contingencies and objectives of the researcher would seem to play a decisive role in the design and execution of the study.

This emphasis has developed with the growing attention focused on ``triangulation'' 23

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Figure 1 Triangulation of qualitative data

researcher should aim to achieve a situation where ``blending qualitative and quantitative methods of research can produce a final product which can highlight the significant contributions of both'' (Nau, 1995), where ``qualitative data can support explicitly the meaning of quantitative research'' (Jayaratne, 1993). By adopting the following assumptions, the researcher should ensure that the final product maximises the strengths of a mixed method approach (adapted from Jones, 1997): . Qualitative methods, especially observation, or unstructured interviews, allow the researcher to develop an overall ``picture'' of the investigation. . Quantitative analysis may be more appropriate to assess the behavioural or descriptive complements of the BE. . The descriptive analysis, such as capabilities of employers, may allow a representative sample to be drawn for the qualitative analysis. Marsh et al. (1978) note that quantitative research may confirm or deny the representativeness of a sample group for such qualitative research. Thus the mixed methodology will guide the researcher, who is carrying out qualitative research, that his sample has some representativeness of the overall population. . BE research involves affective characteristics, as well as overall behavioural aspects. Thus a qualitative

.

.

.

.

``core'' is appropriate to investigate such aspects by examining the informant's point of view. Much BE research is still largely exploratory. The use of qualitative methods allows for unexpected developments that may arise as part of such research. Quantitative analysis may complement the findings of qualitative methods by indicating their extent within aspects of the BE. Quantitative analysis may confirm or reject any apparently significant data and the relationships that may emerge from research. Quantitative methods can be used to enable statistical testing of the strengths of such relationships. If such relationships are determined, then quantitative methods are weaker in providing explanations. Qualitative methods may assist in understanding the underlying explanations of significance.

Different tactics for pursuing research Besides the qualitative-quantitative and the positivistic-phenomenological classifications, there are many different ways of describing research approaches and methods. There is an almost limitless number of research tactics and variations in BE studies, many of which have been borrowed from other disciplines, 24

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and some believe that research in these areas is not ``properly'' scientific.

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Participant observation ``When one's concern is the experience of people, the way that they think, feel and act, the most truthful, reliable, complete and simple way of getting that information is to share their experience''. This is precisely the outlook subscribed to by proponents and practitioners of participant observation (Waddington, 1994). Although participant observation is chiefly concerned, as its name suggests, with the observation and recording of human activity, most practitioners of the method adhere to the principle of ``triangulation'' ± the use of more than one source or method of data collection. Thus fieldworkers often rely on other forms of information, such as documentation, mass media coverage and discussions with respondents, which may vary in formality from casual conversations to tape-recorded interviews and routinised surveys (Denzin, 1989). According to Waddington (1994), participant observation is best suited to research projects: which emphasise the importance of human meanings, interpretations and interactions; where the phenomenon under investigation is generally obscured from public view; where it is controversial; and where it is little understood and it may therefore be assumed that an ``insider'' perspective would enhance the existing knowledge.

Qualitative research methods Qualitative data is a source of well-grounded, rich descriptions and explanations of processes in identifiable local contexts. With qualitative data one can preserve chronological flow, see precisely which events led to which consequences, and derive fruitful explanations. Qualitative research may be conducted in dozens of ways, many with long traditions behind them. As Smith (1992) observed, the terms ethnography, field methods, qualitative inquiry, participant observation, case study, naturalistic methods, and responsive evaluation have become practically synonymous. To do them all justice is not the aim of this paper but some of the available methods are described here. The qualitative research interview Without doubt, the most widely used qualitative method in BE research is the interview. It is a highly flexible method, it can be used almost anywhere, and is capable of producing data of great depth (King, 1994). Kvale (1996) defines the qualitative research interview as ``an interview, whose purpose is to gather descriptions of the life-world of the interviewee with respect to interpretation of the meaning of the described phenomena''. The goals of any qualitative research interview are therefore to see the research topic from the perspective of the interviewee, and to understand how and why they come to have this particular perspective. The guidelines below suggest the circumstances in which a research interview is best suited (King, 1994), where: . a study focuses on the meaning of particular phenomena to the participants; . individual perceptions of processes within a social unit are to be studied prospectively, using a series of interviews; . individual historical accounts are required of how a particular phenomenon developed; . exploratory work is required before a quantitative study can be carried out; and . a quantitative study has been carried out, and qualitative data are required to validate particular measures or to clarify and illustrate the meaning of the findings.

Tracer studies Tracer studies are a method of identifying and describing organisational processes across time and stakeholder group by the use of ``tags'' as a way of following the unfolding process through the organisation, prompting the discussion of the process with organisational members, and identifying further important sources of information. All tracers are concerned with elucidating processes and so, by definition, tracers are associated with the description of activities over time ± tracing may be carried out concurrent with the process as it occurs and/ or retrospectively (Hornby and Symon, 1994). Data gathered enable many hypotheses to be tested that were not amenable to survey data. Greater control is achieved by focusing on a sub-group of a larger population. 25

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Survey techniques, such as questionnaires, interviews etc., are highly labour-intensive on the part of respondents and particularly on the part of the researcher, while a further consequence is the low response rate (Fellows and Liu, 1997). Descriptive survey is a common type of research setting which could be categorised under quantitative research in BE and is concerned with information generally obtained by interview or mailed questionnaire. Other sources include official reports or statistics. The prospective outcome will be a sizeable volume of information that can be classified by type, frequency, and central tendency. The expense of a survey will be very large if the population is substantial.

Case studies in built environment research The case study is a research strategy which focuses on understanding the dynamics present within single settings (Amaratunga and Baldry, 2000) and usually refers to relatively intensive analysis of a single instance of a phenomenon being investigated. Yin (1994) defines case study as an empirical investigation into contemporary phenomenon operating in a real-life context. It is particularly valuable when there is no clear definition between the phenomenon and the context itself. Case study research is a heterogeneous activity covering a range of research methods and techniques, a range of coverage, differing lengths and levels of involvement in organisational functioning and a range of different types of data (Hartley, 1994). Case studies are tailor-made for exploring new processes or behaviours or those which are little understood. In this sense, case studies have an important function in generating hypotheses and building theory in BE research. They have a high likelihood of generating new theory and, furthermore, the emergent theory is likely to be testable with constructs that can be measured and hypotheses that can be falsified. Detailed case studies may be essential in comparative research, where an intimate understanding of what concepts mean to people, the meanings attached to particular behaviours and how behaviours are linked. The key feature of the case study approach is not method or data but the emphasis on understanding processes as they occur in their context. The investigator interviews individuals or studies life history documents to gain an insight into behaviour and attempts to discover unique features and common traits shared by all persons in a given classification. Much case study research, because of the opportunity for open-ended inquiry, is able to draw on inductive methods of research, which aim to build theory and generate hypotheses rather than primarily to test them.

Research tactics and their philosophical relationships Galliers (1992) (cited in Remenyi et al., 1998) provides a list of approaches or tactics. Table VIII summarises this list according to the general philosophical base underpinning the different research tactics. It is important to note that most research tactics listed in the table can be used, at least to some extent, as either positivistic (quantitative) or phenomenological (qualitative) devices.

Analysing research evidence The analysis and interpretation of research data form the major part of the research. The definition of what is the ``analytical method'' is of paramount importance to any analytical strategy. It is stressed that, only when the correct analytical strategy is put together with its correspondent interactions, does it enable the generation of ``laws'', as the term law is usually employed in science. Different types of methods can be found including examining, categorising, tabulating, or otherwise recombining the evidence to address the initial propositions of a study. The definition of the analytical strategy determines the limits of data collection and dissemination of results. Some of the common analytical methodologies are summarised below.

Quantitative research methods Considerable research in BE involves asking and obtaining answers to questions through conducting surveys of people by using questionnaires and interviews. Often, responses are compared with ``hard data'', such as total cost of a construction project.

View of qualitative data analysis Miles and Huberman (1994) define qualitative data analysis as consisting of three concurrent flows of activity: data reduction, 26

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Table VIII Research tactics and philosophical bases Research approaches Action research Case studies Ethnographic Field experiments Focus groups Forecasting research Futures research Game or role playing In-depth surveys Laboratory experiments Large-scale surveys Participant observer Scenario research Simulation and stochastic modelling

Positivistic (quantitative)

Phenomenological (qualitative) Strictly interpretivist Have scope to be either Strictly interpretivist Have scope to be either Mostly interpretivist

Have scope to be either Have scope to be either Strictly positivistic with some room for interpretation Have scope to be either

Have scope to be either Strictly interpretivist Mostly interpretivist

Strictly positivistic with some room for interpretation Strictly positivistic with some room for interpretation Strictly interpretivist Mostly interpretivist Strictly positivistic with some room for interpretation

interwoven before, during, and after data collection in parallel to make up the general domain called ``analysis''. The three streams can also be presented, as shown in Figure 2 (Miles and Huberman, 1994). In this view, the three types of analysis activity and the activity of data collection itself form an interactive, cyclical process.

data display, and conclusion drawing and verification. Data reduction refers to the process of selecting, focusing, simplifying, abstracting, and transforming the data that appear in written-up field notes or transcriptions. Data reduction is not something separate from analysis. As Tesch (1990) points out, it also can be seen as ``data condensation''. Data reduction occurs continuously throughout the life of any qualitatively oriented project. Even before the data are actually collected, anticipatory data reduction is occurring, as the researcher decides which conceptual framework, which cases, which research questions, and which data collection approaches to choose. The most frequent form of display for qualitative data in the past has been extended text. Miles and Huberman (1994) have become convinced that better displays are a major avenue to valid qualitative analysis. As with data reduction, the creation and use of displays are not separate from analysis, they are a part of analysis. Conclusion drawing and verification, in Miles and Huberman's (1994) opinion, are only half of a Gemini configuration. ``Final'' conclusions may not appear until data collection is over, depending on the size of the corpus of field notes; the coding, storage, and retrieval methods used; and the sophistication of the researcher, but they often have been prefigured from the beginning, even when a researcher claims to have been proceeding ``inductively''. Data reduction, data display, and conclusion verification were described ± as

Pattern matching For qualitative data analysis, one of the most desirable strategies is to use a patternmatching logic (Yin, 1994). Such logic compares an empirically-based with a predicted pattern. In this process, when similar results happen and for predictable reasons, the evidence produced is seen to involve the same phenomena described in the theory, and is called ``literal replication''. In contrast, when the qualitative data analysis produces contrasting results, but also for predictable reasons, it is called ``theoretical replication''. There is some criticism in the literature concerning the lack of precision of the pattern-matching approach. Yin (1994) alerts that there is a risk of some interpretive discretion on the part of researchers. The overall quality of pattern matching could be improved by using quantitative analytical strategies. Explanation building This strategy is in fact a special type of pattern matching, but the procedure is more difficult and therefore deserves separate attention. Here, the goal is to analyse the qualitative 27

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Figure 2 Components of data analysis: interactive model

data by building an explanation about the situation. To ``explain'' a phenomenon is to stipulate a set of causal links about it. Increasing the accuracy of the pattern matching described above and explanationbuilding analysis are one of the key strategies in searching for the typical behaviour and practical boundaries of quantitative indicators (Pacitti, 1998).

Quantitative data analysis Data display is generally an organised, compressed assembly of information that permits conclusion drawing and action. Quantitative data analysis often deals with statistical data analysis techniques, specifically in the analysis of behavioural elements of performance. Some of the most commonly used techniques are: chi-square analysis, correlation analysis, factor analysis, etc. A quantitative data analysis plan generally consists of: raw data assessment; data entry and transfer; data processing; communicating findings; data interpretation; and completing data analysis (Pacitti, 1998). No matter what the nature of data collected, it is appropriate to begin analysis by examining the raw data to search for patterns. Many analyses of quantitative data concern searching the data patterns of various types, so that hypothetical relationships can be established. Many quantitative approaches are subject to particular analytical techniques with prescribed tests, such as conversion and discourse analysis; therefore comparisons may be made and hierarchies of categories may be examined. Most quantitative type information yields data which are suitable for statistical analyses. The purpose of analysing the data is to provide information about variables and, usually, relationships between them. Hence, quantitative studies are undertaken to yield statistical evidence of relationships and their strengths, as statistics are very useful in determining directions of relationships when combined with theory and literature.

Time series analysis This strategy deals with conducting a timeseries analysis, directly analogous to the time series analysis conducted in experiments and quasi-experiments. Such analysis can follow many intricate patterns (Yin, 1994). The essential logic underlying a time series analysis is the match between a trend of data points compared with a theoretically significant trend specified before the onset of the investigation, versus some rival trend, also specified earlier, versus any trend based on some artefact or threat to internal validity. When interpreting the data when the mixed method is used, the following steps are recommended: . look for patterns of agreement ± across data sources, by mediating variables, with literature, with experience; . look for contradictions ± across data sources, by mediating variables, with literature, with experience; . try to resolve contradictions ± through alternative plausible explanations for a finding, by re-examining the data, by collecting specific data to test an alternative hypothesis; . identify the most important findings ± rank and organise them; and . present the findings simply ± through charts and tables, selected photos or videos that illustrate an important point.

Evaluation criteria Any review of research methods will be incomplete without considering the fundamental issues relating to evaluation of 28

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It is worth noting that there is a different perspective on validity when viewed within the context of qualitative and quantitative research (Then, 1996). Qualitative research identifies the presence or absence of a given feature in a given problem or situation, as opposed to quantitative research which measures the degree of presence of the feature itself.

any research outcomes. In many respects an evaluation is often focused on measures to counteract the weaknesses inherent in the particular research strategy chosen to carry out a particular piece of research (Then, 1996). The technical language of such research evaluation includes terms such as validity, reliability and generalisability. The debate is rooted in philosophical differences about the nature of reality and takes the form of qualitative versus quantitative methods, as described earlier. In general, the value of any research stems from the validity of its results and the extent of its contribution to the body of knowledge. Research into the BE is no exception. These results are the outcomes from the collection, interpretation, analysis and evaluation of data.

Reliability Reliability is the extent to which a test or procedure produces similar results under constant conditions on all occasions (Yin, 1994). Another definition by Simon and Burstein (1985) states that: . . . reliability is essentially repeatability ± a measurement procedure is highly reliable, if it comes up with the same result in the same circumstances time after time, even employed by different people.

Validity For a given problem, validity is one of the concepts used to determine how good is an answer provided by research (Then, 1996). It means in essence that a theory, model, concept, or category describes reality with a good fit:

The goal of reliability is to minimise the errors and biases in a study. The object is to ensure that, if a later investigator followed exactly the same procedures, the same findings and conclusions would result. From the above discussion, it can be seen that the basic difference between reliability and internal validity is that reliability deals with the data collection process to ensure consistency of results, while internal validity focuses more on the way such results support conclusions (Then, 1996). It should also be noted that the above deliberation refers very much to the traditional evaluation criteria of validity and reliability that are governed by the convention of the quantitative research paradigm. Although early qualitative researchers felt compelled to relate traditional notions of validity and reliability to procedures in qualitative research, later writers (Miles and Huberman, 1994; Yin, 1994; Easterby-Smith, 1991) developed their own language to describe the quality criteria in a qualitative research paradigm. Miles and Huberman (1994) concentrate on improved and rigorous techniques for data gathering and analysis as the best way to enhance credibility and acceptance. Yin (1994) identifies the following to establish validity and reliability in qualitative research: (1) establish a chain of evidence; (2) have the draft study report reviewed by the key informants; (3) use of single research exploratory design by: establishing a causal relationship; use

A valid measure is one which measures what it is intended to measure. In fact, it is not the measure that is valid or invalid but the use to which the measure is put . . . the validity of a measure then depends on how we have defined the concept it is designed to measure (De Vaus, 1991).

In research methodology literature, the measure of validity is often considered under either internal or external validity (Yin, 1994; Gill and Johnson, 1991). Internal validity refers to whether or not what are identified as the causes actually produce what has been interpreted as the ``effect'' or ``responses'' and checks whether the right cause-and-effect relationships have been established. Thus internal validity is the issue of establishing theoretical territory that goes with the defined construct and ensuring consistency between it and other recognised constructs. External validity criterion refers to the extent to which any research findings can be generalised beyond the immediate research sample or setting in which the research took place; thus the extent to which findings drawn from studying one group are applicable to other groups or settings (the applicability of findings beyond the group). External validity could be achieved from theoretical relationships. 29

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research is being done and what it is supposed to achieve. (3) A research plan must be formulated. The purpose of the plan should be directed towards the testing of a hypothesis (deduction) or evaluation of evidence in terms of constructing a hypothesis (induction). (4) The outcome of the enquiry is stated in explicit terms, which may result in the support or refutation of an existing hypothesis (deduction) or a proposed one (induction). (5) The conclusions are documented with sufficient support and clarity to establish what was done, what was found, and what significance the findings may have. The researcher is also careful to separate their work from that of others, and to show how their methodology or findings mesh with other efforts within the same field of inquiry.

of a single case explanatory design; and specification of the unit of analysis. (4) develop formal research study framework, which typically has the following sections: . an overview of the study project (objectives, issues, topics being investigated); . field procedures (credentials and access to sites, sources of information); . research study questions (specific questions that the investigator must keep in mind during data collection); and . a guide for research report (outline, format of the narrative).

Development of knowledge Research can be differentiated by looking at the approach, as described above, adopted by the researcher. Some researchers prefer a quantitative approach which is objective in nature and concentrates on measuring phenomena. Therefore, a quantitative approach involves collecting and analysing numerical data and applying statistical tests. Other researchers prefer a qualitative approach, which is more subjective in nature and involves examining and reflecting on perceptions in order to gain an understanding of social and human activities. One of the early decisions during the research process is to decide which is the best approach for the research under consideration. Some researchers avoid taking a quantitative approach, because they are not confident with statistics and think a qualitative approach will be easier. They further find that it is harder to start and decide an overall design for a quantitative study, but it is easier to conduct and write up the analysis because it is highly structured. Qualitative research is generally easier to start, but researchers often find it difficult to analyse the data and write up the final output. Buckley et al. (1975) (cited in Then, 1996) provide five essential steps as the requirements to ensure the assurance of quality research and the achievement of reliability and validity: (1) Knowledge stems from observations which take place through a definable searching process. (2) The research problem is defined, which means answering the questions why the

There are many arguments in the literature regarding the merits of qualitative versus quantitative approaches, some of which have been examined in this paper. It is important that researchers need to be aware that the choice is influenced by the nature of the research as well as the researcher's own philosophical preferences.

Conclusion There is no uniquely best approach to research, either in the natural world or in the BE in particular, and the best that can be done is to describe the ways in which research is carried out in a variety of situations. Nevertheless, there are lessons that can be learned and some of these are discussed in this paper. Further, the purpose of this paper is not to suggest that a mixed methodology is the only suitable research design, rather that it is an appropriate and, at times, desirable design. The overall choice needs, of course, to be the most suitable to achieve the objectives of the specific piece of research. A mixed methodology, however, has a number of advantages within BE research, as well as other disciplines, and may be able to enhance the quality of such work in such ways as have been outlined. The above review highlighted a variety of issues that a BE researcher is likely to face in 30

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trying to formulate a sound research design. These issues, if overlooked, increase the risk of invalid, erroneous, or distorted design. In order to avoid potential problems, adequate steps must be taken to identify the correct research methodology, which will guide the research process from the beginning to the conclusion. Therefore, an understanding of fundamental issues pertaining to different types of research typologies is important, which is likely to affect the whole research process, as the success of a research project will be largely dependent on the robustness of this strategy.

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