Approaches to Qualitative Research

Published Date: 23 Mar 2015 Last Modified: 09 Jan 2018

Examples of qualitative methods are action research, case study research and ethnography. Qualitative data sources include observation and participant observation (fieldwork), interviews and questionnaires, documents and texts, and the researcher's impressions and reactions

Quantitative research

Is mean of testing objective theories by examining the relationship among variables.

These variables in turn can be measured typically on instruments, so that numbered data can be analyzed using statically procedures.

Quantitative research methods were originally developed in the natural sciences to study natural phenomena. Examples of quantitative methods now well accepted in the social sciences include survey methods, laboratory experiments, formal methods (e.g. econometrics) and numerical methods such as mathematical modelling.

Mixed methods Research

Is an approach to inquiry that combines or associates both qualitative and quantitative forms? Its involves philosophical assumptions, the use of qualitative and quantitative approaches and mixing the both approaches in a study.

.Mixed research is research in which quantitative and qualitative techniques are mixed in a single study. It is the third major research paradigm, adding an attractive alternative (when it is appropriate) to quantitative and qualitative research.

Worldviews in Creswell

Worldviews/ Paradigms are intellectual Frameworks embodying tradition of scientific Theories and research

The research design (strategies of inquiry and specific methods) is based on the

espoused paradigm

Worldviews/Paradigms

Ontology - what exists in reality

_ Epistemology - what can we know; how can we acquire knowledge

_ Methodology - which research methods are appropriate for generating valid evidence.

The four main worldviews/paradigms

(Post)positivism numerical measures of observation and studing the behaviour of individals become paramount of post positivist

Constructivism

Advocacy / Participatory

Pragmatism

(Post)positivism

_Constructivism Interpretivism

_ Advocacy/Participatory

Critical research

_ Pragmatism

The four main worldviews/paradigms

(Post) positivism

Constructivism, (Development, testing, Refinement of theories)

Advocacy/Participatory Pragmatism (Change, improvement, action in the ystem)

Positivism

Positivist ontology and epistemology

_Objective reality exists independent of humans

_Reality is relatively stable and orderly and it can be described in models, i.e. theories

_ The entities used in the theories can be identified in reality, and measured and

often even controlled separately (reduction)

Positivist ontology and epistemology

Post positivism acknowledges the human rationality, free will and deterministic

Worldview is compatible.

However, the total system is supposed to work orderly, contradictions are problems that must be eliminated.

Positivist ontology and epistemology

The entities can be measured objectively, independent of the observer and instruments.

Consequently, the measurements can be repeated by other researchers and the Results can be generalised.

The ideal positivist inquiry is objective and value-free.

Constructivism

Constructivist ontology and epistemology

Social realities are not given; they are produced by humans through their actions and interactions.

The reality can only be understood through social constructions such as language and the meanings that involved persons assign to phenomena.

The total social system is supposed to work relatively orderly, but human

Interactions include always negotiation in order to avoid conflicts and contradictions.

The social reality cannot be measured in an objective way, it can only be interpreted by the researcher

The studied phenomena must be interpreted in the current context, in their natural settings

The researcher's prior beliefs, values, interests and assumptions influence the

Interpretation

The researcher can be an observer but also a participant in the social reality

Consequently, the study cannot easily be repeated by other researchers and the

Results can not always be generalised.

Critical research

Critical ontology and epistemology

The social reality is historically and politically constituted, produced by people

Social relations are not stable and orderly, there are often contradictions and conflicts in the relations, which leads to inequality and unjustice in the society

Interpretation of the world is not enough, the contradictions should also be criticised

People can change their society if they become aware of the hidden

contradictions and new possibilities

However, their ability to initiate change is often constrained

Researcher's main aim is to expose the restrictive conditions and to facilitate

Change in cooperation with the participants.

Pragmatism

Pragmatism

The main focus is on how to understand and solve the research problem and to

Conduct a practical action in the real world problem setting

Action is socially situated in a given context; researcher cooperates with the

Participants and also becomes a participant observer

Multiple approaches, theories and methods can be used

Theories must be refined according to the practical outcome of the action

A framework for research design according Creswell Worldviews

Strategies of inquiry (see Table 1.2, p 12)

Research methods (see Table 1.3, p 15)

Qualitative

Quantitative

Mixed methods

Induction and deduction

Inductive and hypothetico-deductive method

Hypotheses

Structure, context Inductive method Mostly Qualitative

and relations Hypotheticodeductive method Mostly Quantitative

Definitions

Facts from

observations

Predictions and

Explanations

Inductive method

The fundamental problem with induction is that the conclusion of an inductive argument could always be false, even if a large number of observations is made

There is no generally established solution to the problem of induction.

Generalisation of theories

Theories can be on different levels, i.e. the explanation they provide covers smaller or larger parts of the reality.

Level of generalisation.

Macro-level: societies, cultural Systems, Meso-level: communities, organisations

Micro-level: small groups, individuals

Hypothetico-deductive method

Demarcation criterion would make it possible to decide whether a theory is

Scientific or not; distinction between science and pseudoscience

A theory is scientific only if it is falsiable, i.e it can be tested empirically

Once a theory/hypothesis has been formulated, predictions must be deduced

from it and these predictions are to be tested experimentally

If a theory is falsified it is abandoned, thus the method is often called conjectures and refutations

According to Popper a theory cannot be confirmed, as more severe testing will

eventually lead to falsification

Theories that have survived testing are said to be corroborated

_However, all scientific knowledge must be considered as tentative and is subject to orrection in the future

Testing of theories

The predictive power of theories is greater when the theory

_has greater ability to describe past observations

has greater ability to make correct predictions of new observations and does not make false predictions

is able to make more precise predictions

does not need additional assumptions (auxiliary hypotheses) in order to make predictions, especially not"ad hoc hypotheses.

Chapter 2 - Review of Literature

What is "literature"?

A literature review helps to

determine whether the topic is worth studying,

draw the scope of the research inquiry,

shows the results of previous studies,

filling in gaps and extending prior studies,

Establishing the importance of the study.

Topic is the subject or subject matter of a propose study. ( see the six stages of choosing a topic by Fisher)

Draft a title for the study,

Pose the title as a brief research question,

Access to participants and resources,

Contribution to the knowledge,

Audience.

The use of literature (see Table 2.1, p. 27):

As an orienting framework at the beginning of research to frame the problem or at the end as "related" literature to compare and contrast results (mostly in qualitative and theoretical research),

As a separate section (mostly in quantitative research) at the beginning of research to develop hypotheses,

Integrative to summarize broad themes in the literature,

theoretical and methodological reviews.

How to conduct a literature review:

Identify Keywords,

Go to the library,

Online resources i.e. ELIN, Google Scholar,

Pick up a number of articles,

Filter the articles,

Make a literature map,

Make summaries,

Assemble the literature and develop a thematic structure.

Searching Computerized Databases:

Online databases,

Indexes,

Online Journals and conference home pages.

A priority for selecting literature material:

Start with broad themes,

Look for journal and conference articles, books, dissertations,

The WWW.

A literature map (see p. 35):

I recommend making an outline or a structure for the literature.

Abstracting studies:

An abstract includes major elements of any study such as problem, purpose, research question, method, and results.

Style manuals (important):

Provide guidelines on how to write and structure a scholarly manuscript.

The use of a referencing system i.e. Harvard System (available on Blackboard).

Definition of terms.

In qualitative studies definitions may emerge throughout the analysis,

In quantitative studies there is an extensive definition of terms.

In mixed method a consistent strategy of the previous two strategies is used.

Chapter 3 - Use of Theory

There are various ways of using theory in qualitative research:

As a broad explanation of behavior and attitudes e.g. in ethnographic research, researchers employ cultural themes such as stability, control, social organization, etc.

As a theoretical lens or perspective which provides a lens for the study, shapes the types of questions asked, informs the data collection and analysis, and provides a call for action and change. Also it guides researcher to important issues for the study, the people that need to be studied, the position of the researcher, and how final accounts need to be written e.g. feminist perspective.

As a grounded theory that is an end or an outcome of the research. This is the induction process in which theories are developed through empirical data that participants express in the research. See Figure 3.5, p. 64.

Some studies do not employ any explicit theory. Researchers try to build the essence of the experience from the participants.

Tips for theory use

Decide if theory is to be used in the qualitative study.

If it is used, then identify how the theory will be used in the study such as an up-front explanation, as an end point, or as an advocacy lens.

Locate the theory in the proposal in a manner that is consistent with its use.

Location of theory either at the beginning or an end influences how it is used.

Theory should be used in a sense that allows the use of a priori theory to pour from data but at the same time this priori theory shall not be used a container.

See examples 3.2 & 3.3 at p.65.

Theory use in mixed methods

Theory use in mixed methods may include deductive theory in quantitative studies and inductive theory in qualitative theory or patterns.

Theory is used as a theoretical lens or a perspective to guide the study.

The use of transformative design in mixed methods.

Mixing value commitments (bias in both quan. and qual. studies)

The use of various methods.

Focus on action solutions.

Chapter 5 - The Introduction

The introduction is the first passage in a journal article, dissertation, or scholarly research study.

Interest in the topic, establish the problems that lead to the study, place the study within the larger context of scholarly literature, and reach out to specific audience.

Research problem is the problem or issue (opportunity) that leads to the need for a study.

In Qualitative studies, the research problem is described by exploring a concept or phenomenon.

In Quantitative studies, the research problem is described by understanding what factors or variables influence the outcome.

In Mixed Methods, the introduction discusses the emphasis of one method and the problem focuses on understanding the relationships among particular variables as well as explore a topic in further depth.

A model for an introduction

The research problem

Studies that have addressed the problem.

Deficiencies in the studies.

The significance of the study for particular audiences.

The purpose statement

Be careful about the opening sentence (narrative hooks); attract the reader and make it easy to understand by the audience.

Two primary objectives must be accomplished by the introduction:

Piquing interest in the study.

Conveying a distinct research problem or issue.

Problems arise from issues, difficulties, and current practice.

Studies addressing the problem (reviewing studies).

Summarize large groups of studies.

Distinction between past studies and the proposed one.

Setting the research problem within the larger academic debate.

Deficiencies in past literature.

Significance of the study

Chapter 6 - The purpose statement

Purpose statement sets the objective, the intent, or the major idea of a proposal or a study.

It can be formulated in one or several sentences.

To be framed apart from other parts of the proposal to emphasize its importance and to avoid confusion with research problems or questions.

A qualitative purpose statement

A good qualitative purpose statement contains information about the central phenomenon explored in the study, the participants in the study, and the research site.

Design features for writing the qualitative purpose statement:

Use words such as purpose, intent, or objective.

Focus on a single phenomenon or idea.

Use action verbs to convey how learning will take place such as describe, understand, develop, examine the meaning of, etc.

Use natural phrases such as "exploring the experiences of individuals" rather than "successful experiences of individuals".

Provide a general working definition of the phenomenon.

Include words donating to the method of inquiry.

Mention the participants in the study (individuals, groups, organizations).

Delimit the scope of participation or research sites.

A Quantitative Purpose statement

The Quantitative Purpose statement includes the variables in the study and their relationship, the participants, and the research sites.

Design features for writing the quantitative purpose statement:

Include words to signal the major intent of the study such as purpose, intent, or objective.

Indentify the theory, model, or conceptual framework.

Identify dependent and independent variables.

Use words to connect these variables such as " the relationship between..", "two or more variables", etc.

Order the variables with the independent variable followed by the dependent variable.

Mention the specify type of strategy of inquiry.

Make reference to the participants.

Define each key variable.

A Mixed Method Purpose statement

A Mixed Method Purpose statement contains the overall intent of the study, information about both the quantitative and qualitative strands of the study, and a rationale of incorporating both strands of the study the research problem.

Begin with signaling words such as the purpose, the intent, etc.

Indicate the overall intent of the study from a content perspective such as "the intent is to learn about organizational effectiveness" or "the intent is to study families with step-children.

Discuss the reasons for combining both qualitative and quantitative data.

Include the characteristics of both qualitative and quantitative purpose statements.

Consider adding information about the specific types of both qualitative and quantitative data collection.

Chapter 7 - Research Questions and Hypothesis

The central "qualitative" question is a "broad" question that asks for an exploration of the central phenomenon or concept in a study.

It should be consistent with the emerging methodology of qualitative research.

Guidelines for writing "broad", qualitative research questions:

Ask one or two central questions followed by no more than five to seven sub questions.

Relate the central question to the specific qualitative strategy of inquiry.

Begin the research questions with the words what or how to convey an open and emerging design.

Focus on a single phenomenon or concept.

Use exploratory verbs that convey the language of emerging design such as discover, seek to understand, etc.

Use more exploratory verbs that suggest qualitative research such as affect, influence, impact, determine, cause, etc.

Expect the research question to evolve and change during the study.

Use open-ended questions.

Specify the participants and the research site.

Quantitative Research Questions and Hypothesis

A quantitative research question inquires about the relationship among variables that the investigator seeks to know.

Quantitative hypotheses are predictions the research makes about the expected relationships among variables. They are numeric estimates of population values based on data collected from samples.

Guidelines for writing good quantitative research questions and hypotheses:

Different uses of variables in quantitative research questions (compare, relate, describe)

Testing theories.

Separate measures for independent and dependent variables (cause-and-effect logic)

To avoid redundancy, write either research questions or hypotheses, not both.

Null, alternative, and non-directional hypotheses.

Mixed Methods Research Questions and Hypotheses

Often, there are no specific questions or hypotheses tailored to mixed methods research.

Guidelines for mixed methods RQs and Hypotheses:

Both Qual. and Quan. RQs need to be advanced in a mixed methods study to narrow and focus the purpose statement.

Follow previous guidelines for Qual. and Quan.

Attention to the order of the RQs and Hypotheses.

Include a mixed methods research question that directly addresses the mixing of the Qual. and Quan. Strands of the research.

Chapter 8 - Quantitative Methods

Defining surveys and experiments:

A survey design provides a quantitative or numeric description of trends, attitudes, or opinions of a population by studying a sample of that population.

Experiment design is to test the impact of a treatment (or an intervention) on an outcome. Controlling for all other factors that might influence that outcome.

Components of a survey design

The survey design:

Identify the purpose of survey research.

Indicate why a survey is the preferred type of data collection procedure for the study.

Indicate whether the survey will be cross-sectional, with the data collected at one point in time, or longitudinal with data collected over time.

Specify the form of data collection (self-administered, questioners, interviews, structured record reviews to collect financial, medical, or school info, and structured observations.)

See Table 8.1 (p. 147) Checklist for designing a survey.

The population and sample

Essential aspects of the population and sample:

Identify the population in the study and state the size of this population.

Identify whether the sampling design for this population is single stage or multistage.

Identify the selection process for individuals.

Identify whether the study will involve stratification.

Discuss the procedures for selecting the sample from available lists.

Indicate the number of people in the sample and the procedures used to compute this number.

Instrumentation

The actual instrument or "tool" used in the study:

Name the survey instrument used to collect the data (designed for the research, modified instrument, intact instrument used by someone else).

To use an existing instrument, discuss its validity and reliability.

Considering validity and reliability issues when modifying or combining instruments.

Include actual items from the instrument so that readers can see the actual items used.

Indicate the major content sections in the instrument, such as a cover letter, the items, etc.

Discuss plans for pilot testing or field survey and provide a rationale for these plans.

For a mailed survey, identify steps for administering the survey and for following up to ensure a high response rate.

Variables in the study & Data analysis and interpretation

Relate variable to the specific questions or hypotheses on the instrument.

Present information about the steps involved in analyzing the data.

Report info about the number of members of the sample who did and who did not return the survey.

Discuss the method by which response bias will be determined (response bias is the effect of nonresponses on survey estimates )

Discuss a plan to provide a descriptive analysis of data for all independent and dependent variables in the study.

If the proposal contains an instrument with scales or a plan to develop scales (combining items into scales) indentify the statistical procedure for accomplishing this.

Identify the statistics and the statistical computer program for testing the major inferential research question or hypothesis in the study.

Present the results in tables and figures and interpret the results from the statistical test.

Components of an experimental design

Participants: random and nonrandom sampling, matching participants, true experiment, number, and values.

Variables: dependent, independent.

Instrumentation and Materials: instruments completed by the participants, materials used for experimental treatment.

Experimental procedures: type of design, what is being compared, illustration of the specific research design.

Threats to validity: effects on the experiment outcome.

The procedure: step-by-step explanation of the procedure.

Data analysis: types of statistical analysis used during the experiment.

Interpreting result: interpretation of the results in the light of the RQ and hypothesis.

Chapter 9 - Qualitative Procedures

Characteristics of Qual. Research:

• Natural setting.
• Researcher as key instrument.
• Multiple sources of data.
• Inductive data analysis.
• Participant's meanings.
• Emergent design.
• Theoretical lens.
• Interpretative.
• Holistic account

Philosophical Perspectives

All research (whether quantitative or qualitative) is based on some underlying assumptions about what constitutes 'valid' research and which research methods are appropriate. In order to conduct and/or evaluate qualitative research, it is therefore important to know what these (sometimes hidden) assumptions are.

For our purposes, the most pertinent philosophical assumptions are those which relate to the underlying epistemology which guides the research. Epistemology refers to the assumptions about knowledge and how it can be obtained (for a fuller discussion, see Hirschheim, 1992).

Guba and Lincoln (1994) suggest four underlying "paradigms" for qualitative research: positivism, post-positivism, critical theory, and constructivism. Orlikowski and Baroudi (1991), following Chua (1986), suggest three categories, based on the underlying research epistemology: positivist, interpretive and critical. This three-fold classification is the one that is adopted here. However it needs to be said that, while these three research epistemologies are philosophically distinct (as ideal types), in the practice of social research these distinctions are not always so clear cut (e.g. see Lee, 1989). There is considerable disagreement as to whether these research "paradigms" or underlying epistemologies are necessarily opposed or can be accommodated within the one study.

It should be clear from the above that the word 'qualitative' is not a synonym for 'interpretive' - qualitative research may or may not be interpretive, depending upon the underlying philosophical assumptions of the researcher. Qualitative research can be positivist, interpretive, or critical (see Figure 1). It follows from this that the choice of a specific qualitative research method (such as the case study method) is independent of the underlying philosophical position adopted. For example, case study research can be positivist (Yin, 1994), interpretive (Walsham, 1993), or critical, just as action research can be positivist (Clark, 1972), interpretive (Elden and Chisholm, 1993) or critical (Carr and Kemmis, 1986). These three philosophical perspectives are discussed below.

1. Positivist Research

Positivists generally assume that reality is objectively given and can be described by measurable properties which are independent of the observer (researcher) and his or her instruments. Positivist studies generally attempt to test theory, in an attempt to increase the predictive understanding of phenomena. In line with this Orlikowski and Baroudi (1991, p.5) classified IS research as positivist if there was evidence of formal propositions, quantifiable measures of variables, hypothesis testing, and the drawing of inferences about a phenomenon from the sample to a stated population. Examples of a positivist approach to qualitative research include Yin's (1994) and Benbasat et al's (1987) work on case study research.

2. Interpretive Research

Interpretive researchers start out with the assumption that access to reality (given or socially constructed) is only through social constructions such as language, consciousness and shared meanings. The philosophical base of interpretive research is hermeneutics and phenomenology (Boland, 1985). Interpretive studies generally attempt to understand phenomena through the meanings that people assign to them and interpretive methods of research in IS are "aimed at producing an understanding of the context of the information system, and the process whereby the information system influences and is influenced by the context" (Walsham 1993, p. 4-5). Interpretive research does not predefine dependent and independent variables, but focuses on the full complexity of human sense making as the situation emerges (Kaplan and Maxwell, 1994).

Examples of an interpretive approach to qualitative research include Boland's (1991) and Walsham's (1993) work.

References on Interpretive Research

3. Critical Research

Critical researchers assume that social reality is historically constituted and that it is produced and reproduced by people. Although people can consciously act to change their social and economic circumstances, critical researchers recognize that their ability to do so is constrained by various forms of social, cultural and political domination. The main task of critical research is seen as being one of social critique, whereby the restrictive and alienating conditions of the status quo are brought to light. Critical research focuses on the oppositions, conflicts and contradictions in contemporary society, and seeks to be emancipatory i.e. it should help to eliminate the causes of alienation and domination.

One of the best known exponents of contemporary critical social theory is Jurgen Habermas, who is regarded by many as one of the leading philosophers of the twentieth century. Habermas was a member of the Frankfurt School, which included figures such as Adorno, Horkheimer, Lukacs, and Marcuse. Examples of a critical approach to qualitative research include Ngwenyama's (1991) and Hirschheim and Klein's (1994) work.

References on Critical Social Theory

Qualitative Research Methods

Just as there are various philosophical perspectives which can inform qualitative research, so there are various qualitative research methods. A research method is a strategy of inquiry which moves from the underlying philosophical assumptions to research design and data collection. The choice of research method influences the way in which the researcher collects data. Specific research methods also imply different skills, assumptions and research practices. The four research methods that will be discussed here are action research, case study research, ethnography and grounded theory - for more detail see Myers (2009).

1. Action Research

There are numerous definitions of action research, however one of the most widely cited is that of Rapoport?s, who defines action research in the following way:

Action research aims to contribute both to the practical concerns of people in an immediate problematic situation and to the goals of social science by joint collaboration within a mutually acceptable ethical framework (Rapoport, 1970, p. 499).

This definition draws attention to the collaborative aspect of action research and to possible ethical dilemmas which arise from its use. It also makes clear, as Clark (1972) emphasizes, that action research is concerned to enlarge the stock of knowledge of the social science community. It is this aspect of action research that distinguishes it from applied social science, where the goal is simply to apply social scientific knowledge but not to add to the body of knowledge.

Action research has been accepted as a valid research method in applied fields such as organization development and education (e.g. see the Special Issue on action research in Human Relations, Vol. 46, No. 2, 1993, and Kemmis and McTaggart, 1988). In information systems, however, action research was for a long time largely ignored, apart from one or two notable exceptions (e.g. Checkland, 1991). More recently, there seems to be increasing interest in action research.

A brief overview of action research is the article by Susman and Evered (1988). The article by Baskerville and Wood-Harper (1996) provides a good introduction to how action research might be used by IS researchers. An empirical example of action research is the article by Ytterstad et al. (1996).

2. Case Study Research

The term "case study" has multiple meanings. It can be used to describe a unit of analysis (e.g. a case study of a particular organisation) or to describe a research method. The discussion here concerns the use of the case study as a research method.

Case study research is the most common qualitative method used in information systems (Orlikowski and Baroudi, 1991; Alavi and Carlson, 1992). Although there are numerous definitions, Yin (2002) defines the scope of a case study as follows:

A case study is an empirical inquiry that:

Investigates a contemporary phenomenon within its real-life context, especially when

The boundaries between phenomenon and context are not clearly evident (Yin 2002).

Clearly, the case study research method is particularly well-suited to IS research, since the object of our discipline is the study of information systems in organizations, and "interest has shifted to organizational rather than technical issues" (Benbasat et al. 1987).

Case study research can be positivist, interpretive, or critical, depending upon the underlying philosophical assumptions of the researcher (for a fuller discussion, see the section of Philosophical Perspectives above). Yin (2002) and Benbasat et al. (1987) are advocates of positivist case study research, whereas Walsham (1993) is an advocate of interpretive in-depth case study research.

»References on Case Study Research

3. Ethnography

Ethnographic research comes from the discipline of social and cultural anthropology where an ethnographer is required to spend a significant amount of time in the field. Ethnographers immerse themselves in the lives of the people they study (Lewis 1985, p. 380) and seek to place the phenomena studied in their social and cultural context.

After early ground-breaking work by Wynn (1979), Suchman (1987) and Zuboff (1988), ethnography has now become more widely used in the study of information systems in organizations, from the study of the development of information systems (Hughes et. al, 1992; Orlikowski, 1991; Preston, 1991) to the study of aspects of information technology management (Davies, 1991; Davies and Nielsen, 1992). Ethnography has also been discussed as a method whereby multiple perspectives can be incorporated in systems design (Holzblatt and Beyer, 1993) and as a general approach to the wide range of possible studies relating to the investigation of information systems (Pettigrew, 1985).

In the area of the design and evaluation of information systems, some very interesting work is taking place in a collaborative fashion between ethnographers on the one hand, and designers, IS professionals, computer scientists and engineers on the other. This collaborative work is especially strong in the UK and Europe and is growing in the US.

»Myers (1999) overview article entitled "Investigating Information Systems with Ethnographic Research" (this is the PDF version of a paper published in Communications of the AIS. Please note that the Association for Information Systems owns the copyright and use for profit is not allowed)

»AIS-Pert Workshop on Ethnographic Research in Information Systems from 8-11 March 1999

»References on Ethnographic Research

4. Grounded Theory

Grounded theory is a research method that seeks to develop theory that is grounded in data systematically gathered and analyzed. According to Martin and Turner (1986), grounded theory is "an inductive, theory discovery methodology that allows the researcher to develop a theoretical account of the general features of a topic while simultaneously grounding the account in empirical observations or data." The major difference between grounded theory and other methods is its specific approach to theory development - grounded theory suggests that there should be a continuous interplay between data collection and analysis.

Grounded theory approaches are becoming increasingly common in the IS research literature because the method is extremely useful in developing context-based, process-oriented descriptions and explanations of the phenomenon (see, for example, Orlikowski, 1993).

Qualitative Techniques for Data Collection

Each of the research methods discussed above uses one or more techniques for collecting empirical data (many qualitative researchers prefer the term "empirical materials" to the word "data" since most qualitative data is non-numeric). These techniques range from interviews, observational techniques such as participant observation and fieldwork, through to archival research. Written data sources can include published and unpublished documents, company reports, memos, letters, reports, email messages, faxes, newspaper articles and so forth.

In anthropology and sociology it is a common practice to distinguish between primary and secondary sources of data. Generally speaking, primary sources are those data which are unpublished and which the researcher has gathered from the people or organization directly. Secondary sources refers to any materials (books, articles etc.) which have been previously published.

Typically, a case study researcher uses interviews and documentary materials first and foremost, without using participant observation. The distinguishing feature of ethnography, however, is that the researcher spends a significant amount of time in the field. The fieldwork notes and the experience of living there become an important addition to any other data gathering techniques that may be used.

Modes of Analysis

Although a clear distinction between data gathering and data analysis is commonly made in quantitative research, such a distinction is problematic for many qualitative researchers. For example, from a hermeneutic perspective it is assumed that the researcher's presuppositions affect the gathering of the data - the questions posed to informants largely determine what you are going to find out. The analysis affects the data and the data affect the analysis in significant ways. Therefore it is perhaps more accurate to speak of "modes of analysis" rather than "data analysis" in qualitative research. These modes of analysis are different approaches to gathering, analyzing and interpreting qualitative data. The common thread is that all qualitative modes of analysis are concerned primarily with textual analysis (whether verbal or written).

Although there are many different modes of analysis in qualitative research, just three approaches or modes of analysis will be discussed here: hermeneutics, semiotics, and approaches which focus on narrative and metaphor. It could be argued that grounded theory is also a mode of analysis, but since grounded theory has been discussed earlier, that discussion will not be repeated here.

1. Hermeneutics

Hermeneutics can be treated as both an underlying philosophy and a specific mode of analysis (Bleicher, 1980). As a philosophical approach to human understanding, it provides the philosophical grounding for interpretivism (see the discussion on Philosophical Perspectives above). As a mode of analysis, it suggests a way of understanding textual data. The following discussion is concerned with using hermeneutics as a specific mode of analysis.

Hermeneutics is primarily concerned with the meaning of a text or text-analogue (an example of a text-analogue is an organization, which the researcher comes to understand through oral or written text). The basic question in hermeneutics is: what is the meaning of this text? (Radnitzky 1970, p. 20). Taylor says that:

"Interpretation, in the sense relevant to hermeneutics, is an attempt to make clear, to make sense of an object of study. This object must, therefore, be a text, or a text-analogue, which in some way is confused, incomplete, cloudy, seemingly contradictory - in one way or another, unclear. The interpretation aims to bring to light an underlying coherence or sense" (Taylor 1976, p. 153).

The idea of a hermeneutic circle refers to the dialectic between the understanding of the text as a whole and the interpretation of its parts, in which descriptions are guided by anticipated explanations (Gadamer 1976, p. 117). It follows from this that we have an expectation of meaning from the context of what has gone before. The movement of understanding "is constantly from the whole to the part and back to the whole" (ibid, p. 117). As Gadamer explains, "It is a circular relationship. . . The anticipation of meaning in which the whole is envisaged becomes explicit understanding in that the parts, that are determined by the whole, themselves also determine this whole." Ricoeur suggests that "Interpretation . . . is the work of thought which consists in deciphering the hidden meaning in the apparent meaning, in unfolding the levels of meaning implied in the literal meaning" (Ricoeur 1974, p. xiv).

There are different forms of hermeneutic analysis, from "pure" hermeneutics through to "critical" hermeneutics, however a discussion of these different forms is beyond the scope of this section. For a more in-depth discussion, see Bleicher (1980), Myers (2004), Palmer (1979), and Thompson (1981).

If hermeneutic analysis is used in an information systems study, the object of the interpretive effort becomes one of attempting to make sense of the organization as a text-analogue. In an organization, people (e.g. different stakeholders) can have confused, incomplete, cloudy and contradictory views on many issues. The aim of the hermeneutic analysis becomes one of trying to make sense of the whole, and the relationship between people, the organization, and information technology.Good examples of research articles in IS which explicitly use hermeneutics are those by Boland (1991), Lee (1994), and Myers (1994). Myers (2004) provides an overview of the use of hermeneutics in IS research.

»References on Interpretive Research

2. Semiotics

Like hermeneutics, semiotics can be treated as both an underlying philosophy and a specific mode of analysis. The following discussion concerns using semiotics as a mode of analysis.

Semiotics is primarily concerned with the meaning of signs and symbols in language. The essential idea is that words/signs can be assigned to primary conceptual categories, and these categories represent important aspects of the theory to be tested. The importance of an idea is revealed in the frequency with which it appears in the text.

One form of semiotics is "content analysis." Krippendorf (1980) defines content analysis as "a research technique for making replicable and valid references from data to their contexts." The researcher searches for structures and patterned regularities in the text and makes inferences on the basis of these regularities.

Another form of semiotics is "conversation analysis." In conversation analysis, it is assumed that the meanings are shaped in the context of the exchange (Wynn, 1979). The researcher immerses himself/herself in the situation to reveal the background of practices.

A third form of semiotics is "discourse analysis." Discourse analysis builds on both content analysis and conversation analysis but focuses on "language games." A language game refers to a well-defined unit of interaction consisting of a sequence of verbal moves in which turns of phrases, the use of metaphor and allegory all play an important part.

At ICIS 1996 in Cleveland, the subject of The Merits of Three Qualitative Research Methods was discussed in a panel session. The Panel Session was chaired by Michael D. Myers, with Heinz K. Klein, Duane Truex and Eleanor Wynn as panelists. The presentation by Duane Truex on the subject of Text-Based Analysis Techniques is available.

A brief introduction to the use of semiotics in information systems is the book by Liebenau and Backhouse (1990). Wynn's (1991) paper is a good example of the use of conversation analysis in information systems, while Klein and Truex's (1995) paper is a good example of the use of discourse analysis in IS.

»References on Interpretive Research

3. Narrative and Metaphor

Narrative is defined by the Concise Oxford English Dictionary as a "tale, story, recital of facts, especially story told in the first person." There are many kinds of narrative, from oral narrative through to historical narrative. Metaphor is the application of a name or descriptive term or phrase to an object or action to which it is not literally applicable (e.g. a window in Windows 95).

Narrative and metaphor have long been key terms in literary discussion and analysis. In recent years there has been increasing recognition of the role they play in all types of thinking and social practice. Scholars in many disciplines have looked at areas such as metaphor and symbolism in indigenous cultures, oral narrative, narrative and metaphor in organizations, metaphor and medicine, metaphor and psychiatry etc.

In IS the focus has mostly been on understanding language, communication and meaning among systems developers and organizational members. In recent year's narrative, metaphor and symbolic analysis has become a regular theme in the IFIP 8.2 Working Group conferences, the proceedings of which are now published by Kluwer.

Features of Qualitative & Quantitative Research

Qualitative

Quantitative

"All research ultimately has

a qualitative grounding"

- Donald Campbell

"There's no such thing as qualitative data.

Everything is either 1 or 0"

- Fred Kerlinger

The aim is a complete, detailed description.

The aim is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

Researcher may only know roughly in advance what he/she is looking for.

Researcher knows clearly in advance what he/she is looking for.

Recommended during earlier phases of research projects.

Recommended during latter phases of research projects.

The design emerges as the study unfolds.

All aspects of the study are carefully designed before data is collected.

Researcher is the data gathering instrument.

Researcher uses tools, such as questionnaires or equipment to collect numerical data.

Data is in the form of words, pictures or objects.

Data is in the form of numbers and statistics.

Subjective - individuals� interpretation of events is important ,e.g., uses participant observation, in-depth interviews etc.

Objective � seeks precise measurement & analysis of target concepts, e.g., uses surveys, questionnaires etc.

Qualitative data is more 'rich', time consuming, and less able to be generalized. 

Quantitative data is more efficient, able to test hypotheses, but may miss contextual detail.

Researcher tends to become subjectively immersed in the subject matter.

Researcher tends to remain objectively separated from the subject matter.

Main Points

Qualitative research involves analysis of data such as words (e.g., from interviews), pictures (e.g., video), or objects (e.g., an artifact).

Quantitative research involves analysis of numerical data.

The strengths and weaknesses of qualitative and quantitative research are a perennial, hot debate, especially in the social sciences.  The issues invoke classic 'paradigm war'.

The personality / thinking style of the researcher and/or the culture of the organization is under-recognized as a key factor in preferred choice of methods.

Overly focusing on the debate of "qualitative versus quantitative" frames the methods in opposition.  It is important to focus also on how the techniques can be integrated, such as in mixed methods research.  More good can come of social science researchers developing skills in both realms than debating which method is superior.

Strategies of Inquiry & the Researcher's role

Strategies of inquiry focus on data collection, analysis, and writing.

Different strategies of inquiry such as case studies, ethnography, phenomenology, etc.

Qualitative researchers (inquirers) are involved in the natural settings and the field of study with intensive experience with participants.

See Fisher (2010) for more discussion on the role of researcher.

Ethical issues arise from such inquiries.

Data collection & gathering procedures

Identifying individuals and sites.

Identity types of data to be collected: observations, documents, interviews, documents, audio-visual materials

The use of protocols for recording observational data: observation protocol to register notes, interview protocol, hand-written notes, and visual and audio recorders

Data analysis and interpretation

Analysis of data is to make sense of the collected data through using analytical techniques to get into deeper understandings of the meanings in the text.

See Figure 9.1 at page 185.

Reliability, validity, and generalizability

Qualitative validity: means that the researcher checks for the accuracy of the findings by employing certain procedures.

Qualitative reliability: indicates that the researcher's approach is consistent (using reliability procedures) across different researchers and different projects.

Generalizability: the extent of data generalization to other contexts.

The Qualitative Write-Up

Reporting the results of a qualitative study is to develop descriptions and themes from the data.

Writing strategies: See pp. 193 - 194

Chapter 10 - Mixed methods procedures

A relatively new and distinct approach in social science research.

Evolution of research methodologies.

Interdisciplinary nature of research and diversity of researchers.

Expanded understanding of research problems.

More interest in mixed methods and the establishment of new journals i.e. Journal of Mixed Methods Research.

Combines the use of both Qual. and Quant. methods.

Both Qual. and Quant. data are also combined.

Look up Mixed Methods research

History and evolution, growth, and challenges.

Planning Mixed Methods procedures

Timing: data collected sequentially in stages or concurrently at the same time.

Weighting: priority or weight given to a either Qual. or Quan. method, might be equal as well.

Mixing: mixing Qual. and Quan. data is difficult since they reflect different data types (connecting, integrating, and embedding).

Theorizing or transforming perspectives: what theoretical perspective guides the design

Alternative strategies and visual models

Sequential exploratory strategy

Preferable strategy for a strong quantitative understanding.

Weight for quantitative data; it comes first.

Used to explain and analyze quantitative results followed by qualitative analysis.

Sequential explanatory strategy.

Similar to the explanatory strategy but rather reversed.

Sequential transformative strategy.

A two-phase strategy with a theoretical lens.

Either quan. Or qual. can come first.

Concurrent triangulation strategy.

Collecting both qualitative and quantitative data at the same time and then compare them to find any convergence, difference, or combination in them.

One phase, equal weight

Concurrent embedded strategy.

One phase to collect both qualitative and quantitative data simultaneously.

Priority is given to one of the two methods.

Secondary data is embedded within the primary.

Concurrent transformative strategy.

Guided by a specific theoretical lens.

Concurrent collection of both types of data

Data collection procedures

Identify the types of data.

Recognize that quantitative data often involve sampling.

Include detailed procedures in your visual model.

Data analysis and validation procedures

Data transformation: quantifying qualitative data by coding the latter data into themes and then count the occurrences of these themes in the text.

Explore outliers: previous data can yield outlier cases which need to be explored using another method.

Instrument development: you can use the themes and categories which emerge from the participants and develop a survey, for instance, for further research.

Examine multiple levels: collect data quantitatively focusing on a sample of families, and at the same time conduct interviews with individuals.

Create a matrix: combine concurrent qualitative and quantitative data into a a matrix to allow for comparison.

Report presentation structure

For sequential studies, researchers often organize the report into quan. data collection and quan. data analysis followed by qual. data collection and qual. Data analysis.

In concurrent studies, the quan. and qual. data maybe presented in separate sections but the analysis combines the two forms of data.

In a transformative study, the structure typically involves advancing the advocacy issue in the beginning either the sequential or concurrent structure as a means of organizing the content.