graphic design case study examples

Case studies are used in design research to analyze a phenomenon, to generate hypotheses, and to validate a method. Though they are used extensively, there appears to be no accepted systematic case study method used by design researchers. Considering its nature and objectives, the case study method could be considered as a suitable method for conducting design research. Many times, design researchers have to confront questions about the validity of using case studies and their results. The objective of this paper is to present a brief overview of case study method, compare it with other qualitative and quantitative research methods, and study the merits and limitations of using the same in design research. Requirements are derived from the general characteristics of design research. Four popular research strategies are evaluated with respect to the requirements. A preliminary benchmark study suggests that case study method is a suitable method for conducting design research.

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Proceedings of IDETC/DTM 2008

ASME 2008 International Design Engineering Technical Conferences

& Computers and Information in Engineering Conference

August 3-6, 2008, New York city, New York, USA

DETC 2008-xxxxx

CASE STUDY METHOD FOR DESIGN RESEARCH

Sudhakar Teegavarapu

Graduate Research Assistant

Mechanical Engineering

Clemson University

Clemson, SC 29634-0921

steegav@clemson.edu

Joshua D. Summers

Assistant Professor

Mechanical Engineering

Clemson University

Clemson, SC 29634-0921

joshua.summers@ces.clemson.edu

(corresponding author)

ABSTRACT

Case studies are used in design research to analyze a

phenomenon, to generate hypotheses, and to validate a method .

Though they are used extensively, there appears to be no

accepted systematic case study method used by design

researchers. Considering its nature and objectives, the case

study method could be a suitable method for conducting design

research. However, the „scientific method‟ of conducting

research is considered to be the only appropriate method. Many

times, design researchers have to confront questions about the

validity of using case studies and their results. The objective of

this paper is to justify the use of the case study method in

design research. A brief overview of case study method is also

included. Requirements are derived from the general

characteristics of design research. Four popular research

strategies are evaluated with respect to the requirements. A

preliminary benchmark study suggests that case study method

is most suitable for design research.

Keywords: Case study research, design research,

developing design methods/tools.

INTRODUCTION

Research must follow a systematic method for its results to

be valid [1]. The „scientific method‟ shown in Figure 1 is an

example of an established research method found in the natural

sciences [2]. This method resulted from an importance ranking

of activities performed by scientists while they do research [3].

Though this is not the only method that could be used to

conduct research, it is a generally accepted series of steps taken

by researchers in scientific domains. Design research as a

distinguished field of study requires its own research methods

[1]. Many unique characteristics, for example, the qualitative

aspect of design research, ought to be accommodated by the

method used to conduct research. The Validation square is an

example of a research method, particularly focusing on

validation of design methods/tools, which takes into account

both qualitative and quantitative aspects of design research [4].

There is a need for extending similar approaches to the entire

process of research in the field of design.

Figure 1: Scientific method of research [46]

Research in design is truly inter-disciplinary, with

influences from engineering sciences, sociology, psychology,

and economics. When researchers from different disciplines

come into design research, they bring a wide variety of research

methods particular to their field [1]. Though a few methods

from social sciences are being formally adopted and utilized in

design research, the „Social science view of design‟ is not yet

well developed [5]. Recently, the use of case studies for formal

design education has been suggested [6]. Though the case study

method is formally not incorporated into design research, its

use is widespread. DETC/DTM and DETC/DAC conferences

have published up to four papers with the phrase "case study"

in their titles every year from 2004 to 2007. Furthermore, there

were papers which report on case studies, but did not make it

explicit in their titles [ref]. Before the advent of formal „Design

research‟, design was mostly considered to be a skill or an art

[Asimov]. There have been numerous efforts to understand and

replicate good designs/designers [7, 8, 9]. Much of design

methods, tools and processes are a result of close and

meticulous observations collected over years from industry

[10]. One such design process that resulted from industry

observations is the German systematic design (GSD) [11]. The

research method used by the authors of GSD is not evident, but

can be safely assumed to be a large informal case study. This

case study would have utilized multiple modes of collecting

data, both qualitative and quantitative.

A brief review of design research focusing on its

characteristic features forms the next section of this paper. An

overview of methods used in design research is also included.

Case study is an established research method in social sciences

and is the focus of this paper. Its flexibility, applicability and

ease of use have made it possible to apply it in a wide variety of

fields. Case study research method is often considered to be

invalid, invaluable and improper [12]. It is a common

complaint that case study does not have a rigorous systematic

method. On the contrary, case study research has a systematic

method which is prescriptive. Later sections of this paper

introduce the case study method, some common

misconceptions about it and responses found in literature in its

defense. Thanks to the efforts of dedicated case study

researchers, it has been gaining popularity in recent years [12,

13, and 14]. The next section of this paper gives a description

of case study as a research method. This is followed by a

comparison with other available qualitative and quantitative

research methods. Advantages and limitations of the case study

research are discussed.

Case study research and design research exhibit similarity

between themselves in terms of their nature and evolution. Both

are used to serve non-quantitative aspects of the field to which

they are applied and are shadowed by the misconception that

theoretical knowledge is more valuable than practical

knowledge [14]. This and other aspects that make case study a

suitable method for design research are elucidated.

MOTIVATION

As part of research to propose a systematic approach for

developing design methods [15], the authors had to conduct

several case studies. Lack of a systematic method for

conducting, justifying, and validating results from case studies

posed problems. Upon a review of literature in social sciences,

it was observed that case study research is well developed and

had systematic methods for conducting and validating the work

[12]. This abundance of case study literature and striking

similarities between social science and design research

motivated the authors to implement case study method for

design investigation. The case study protocol explained in this

paper could serve as a template for researchers who find cases

study method suitable for their design research.

DESIGN RESEARCH

Engineering design research is a means to explore, describe,

justify, validate, and utilize design knowledge [16, 17, and 18].

Since its formation, design research has seen major changes in

its definition, scope, agenda, goals, criteria; many of which still

lack agreement among researchers [19, 20]. Early definition of

design was „a series of steps taken by designers to transform a

given situation into a preferable one‟ [21]. While many

researchers are inclined towards conceptual or epistemological

view, others have considered „design‟ from an empirical

perspective [20, 22, and 23]. In this view, design knowledge

has two components: scientific knowledge and tacit human

knowledge [24] . Design research is engaged in many strands,

notably:

1. Prescriptive models of design process

2. Descriptive models of design

3. Computer based models of design processes

4. Representations for design

5. Analysis supporting design

6. Design for X [25, 26].

Attempts to scientize design by following the „scientific method

of research‟, shown in Figure 1, resulted in identification of ten

scientific area classifications [27]. This classification was

intended to make design research systematic, by dividing it into

smaller focus areas. Many considered design as a highly

complex activity; it cannot be compared with any existing field,

cannot adopt paradigms from any known areas of research and

hence could not accept the scientific classification scheme. Due

to its wide scope and relatively young age, design research

could apparently look chaotic, but has a hidden order [24].

Major objectives of conducting design research are grouped in

to five main categories viz., (1) empirical research, (2)

Experimental research, (3) Development of new tools and

methods, (4) Implementation studies and (5) Others, which

include design theory and education. The inter-relationship

between these objectives is shown in Figure 2 [22]. A high

level taxonomy of design research would include design

epistemology, design praxiology and design phenomenology

[28 ]. As true with any other type of research, design research is

constituted to be purposive, inquisitive, informed, methodical,

and communicable [29]. It is noted that imposing such

requirements on design research would only lead to rejecting

research work that is sub-standard, invalid and irrelevant and

does not hinder any quality development [29].

Figure 2: Design research objectives [30]

METHODS USED IN DESIGN RESEARCH

Need for an established method for conducting design

research has been emphasized by many authors [4, 22, 1, 20,

23, and 29]. It is important to have a systematic method for

conducting research, so that the results are valid and accepted

[1]. Design research shares its characteristics with a wide

variety of domains like computer science, engineering science,

psychology, economics, sociology etc, yet is peculiar from

every one of them. This peculiarity makes adaptation of

research methods from a single or a collection of few fields,

which could fit into the context of design research, almost

impossible. It has been observed that researchers from

computer science and psychology, who were with a view that

design research is no different than their own respective fields,

had to change their perspective [29]. Use of research methods,

which are not suitable, could degrade the quality of design

research [29]. It is important to differentiate between the

conceptual and empirical perspectives of design research.

While conceptual perspective of design research deals with the

philosophical ideology, which is nevertheless significant, the

empirical perspective looks at systematic ways of conducting

design research [ 22]. There is an increase in researchers

looking at social science, with an intention to try and

implement some of its methods into design research [1, 22 and

29]. Methods used in design research have to satisfy the general

criteria of soundness [30], viz.

1. Credibility or Internal validity

2. Transferability or External validity

3. Dependability or Reliability

4. Objectivity or Confirmability

Both qualitative and quantitative methods are being used

in design. Quantitative methods are positivistic in nature. The

goal of quantitative methods is to find objective data by

investigating in a scientific fashion. While using these methods,

the researcher acts as an external observer. Qualitative methods

are anti-positivistic. They deem subjectivity of researcher as a

significant factor in analysis. Though qualitative methods are

more suitable for research in a field involving human

interactions, such as design, quantitative methods contribute in

their own way [20]. The methods used for research in design

fall into the three broad categories [1], viz.

1. Methods used to observe designers while they are doing

design

2. Methods used to interview or survey designers

3. Methods used to analyze documents generated during the

design process.

Table 1 is a list of methods that are used in design research.

Methods that are most frequently used are explained in the

later parts of this section. Several of these methods,

highlighted in the table, are examined below.

Table 1: List of research methods

Individual / group

Interview

Written survey

Survey can be of two types; a written survey (questionnaire)

and an interview. Each has their own advantages and

limitations. Written surveys are quantitative and cost effective

but give enough time to respondents to form their responses.

Turn around rate is typically low for a written survey. Written

surveys are one of the most used research method in design.

Interview

Interviewing is a type of qualitative research method in which

the observer gathers data from a participant through a question

and answer process. Interviews can be structured or

unstructured. Structured interviews help in quantitative data

collection, while unstructured interviews are qualitative.

Interviews require a personal sensitivity and adaptability while

staying within prescribed protocol limits. Interviews give the

observer an opportunity to ask follow-up questions.

Ethnographic study

Ethnographic study is a field research technique in which the

observer immerses self into the situation under study. For

instance, for an ethnographic study to understand the design

process of a company, the observer appoints himself as a

designer in that company [23]. Even as the traditional

techniques of ethnographic studies are not being used in design

research, the fundamental principle is maintained [ 31]. This

type of research method has to be applied with care as they can

turn out to be infeasible in terms of time taken and cost [ 31].

Experiential analysis

Experiential analysis is a practice in which designers develop

theories based in their own experiences. In the field of design

research, „Engineering design: A systematic approach‟ by Pahl

& Beitz is a popular example of experiential analysis. Other

variants of this method, for example, „focus groups‟ is also

getting popular among design researchers.

Protocol analysis

Protocol analysis is a type of experimental method in which

designers are observed in a controlled laboratory environment.

There is an increased thrust in using protocol analysis for

design research as it seems to be closer to scientific method.

Recently, there have been concerns raised against protocol

analysis, as it is said that they do not depict designers in actual

practice [23] .

Surprisingly, design research literature does not mention case

studies as a suitable method. Yet, according to a survey of

ICED conference papers, 46.9 % used case studies, while

43.5% used surveys in their articles. Several authors have

emphasized numerous advantages of using case based approach

in design research [32].

CASE STUDY AS A RESEARCH METHOD

Case study is probably one of the most criticized social

research method. Despite it being stereotyped as a weak,

imprecise, objective and rigor less method [ 12], it is being used

extensively in a wide variety of fields, including design

research. Case study can be defined as an empirical research

method used to investigate a contemporary phenomenon,

focusing on the dynamics of the case, within its real life context

[12, 20]. Case study could be exploratory, descriptive or

explanatory.

Case study as a research method should not be confused

with (1) case studies used for teaching, (2) ethnographic

studies/ participant- observant studies and (3) case study as a

form of record keeping. While other methods focus on certain

specific phases of research like (1) problem definition, (2)

formation of hypothesis, (3) data collection or (4) data analysis

etc, case study is an all-encompassing method that covers all

these phases. Case study is an ideal method, when

1. The aim of research is to find answers to „why‟ and „how‟

types of questions

2. It is not possible to control the behavioral events

Contemporary events are studied.

Table 2 compares case study with other social research

strategies. It can be seen that experiments and historical studies

also address the same type of research questions, but the former

requires control over the behavioral events, while the later does

not deal with contemporary events. Hence, case study is the

only suitable method under the prescribed conditions.

Table 2: Choice of research strategy

Type of

research

question

Requires

control of

behavioral

events?

Focuses on

contemporary

events?

Who, what,

where, how

many, how

much?

Who, what,

where, how

many, how

much?

Case studies are specifically used in situations where the

contextual details have to analyzed, but the phenomenon is not

distinct from context. Many other research methods fail when

put to use in studies where the variables of analysis are more

than the data point [12]. Case study method recommends

triangulation of data by giving the observant an opportunity of

collecting data using different techniques, such as a survey,

interview, experiment etc., all under a single study [13].

It should also be noted that case study is not a qualitative

method of research. It is an empirical method and could be

limited to entirely quantitative or qualitative data, depending

upon the case being studied [13]. Case study method does not

enforce sample logic; there could be a single case from which

generalization is made. Multiple cases could be analyzed under

a single case study, referred to as „multiple - case study‟, in

which case selection of cases is based on repetition logic, rather

than sample logic [ 12]. Case studies could be conducted with

various goals, such as to describe a phenomenon, test theory or

generate a theory. They could also be implemented at multiple

levels of analysis [13]. Several social researchers had

emphasized on varying characteristics of case studies, such as,

(1) case study as a theory building method [13] and (2) case

study as a research strategy [12]. Design research could benefit

from the view of case study as a research strategy. Applicability

of case study as a research strategy could be mostly attributed

to its design procedure, which is outlined in the following

section.

CASE STUDY DESIGN

Figure 3 shows a typical case study method, describing

generic high-level st eps taken by a researcher while performing

a case study.

Figure 3: Case study method

As shown in Figure 3, case study method could be categorized

into three distinctive phases: (1) Define & design phase, (2)

Prepare, collect &Analyze phase, and (3) Analyze & conclude

phase. Phase 1 involves design of case study protocol. This

phase includes a complete plan and rationale for methods used

to select specific cases, form hypothesis, build rival theories,

collect and analyze data, and interpret findings. Design of a

research method defines its success. At the outset, the case

Identify/define problem

build theory

select cases design data collection

protocol

Conduct single/multiple case

studies

Write individual case report

Draw cross case conclusions

Compare with rival theories

Modify theory if required

write cross case report

Prepare,

Collect

Analyze

study method may look like the generic process followed by

design researchers in their respective investigations. However,

the essence of case study lies in its design, the idea of which is

not rigorously implemented in the field of 'design research' .

After laying out a complete design, the researcher conducts the

case study in phase 2. This phase involves preparation, data

collection, and writing individual case reports (in case it is a

multiple-case study). Phase 3 mainly involves writing case

study reports by drawing conclusions from various cases

studied (single or multiple).

Upon comparison of case study method with the scientific

method, similarities between the two can be identified. They

mostly vary in the data collection techniques used; while the

scientific method strictly uses experiments, case study method

could use any/all of the data collection methods explained in

the previous section, including an experiment. Both methods

prescribe forming a hypothesis, even before the study is

undertaken. Case study research emphasizes more on

hypothesis formulation, often referred to as „Theory building ‟

[13]. There is one major difference in terms of reporting the

results. Scientific method recommends reporting results,

provided, they satisfy observer‟s aims. In other words,

scientific method only reports success. Failures of experiments

are not reported [3]. Case study method recommends reporting

all results of a study, even if they prove the initial hypothesis

wrong. It is interesting to note that most of the case studies use

a falsification logic , wherein the observer tries to prove that the

initial hypothesis is wrong [14].

Among the three phases of case study method, described

above, phase 1, which is the design phase, is probably the most

important. Every empirical research method has a design,

sometimes implicit. It is the logic connecting the data gathered

during the study, to the study‟s questions. Since the readers are

now familiar with case study research, it is worthwhile to

describe critical considerations, which should be kept in mind

while designing a case study. The following five components of

research are significant for case study design and therefore its

success:

 Case study questions

 Case study propositions (Similar to hypothesis)

 Units of analysis

 Logic linking data to propositions

 Criteria to interpret case study results [12]

Case study questions

Case studies are most suitable for „how‟ and „why‟ types of

research questions. Before getting ready to conduct a case

study, the observer should have the questions articulated. This

is the most time consuming part of case study design upon

which the success depends, and thus should be done

meticulously. For example, for a case study on development of

design methods [15], questions could be formulated as follows:

1. How are design methods currently being developed?

2. Why is the generic design process not used while

developing design methods?

Case study propositions

Propositions are needed to guide the researcher into the right

path. They help the researchers in narrowing down the scope of

the study, limiting them to the boundaries of the issue being

studied. Propositions also help in pointing the researcher to the

source of evidence. Without a proposition, the researcher would

have to gather all the information possible, while conducting a

case study, which is almost always infeasible. It is

recommended to build, preferably, multiple „rival‟ theories

from these propositions [12]. Considering the same example of

development of design methods [15], some of the propositions

could be:

1. Designers do follow a systematic method, though it is not

apparent, as the documents that are generated during the

process focus on results, rather than methods.

2. The generic design process could be applied to develop

design methods, because some of their attributes, for

example, the requirements, constraints, criteria, and goals

are comparable to the ones of a physical artifact.

Units of analysis

Unit of analysis is the definition of the case being studied;

individual, group, organization, event, process. Definition of

the unit of analysis depends on the research questions

developed before starting a case study. Research design and

data collection procedures have to be modified according to the

units of analysis [12].

Logic linking data to propositions

This is an important step in data analysis during a case study.

Data analysis helps in examining, testing, verifying,

interpreting, and categorizing various qualitative and

quantitative data collected during a case study. While other

research methods leave this as a grey area, case study research

method prescribes specific methods for data analysis and

interpretation. In order to effectively analyze case study data, it

is recommended to decide on a strategy during case study

design. Three such analytic strategies , which determine „what‟

and „why‟ to analyze are:

1. Relying on case study proposition formed in the initial

stages.

2. Formulating rival theories

3. Forming description for organizing the findings [12].

Strategies 1 and 2 require formulation of propositions/ theories.

The data is then analyzed to verify which proposition/theory it

supports. This process, called analytic generalization, is used

for case studies, in contrast with statistical generalization used

for surveys and experiments, as illustrated in Figure 4.

Figure 4: Linking findings to theories (adopted from [12])

Statistical generalization

The third strategy is to form a description of case. The

description could be viewed as a case study report. Case study

data could be organized into different chapters of the report,

fixed a priori. This is the least preferred analytic strategy, and

should be used only when applying other strategies becomes

difficult. Once the strategy is fixed, one of the following

analytic techniques could be used in conjunction with it:

1. Pattern matching

2. Explanation building

3. Logic models

4. Time series analysis

5. Cross-case synthesis [ 12]

While the first four techniques could be used with single and

multiple-case studies, cross-case synthesis is suitable only for a

multiple-case study.

Criteria to interpret case study results

Data collected through the case study need to be classified

under various theories as mentioned above. The criteria for this

classification have to be well defined a priori, no matter which

type of analytic strategy and techniques are being implemented.

In case defining these criteria precisely becomes difficult, it is

recommended to formulate well distinguishable theories, rather

than theories with subtle difference [12].

Due to space constraints, case study method could not be

explained in more detail in this paper. Literature on case study

research is recommended for further reading [12, 13 , and 14].

COMMON OBJECTIONS AND RESPONSES

Despite being widely used, case study method is often a victim

of derogatory criticism [12]. This section provides responses

found in literature for major objections to case study research

method. Four of the numerous questions, which design

researchers face when they use case studies in their

investigations, are elaborated. It is nevertheless important to

have clarity, in order to justify the use of methods in our

respective research.

One cannot generalize from a single case.

This is probably the most frequent objection to case study

research. Case study is not based on sample logic; the aim is to

attain analytic, not statistical generalization. An analogous case

of analytic generalization would be a scientific experiment.

While generalizing their scientific theories, prominent

researchers like Galileo, Newton, and Darwin did not conduct

experiments until they reached a statistically valid sample size.

Rather, they proposed generalized theories based on few

replicated experiments. Similar to an experiment, it should be

noted that the aim of a case study is not to propose a theory that

is universally valid, but to arrive at a theory that is valid for the

set of propositions [12]. In some cases, scientists have produced

generalized theories based on a single experiment. For

example, Galileo view of gravity is believed to be based on the

„Pisa tower‟ experiment. Galileo should be acknowledged for

choosing the experiment wisely that one „critical‟ case was

sufficient to prove that earlier view of gravity was flawed [14].

Similarly, while conducting case studies, one should select

cases which are „critical‟ [12]. Case studies are in-depth,

allowing the researcher to observe details, which are otherwise

not possible. This characteristic of case study could be utilized

to implement falsification logic. According to falsification

logic, if a theory is not true for one case, it cannot be generally

true. Case studies are very efficient in identifying the one case

for which a theory would not be true [33]. Hence, it is possible

to generalize from a single case; depending on the case and the

way the case is chosen [33].

Case study research lack rigor.

It is a common concern that case study research does not

provide strict, systematic guidelines and therefore lacks rigor.

From the previous sections of this paper, and from the case

study literature [12], the reader probably is convinced that case

study research method prescribes specific techniques to be

followed during each stage of the investigation. Most often,

case study researcher does not show thoroughness, does not

follow the guidelines specified, and does not analyze and report

data correctly. This lack of rigor on the part of the researcher

overshadows case study method. Also, case study as a research

method is many times confused with case studies used for

teaching [12]. The case studies used for teaching are

manipulated to focus on specific issues that the teacher wants

the students to learn about. It may seem that those case studies

used for teaching are biased, are not systematic and lack rigor.

Bad experiences with case studies used for teaching often lead

to rejection of case study as a research method in general.

Case studies take long time.

It is believed that case studies take a long time to be completed.

Also, researchers complain that they often result in large

number of documents that are never put to use. A case study

may lead to such situation if it is carried out without firm

propositions. As mentioned in the previous sections of the

paper, the case study propositions guide the researcher towards

required data and its source. If a researcher develops valid

propositions and follows them rigorously, unnecessary and

invalid data would not be gathered during a case study. Also,

case study research method specifies particular techniques for

writing case study reports that does not consume large amount

of time [12].

Case studies are biased.

Case studies are considered to be influenced by the subjectivity

of researcher and hence are believed to be biased. Every

research method, including the scientific method involves some

form of subjectivity [3]. In fact, there are two good reasons for

rejecting this objection on case studies. Firstly, most of the case

studies utilize falsification logic, wherein the researcher tries to

prove his hypothesis wrong. Hence, a researcher is not biased

in his observation in order to prove his pre- conceived notion.

Secondly, case studies use triangulation technique which

requires data from multiple sources of evidence, using multiple

data collection techniques to converge [ 12, 14]. This helps to

remove any biases induced by researcher‟s subjectivity.

Triangulation works better with a case study than any other

form of quantitative research method, as they use only one data

collection method. Hence, the allegation that case study results

are biased is false.

JUSTIFYING USE OF CASE STUDY METHOD FOR

DESIGN RESEARCH

Case studies are long being used in design research

investigations. A review of publications in Journal of

engineering design, reports an increase in use and acceptance

of case based research, both by industry and academia [32].

Most of the case studies in design research are either

exploratory or are done as part of a validation study. However,

case study as a comprehensive research method is not widely

accepted in design research. As mentioned earlier, the aim of

this paper is to shed light on the appropriateness of case study

method for design research. In order to accomplish this task:

1. General soundness of method is verified.

2. Case study is compared with three other most used methods,

against the characteristic requirements of design research.

General soundness of case study method

Any empirical research method has to satisfy certain

criteria for soundness [12]. These criteria for soundness

were mentioned in a previous section of this paper. Case

study method offers unique tactics to address these four

criteria as shown in

Table 3.

A case study‟s construct validity test makes sure that the

change being studied and measures that reflect this change are

well defined [12]. Case study method uses multiple sources of

evidence and also establishes a chain of evidence to tackle

construct validity. Internal validity tests the procedure of

making inferences from case study findings. Case study

recommends the use of analytic strategies and analytic

techniques for addressing this criterion. External validity tests if

the case study results could be generalized to external

problems. This criterion could be satisfied by formulating

theories (or rival theories) for a single case study and following

replication logic for multiple-case studies. Reliability is

concerned with the repeatability of case study findings.

Repeatability of a case study could be improved by following

standard guidelines, formulating a case study protocol and

following the same for multiple cases [12].

Table 3:Soundness of case study method(adapted from [12])

 Use multiple sources of

evidence

 Establish chain of evidence

 Let key informants review

case study reports

Data collection

Report

generation

 Do pattern matching

 Do explanation building

 Address rival explanations

 Use logic models

Data analysis

 Use theory in single- case

studies

 Use replication logic in

multiple-case studies

Research

design

Research

design

 Use case study protocol

 Develop case study

database

Comparison of case study method

Being convinced with the general soundness of case study

method, we now verify its suitability for design research. As

mentioned in the early sections of the paper, in order to deem a

method suitable, it has to satisfy the unique characteristic

requirements of design research. Following are characteristics

of design research that makes usage of any empirical method a

challenge:

1. The sample sizes are statistically invalid [1].

2. Number of variables is greater than data points.

3. A design task cannot be appropriately replicated /simulated

outside its real life context.

4. Intrusion by external factors, including a research method,

would affect the design process.

5. Direct observation of variables is many times impossible

[1].

6. There is no fixed measure of success in design [1].

7. Each case and each participant are different [1].

8. Some of the decisions made by designers, many times

based on their intuition, could not be explicitly justified.

9. A design task cannot be performed twice without the effect

of learning bias [1].

10. The units of analysis are highly complex [1].

11. Design lacks a firm theory, which makes it difficult to

setup a hypothesis [1, 20].

12. Definition of variables is difficult [1].

13. Variables and influences are highly interconnected [1].

The characteristics enumerated above lead to a list of

requirements for a research method to be adapted into design.

The method should:

Problem definition

1. Help in defining the problem

2. Help in formulating a hypothesis

3. Help in building theories

4. Help in defining units of analysis

Data collection

5. Be appropriate for statistically invalid sample sizes

6. Work well even when variables are more than data points

7. Aid in collecting data within the context of design

8. Accommodate indirect observation of variables

9. Elicit implicit and explicit data from the subject

10. Be adaptable for both qualitative and quantitative types of

data collection

Data analysis / Interpretation

11. Include specific techniques for data analysis and

interpretation

12. Help in generalization of study‟s findings

13. Provide means for validation of findings

General

14. Be minimally intrusive

15. Work well with variety of cases within the study

16. Work well with variety of participants within a case

17. Facilitate use of multi-method approach

Case study method is compared to three other empirical

research methods with respect to the above mentioned

requirements as shown in Table 4.

Table 4: Comparison of case study with other empirical

research methods

Characteristic

requirements

Help in define the

problem

Help in formulate

the hypothesis

Should help in

constructing

theories

Should aid in

collecting data

within context

Should be

appropriate for

statistically

invalid sample

sizes

Variables greater

than data points

Should

accommodate

indirect

observation of

variables

Should be

adaptable to both

quantitative and

qualitative studies

Should be able to

elicit implicit and

explicit data from

the subject

Should help in

data

analysis/interpret

ation

Work well with

variety of cases

within same

study

Work well with

variety of

participants

within same

study

Facilitate use of a

multi-method

approach

Should provide

means for

validation

Should help in

generalization of

findings

Should be

minimally

intrusive

From Table 4 it could be inferred that case study method is

the only method which could address all the requirements set

forth by design research. From the previous sections of this

paper, it could be noted that the case study method is an

effective way of doing research while dealing with problems

involving human interaction. Case study method has specific

procedures, techniques and strategies for conducting a

systematic empirical research. It could be considered as the best

available method for constructing theories and generalizing

study findings. Case study method does not need a large

sample, aims for analytic generalization, utilizes multiple

methods of data collection/analysis, and triangulates data. It

does all the above within the context of the problem, with

minimal intrusion whatsoever. Case studies are limited by the

representativeness and generalizability of the cases. They

cannot predict the average 'causal' effect of variables across

all the cases [33]. They also suffer from a selection bias [33].

These limitations should be considered while using the case

study method in design research.

CONCLUSION

Case studies are gaining popularity and are being widely

used in design research. While most of the applications are

related to teaching design and doing exploratory studies, the

scope of case study as a systematic research method is often

ignored or under estimated. Recently, there has been an

increased thrust to introduce methods from social science into

design research. While other empirical methods are in

consideration, case study method seems to be ignored.

Advantages of case studies overshadow the limitations of

statistics-based research methods like surveys. Case study

method is often a victim of negative criticism. It is shown that

major objections to case study method are invalid. At a higher

level, case study method illustrated in this paper is similar to

general steps taken by design researchers. However, the

essence of the case study method lies in its design, which is

often not rigorously followed. Case study method stipulates the

use of specific techniques at each phase of research. Following

these guidelines is critical for the validity of case study

findings. Based on objectives and requirements derived from

the unique characteristics of design research, it can be seen that

case study method is more suitable than survey, interview or

experiment. Case study method is particularly suitable for

developing theories, which is the need of the day in design

research. An attempt is made through this paper to formally

initiate the adoption of case study method into empirical design

research. Case study method could effectively fill the void that

exists due to the lack of a formal method of conducting

systematic research in design.

FUTURE WORK

This paper could be considered as a preliminary capability

analysis of case study method with respect to requirements of

design research. Though it is generally acceptable, parts of case

study method have to be defined / tweaked specific to design

research. In order to be able to generalize results from a study,

it is recommended to select a critical case. Little guidance is

offered with respect to procedure of finding a critical case. This

problem is more profound in the context of design, as there are

no definitive critical cases available for us to study. Developing

guidelines for selecting cases in design research is a part of

future work. The next step is to conduct case studies, following

the systematic procedures mentioned in this paper, to arrive at

specific guidelines to develop design methods (mentioned in

motivation).

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... • Case study research has been widely used in Operations Management (Voss et al. 2013) and there are several articles using this methodology when analysing issues related to this discipline (Crute et al. 2003;Slomp, Bokhorst, and Germs 2009;Deflorin and Scherrer-Rathje 2012;Westin, Chronéer, and Segerstedt 2013;Matt 2014;Thomassen, Alfnes, and Gran 2015). • A case study is also considered to be a suitable method for design research (Breslin and Buchanan 2008;Teegavarapu, Summers, and Mocko 2008;Veisz et al. 2012) and it has also specifically been employed in research related to sketching (Jonson 2005;Veisz et al. 2012;Petersson, Lundberg, and Rantatalo 2017). • Likewise, authors as Kitchenham, Pickard, and Pfleeger (1995) and Schippers (2000) present this model as ideal to evaluate the applicability of certain methods or tools for the improvement of industrial performance, as pursued by this research. ...

... Interviews enable the main actors in the process to participate in information generation, as research requires attitude, perception, motivation, knowledge and/or behavioural data, for which responses from personnel are therefore ideal (Snow and Thomas 1994;Voss et al. 2013;Teegavarapu, Summers, and Mocko 2008). This research opted for semi-structured interviews, using flexible questionnaires to better record different interviewee's viewpoints and to open the field of study to new perspectives (Fontana and Frey 2005;DiCicco-Bloom and Crabtree 2006;Jonsen and Jehn 2009;Punch 2013). ...

... Finally, in the last month of the investigation, the research team arranged another last analysis meeting to accomplish a triangulation and compilation process of both the quantitative and qualitative analysis (Creswell et al. 2003;Denzin and Lincoln 1994;Jonsen and Jehn 2009;Robson 2002;Voss et al. 2013;Yin 2003;Teegavarapu, Summers, and Mocko 2008). The staff of the company directly involved in the project, together with the customer by videoconference, also participated, offering their final contributions and validating the final results of the research. ...

The identification of new applications for sketching and freehand drawing in the field of engineering is a subject of interest for researchers and practitioners, especially after a significant drop in use in the conceptual design processes due to the expansion of CAD systems. A new opportunity for research arose when an industrial company, belonging to the machine tool sector, in the scope of Engineered-To-Order (ETO) production systems, introduced sketching into the first conceptual design stages of a new field: the Order To Delivery (OTD) process of customised manufacturing solutions. A research team carried out a case study, combining both quantitative and qualitative analysis, to evaluate the impact of this innovative application. The results prove the value of sketching to enhance delivery times and reduce reprocessing and correction times. This relatively quick and economical tool enabled the company to work more closely with the customer and to reduce the variability and uncertainty problems linked to ETO systems. Hence, these findings are interesting both for the scientific community and for companies with a similar ETO production type. First of all, to further expand this new application, and also, to give sketching the place it deserves as an operational tool.

... In hydrology watershed process is fully based on three different characters of DEM such as (1) area Features (size, shape, and slope of the area), (2) length of the channel network and stream, and (3) elevation of the mainstream which was automatically extracted from DEMs is varying with using different resolution [50]. (Teegavarapu et al., 2008), [51] used two DEM resolutions, to define the watershed boundaries 10m and 90m. The different sources and resolution of DEM data may affect the outcomes of hydrological model and the investigated the effects of DEMs resolution on driving topographic and hydrological attributes based on generating stream network and watershed [52]. ...

... In addition to reducing the risks of unrepresentativeness and inadequacy of nonprobability, the purpose of such a large sample in a single case was to achieve a repetition logic in place of a sample logic in scientific surveys. With a large sample, our explanatory case study stands in a better stead of yielding a more holistic knowledge and giving a clearer picture of our research objectives (Teegavarapu and Summers, 2008). Questions were guided by falsification logic such that respondents could freely negate research presumptions, as against the analytic logic that is said to foster generalisations. ...

Chike F. Okolocha

Intersectionality is discussed as a harvest of multiple disadvantages and deprivations by majority of urbanites. Parameters of disadvantage include cash poverty, poor health, lack of electricity, water and sanitation, proneness to crime and illiteracy, unemployment and underemployment. The study adopted a mixed method model and proceeded with a structured questionnaire administered to a sample of 1022 respondents in Upper Saponba area, the largest slum district in Benin City, southern Nigeria. Supplementary data were collected through in-depth interview with a purposive sample of 10 community members. Results seem to negate the culture of poverty hypothesis even as many poor residents express despair on the prospects of a good life in the city. This desolation coincides with new public policy by which governments withdraw from public space in the face of increasing poverty. We conclude that social intersectionality in urban Africa is a simultaneity of poverty and deprivations exacerbated by exclusionary public policies. Effectual public policy will depend on a recognition of the inter-linkages between parameters of disadvantage, deprivation and social exclusion.

... It emphasizes the design and Mass customization construction of the proposed artifacts (i.e. the production information system in this study), where the development process is a search process drawn from existing knowledge (Peffers et al., 2007). Using a case study under the paradigm of DSR also helps to explore the contextual details of the research question (Teegavarapu et al., 2008). In this manner, the system flow (i.e. ...

Purpose: In response to increasing demand for a fully customized and individualized home environment, mass customization (MC) has been suggested as an effective strategy to fulfill the customer's customization needs while keeping production cost-effectiveness. However, in current practice, the implementation of the MC in the industrialized housing industry has not achieved an ideal level. Little effort was devoted to customer value generation and achieving lean production in a multi-disciplinary MC environment. In this concern, a highly efficient and flexible production information system is expected to capture accurately the customer's demand and efficiently perform work planning for encouraging customer involvement and mass efficiency production. Design/Methodology/Approach: To gain an insight into the development of the MC production information system for the housing industry and to depict the interaction among system modules, this study used a design science research (DSR) methodology for a case study of customized cabinet production information system development. Findings: A prototype of the production information system was proposed in this paper, supported by three information technologies to facilitate the MC implementation in the millwork manufacturer. A focus group discussion (FGD) method was carried out for evaluating the system feasibility and the subsequent survey analysis on the virtual reality (VR) interface experiment. The evaluation process results showed that the VR interface is an effective medium for design information communication and encourages customer involvement. Most participants believed that the proposed production information system could generally benefit the MC implementation and improve production efficiency. Originality/Value: This study integrated lean production principles along with building information modelling (BIM), virtual reality (VR), and discrete-event simulation (DES) in the production information system to assist the manufacturer in effectively handling variant product information and enabling quicker reactions in response to diverse customer requirements in housing industries. The coordination among system modules and the managed information flow could be a valuable reference for future MC production system development in housing industries.

... Descriptive case studies, for example, make a significant contribution to understanding design processes and gaining detailed information on the application of methods, because they do not focus on single aspect. Case studies are especially helpful to identify phenomena only observable within a practical context (Teegavarapu, Summers, and Mocko 2008). This is because they form an important component in comprehensive design method validation. ...

Validation of design methods is a challenge in design research, as there is a lack of common methodology. This contribution investigates how validation of design methods is currently conducted in order to clarify this issue and identify approaches that might be suitable as best practices. A mixed-methods literature study including the years 2010–2020 is conducted. Systematic mapping structures the identified literature in an overview. The following state-of-the-art review focuses on challenges in validation and on how researchers address them. The overview of 54 identified studies shows a preponderance of non-comparative studies conducted in laboratory environment. Challenges arising in conducting experiments and field studies are caused by a lack of common metrics and established study designs. In success evaluation, the challenge is to objectively measure the effects of method application on the design outcome. Based on the identified examples, possible strategies to overcome the challenges are proposed.

... This research consists of a case study of CRISPR regulation, which is selected as an instance of regulatory policy of emerging technologies. The use of case studies in design research has been widely discussed (Chow 2008;Teegavarapu, Summers, and Mocko 2008;Hathaway and Norton 2018). Case studies provide a way to investigate in detail how outcomes originate from the joint occurrence of process features and context factors (Barzelay 2007). ...

Externalities and uncertainty play an important role in the design of regulatory policies. Regulatory tools must be selected while taking into consideration the side-effects that regulated products or services have on other individuals and on the environment. This study investigates the externalities and uncertainty that arise from the use of genome editing (with specific reference to CRISPR technique) and how they relate to regulatory policy design choices. Building on evidence from genome editing regulation and on the NATO (Nodality, Authority, Treasure and Organization) policy tools framework, this study argues that a mix of regulatory tools is required to tackle externalities of genome editing applications and to cope with sources of uncertainty about their beneficial, neutral and harmful side-effects. The study provides some recommendations to policy-makers about reducing uncertainty, diversifying regulatory tools over time, and communicating to the public about features of genetically edited products.

Public lighting connects hundreds of millions of streetlights with access to power across the globe, being responsible for 19% of global electricity usage, 30% - 50% of a typical city's energy bill and the already exceeding levels of CO2 emissions. Consequently, this represents a priority issue for cities in their strategy towards sustainability. In this framework, the momentum for smart public lighting is growing as its implementation represent quick wins (such as increase security and safety, improve mobility, increase the attractiveness of public spaces, or improve quality of life for citizens) with a massive impact on energy savings and maintenance, and can be achieved through low-cost connectivity. This paper discusses the effectiveness, efficiency, and feasibility of any city establishing a smart public lighting infrastructure network. With this aim, a pilot intervention in San Sebastian's public lighting network is presented together with a holistic analysis based on the Value Creation Ecosystem (VCE) and the City Model Canvas (CMC) to visualise how such plans may offer public value with a long-term and sustainable approach. Additionally, relevant, and fundamental patterns and recommendations are provided, which may help other public managers effectively implement this service and scale-up its use and business model.

Ahmed Syed
Syed Ahmed Hasnain

This study looks at instructors perceptions of blended learning (BL) at a Medical School (MS) in one of the Gulf Cooperation Council (GCC) countries. The study also looks at the effects of instructors perceptions on implementation of BL in the classroom. And the effect of student perspectives on instructors perceptions of BL. The study is important as it looks into the impact and effectiveness of technology in the classroom, from an instructor's perspective in the GCC. The study also captures how an instructors' experiences with technology effect their practice in the classroom. The target populations of the study are eight instructors and five students. Data analysis starts with narratives of each instructor to give the reader an idea of their background, and technology usage preferences.

Sudhir D. Shivankar
R. Deivanathan

Changes in a product are necessary to guarantee high quality product and to remain competitive in the market. Engineering Change Management process ensures planning and implementation of changes effectively. Product design changes may be required in each step of product life cycle from its design to decline phase. Different tools are developed to study change propagation impact. Product architecture and change propagation path selection are the main focus areas found in methodologies developed for change management in recent years. Still, the manufacturing industry is facing challenges to control changes in implementation phase. A case study is conducted in an automotive company to understand perceived effect of product design change in manufacturing environment. Results of case study draws attention towards concerns reported, starting from raw material planning to disposition of changed part and the need for prediction of change in implementation phase across the functions, as well as in complete supply chain of automotive industry. Change propagation tools can be, if needed, extended from design phase to manufacturing environment.

Bent Flyvbjerg

This article examines five common misunderstandings about case-study research: (1) Theoretical knowledge is more valuable than practical knowledge; (2) One cannot generalize from a single case, therefore the single case study cannot contribute to scientific development; (3) The case study is most useful for generating hypotheses, while other methods are more suitable for hypotheses testing and theory building; (4) The case study contains a bias toward verification; and (5) It is often difficult to summarize specific case studies. The article explains and corrects these misunderstandings one by one and concludes with the Kuhnian insight that a scientific discipline without a large number of thoroughly executed case studies is a discipline without systematic production of exemplars, and that a discipline without exemplars is an ineffective one. Social science may be strengthened by the execution of more good case studies.

Kathleen M. Eisenhardt
A.M. Huberman
M.B. Miles

- This paper describes the process of inducting theory using case studies from specifying the research questions to reaching closure. Some features of the process, such as problem definition and construct validation, are similar to hypothesis-testing research. Others, such as within-case analysis and replication logic, are unique to the inductive, case-oriented process. Overall, the process described here is highly iterative and tightly linked to data. This research approach is especially appropriate in new topic areas. The resultant theory is often novel, testable, and empirically valid. Finally, framebreaking insights, the tests of good theory (e.g., parsimony, logical coherence), and convincing grounding in the evidence are the key criteria for evaluating this type of research.

Susan King Roth

The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.

Tetsuo Tomiyama

This paper aims at providing a classification of various design theories and methodologies (DTM) based on a philosophically sound foundation. Such a classification is necessary in order to develop further, in particular, so-called descriptive and prescriptive theories and methodologies. As a scientific foundation, this paper chose General Design Theory (GDT) which is a theory of design knowledge based on axiomatic set theory. First, the paper briefly reviews GDT and establishes a knowledge-centric view of design. Then, it gives an alternative systematic categorization framework including (1) DTM to generate a new design solution (including creativity-based design and modification-based design), (2) DTM to enrich information about functional and attributive information, (3) DTM to manage design processes, and (4) DTM to represent design information and knowledge. Finally, the paper categorizes some representative work in DTM and further discusses educational implications of this categorization.

R. B. Frost

In Section 5 of a recent paper, Professor Ernst Eder [1] pointed out that 'Design science has considered the more difficult problems concerned with novel products. With suitable adaptation, the results can easily be applied to re-designing, adapting and modifying existing products.' He goes on to point out that 'With these claims, it may be surprising that industry has not yet accepted the newer methods (including design science), and does not even know about them. Yet the methods that industry does accept and use (e.g. TQM, QFD, Taguchi, and many more) are claimed as "industry best practice", and industry wants academe to accept these methods as the ultimate height of knowledge. An explanation for this delay in accepting "foreign" results (in both directions) is needed. The circumstances are very complex and interacting.' An explanation for this perceived situation is indeed needed, but experience in and with industry, in a variety of roles relating to the design function in a variety of ways, extending over a period of 40 years, suggests that the reasons are in fact simple and pragmatic once the view is relinquished that the world ought to conform to one's own perceptions. These reasons themselves show the pathway to the alleviation of this perceived situation.

Gerhard Pahl
Wolfgang Beitz

Due to the complexity of contemporary technology, product and system design efforts often require intensive organization and communication within teams; the design venture must accordingly be carefully planned and systematically executed, integrating the various aspects of the design process into a logical and comprehensible whole. The present comprehensive and systematic treatment of this methodology proceeds by clarifying the design task, establishing the function structures of a conceptual design, and finally determining the definitive layout embodying the design. Illustrative examples of actual product design processes and their results are presented and evaluated.