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Published in “Selected Methodological Issues for Doctoral Students”, Publisher: Warsaw

School of Economics Publishing 2009, edited by Marianna Strzyżewska, pp.83-98

Application of multiple case study method in doctoral dissertation

Piotr Zaborek

In the article I demonstrate the usefulness of the multiple case study method in an empirical

project carried out for doctoral dissertation purposes. I will discuss all crucial issues in the

process of conducting a research study pointing out the critical conditions for obtaining high

quality research results. Throughout the paper I will illustrate all the important aspects of

planning and implementing a case study research project with examples from my own

experience in completing a successful doctoral research study based on the multiple case

method

When case study method is appropriate for doctoral dissertation?

The single most important factor in deciding upon a research method is the nature of

research problem. Research problem formulation should only take place after a thorough

study of secondary data sources found in scientific literature. The research problem together

with its specific components (research questions) helps greatly in deciding upon the optimal

design of the study.1 My dissertation research problem was based on the apparent gap in the

scientific knowledge and was formulated as follows:

Is the application of Internet technologies increasing efficiency of manufacturing companies?

The research problem was broken down into three general research questions:

1. Are the Internet technologies causing noticeable changes in efficiency as measured by

operating profit or are they only visible at the level of specific cost and income

sources?

1 A more detailed discussion of issues involved In research problem definition can be found in Naresh Malhotra,

Marketing Research, An Applied Orientation, Pearson Education International, 2004, p. 30-60. Even though the

book is focused on research which is supposed to solve practical business problems most of the guidelines

presented there are of universal nature and thus applicable in scientific research.

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2. What costs and incomes are being affected by different kinds of Internet technologies?

3. What internal and external factors determine relationships between the Internet

technologies and efficiency of manufacturing companies?

To answer the research questions I considered three alternative approaches which are

illustrated in the following figure.

Figure 1: Three alternative approaches to solving the research problem of the doctoral

dissertation considered by the author

Source: own elaboration

My first choice was to rely on quantitative method, either alone or with elements of

qualitative approach. In part it was caused by my previous extensive experience with these

type of studies, but also by the great prevalence of quantitative approach in economics and

management. Most doctoral dissertations in these disciplines in Poland apply various forms of

quantitative methods, mostly surveys, where respondents are asked questions by interviewers

through direct contact or by telephone. Quantitative approach is selected most often by

doctoral candidates as the majority of them seems to be convinced it is the safest way to

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handle the empirical part of their theses. This perception of safety appears to come from the

general acceptance of survey studies by the faculty as a viable method for solving most of

research problems in management and economics. An additional benefit are well developed

and relatively easy to apply techniques of data analysis and interpretation based on statistics

and powerful as well as user friendly software like SPSS or Statistica. On the other hand

qualitative studies are often viewed by academia as “non-scientific” due to alleged

subjectivity and problems with generalizing results. Researchers with fondness for

quantitative methods typically accept qualitative techniques (e.g. in-depth and focus group

interviews) at the preliminary stages of a project to better explore research problem and also

after completing survey to help elaborate and deepen final insights.

As it was already mentioned the guiding factor in selecting the proper methodological

approach should be the research problem at hand and not convention or convenience. In

designing research problem it is advisable to adopt the suggestion of Bent Flyvberg who

writes: “Good social science is problem-driven and not methodology-driven, in the sense that

it employs those methods that for a given problematic best help answer the research questions

at hand.”2 In my situation it was the previously unknown characteristics of the research

problem, which emerged in early phases of the research project, that made me change my

methodological choices. Particularly the following consideration compelled me to resign from

my initial intention to use survey technique:

1. My pilot study involving a questionnaire filled in by managers have shown different

results from the ones obtained from the same companies by direct analysis of other

sources of data

2. The most advanced Internet technologies (extranet) were used only by a small

fractions of the Polish manufacturing companies (3-4%): randomized sampling

technique might result in too small number of these companies to draw statistically

significant conclusions

3. Some scholars have maintained that survey method may not uncover the whole range

of benefits from Internet technologies

4. Evidence from American and European scientific literature of potential usefulness of

case study method in analyzing information systems

2 Flyvbjerg B.: Five Misunderstandings About Case-Study Research, Qualitative Inquiry, vo. 12, no. 2, 2006, p.

219-245.

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Below I will explain every rationale in more detail.

Let’s begin with the pilot study results. I have designed a questionnaire which was to serve as

a data collection tool in the survey of manufacturing companies’ managers. Before starting

field work it is always advisable to test the research tool on several typical respondents. To

this end, I decided to test my research tool on managers from several companies located

nearby the area where I lived. As it happened, I had very good working relationships with the

people who were to participate in the pilot study from the time I provided them with some

business consulting services. Thus, it was relatively easy for me to gain access to financial

data to check them against opinions measured by the questionnaire. Through the pilot study I

especially wanted to make sure if my questionnaire met the criteria of construct validity, or –

in other words – I wanted to make sure if I measured what I thought I measured.3 In particular

I was interested in finding out if:

1) all items (questions and answers) on the questionnaire are understood in the same way

by every respondent,

2) opinions expressed by managers are an accurate measure of gains or losses in

companies’ efficiency due to application of the Internet technologies.

As it turned out the first issue wasn’t problematic. After only a few minor amendments I have

obtained a questionnaire which managers didn’t have any difficulties in comprehending and

filled it in with relative ease, and only on rare occasions had to refer to their employees’

knowledge to answer questions properly. Much more disturbing was the second criterion of

construct validity. Having collected data from managers I tried to verify them using other data

sources including financial statements, other kinds of documents, direct observations of

information systems and interviews with lower level personnel, who had firsthand experience

of using Internet technologies. All this data sources were usually more reliable then

managers’ opinions but were difficult to standardize and access in the questionnaire data

gathering and thus were meant not to be studied in the planned survey. The results of

verification have shown that other data sources usually seemed to provide strong evidence of

visible efficiency gains, which was contrary to what I heard from most of the managers. Later

I learned that managers who were of opposite opinion to other sources in their companies

were wrong, mostly because they didn’t monitor the results of Internet technologies

3 A formal definition of construct validity will be given in a later part of the article.

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implementation appropriately but were unable to admit it in the pilot interview. Faced with

apparent difficulty of obtaining valid data with highly structured questionnaire I had to

dismiss survey method in favor of case study approach; additional arguments presented

below only made me more convinced that this choice was a right decision.

The other rationale for relatively low usability of survey method in handling the dissertation

research problem refers to low level of application of the most advanced Internet technologies

in Polish manufacturing companies. According to one study, which findings were published

in one Polish economic newspaper, in 2004, which was the year when I made the final

decisions on research design, only 3-4% of Polish manufacturers utilized the most advanced

extranet systems in relations with their trading partners and less than 15% of industrial firms

possessed intranet solutions to help them in streamlining internal communication. It was

especially unwelcome information given that one of the most important objectives of my

research project was the comparison of Internet technologies’ impact on efficiency across

three groups of companies: (1) those that only used publicly available web pages, (2) those

which also had intranet and (3) businesses which on top of the first two kinds of technologies

put to use extranet systems. In statistics analysis books a suggestion can be found that to be

able to draw valid (statistically significant) inferences about differences between subgroups

one need to have at least 30 observation in every comparison category. If we assume that the

study sample had to be representative of the whole population of the Polish manufacturers and

the selection of sample units were to be based on the simple random sampling technique it is

likely that a group of companies with enough of businesses using extranet would measure

way beyond 700 units. It must be noted that in 2004 available databases which could serve as

sampling frames lacked important auxiliary information (e.g. the type of Internet systems

used) to make it practical to relay on one of more sophisticated and effective sampling

schemes (e.g. stratified sampling) to obtain a sample which were representative but smaller in

size. These conditions put an enormous pressure on a single PhD student’s resources

especially because to obtain the most reliable results I wanted to gather data through the most

time consuming face-to-face interviews instead of telephone or e-mail interviews. The above

limitations made quantitative approach even less suitable.

The two last arguments in favor of the case study method were referring to the position of

some scholars regarding the use of this qualitative approach in investigating business

application of information systems. Some of the authors are suggesting that the so called

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“productivity paradox”, which was defined as “the apparent contradiction between the

remarkable advances in computer power and the relatively slow growth of productivity at the

level of the whole economy, individual firms and many specific applications”,4 might have

been caused by measurement errors, which could be a more important factor than faults of the

technology itself or errors in implementation process.5 Specifically it was questionnaire based

quantitative methods which were often blamed for being too superficial, simplistic and

detached from the implementation context, so that true values of inputs and outputs related to

the use of information technologies were not revealed.6 Measurement related problems

seemed especially apparent in comparison of qualitative and case study based research articles

published in management science journals, with the former much more often reporting week

or no efficiency gains due to application of Internet technologies. Suitability of case studies in

investigating IT systems was also confirmed by the sheer number of publications in

mainstream scientific journals using this approach as a main research method. A study by

Line Dube and Guy Pare covering 7 top-ranked English language academic journals from the

field of information systems management in the period 1990 through 1999 have shown that

15% of all published articles used case study as a primary methodology.7

How many cases should I study and how to select them?

After taking decision that case study is actually the most preferred research strategy there are

other fundamental choices to be made. These choices relate to specific components of case

study design. The choice between single- and multiple case study is thought to be the single

most important decision in research design . It strongly affects all other elements of case study

design, particularly analysis techniques and criteria for interpreting findings.

The single case design can be justified under several circumstances:8

1) it represents the critical test of a significant theory,

4 Brynjolfsson E.: The Productivity Paradox of Information Technology, Communications of the ACM,

December, 1993. 5 Irani Z.: Information Systems Evaluation: What Does It Mean?, Construction Innovation, vol. 8, no. 2, 2008, p.

88-91. 6 Rei Mendes C.: Causal Evidence on the Productivity Paradox and Implications for Managers, International

Journal of Productivity and Performance Management, vol. 53, no. 2, 2004 7 Dube L., Guy Pare.: Rigor in Information Systems Positivist Case Research: Current Practices, Trends, and

Recommendations, MIS Quarterly, vol. 27, no. 4, 2003, pp. 597-635. 8 Yin R.: Case Study Research: Design and Methods, SAGE Publications, Inc., Thousand Oaks, California,

USA, 2003, pp. 40-41

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2) it pertains to so rare phenomenon that any single case is worth documenting and

analyzing,

3) it represents phenomenon which is hardly accessible to scientific investigation,

4) the same case is studied at two or more points in time,

5) the single case serves as a pilot case for a more complex research design.

In all other situations the better choice seems to be the multiple-case study design. If the

research is being conducted for doctoral dissertation purposes I would strongly advice against

using single case design, even when one or more of the above factors are present. One case

design runs higher risk of being accused as subjective and “non-scientific” by more

quantitatively oriented evaluators and members of doctoral examination commission, as it

doesn’t allow the use of more complex analysis techniques based on comparison of studied

cases and therefore richer theory building.

Having said that the best for dissertation is multiple case study, there is still an unanswered

question of how many cases should be included in the research project and what rules of

selection might be used. As many prominent scholars in case study area claim (i.e. Michael

Patton, Robert Yin and others), no rules for sample size in qualitative inquiry exist. If any

guidelines are provided in case study literature they are by no means as precise as what can be

found in statistics books concerning sampling in survey method. Michel Patton writes that

“Sample size depends on what you want to know, the purpose of the inquiry, what will be

useful, what will have credibility, and what can be done with available time and resources.”

and later he adds “The validity, meaningfulness, and insights generated from qualitative

inquiry have more to do with the information richness of the cases selected and the

observation/analytical capabilities of the researcher then with sample size.”.9 One of the most

specific advices on sample size that one can find in the literature is the recommendation that

that additional case should be selected to the so called “point of redundancy”,10 which is

achieved when your analysis will not be significantly enriched by admitting an extra case into

the sample. The underlying idea here is that every additional case provides less new insights

then the previous one, in a fashion somewhat similar to the theory of diminishing marginal

9 Patton M.: Qualitative Research and Evaluation Methods, Sage Publications, USA, 2002, pp. 244-245. 10 Lincoln Y., Guba E.: Naturalistic Inquiry, Sage Publications, USA, 1985.

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returns in microeconomics. Of course the decision that the point of redundancy was reached

would be still quite subjective.

Nevertheless, while preparing dissertation you must be aware that your work will probably be

assessed from the positivist position of scholars who are mostly using quantitative approach in

their empirical studies. In such circumstances a suggestion can be helpful from Chad Perry,

who - drawing on his experience from an Australian PhD program and literature review -

concludes that “the widest accepted range seems to fall between 2 to 4 cases as the minimum

and 10, 12 or 15 as the maximum.”11 I personally would suggest a somewhat narrower

range of 4 to 8 cases, with an exact number depending on:

1) how detailed analysis will be at the level of each case (the more complex the analysis

and the more data sources will be handled the smaller number of cases is required),

2) how much information is needed to adequately address the research problem (you

must be aware that you have reached a point of redundancy by covering every with

data sources every important research question).

As regards specific selection criteria of cases to the sample, one issue is clear enough:

selection should not be based on representativeness, which is the most common practice in

quantitative studies. I have never found an author in the case study area who disagrees with

this notion. Selection should follow rules which will give a purposeful not random sample.

There are many rules which may be employed to chose a desired number of cases; for

instance Patton lists no less than 16 of them.12 From my experience to build an adequate

sample in a case study research usually the most useful are tactics based on:

1) typical cases (the most characteristic or prevalent examples of a studied phenomena),

2) extreme cases (unusual observations which may contain some useful insights in

explaining research problem, such as most successful companies and firms which

suffered spectacular failures; some scholars believe extreme cases to be especially

“information rich” and thus worth in-depth study),

3) diversified cases (observation ensuring high variation of causes, results and

contextual conditions of studied phenomena),

11 Perry C.: Processes of a Case Study Methodology for Postgraduate Research in Marketing, European Journal

of Marketing, vol. 32, no. 9/10, 1998, p. 785-802. 12 Patton M.: Qualitative Research and Evaluation Methods, Sage Publications, USA, 2002, p. 243-244.

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4) most accessible cases (case which allow an easy access to a large number of rich

information sources, which is especially important for studies undertaken in countries

such as Poland, where many managers are not willing to participate in research

projects for mostly unsubstantiated fear of disclosing sensitive information, which as

they believe can harm their businesses).

Other important consideration in selecting cases in multiple case design is the ability to obtain

a sample, which will allow to achieve literal and theoretical replications. Robert Yin believes

replication to be one of the strongest means available to case study researcher to ensure high

credibility of results. He describes the basic idea of replication using an analogy to

experiments, where this technique was originated: “The replication logic is analogous to that

used in multiple experiments. For example, upon uncovering a significant finding from a

single experiment, the immediate research goal would be to replicate this finding by

conducting a second, third, and even more experiments. Some of the replications might have

attempted to duplicate the exact conditions of the original experiment. Other replications

might have altered one or two experimental conditions considered irrelevant to the original

finding, to see whether the finding could still be duplicated. Only with such replications

would the original finding be considered robust and worthy of continued investigation or

interpretation.”. 13

There are two types of replication which should be achieved in a high quality multiple case

study and which ought to guide the process of selecting research units:

1) literal replication – which takes place when at least two cases give the same or very

similar results,

2) theoretical replication – when at least two cases give contrary results but because of

predictable reasons

In my dissertation I have adopted the above described multiple-case design, with the research

unit (or single case) defined as a manufacturing company of middle or large size (employing

in excess of 50 people), operating in B2B area, utilizing Internet technologies according to

adopted replication pattern. In selecting cases I have tried to acquire firms which were both

diversified with respect to the used Internet technologies and typical referring to other

13 Yin R.: Case Study Research: Design and Methods, SAGE Publications, Inc., Thousand Oaks, California,

USA, 2003, p. 47

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specified criteria. A limiting factor was accessibility: given the fact that I have planned a very

detailed analysis of each company I had to make sure to select only such businesses which

managers allowed me an almost unobstructed access to numerous data sources which I

intended to study, including employees, artifacts (information systems) and various

documents allowing to measure impact of technologies on a wide array of cost and income

categories. Finally I have arrived at a 6 unit sample, representing 3 levels of advancement in

internet technologies application. The respective levels were made up of 2 firms using

publicly available web sites only, 2 with intranet implementation, and 2 utilizing elements of

extranet technology. With this sample structure I hoped to obtain literal replications expecting

companies with similar levels of internet technology implementation to achieve comparable

efficiency gains and theoretical replications which were to be reached when a pattern was

found that the more of Internet technology was used the stronger efficiency improvements

were observed.

How should I analyze and interpret case study data?

One of the most characteristic features of the case study method is it’s unique approach to

analyzing empirical data, especially when compared with statistics intensive quantitative

methods. Case study is considered to be more flexible in terms of admissible analysis

strategies and techniques. In conducting scientific inquiry using this method researcher needs

to make decision which analysis strategy will they adopt as a dominant one. At the general

level the choice is between deductive and inductive approaches.14 Deductive approach is

typical for natural sciences and with most of economics and management scholars who prefer

quantitative method. It’s process starts with previous theory which is used to formulate

research hypotheses, which are then tested using empirical data gathered during the field work

part of the project. To verify hypotheses with qualitative research it is often used “the type of

test which Karl Popper called falsification (…). Falsification is one of the most rigorous tests

to which a scientific proposition can be subjected: if just one observation does not fit with the

proposition, it is considered not valid generally and must therefore be revised or rejected.”15

14 For a more In-depth discussion of both approaches refer to Perry C.: Processes of a Case Study Methodology

for Postgraduate Research in Marketing, European Journal of Marketing, vol. 32, no. 9/10, 1998, p. 785-802. 15 Flyvbjerg B.: Five Misunderstandings About Case-Study Research, Qualitative Inquiry, vol. 12, no. 2, 2006, p.

219-245.

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On the other hand, inductive approach only to minimal extent relies on existing theory.

Instead it is using empirical data to gradually close in on the final revision of a new theory; in

this situations the theory is being constructed in iterations, by studying consecutive data

sources within following case studies. It is assumed that with inductive theory building, the

theory itself is changing to fit the findings from investigated cases and finally achieves an

explanation which suits every studied research unit.

For doctoral dissertation I suggest to adopt deductive approach, with an extensive

analysis of current theoretical background showing at significant gaps in knowledge which

will translate into the dissertation research problem. To break down the research problem into

hypotheses it is also useful to refer to the existing theory. Therefore, in deductive approach

primary data are mostly used to confirm or falsify theoretical proposals. It is also possible,

and quite practical, to apply both strategies: inductive one to develop theory with a few initial

cases and then deductive one to test the constructed theory using data gathered from the final

set of cases. In my dissertation I have used deductive approach, with a very strong reliance on

current theory. If you prefer to make use of an inductive approach you should make sure that

it will be acceptable by the majority of your doctoral commission members.

Analysis techniques Pattern matching for dependent variables. Dependent variables were

contained in research hypotheses which predicted certain outcomes of applying specific

internet technologies. Comparison was made with empirical results

Following the deductive strategy, my main objective in the study was to solve the research

problem by verifying a set of 9 hypotheses, which concerned relationships between specific

types of Internet technologies and various categories of costs and income as well as factors

affecting the strength and direction of these relationships. To link data gathered from cases,

link them to research hypotheses and find out which hypotheses were true I have used a

pattern matching approach, which is a popular and well documented analysis technique in

case study and experimental research. The basic idea here is to describe two patterns – one

closely fitting the research hypotheses and an alternative one constituting a rival explanation.

Then research data are compared to both patterns to see which explanation matches the data

better. Given the typical way to formulate research hypotheses in economics and management

dissertations in Poland it is usually a good idea to use as rival explanations an “effects” and

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“non-effects” patterns which in my doctoral thesis referred to “efficiency gains due to various

Internet technologies” for one explanation and “the lack of efficiency gains due to respective

Internet technologies” for rival explanation. It is worth to note that to use pattern matching

every hypothesis should contain a pair of variables (independent and dependent one) which

are proposed to be linked in some kind of relationship.16

To build adequate explanation in line with pattern matching approach and present these

insights in a convincing manner I used four following measures:

1. Every hypothesis was verified based on measurable variables denoting specific

changes in costs and income which could be linked to application of Internet

technologies. Any “soft” evidence, such as opinions of interviewees, was never the

sole proof which was used in testing the hypotheses. Verification process of each

hypothesis in each company was defined by the following elements:

a. Decision to accept or reject hypothesis was based on financial results of

applying respective internet technologies.

b. Quantifications were made by comparison of current performance measures to

historical levels of the same measures from before implementation of the

internet technology.

c. When historical data were unavailable current performance measures were

compared to a hypothetical situation in which a given technology was not

used at all (scenario method).

d. Hypothetical scenarios were built using insights from the company’s

employees and pertinent documentation and later verified by the most

competent employees

2. It was checked if literal replication occurred, which in my research was about

finding out if pairs of companies with comparable levels of the Internet adaptation

have shown similar changes in efficiency.

3. In was checked if theoretical replication took place, in other words my prediction

that higher levels of internet technology application should be associated with larger

efficiency gains.

16 For more information on pattern matching I strongly recommend to refer to Yin R.: Case Study Research:

Design and Methods, SAGE Publications, Inc., Thousand Oaks, California, USA, 2003

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4. Simple statistical techniques were used to provide objective confirmation of

relationships – it must be stressed that it was not an attempt at formulating statistical

generalizations, which were not possible with the sample size and selection criteria,

but merely a way to obtain clear and not subjective interpretation criteria.

The whole process of analysis – which is typical and advisable for case method – started not

only after all data from every case were collected but just after a first interview at the first

company was completed. Making use of high flexibility of the method I conducted basic

analysis after gathering data from each source and sometimes even during data gathering. In

this way I was able to control and modify data gathering process to make best use of unique

but previously unknown characteristics of studied companies. Although in most cases there

were some unavoidable idiosyncrasies the basic structure of data collection process in each

firm looked like in the below display.

Figure 2: Stages in data collection process for doctoral dissertation in every company.

Source: own elaboration

The general analysis and verification procedure was consisting of four stages, starting with

testing hypotheses in each company, then checking literal and later theoretical replications

with final phase of definitive verifying hypotheses and solving research problem using all data

from the whole sample of manufacturing firms. This format in which first a detailed

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description of each case is provided and then follows a cross-case analysis is suggested in

literature for multiple case study.17 This process is illustrated below with a flowchart.

Figure 3: Stages in analysis and verification process in the dissertation case study research

Source: own elaboration

How to make my case study research results credible?

To succeed in defending your doctoral dissertation you must not only obtain novel and

valuable findings. It is equally important to convince scholars who will assess your work that

your results are justifiable and not seriously flawed by subjectivity. In other word you must

make your outcomes credible. Credibility of research results is determined by their quality,

which in turn, is defined by fulfilling the four criteria:18

1. Construct validity – which is about establishing correct operational measures to

lower the risk of subjective judgments.

17 Creswell J.: Qualitative Inquiry and Research Design; Choosing Among Five Traditions, SAGE Publications,

Inc., Thousand Oaks, California, USA, 1998, p.63. 18 Yin R.: Case Study Research: Design and Methods, SAGE Publications, Inc., Thousand Oaks, California,

USA, 2003, p.36.

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2. Internal validity – consisting in establishing clear causal relationships, whereby

certain conditions are shown to lead to other conditions as distinguished from

spurious relationships.

3. External validity – is concerned with establishing a domain to which a study’s

findings can be generalized.

4. Reliability – should demonstrate that the operations of a study, mostly the data

collection procedures, can be repeated with the same results

To increase probability of obtaining high quality research study by meeting the four criteria

Robert Yin suggested the following set of measures and techniques.

Figure 3: Tactics for increasing case study quality by Robert Yin

Quality aspect Case Study Tactic Phase in which tactic

occurs

Construct

validity

• Use multiple sources of evidence

• Establish chain of evidence

• Have key informants review draft case

study report

Data collection

Data collection

Composition

Internal validity • Do pattern-matching

• Do explanation-building

• Adress rival explanations

• Use logic models

Data analysis

External

validity

• Use theory in single-case studies

• Use replication logic in multiple-case

studies

Research design

Reliablility • Use case study protocol

• Develop case study database

Data collection

Source: Yin R.: Case Study Research: Design and Methods, SAGE Publications, Inc.,

Thousand Oaks, California, USA, 2003, p.36.

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In the final part of the article I will address the way I have attempted to increase every aspect

of research quality, heeding guidelines from Yin and other case study authors.

To obtain high construct validity I have reached for the technique called triangulation.

Triangulation is often defined as “a combination of methods used to study the interrelated

phenomena from multiple and different angles or perspectives”.19 There are four basic types

of triangulation:20

triangulation of methods of data collection – using different research methods (e.g.

interviews, observations, surveys, document analysis) in trying to arrive at the same

set of conclusions,

investigator triangulation – different investigators independently collect and analyze

data from the same sample to solve identical research problem,

theory triangulation – examining data using different theoretical perspectives (e.g.

economics, management science, sociology) to check if they can provide coherent

explanations,

triangulation of data sources – drawing evidence from a variety of data sources

trying to verify the same set of findings. The sources may include different people

knowledgeable about the studied phenomena, documents, public records, personal

papers, photograph etc.

In my dissertation I used multiple sources of evidence to establish convergent lines of inquiry

in the process of triangulation of sources of data. I tried to achieve a situation in which at least

two sources independently confirmed a finding. As a result I have considered a finding valid

when it was confirmed by at least two sources of evidence and no source presented

contradictory information

The other tactics I applied to increase construct validity was establishing chain of evidence.

To establish chain of evidence is to give the case study reader a possibility to follow the

derivation of any evidence, ranging from initial research questions to ultimate case study

conclusions. In the dissertation every step of conducting research study was amply

19 Given L.M: The SAGE Encyclopedia of Qualitative Research Methods, SAGE Publications, USA, 2008, p.

892. 20 See also Ibidem, p. 893. and Stake R.: The Art of Case Study Research, SAGE Publications, Inc., Thousand

Oaks, California, USA, 1995, p. 112-116.

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documented. I have dedicated a whole, 271-pages-long appendix to the detailed presentation

of results from every company. I assumed that for every finding such an amount of

information on application of Internet technologies and its context must be presented that the

reader should be able to draw its own conclusions and see if they matched those of the author.

To further strengthen construct validity I had key informants review my draft case study

report. At the end of writing-up case-study report from each company a management-board

member was consulted to check the most important findings of the study. When justifiable

objections were raised I corrected the case study report accordingly.

With regard to internal validity I have taken the following steps to maximize its level:

• Data in each case study were analyzed using earlier described pattern matching

approach for dependent variables, whereby each hypothesis contained a single,

measurable dependent variable

• To increase contrast between solutions only two dichotomous patterns were used:

when there is an increase in benefits or decrease in costs as measured by a variable or

lack thereof

• Attention was paid to definitely rule out this benefits which might have been brought

about by other causes then internet technologies

• Every more complex chain of cause and effect was illustrated by a chart, which

form was inspired by graphs presented by M. Miles and A. Huberman

I attempted to achieve the highest external validity with a design where both literal and

theoretical replications were used. It included three literal replications and three pairs of

theoretical replications based on three different levels of advancement in using internet

technologies. Obtained results have shown that both types of replication took place which

increased strength of the theoretical proposals of the study

And finally as a means to increase reliability of the findings I published in the dissertation a

detailed case study protocol containing the instrument as well as the procedures and the

general rules to be followed in conducting case study. In fact most of the third chapter of the

dissertation contained elements of case study protocol, including general and probing

questions, procedure for collecting data, methods of analysis and templates of tables and

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charts to be used in displaying information. The information contained in the third chapter

appeared to be enough to repeat the investigation, thus it is safe to say that the result was

increased reliability of the study.

Conclusion

I hope that after completing the lecture of my paper readers are aware that case study is both

powerful and versatile but also quite difficult and time consuming research method. This may

go against the common knowledge of quantitatively oriented scholars who quite often

maintain that case studies – like other qualitative methods in general - are easy to use but not

very “scientific”. The case study method worked for me very well as I managed to defend my

dissertation with distinction proving that there is a positive relationship between the number

Internet technology applications and increase of efficiency. I also noticed in recent years an

emerging trend of growing favorable attitude of Polish academia towards case studies, as is

evidenced by the increasing number of research projects conducted with this method. Even

though I would still advice that the decision to use case study should only be made after

quantitative approach have been shown to be inappropriate to handle a given research

problem. My other suggestion is to devote a significant part of doctoral thesis to meticulously

explain the rationale behind using this inquiry approach as well as its scientific nature and to

describe very thoroughly measures taken to ensure high quality of research findings.

For those who are interested in learning more about case study I would like to recommended

the following set of publications, which in my opinion are the best introductory lectures on

the topic:

1. Robert Yin.: Case Study Research: Design and Methods, SAGE Publications, Inc.,

Thousand Oaks, California, USA, 2003 – Possibly the best primer of case study

method for economics and management sciences; reasonably short, extremely useful,

readable and filled with illustrative examples

2. Perry C.: Processes of a Case Study Methodology for Postgraduate Research in

Marketing, European Journal of Marketing, vol. 32, no. 9/10, 1998, p. 785-802 – Lots

of useful guidelines for conducting case studies for doctoral thesis

19

3. Miles M., Huberman A.: Qualitative Data Analysis: An Expanded Sourcebook, SAGE

Publications, Thousand Oaks, California, USA, 1994 – A comprehensive collection of

analysis techniques applicable in case study research

Bibliography

1. Brynjolfsson E.: The Productivity Paradox of Information Technology,

Communications of the ACM, December, 1993

2. Creswell J.: Qualitative Inquiry and Research Design; Choosing Among Five

Traditions, SAGE Publications, Inc., Thousand Oaks, California, USA, 1998

3. Dube L., Guy Pare.: Rigor in Information Systems Positivist Case Research:

Current Practices, Trends, and Recommendations, MIS Quarterly, vol. 27, no.

4, 2003, p. 597-635.

4. Flyvbjerg B.: Five Misunderstandings About Case-Study Research, Qualitative

Inquiry, vo. 12, no. 2, 2006, p. 219-245.

5. Given L.M: The SAGE Encyclopedia of Qualitative Research Methods, SAGE

Publications, USA, 2008

6. Irani Z.: Information Systems Evaluation: What Does It Mean?, Construction

Innovation, vol. 8, no. 2, 2008, p. 88-91.

7. Lincoln Y., Guba E.: Naturalistic Inquiry, Sage Publications, USA, 1985.

8. Miles M., Huberman A.: Qualitative Data Analysis: An Expanded Sourcebook,

SAGE Publications, Thousand Oaks, California, USA, 1994

9. Naresh Malhotra, Marketing Research, An Applied Orientation, Pearson

Education International, 2004

10. Patton M.: Qualitative Research and Evaluation Methods, Sage Publications,

USA, 2002

11. Perry C.: Processes of a Case Study Methodology for Postgraduate Research

in Marketing, European Journal of Marketing, vol. 32, no. 9/10, 1998, p. 785-

802.

12. Rei Mendes C.: Causal Evidence on the Productivity Paradox and

Implications for Managers, International Journal of Productivity and

Performance Management, vol. 53, no. 2, 2004

13. Stake R.: The Art of Case Study Research, SAGE Publications, Inc., Thousand

Oaks, California, USA, 1995

14. Yin R.: Case Study Research: Design and Methods, SAGE Publications, Inc.,

Thousand Oaks, California, USA, 2003