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THE USE OF THE CASE STUDY METHOD
IN LOGISTICS RESEARCH
Lisa M. Ellram
Arizona State University
The case study method is one of the least understood and most often criticized
research methods today.' Despite this, there appears to be a growing interest in,
and use of the case study methodology in business research.^ A few articles have
used the case study method in materials management research.-^ However, recent
publications still indicate that the case study method is not well understood in
genera!'* and in purchasing and logistics management in particular.This paper shows how the case study method can be used in business research,
with a particular focus on purchasing and logistics research. Based on a framework
developed by Yin,^ supplemented by works of many others,'' this paper seeks to:
1. Demonstrate some of the misuses and misconceptions associated with
the application of the case study method.
2. Provide an understanding of general research design issues related
to what case study research is, when it can and should be applied,
and its application in quantitative and qualitative research.
3. Provide a detailed example of the development of a case study research
design based on an actual logistics related research problem.
4.
Present some case study analysis methods, and use actual data from
case study research to apply such methods.
5. Discuss future potential applications of the case study method to
purchasing and logistics problems.
To respond to the five points above, the paper is organized as follows. First,
seven major misconceptions associated with case study research are introduced.
These are addressed throughout the paper as the associated topics are developed.
Next, an overview of case study research, its relevance, and applications is provided.
^
ELLRAM
After this introduction, an example of the development of a case study based research
design is provided. Based on this case study, some data analysis methods are
demonstrated. The paper concludes with a summary of some potential applications
of the case study method in purchasing and logistics.
MISCONCEPTIONS ABOUT CASE STUDY RESEARCH
Table 1 summarizes some of the common misconceptions associated with case
study research. The first misconception is that case studies for teaching and research
are closely related. Case studies for teaching are a leaming tool that focuses "on
organization and presentation of data so that others may understand what the
organizational context was really like."^ Cases for teaching give students the
opportunity to make decisions or solve problems in a real-life context, as a basis
for discussion. On the other hand, case studies as a research methodology explain,
explore, or describe a phenomenon of interest. This requires a methodologically
rigorous and accurate representation of empirical data.^ Thus, the purposes,
presentation of data, and methods for gathering data are quite different between
cases as a research method and teaching tool.
TABLE 1
MISCONCEPTIONS RELATED TO THE USE
OF THE CASE STUDY METHOD
1. Case study research and teaching are closely related.
2. The case study method is only a qualitative research too!.
3. The case study method is an exploratory tool that is appropriate only
for the exploratory phase of investigation.
4.
Each case study represents the equivalent of one research observation.
Thus, extremely large numbers of case studies are required to produce
any meaningful results.
5. Case studies do not use a rigorous design methodology.
6. Anyone can do a case study; it's just an ad hoc method.
7. Results based on the case study methodology are not genera I izabie.
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Misconceptions two and three, that case studies are only exploratory and
qualitative, are discussed in the section on research design issues. Misconception
four, the notion that each case study is just a single observation rather than a
unique experiment, is explored at the end of the research design section.
Addressing misconceptions five, six, and seven are the goals of the bulk of
this paper. These are areas of great concem, because without proper research design,
execution and data analysis, case study research will produce poor results. This,
In tum, will support the misconceptions and misapplication of case study research.
What lies behind misconceptions five, six and seven is that:
Most people feel that they can prepare a case study, and neariy ail of
us believe we can understand one. Since neither view is well founded,
the case study receives a good deal of approbation it does not deserve.
The sections on case study design and data analysis verification address these
misconceptions.
RESEARCH DESIGN ISSUES
Recently, there has been attention given to the fact that the majority of empirical
research done in logistics, operations, and materials management focuses on
quantitative research methods." Quantitative methods include simulations and model
building as well as statistical testing of survey data. The survey method places
an emphasis on quantitative analysis of a few variables across a large number of
observations.
As pointed out by Mentzer and Kahn,'^ qualitative techniques have not received
widespread use and acceptance in logistics, operations, and materials management
research. The case study method generally emphasizes qualitative, indepth study
of one or a small number of cases.'^ However, case studies may also gather
quantitative data. Quantitative case research design generally focuses on a small
number of cases due to the depth required.'** Thus, misconception one, that cases
are only relevant for qualitative research, is not true. White it is the norm, it is
not absolute; therefore, it is not really a question of a survey being superior to
a case study. Each serves a different purpose.
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Overview of Methodologies
As shown in Table 2, research methodologies can be classified according to
the type of data used and the type of analysis perfomied on the data. The type
of data can be empirical, which is data gathered for analysis from the real worid,
often via surveys or case studies. The data may also be modeled data, which means
it is either hypothetical or real worid data to be artifically manipulated by a model.
TABLE 2
BASIC RESEARCH DESIGN
Types ot Analysis*
a.
Primarily Quantitative
Primarily Qualitative
Survey data, secondary daia.
in conjunction with statistical
analysis such as:
factor analysis
cluster analysis
discriminant analysis
Case studies, participant
observation, enthnography.
Characterized by:
limited statistical analysis.
often non-parametric
• simulation
• simulation
• linear programming
• role playing
• mathematical programming
• decision analysis
•This table provides a sample of techniques rather than a complete
explanation.
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Empirical research has not been as popular as modeling within materials
management for a number of reasons. First, empirical research poses a greater risk
than modeling. When using real worid data, results tend to be less predictable
and less controllable. Significant effort may be expended without achieving any
meaningful results. However, empirical methods are receiving increased attention
due to the increasing call to incorporate real world data to improve the relevance
of business research.^
Empirical data can use quantitative analysis, qualitative analysis, or a mixture
of both. Quantitative results are expressed in numerical, quantifiable terms.
Qualitative results are frequently expressed verbally, often to create an understanding
of relationships or complex interactions. Alternatively, both methods may be
combined, as in some case study research.'^ Case studies may be used to create
theory to then test with surveys, or as a follow up to surveys to provide greater
insight. The appropriate class of research methods to choose from depends upon
the researcher's goal and the nature of the research question.
How Research Questions Affect the Appropriate Methodological Choice
As indicated by Table 3, both qualitative and quantitative approaches to data
analysis might be appropriate in most situations. The four primary objectives of
research are shown on the far left of Table 3. The general questions typically used
to support each objective are shown in the middle column, while examples of
appropriate methodologies for gathering data are shown on the far right. Note that
this is not meant to be a comprehensive listing of all appropriate methodologies.
Rather, it is designed to list some of the more popular and frequently used methods.
In exploratory research, the issue could be how or why is something being
done? A case study methodology would be desirable in those circumstances because
it provides depth and insight into a little known phenomenon. However, if the
researcher believes that some activity is occurring, and wants to get a better
understanding of the incidence, a quantitative method is preferred.
If explanation of a phenomenon is a goal, qualitative methods are preferred
because they provide a depth and richness, allowing the researcher to really probe
the how and why questions^^ and construct idiographic knowledge.' ^ A more common
application of a case study research is to build theory that can then be tested using
further case studies, survey data, or another relevant method.
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TABLE 3
CLASSIFICATION OF RESEARCH METHODS ACCORDING
TO KEY RESEARCH OBJECTIVES AND QUESTIONS
Objective
Exploration
Question
how, why
Examples of Appropriate
Methodologies
Qualitative
• experiment
• case study
• participant observation
how often, how much, how
Quantitative
many, who, what, where
• survey
• secondary data analysis
Explanation
how, why
Qualitative
• experiment
• case study
• grounded theory
• participant observation
• ethnography
• case survey
Description
who, what, where, how
Quantitative
many, how much
• survey
• longitudinal
• secondary data analysis
who, whai, where
Qualitative
• case study
• experiment
• grounded theory
• participant observation
• ethnography
• case survey
Prediction
who. what, where, how
Quantitative
many, how much
• survey
• longitudinal
• secondary data analysis
who, what, where
Qualitative
• case study
• experiment
• grounded theory
• participant observation
• ethnography
• case survey
Synthesized from Yin. Crabtree and Miller, Strauss and Corbin, Marshall and
Rossman. Miles and Huberman.
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Description and ptediction can be served by both quantitative and qualitative
methods, depending on the nature of the description and prediction desired. Broad
description, iticluding the nature of a phenomenon (how much, how many), as
well as establishing who is performing or participating in the activity of interest,
and where it is being done on a broad scale are best answered by quantitative
techniques. Quantitative techniques also provide better statistical predictability of
the above factors, extrapolating large data sets of past outcomes, activities, and
patterns into the future.
However, case studies can also provide description and prediction on a smaller
scale. For example, single or multiple case studies can be used to describe a
phenomenon, or predict outcomes based upon past occurrences in similar cases.
Thus, misconception three, that case studies are appropriate only for exploratory
research, is not supported.
General Issues in Qualitative Methods
While quantitative methods have prevailed in many disciplines—particularly
business disciplines such as purchasing and logistics, operations management,
marketing, and general management—qualitative methods appear to be gaining both
recognition and acceptance as viable and valuable alternatives. Qualitative methods
have long been the norm in other social sciences such as anthropology, sociology,
and primary care.
In the social sciences, qualitative research is often referred to as field research,
because the researcher is personally involved in, " . . . an interpretive focus on
the human field of activity with the goal of generating holistic and realistic
descriptions and/or explanations."^'' Focused and specific methods are used to select
the sample, and to gather and analyze data.
The general qualitative methods used in the social sciences may be classified
as either a case study or a topical study. Case studies focus on holistic situations
in real life settings, and tend to have set boundaries of interest, such as an organization,
a particular industry, or a particular type of operation. Topical studies, on the other
hand, investigate more focused activity, yet within a less distinctly bounded area.^'
An example of this might be how implementation of just-in-time inventory
philosophies have affected U.S.-based businesses.
One of the issues that has been confused in the discussion of case study research
in the literature is that case study research has often been discussed as a "single
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technique," such as the structured interview. It is common to confuse data collection
and data analysis techniques as other methcxls of qualitative inquiry, like case studies
and topical studies. However, data collection and analysis techniques are really
part of the process of the case study method. Triangulation, which is the use of
the different techniques to study the same phenomenon, provides validity within
the case study method. The three primary qualitative techniques that may be used
as part of the case study method are direct observation, recordings, and interviews.
Each primary category has many subtechniques. A partial listing of these qualitative
techniques is shown in Table 4.
As is obvious from Table 4. quantitative data may also be gathered using
"qualitative" case study research methods. These data may include:
. observing the number of occurrences of a particular phenomenon;
. determining the degree or level of occurrence of an activity;
- asking participants to complete questionnaires or scales related to a
particular phenomenon.
Thus, the case study methodology can apply to a broad range of research issues.
Single Versus Multiple Case Design
One of the fundamental issues in case study analysis is to determine whether
a single case study or multiple case studies should be used.^^ If a multiple case
design is chosen, the question becomes, how many cases are necessary to achieve
the desired generalizability of results? This question must be answered before data
collection as part of research design. One common misconception that must be
cleared up before proceeding is the belief that each case study is like a single
observation of an experiment. On the contrary, each case study is in and of itself
a self-contained experiment, with unique context that is part of the experiment.
Indeed, a case study method is often chosen because the researcher wants to know
how the context of the phenomenon of interest affects the outcomes.^^
Thus, a single case, like one experiment, is suitable when that case represents
a critical case to test a well-formulated theory, an extreme or unique case, or a
case which reveals a previously inaccessible phenomenon. A great deal of background
preparation is required to minimize the probability of misrepresenting the single
case and associated findings. Thus, in response to misconception four, each case
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TABLE 4
QUALITATIVE DATA COLLECTION TECHNIQUES
Direct Observation
Kinesics (body language)
Unstructured observation
Street Ethnography—observe location
Structured observation using:
• checklists
• scales for rating
• predetermined categories
Participant observation
Proxemics (use of personal space)
i
^_^^^^^^^_^^_^_
Indirect Observation
Audio recordings
Video tapes
Content analysis
Diary/self-reporting
Interviewing
Unstructured
• conversational
• key information/elite interview
Semistructured
• ethnographic interview
• focus group
• individual biography
• critical incidents
• historical analysis
Structured Interview
• questionnaire (open ended)
• ranking/rating scales
• closed end "tests"
Adapted from Marshall and Rossman, Miller and Crabtree, Miles and Huberman,
Ellram and Siferd.
'^^
ELLRAM
is not the equivalent of a single observation—it is like a single experiment. Single
versus multiple case designs support different goals.
Multiple cases, like multiple experiments, represent replications that allow for
development of a rich, theoretical framework. Thus, multiple case design should
be used to either predict similar results among replications, or to show contrasting
results, but for predictable, explainable reasons. In most situations, six to ten cases
should provide compelling evidence to support or reject an initial set of
propositions.^'^ The issue of generalizability will be discussed in greater depth in
conjunction with the case study example in the following sections.
CASE STUDY DESIGN
The example presented here demonstrates the application of the case study
technique to a research project that examined the use of Total Cost of Ownership
modeling in purchasing {TCO study). The purpose and design of the TCO research
are presented below to provide a better understanding of the key research goals
and issues.
Basic Case Research Design
The research on TCO analysis was undertaken with the following objective
in mind:
To assess the state of TCO practice and implementation among a sample
of North American firms currently using TCO modeling, with the goal
of educating and easing the implementation process of other organizations
interested in TCO implementation.
Thus, the research was largely exploratory and explanatory in nature, designed to
extend earlier conceptual work^*" and case study research.^^ The decision to use
a case study method was made because this research proposes to examine how
and why TCO is pursued. The purpose of this study is to obtain a depth of
understanding of TCO practices, rather than a breadth. A copy of the research plan
is included as Appendix 1.
JOURNALOF BUSINESS LOGISTICS. VoL 17, No. 2, 1996
The
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Sample
Because relatively few firms use a total cost of ownership approach, this study
used a purposive sample, as is generally the situation in case study and other
qualitative research. Sample selection focuses the site and the sample in order to
gain accessibility to the type of phenomenon of interest.^^ In order to identify
organizations of potential interest, the researcher formed an advisory board of industry
executives to support this project and help identify and provide contact with potential
case study candidate organizations. The researcher also contacted many other
purchasing professionals and academics and conducted an extensive review of the
literature.
Approximately 40 organizations were personally contacted by telephone. The
goal was to perform six to twelve case studies. In most organizations, the call
began with a high level purchasing representative such as a vice-president or director.
In some cases, initial contact was made through a purchasing manager.
Some organizations were not qualified, interested, or able to participate in the
research. Those firms were immediately disqualified. The qualification process
yielded in a list of approximately twenty organizations that fit the criteria and
expressed a willingness to participate in the research. The list included a high number
of firms in the computer/electronics industry. Some of those were randomly eliminated
simply because the researcher did not want to rely too heavily on activities in
one industry. Other organizations had scheduling conflicts. The net result was that
eleven case studies were performed.
Development of the Research Instrument
The researcher developed a preliminary research protocol based on previous
research and a review of the literature, using the design suggested by Yin.^® The
research protocol included key research issues, the design of the research, the
proposed methodology and the interview guide. The interview guide was extensively
critiqued in writing by several academics and eight purchasing professionals. In
addition, the previously mentioned advisory board of three purchasing professionals
and a representative from the Center for Advanced Purchasing Studies provided
the researcher with input into the research plan at a half-day meeting.
This section and the following section refute case study research misconception
five, that case studies do not require a rigorous design method. These sections
also discredit the sixth misconception: that case studies can be performed by anyone.
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Clearly, proper application of the case study method requires extensive training
and/or self-study, as does any other research method. It is only a misunderstanding
of the case study method that causes people to believe otherwise.
Research Design Quality
Whether quantitative or qualitative, good research design requires external
validity, reliability, construct validity, and internal validity. Each is discussed below
as it relates to the case study research method.
'
External Validity
First, external validity is an issue that must be addressed during the design
of the research. External validity reflects how accurately the results represent the
phenomenon studied, establishing generalizability of results.^^ Lack of generalizability
has been the major criticism of case studies, which is best addressed by replicating
case studies and verifying patterns. In the TCO study, the researcher determined
at the outset that 6-12 indepth case studies would be conducted.
Reliability
The second issue in research design quality—reliability—addresses the
repeatability of the experiment, and whether replication is possible and will achieve
the same results.^^ In a case study context, there are two keys to reliability: use
of a case study protocol, and development of a case study data base. A case study
protocol includes the interview guide, as well as the procedures to be followed
in using the test instrument. It is always good practice to have a case study protocol.
In multiple case methodologies, it is even more important to ensure reliability.
The case study interview guide is included in Appendix 2. It was developed
based on the research issues in the research plan that is included in unedited form
in Appendix 1. The case study protocol encompasses all three of the appendices
included here. Based on the input of the advisory board, the protocol was substantially
revised and sent out for re-review before the pilot case study was conducted.
The actual field portion of the research began with a pilot study. In case study
research, the purpose of a pilot study is not to pretest as it is with survey research.
Rather the pilot study is used to further refine the research, regarding both content
and procedure. The case study approach can then be modified not only for the
pilot test, but also for the later case studies. While the pilot study contains interesting
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findings for the larger project, it is of special importance to the researcher in improving
the research plan before investing further time in the field.
All of the case studies involved on-site visits. Those who agreed to participate
in the research were sent a letter of introduction and an overview of the research
to prepare them for the session. They were also sent a copy of the interview guide
so they knew what types of questions to expect and the type of documentation
that might be requested. A standard form of the letter of introduction and overview
of the research is included in Appendix 3. It was modified slightly for each
organization, depending on whom the researcher met, in the case study organization,
and amount of advance data provided by telephone and mail.
To further corroborate the evidence and to provide a formal assembly of evidence
separate from this report, a case study data base was established. The case study
data base includes a copy of the completed interview guide or guides for each
firm, any additional notes taken outside of the interview guide, and a detailed
summary write-up of each case. Use of case studies involve multiple data sources,
and may include internal and external documentation as well as interviews. Thus,
any printed material the participating organizations provided the researcher, such
as samples of TCO analysis, written training guides, presentations, memos and
other internal documentation are also included in the data base. "^
Construct Validity
Construct validity, the third issue in research design quality, addresses
establishtnent of the proper operational measures for the concepts being studied.- •
Thus, it is part of the data collection phase, and is closely tied to reliability. Three
elements are associated with the establishment of construct validity: using multiple
sources of evidence, establishing a chain of events, and having key informants
review the case study research. Each is summarized below.
I. Multiple Data Sources. A primary element of construct validity in research
is through triangulation. As mentioned earlier, triangulation is the use of multiple
data sources to corroborate evidence.^'* Informant bias has been a criticism of research
that involves interviewing human subjects.-^^ Triangulation of data helps to overcome
this potential problem by using some combination of multiple informants, internal
company memos, procedures and other documents, use of direct observation, written
questionnaires, and other data gathering techniques. Multiple indicators also tend
to produce more stable and reliable results.^
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ELLRAM
In nine of the eleven cases, multiple informants were involved in order lo
give the results greater breadth and better validity.-'^ Infortnants always included
a member of the purchasing function actively involved in TCO analysis. Other
informants varied in functional representation because there was no other functional
group consistently involved in TCO analysis, and the researcher sought to interview
other functions with the greatest direct involvement. All of the case studies included
on-site visits. In addition, extensive telephone interviews, exchange of documents,
and other discussions were conducted to clarify issues and corroborate data where
the researcher deemed it necessary.
Based on precedence in case study research, the interview protocol served as
a guide for the researcher. The researcher used a focused interview or semistructured
To
approach.'* Thus, when interesting avenues not directly pertaining to the interview
guide arose, those lines of questioning were pursued, and the comments noted.
The researcher tried to obtain as many relevant documents and examples of the
organization's approach to TCO as were available. This included internal memos,
copies of reports, presentations, training manuals, and samples of actual analysis.
Such written data are an important means of corroborating verbal evidence.-^^
2. Establish and Maintain a Chain of Evidence. This second element of construct
validity relates to the ability of the reader of the case study to follow the case
study data and analysis from the initial formulation of the research questions to
its final conclusions.'^ In the case of this report, five external reviewers examined
the entire document, including research questions, research plan, interview protocol,
and individual case study summaries. Three reviewed the document specifically
for logic, flow, clarity and content. Two others reviewed it for all of the preceding
reasons, as well as for editorial changes. This provided an external verification
that there was, indeed, a logical flow and "chain of evidence."
3. Draft Revievy by Key Informants. The third element to support construct
validity was to have each of the key informants review the overall case study
report compiled by the researcher for his or her organization. The participants were
also required to sign a release form verifying that the case facts were accurate.
As a result of this review process, some changes were made to the individual
cases, which were sent to the informants for re-review and approval.
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107
Internal Validity
The fourth and final issue in research design quality, internal validity, is only
a concem in explanatory case studies, where the researcher is trying to demonstrate
that some outcome was caused by an independent variable."*' It is irrelevant for
those case studies that are solely exploratory or descriptive in nature. Internal validity
in case study research relates to making proper inferences from the data, considering
alternative explanations, use of convergent data, and related tactics.'*^ This concept
will be illustrated below in the discussion of the data analysis and processes employed:
open coding, axial coding, and selective coding.
DATA ANALYSIS
Data analysis processes used in case study research may come from quantitative
or qualitative disciplines, depending upon the type of data gathered. In the TCO
study, qualitative data were gathered. Processes for analyzing these data are discussed
below.
Prestructured Case Outline
The researcher used a prestructured case outline, as shown in Appendix 1,
part II.C. and part IV. The prestructured case is an excellent way to deal with
the recurrent problem of data overload in qualitative studies. In addition, it is
easy to follow when the informants are reviewing the case for accuracy. By using
a standard format, it is easier for the researcher to locate the data related to a
particular issue across all cases. Note that the structured case does not replace
the case study data base, or the data coding processes discussed below.
Data Coding Processes
The data from the case studies were analyzed in several ways, based on
precedence in case study research and building grounded theory. Through the use
of open coding, the data were broken down, examined, compared, contrasted, and
categorized. Axial coding made preliminary connections among the categories
developed in open coding, while selective coding processes were used to integrate
the theory into a cohesive whole.**
Each of these processes is explained and discussed beiow. It is important to
keep in mind that case studies are also very difficult and present unique challenges
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ELLRAM
to the researcher in terms of providing explanation for the events that are described.^^
Due to the complexity and sheer volume of data, the data analysis process is an
iterative one. The analysis begins simultaneously with the gathering of the data,
and continues throughout the data collection process and beyond.
Open Coding
"Open coding," the first data coding process, refers to methods used to break
down case study data in order to analyze, conceptualize, and develop categories
for the data. As in the TCO study, open coding can simultaneously relate to making
comparisons or lo asking questions related to the data."*^ Miles and Huberman**^
refer to this type of coding as first level coding, as it is really a way to summarize
segments of data.
For example, in the TCO study, one comparison that was made was to examine
for which types of purchase decisions the participating organizations used TCO.
This can be done by developing a table that lists the organizations vertically, and
the data categories of interest, in this case, the various types of buys, horizontally.
In developing the type of comparison table shown in Table 5, the question
had to be asked, "How should the data be categorized?" The data could be categorized
so as to encourage further analysis, to ask questions or answer questions related
to the data, or to simply present data "as is" in a descriptive fashion, as it was
in the TCO report. Presenting the raw data in this way allows the reader to develop
his or her own insights.
Similar coding was done with much of the other case study data. Open coding
is an iterative process that allows the researcher to compare similarities and
differences among case studies. This paves the way for axial coding that groups
phenomenon into categories to begin to develop insights.**^
Axial Coding
The second data coding process, axial coding, is a set of techniques thai makes
connections among categories developed in open coding. This approach looks at
interactions and conditions, and helps provide greater insight into the data.-**" Miles
and Huberman'*' refer to this as "pattern coding," in that it groups issues identified
during first level coding, summarizing them into themes. Keep in mind that this
is an iterative process alternating between open and axial coding rather than a
sequential process.
JOURNAL OF BUSINESS LOGISTICS. Vol. 17. No. 2. 1996
109
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ELLRAM
For example, in the TCO study, the use of TCO modeling for specific buys,
as in Table 5. could be further broken down into subcategories. based on whether
the organizations used a "standard" TCO model that could be used repetitively,
or developed a unique model, where a model would need to be developed for
each buy of a different item. One might also look at whether the models were
automated. This grouping is shown in Table 6.
TABLE 6
EXAMPLE OF AXIAL CODING: GROUPING TCO MODELS
INTO UNIQUE VS. STANDARD MODELS
A-oil
Paper or Unique
Spreadsheet
B-medical systems
X
C-defense electronics
X
D-process industry
X
Standard
Spreadsheet
Standard Automated
System
X
E-teiecommunications
equipment/support
F-defense aviation
X
G-semiconductor
X
X
H-semiconductor
X
X
I-OEM for transportation
industry
X
J-diversified electronic/
computer
X
K-semiconductor
X
X
Axial coding is an important step. The analysis of the data is limited to categories
and subcategories developed at these stages of the research. Development of
categories requires a complex, iterative, inductive and deductive thinking and analysis
JOURNALOF BUSINESS LOGISTICS. Vol. 17. No. 2. 1996
111
process.-^ Many researchers do not specifically distinguish between open coding
and axial coding,''-' in part because they are mutually dependent and iterative.
Selective Coding
The third data coding process, selective coding, is defined by Strauss & Corbin-^**
as the process of selecting the central category of the analysis, relating it to other
categories, and validating and further developing categories. Again, this distinct
process of coding has been grouped by some researchers together with open and
axial coding, or pattern coding, as they are mutually dependent, iterative processes.-''^
As Strauss and Corbin-^'' point out, selective coding is an integrative process like
axial coding, but at a much higher, holistic level of analysis. Here, alternative patterns
are sought out and analyzed to explain the key phenomenon of interest. Pattern
matching, which is considered one of the best techniques in case study analysis,**^
is relied upon heavily. Patterns may be developed and compared with a predicted
pattern, or previous research. For example. Table 7 combines the information in
Tables 5 and 6 and could lead to new insights. Alternative explanations of patterns
should also be explored. Explanation building based on patterns and causal links
strengthens the internal validity of case study findings. By demonstrating that
alternative explanations do not account for the patterns, the case for the explanation
supported by the researcher is strengthened.
Theory must also allow for alternative explanations based on different
circumstances or context.^^ As revealed in Table 7 based on data from the TCO
study, some of the capital TCO models were "standard spreadsheets." while some
were unique to each buy. One way to explain that is to say that all of the organizations
using a standardized capital model are affiliated with the semiconductor/computer
industry, and use the TCO model supported by SEMATECH. There were no
exceptions. The researcher could then begin to formulate explanations as to why
that is, based on the facts gathered. For example, the researcher developed the
following possible explanations.
1. The organizations using the standard TCO model focused on a standard
model because the key issues in capital acquisition appear to be similar,
recurring theories across productive capital.
2. Other organizations do not use standard capital TCO models because
they are too difficult to develop internally.
ELLRAM
112
3.
Other organizations do not use standard capital acquisition TCO models
because capital expenditures are not significant or important to them.
4. The semiconductor industry is the only industry that uses a standard
capital acquisition TCO model.
TABLE 7
EXAMPLE SELECTIVE CODING TO DEVELOP FURTHER
EXPLANATIONS OF USE OF UNIQUE VS. STANDARD
TCO MODELS BASED ON TYPE OF BUY
Capital for Capital for Raw
Components Production Support Materials
Services
MRO
A-oil
U
U
U
B-medical systems
U
u
U
Organization
C-defense electronics
U
D-process industry
U
u
u
U
U
U
u
u
u
u
U
SA
E-telecommunications
equ i pme n t/su pport
F-defense aviation
U
G-semiconductor
U
H-semiconductor
U
u
u
i-OEM for iransp.
industry
J-Diversified
electronic/computer
K-Semiconductor
U = Unique;
SS = Standard Spreadsheet;
SA = Standard Automated System
u
U
U
U
U
SS
u
u
SS
u
u
u
u
SS
u
SS
u
JOURNALOF BUSINESS LOGISTICS, Vol.17. No. 2. 1996
113
These explanations need to be examined in light of other case study dara (the
case study data base) and the literature. Such an examination revealed that explanation
(1) was internally and externally consistent. Internally consistency means that tbe
explanation is valid based on the case study data. External consistency means that
the explanation is valid based on known facts and issues occurring outside of tbe
case study data base—such as witbin the literature.''^
Explanation (2) is not internally valid because tbe researcber learned from several
of the cases that the standard TCO model supported by SEMATECH was originally
developed by one of tbe SEMATECH member companies who participated in the
TCO study. Tbus, this is rejected.
Explanation (3) is also rejected due to lack of internal validity. Several of
the case study participants specifically noted tbat capital expenditures are very
important to tbeir organization.
Explanation (4) is valid based on internal consistency. However, it is rejected
as not having external consistency, because the literature review revealed that a
standard capital TCO model is used in some public utilities.^
Discussion of Analysis Issues
Tbe above discussion of case study data analysis is abbreviated and simplified.
Tbe key issues to note are:
1. Specific analytical procedures sbould be followed in formulating case
study research design, gathering evidence, developing theory, explanation
and presenting case study data.
2. Tbe analysis of case study data is an iterative process, resulting in
either the depth and strength of explanation growing, or tbe explanation
being rejected.
3. Case study data analysis sbould embrace concepts of both internal
and external consistency.
^
4.
Searching for patterns among case study data is a key strategy in
providing explanation and validity of results. Use of external reviewers
and review by key informants is important in providing construct
validity.
114
ELLRAM
Generalizability
The seventh and final misconception of the case study method is that research
results are not generalizable. In judging the generalizability of research results,
it is critical to have a clear understanding of the research methodology. The more
sound it appears, the greater the validity/generalizability of results. If case study
results allow for a "range" of activity, while still providing a consistent explanation,
they are more generalizable.^' Thus, multiple case study results may be more
generalizable than the results of a single case study, which tends to be very specific.
Another issue that affects generalizability is whether or not a range of conditions
are incorporated in the explanation. Inclusion of broader issues allows for greater
generalizability. As Yin points out
*'. , . case studies, like experiments, are generalizable to theoretical
propositions and not to populations or universes. In this sense, the case
study, like the experiment, does not represent a "sample," and the
investigator's goal is to expand and generalize theories (analytic generalization)
and not to enumerate frequencies (statistical generalization).
Thus, the generalizabiIity of case study results tends to be qualitative in nature.
SUMMARY AND CONCLUSIONS
The preceding sections have demonstrated through the literature and use of
case study data that case study methodology entails both a vigorous design and
a rigorous analysis. Not just "anyone" can use a case study research methodology.
Its execution requires careful planning and execution. It requires the ability to step
back from the data, analyze data objectively, creatively develop explanations and
search for patterns, and rigorously attempt to find holes or problems in the patterns
suggested. One of the keys in gaining credibility for case study research and
qualitative studies is to make the case study research procedures and process explicit,
so that readers of the study can judge the soundness and appropriateness of the
methodology.'^^ However, this is often difficult in the limited space of a journal
article. It Is suggested that those using such a methodology provide details of the
method iti appendices to their research, or at least develop such appendices, while
inviting interested readers to write to the author and request the details.
JOURNALOF BUSINESS LOGISTICS. Vol. 17. No, 2, 1996
115
It sbould be noted that tbe preceding example presents only one possible use
of case study methods. Case studies are excellent for tbeory building, for providing
detailed explanations of "best practices," and providing more understanding of data
gatbered.
Wbile case studies do not fit every research situation, they have much greater
applicability tban previously believed. Excellent opportunity exists for using case
study research methodology in many areas of logistics and purchasing. Some of
these areas include:
1. Exploring implementation issues and options in the adoption of artificial
intelligence/expert systems in logistics.
2.
Understanding the impact of various types of logistics and purchasing
organizational structures on the role of logistics in an organization.
3. Understanding tbe decision-making process related to:
a. Whetber or not an organization outsources logistics activities.
b. Tbe degree of outsourcing pursued.
4. Developing a theory as to wby materials management activities achieve
a higb level of organizational status and participation in some firms,
while not in otbers. Once a theory is built and constructs developed,
a survey could be used to test tbe theory.
This is clearly only a small list of potential case study topics. Tbe reader is
reminded tbat the case study research methodology should not be undertaken lightly.
Tbe methodology sbould be carefully planned in advanced, and sbould support
systematic gathering of data required to address tbe research questions of interest.
116
ELLRAM
APPENDIX 1
CASE STUDY PROJECT
TCO STUDY RESEARCH PLAN
I. Goal: 6-12 Indepth TCO Case Study Profiles
A. Research QuestionsAssues
i
1. How to get started in TCO?
• impetus
2. Who is involved in the effort?
• include issue of top management support. Whose idea?
3. Information sources used in TCO?
4. Linkages with other systems within the firm, automated or not?
5. Accounting systems/relationships with accounting systems, ABC?
6. Very specific uses/exampies of uses, including applications and
reports.
7. Strategic vs. operational uses of TCO data?
I
8. TCO's impact on internal and external relationships?
9. TCO as a philosophy vs. a tool?
10. Benefits
• soft
• hard
"
••
1 1 . Various types of models used.
12. Pros and cons of each model type.
13. "Generic" vs. "Specific" models.
14. Relation of TCO to ABC/firm's accounting system?
15. Are certain types of models more compatible with certain
types of purchases?
16. Is there any relationship between the charge-out of
purchasing department expenses and TCO modeling?
JOURNALOF BUSINESS LOGISTICS, Vol. 17. No. 2, 1996
•
B. Statement of Purpose: (rationale and direction).
The purpose of this study is to assess the state of TCO
practice and implementation among U.S. firms using TCO
modeling today, with the goal of educating and easing the
implementation process of other firms interested in TCO
implementation.
C. Unit of Analysis—The firm that has implemented and utilized
a TCO system is the unit of analysis.
II. Methodology/Case Study Design
A. Multiple Case Design
1. Each case as an experiment, a replication, not as a single
response to a survey. Not sampling.
2. Write up each case individually—develop a standard case
format.
a. Pattern match
b. Implications
3. Do overall write up of findings hased on patterns, inferences.
B. Sample Selection
1. Firms known lo be using some fomi of TCO modeling
2. Cooperation.
a. 2 people from purchasing (minimum)
b. 1 person from finance
c. Willingness to share samples of:
• TCO reports
• Savings documentation
And have reports published in CAPS study report
3. Firms in a variety of industries, both manufacturing and
non-manufacturing
C. Basic Outline of Overall Case Study Report
1. Overview
• What is TCO?
• Why the increased interest?
• Who cares?
117
118
ELLRAM
2. Research questions/propositions
• Managerially, why these questions were chosen
3. Research design/methodology
4. Presentation of models
,
5. Discussion of results
6.
Conclusions/implications/recommendations
7. Bibliography
8. Appendices
a. Recommendations for TCO implemetitation: A managerial
model
b. Individual case study write-ups
c. Copy of interview protocol
D. Pilot Study
1. Often choose a firm that is located CLOSE, accessible/congenial
informants, lots of documentation (Inte?)
2. Not a "pretest," help refine data collection plans re: content/
procedure
3. Write up re: content/procedural implications
E. Collecting Evidence
1. Three essential ideas
a. Multiple sources of evidence—any 2 or more sources
converging on same facts
b. Case study data base—make information traceable, keep
in one place
c. Chain of evidence that links questions asked, data
collected and conclusions drawn
2. Sources of evidence
a. Documentation
• internal memos, reports, announcements
• proposals, formal studies, news clippings
• corroborate/augment other evidence. Specifically:
JOURNALOF BUSINESS LOGISTICS, Vol.17. No. 2. 1996
1. Documentation on TCO data gathering
2. Copies of TCO savings calculations
3. Copies of TCO savings summaries/reports, including
distribution list
4. Internal training documents
5. Internal memos related to TCO
b. Archival records
1. Copy of organizational chart—total firm, division
2. Copy of purchasing organizational chart
3. Lists of commodities/services included in TCO
c. Interview—key source of information
1. Key informants—op>en ended interview; key events and
options of those events—Why did your firm adopt TCO?
corroborate with other evidence.
2. Focused—respondent is interviewed for a short time
period; certain set of questions may/may not be open
ended
d. Direct observation
• visit "field," only informal data gathered here, see how
reports are filed, etc.
e. Establish a data base—improve case study reliability,
contains:
1. Case study notes
• interviews
• document analysis
2. Case study documents gathered, including any notes
explaining documents
3. Tabular materials—any summaries I create/data I
tabulate
' 4. Nanatives
III. Data Analysis—Overall Project
A. Pattern Matching
1. Look for like patterns of usage/implementation among costbased vs. value-based models
2. Look for patterns based on reason for TCO implementation
U9
120
ELLRAM
3. Look for patterns based on the strength of ties to other internal
accounting/performance reporting systems
4. Patterns based on who participated in model development/
implementation
5. Patterns/associations with TCO/ABC
6. Patterns of internal participation in TCO, including top
management support. Is this related to TCO success/
implementation issues?
7. Patterns based on how TCO is viewed (tool vs. philosophy)
8. Patterns based on how TCO is used in decision support.
B. Explanation Building
1. Exploratory case studies; not to draw conclusions, but develop
ideas for further study.
2. Link current propositions/theory to my previous case study
findings.
IV. Proposal Case Study Format—Individual Case Write-Ups
A. Background on Company
•
•
industry
strategy
•
key competitive issues
B. History of TCO
•
•
•
•
•
•
•
when developed
why
who was involved
how has it changed
barriers
stages/steps they went through training
philosophy toward TCO (tools vs. part of culture)
JOURNAL OF BUSINESS LOGISTICS. Vol. 17, No. 2. 1996
C. Sample of Model Used
•
•
•
classify as dollar or value based
why was this type of model chosen?
variables/cost elements included
D. Update/Maintain Mode!
•
•
•
•
•
linkages with other systems
information sources
who is responsible
frequency of updates
acceptance/questions of model integrity?
E. Model Uses
•
•
•
•
•
•
sample of output
overall reporting
soft vs. hard data
types of decisions—strategic and operation
who gets the output
• internal
• external
TCO expected on key decisions, or is it an extra?
F. Finn's Accounting Systems
•
•
•
purchasing as cost center
allocation of purchasing costs
interest/movement towards ABC
G. Evolution of TCO Over Time
•
•
•
changes in types of models
changes in people involved
expected future direction for TCO
• automation
• usage
• acceptance
i2J
122
ELLRAM
V. Time Table—Revised/Accelerated
Advisory Board Meeting
Revised protocol mailed out
Identify pilot case
Conduct pilot case
Case analysis/write up
Draft of report
8/6/93
8/6/93
end of August
late December-early February 1994
early February 1994
APPENDIX 2
INTERVIEW GUIDE
Total Cost of Ownership Questionnaire
Background
Name
Company
Division
Industry
Job Title
Years in Position
Years with Company
Years in Purchasing
1. What is the major business of your company?
2. What are the key issues/competitive challenges facing your firm?
3. Are you currently undergoing, or have you undergone any major
changes in your purchasing organization or practice in the past year?
Please discuss.
JOURNALOF BUSINESS LOGISTICS, Vol. 17. No. 2. 1996
123
4. How is the purchasing function organized? Do you have an organizational
chart I could have a copy of? (Names may be deleted if necessary.)
Where does the purchasing function report within the firm? (Reporting
chain.)
5. Do you have specific, quantifiable written cost savings/cost management
objectives for purchasing? Give an example. What is the highest level
that reviews those plans?
•
How is the achievement of purchasing's objectives evaluated?
Definition: Total cost of ownership approach a structured approach for
determining the fatal costs associated with the acquisition and subsequent
use of a given item/service from a given supplier. This is a comprehensive
approach that goes beyond price to consider a number of other costs, which
might include: service costs, failure costs, administrative costs, maintenance,
and life cycle costs.
General TCO Questions
6. Does your firm use a structured total cost of ownership approach In
purchasing? If yes, how do you define TCO?
• Do you use TCO as a product approach for selling, purchasing as
a value-added function in your organization?
Allocation of Purchasing Department Costs
7. Do you have formal budgeting procedures for purchasing's administrative
costs?
Are you involved in budgeting for the purchasing function?
• If not involved, are you familiar with it?
Note: If the purchasing person is unfamiliar with the budgeting or chargeout system, ask for name of someone else in purchasing or someone in
accounting to help answer these questions.
12^
'
ELLRAM
8. Are customers/user departments charged for service of the purchasing
department? How are these charges calculated?
9. How often is charge-out method updated/reviewed?
10. Are charges to user departments based on an overhead rate or direct
charge out?
11. Do you feel the current charge-out system is fair/makes sense?
12. What changes, if any do you think should be made in the charge-out
system?
13. Do users have "right" to protest charges? Do they ever?
Breadth and Depth of TCO Model
14. For what types of buys does your firm use a TCO model?
services
capital for production
MRO
capital for office/support
components
raw materials
-
other: Specify
15. Tell me about the way your firm uses TCO. Is there a basic frameworic
that your firm uses for each type of buy, or do you have different
models? If there is a framework, what is it?
16. Are there a set of common factors that are usually considered across TCO
models? If so, what are they?
Which costs do you consider most important?
Which costs do you find easiest to measure and why?
Which costs do you find the most difficult to measure and why?
17. Would you be willing to share with me an example of the TCO models
that your firm uses for different types of purchases? (Ask to see/have
explained, take a copy with me.)
18. If use a direct dollar based model: Do you feel that using all dollar data
adequately refiects the supplier's value? Why or why not? Are there
additional non-dollar issues that are considered inside or outside of the
JOURNALOF BUSINESS LOGISTICS. Vol. 17, No. 2. 1996
125
model? How are soft factors considered (cooperative, responsiveness,
ISO certification, etc.).
19. If you use a multiplier cost based model: Why don't you use a direct
dollar based model? What advantages do you think this model brings
that a dollar base mode! would not bring? How are soft factors
considered? (Get a good understanding of how costs/values are
calculated and updated.)
20. Where does the model reside/exist (paper, mainframe, PC, etc.)? Ask
for source of model.
21. Do you use some type of model for everything your firm buys? Or does
it depend on the importance/dollar magnitude, etc.?
22. If you don't use the model for all buys within a type of buy, what
determines whether or not you use the model for a given purchase?
Do other functional areas in the firm or external customers ever
request a TCO analysis? Under what circumstances/example.
23. Who or what function "owns" the model?
24. What are the sources of information for the model?
What costs are associated with maintaining data for the model?
25. Who is responsible for gathering/maintaining model information (rates,
etc.)—individual, group ad hoc?
26. Are there any direct linkages to other systems such as delivery
performance, quality, and so on? Please explain. Can I see the
information from other systems that feeds into the TCO model?
27. How often is the TCO information in the model updated? Is there a
regular schedule, or is it ad hoc?
How do you measure the effectiveness of TCO model?
28. Are any employees trained on the use of the TCO model/approach? If
so, how does that training occur?
Do you train suppliers in TCO?
126
ELLRAM
TCO History
29. To the best of your knowledge, what year did your firm begin using a
TCO approach?
30. What created the interest in a TCO approach?
31. Whose idea was it/how did the TCO movement get started?
32. Was there any top management involvement in the early levels of TCO
development? What levels/functions were involved?
33. What functional areas worked on developing the model? Who led the
effort? Was it a committee or individual effort?
What do you believe was the single most important factor that assured
TCO implementation in your firm?
34. Is top management aware of/supportive of TCO? Are other functional areas
aware of/supportive of TCO? Has TCO implementation affected the
purchasing function's relationship with other internal functions? Explain.
35. Has TCO modeling increased purchasing's involvement in decision making?
Explain any changes, and why you believe those changes have occurred.
36. If a primary drive behind TCO development and implementation was a
quality improvement effort, how specifically is TCO linked to the firm's
quality programs? Please explain fully, including:
• reporting
• performance expectations
• continuous improvement efforts
• quality awards/certification
• other
37. What specific quality related benefits do you expect to get, or have you
received as a result of TCO information? Can you quantify the cost
implications?
38. Do you believe that the linkage of TCO to the TQM program has helped
the acceptance of TQM, or vice versa? How/why; address both
internally and externally (with supplier).
39. If your firm is involved in "partnering," what impact has TCO had on
your partnering efforts, or vice versa?
JOURNALOF BUSINESS LOGISTICS, Vol.17. No. 2. 1996
127
40. Do you recall what the issues/difficulties/barriers were with early
development and implementation of a TCO approach?
41. How were those difficulties overcome; what did you leam?
42. Tell me about how the TCO model(s) used by your firm have changed
over time. What did the early model look like vs. a model that is in
use today?
43. What factors do you believe infiuenced those changes?
What changes/enhancements would you still make to your TCO models?
Model Applications
44. Who within your firm uses the output of the model? Can I see a copy of
the output if it is different than the example(s) of the models you have
already given to me?
45. What is the output used for specifically within your firm? e.g.. supplier
selection, ongoing evaluation, etc.
46. What impact has TCO had on decision making? Please given specific
examples. Has TCO had an impact on any major/strategic decisions that
you are aware of? Please give strategic examples.
47. What impact has TCO had on cost of material?
48. Is TCO viewed as a tool or a philosophy? Give me an example to
support this.
49. Has TCO affected purchasing's relationship with suppliers? Explain.
50. If TCO is used in supplier selection, how is TCO used when the
selection process includes one or more new suppliers?
What do you do about data unavailability?
What do you do about data credibility, given your lack of experience with
that supplier?
51. Give specific examples of how you do/have used TCO data with
suppliers to:
•
•
negotiate prices
reduce prices
ELLRAM
•
•
•
•
•
•
improve quality
terms
delivery
services
manage supplier performance
other
52. Have you ever changed your requirements of the supplier (specs, delivery,
etc.) as a result of TCO data? Please share an example or two with me.
53. Do you ever share the TCO information with current and/or potential
suppliers? Under what circumstances?
54. What do you see as the benefits of using the TCO approach?
55. Do you track savings from using a TCO approach? What savings are
tracked, and how? Who receives the reports? How much does your firm
save annually by using a TCO approach? May I see/have a copy of the
summary report you issue on TCO savings?
56. Do you track non-monetary benefits from using a TCO approach? If so,
what are they and how are they tracked and reported? May I see/have a
copy of the summary report you issue on non-monetary benefits?
57. What do you see as the drawbacks/difficulties/disadvantages of using the
TCO approach?
58. Are there any problems that you see as so serious that they may distort/
undermine the results of the model?
Cost Accountability
59. What is the purchasing function's responsibility for cost/price of purchased
goods/services?
60 Are you individually responsible for cost/price variances on items
purchased? In what way? Is there a tie-in to performance appraisals/
merit increases?
61. If purehasing is directly responsible for costs, what are costs compared to?
Do you consider market prices?
JOURNALOF BUSINESS LOGISTICS. Vol.17. No. 2. 1996
129
62. Do you feel your firm's emphasis on managing costs of purchased
goods and services has Increased, decreased, or stayed the same? Why?
Development
63. Have you ever benchmarked TCO practices with other firms? Please
discuss.
64. To the best of your knowledge, do your suppliers use a TCO approach?
Do you encourage your suppliers to use a TCO approach?
65. Is there anything else significant about your use of a TCO approach, or
your implementation of a TCO approach that you think I should know
about?
66. Can you give me the name of a corporate controller who could provide
me with some information about your firm's accounting and cost
allocation system?
Questions for Corporate Controller/Cost Accountant
(May be two separate people)
Corporate
1. Are costs for the purchasing/materials management group charged to
users of the department? How?
2. Are allocated costs actual or budgeted?
3. How often is the allocation reviewed/updated? How is it updated?
4. Are charges to user departments based on budget or actual
expenditures from a pool?
Definition: Total cost of ownership approach is a structured approach for
determining the total costs associated with the acquisition and subsequent
use of a given item/service from a given supplier. This is a comprehensive
approach that goes beyond price to consider a number of other costs, which
might include: service costs, failure costs, administrative costs, maintenance,
and life cycle costs.
'^0
•
ELLRAM
5. Have you or others in your department worked with purchasing/materials
on total cost of ownership? If yes, please elaborate.
6. Do you use an activity-based accounting system? If yes, would you
please explain your key cost drivers and allocation pools?
7. If yes to 5, is ABC operationalized in understanding the cost of
ownership for purchased items/services?
• How do you account for costs of quality
•
•
•
•
training
inspection
rework
scrap
• Maintenance/Repair
• Warranty
• Billing errors from suppliers?
• Is this allocated by department, or to product lines?
• What accountability is there for scrap, waste, by product, etc. (by
department, product, worker, etc.)
Plant/Cost Accountant
8. What costs are considered plant overhead costs?
9. How are plant overhead costs allocated to products?
10. What other costs are allocated to product, rather than directly charged?
11. Are there any costs added, either directly or through allocation, to the
costs of materials charged to product?
Note: These questions are only relevant to plant accountant if you talk to
BOTH a corporate account and a plant/cost accountant.
12. Have you or others in your department worked with purchasing/materials
on total cost of ownership? If yes, please elaborate.
13. Do you use an activity-based accounting system? If yes, would you
please explain your key cost drivers and allocation pools?
JOURNAL OE BUSINESS LOGISTICS, Vol. 17. No. 2, 1996
14. If yes to 12, how is ABC operationalized In understanding the cost of
ownership for purchased items/services?
APPENDIX 3
LETTER OF INTRODUCTION AND ATTACHMENT
Dear
,
I enjoyed talking with you on the phone on Friday, September 24. T am
really looking forward to my visit to
on Wednesday, October
27th. I appreciate your willingness to host my visit. I'll plan on arriving at
your facility at approximately 9:(X) a.m.
I've enclosed a brief overview of the research as well as copy of the
interview protocol. Please don't be intimidated by the length of the
protocol—I use it as a guideline only. Total cost systems vary significantly
among companies, and I am interested in leaming about what is unique
about your system.
In addition to spending a minimum of
hours with purchasing, if
possible, I'd also like about 30 minutes with someone who understands the
product costing systems. As we discussed, I look forward to spending some
additional time touring your facility and leaming about your organization in
general.
Finally, if you have any general or purchasing specific information about
your organization that you could send me in advance, I'd appreciate it
greatly. That would help me be more prepared for our visit.
Thanks again! Please call me if you have any questions or concerns.
Best Regards,
131
ELLRAM
Attachment
Statement of Purpose
The purpose of this study is to assess the state of TCO practice and
implementation among a sample of North American firms using TCO modeling
today, with the goal of educating and easing the implementation process of other
firms interest in TCO. With increased emphasis on partnering, cycle-time reduction,
and supply chain management and growing gloha! competition, understanding total
cost of ownership is critical. This research defines total cost of ownership as a
structured approach for determining the total costs associated with the acquisition
and subsequent use of a given item/service from a given supplier. This is a
comprehensive approach that goes beyond price to consider a number of other
costs that might include service costs, failure costs, administrative costs, maintenance,
and life-cycle costs.
Methodology/Case Study Design
Multiple case design (6-12 case studies) will be used to develop an in-depth
understanding of TCO practices. A review of the literature and discussions with
experts in the field indicate that total cost modeling is not widespread. Thus, a
select number of firms known to use total cost modeling approaches will be chosen
for this study, rather than a random sample.
Research Results
Theresultsof this research study will be documented in a comprehensive written
report. This report wilt include a summary and analysis of the overall findings,
as well as detailed individual case studies, to provide depth. In addition, the findings
will be presented at the CAPS Executive Purchasing Roundtabie, NAPM conferences,
and other appropriate settings. Articles will also be written for both the academic
and trade press.
JOURNALOF BUSINESS LOGISTICS, Vol. 17, No. 2, 1996
133
Timetable—Revised/Accelerated
This project begins July 1993. The final draft of the report should be ready
for editing early February 1994, with publication in April 1994.
Advisory Board Meeting
Revised protocol mailed out
Identify pilot case
Conduct pilot case
Identify additional cases
Conduct case studies
Case analysis/write up
Draft of report
Review, edit, print
7/30/93
early August
mid-August
end of August
early September
September-December 1993
late December—early February 1994
early February 1994
March-April 1994
NOTES
'Thomas Bonoma, "Case Studies in Marketing: Opportunities, Problems and
a Process," Journal of Marketing Research 22 (May 1985): 199-208; Barbara B.
Fiynn, Sadoa Sakakibar, Roger G. Schroeder, Kimberly A. Bates, and E. James
Flynn, "Empirical Research Methods in Operations Management," Journal of
Operations Management 9, no. 2 (April 1990): 250-284; Jacques Hamel, Stephane
Dufour and Dominic Fortin, Case Study Methods (Newbury Park, Calif.: Sage
Publications, 1993); and R. K. Yin, "The Case Study Crisis: Some Answers,"
Administrative Science Quarterly (1981): 58-65.
^Flynn, et al. reference in Note 1; Jack R. Meredith, Amitabh Raturi, Kwasi
Amoako-Gyampah and Bonnie Kaplan, "Alternative Research Paradigms in
Operations," Journal of Operations Management 8, no. 4 (Oct. 1989): 297-326;
Robert K. Yin, Case Study Research, 2nd ed. (Thousand Oaks, Calif.: Sage
Publications, 1994); D. M. McLutcheon and J. R. Meredith, "Conducting Case
Study Research in Operations Management," Journal of Operations Management
11, no. 3 (Sept. 1993): 239-256; and John T. Mentzer and Kenneth B. Kahn, "A
Process Model for Logistics Research," 1993 Transportation and Logistics Educator's
Conference Proceedings (Columbus: Ohio State University, 1993), pp. 141-160.
-^Robert A. Novack, John C. Langley, Jr., and Lloyd M. Rinehart, Creating
Logistics Value: Themes for the Future (Oakbrook, III.: Council of Logistics
ELLRAM
Management, 1995); and Bruce Ferrin, "Planning Just-In-Time Supply Operations:
A Multiple Case Analysis," Journal of Business Logistics 15, no. 1 (1994): 53-70.
^Flynn, et al., Hamel, et al., and Yin references in Note 1 and Meredith,
et al., Yin, and McLutcbeon and Meredith references in Note 2.
^Mentzer and Kahn reference in Note 2; Steven C. Dunn, Robert F Seaker,
Alan J. Stenger and Richard Young, "An Assessment of Logistics Research
Paradigms," 1993 Transportation and Logistics Educator's Conference Proceedings
(Columbus: Ohio State University, 1993), pp. 121 -140; John T. Mentzer and Kenneth
B. Kahn, "A Framework of Logistics Research," yourna/ of Business Logistics 15,
no. 2 (1994): 231-250.
^Yin reference in Note 1; Yin reference in Note 2; and R. K. Yin, E. Bingham,
and K. A. Heald, "The Difference that Quality Makes: The Case of Literature
Reviews," Sociological Methods and Research 5 (1976): 139-156.
^Bonoma et al. and Hamei, et al. references in Note 1; Paul Cozby, Methods
in Behavioral Research, 4th ed. (Mountain View, Calif.: Mayfield Publishing Co.,
1989); K. M. Eisenhardt, "Building Theories from Case Study Research," Academy
of Management Review 14 (1989): 532-550; Lawrence R. Jauch, Richard N. Osbom,
and Thomas N. Martin, "Structured Content Analysis of Cases: A Complementary
Method for Organizational Research," Academy of Management Review 5 (1989):
517-525; Anton Kuzel, "Sampling in Qualitative Inquiry," in Doing Qualitative
Research, Benjamin Crabtree and William L. Miller, eds. (Newbury Park, Calif:
Sage Publications, 1992), p. 33; A. S. Lee, "Integrating Positivism and Interpretive
Approaches to Organizational Research," Organization Science 2 (1991): 342-365;
Catherine Marshall and Gretchen B. Rossman, Designing Qualitative Research
(Newbury Park, Calif: Sage Publications, 1989), pp. 54-63; Matthew B. Miles
and A. Michael Huberman, Qualitative Data Analysis (Thousand Oaks, Calif: Sage
Publications, 1994); William L. Miller and Benjamin F. Crabtree, "Primary Care
Research: A Multimethod Typology and Qualitative Road Map," in Doing Qualitative
Research, Benjamin F Crabtree and William L. Miller, eds. (Newbury Park, Calif:
Sage Publications, 1992), pp. 3-30; H. Mintzberg, D. Raisinghani, and A. Theoret,
"The Structure of 'Unstructured' Decision Processes," Administration Science
Quarterly 21 (1976): 246-275; and Anselm Strauss and Juliet Corbin, Basics of
Qualitative Research (Newbury Park, Calif: Sage Publications, 1990).
JOURNALOF BUSINESS LOGISTICS. Vol. 17. No. 2. 1996
135
^Michiel R. Leenders and James A. Erskine, Case Research: The Case Writing
Process, 3rd ed. (London, Ontario: The University of Western Ontario, School of
Business Administration, 1989), p. 3.
^Yin reference in Note 1.
' ^ . L. Hoaglin, R. J. Light, B. McPeek, F Mosteller, and M. A. Stoto, Data
for Decisions: Information Strategies for Policymakers (Cambridge, Mass. Abt
Books, 1982), p. 134.
''Lisa M. Ellram and Sue P Siferd, "The Case Study Method in Operations
and Materials Management Research," Annual Conference Proceedings (Honolulu:
Decision Sciences Institute, 1994); Lisa M. Ellram and Sue P. Siferd, "Purchasing:
The Cornerstone of tbe Total Cost of Ownership Concept," Journal of Business
Logistics, 14, no. 1 (1993): 163-184; Flynn, et al. reference in Note 1; Mentzer
and Kahn, and Meredith, et al. references in Note 2.
'^Mentzer and Kahn reference in Note 2.
'^Rikard Larsson, "Case Survey Methodology: Quantitative Analysis of Patterns
Across Case Studies," Academy of Management Journal 36, no. 6 (1993): 1515-1546.
'*Yin reference in Note 1.
'^Flynn, et al. reference in Note I; Meredith, et al. and Mentzer and Kahn
references in Note 2; and Ellram and Siferd reference in Note II.
'Thomas E. Hendrick and Lisa M. Ellram, Strategic Supplier Partnerships:
An International Study (Tempe, Ariz.: Center for Advanced Purchasing Studies
(CAPS), 1993).
'^For examples of successful case study research in a number of fields, see
Bonoma reference in Note 1; and Niren Vyas and Arch G. Woodside, "An Inductive
Model of Industrial Supplier Choice Processes," Journal of Marketing (Winter 1984):
48, 30-45; Lawrence P. Carr and Christopher D. Ittner, "Measuring the Cost of
Ownership," Journal of Cost Management 6, no. 3 (Fall 1992): 42-51; and Lisa
M. Ellram, "A Developmental Framework for the Total Cost of Ownership," The
International Journal of Logistics Management 4, no. 2 (1993): 49-60.
'^Hoaglin, et al. reference in Note 10 and Larsson reference in Note 13.
'^Mintzberg, et al. and Miller and Crabtree references in Note 7.
136
I
ELLRAM
and Huberman reference in Note 7; Todd D. Jick, "Mixing Qualitative
and Quantitative Methods: Triangulation in Action," Administrative Science
Quarterly 24 (Dec. 1979): 602-611.
'^'Yin reference in Note 1 and Miller and Crabtree reference in Note 7.
"Yin reference in Note 1.
i ,
"Yin reference in Note I.
-
'
^'*Yin reference in Note 6.
^^David N. Burt, Warren E. Norquist. and Jimmy Anklesaria, Zero Base Pricing
(Chicago, 111.: Probus Publishing, 1990); Jose Fernandez, "Life-Cycle Costing,"
NAPM Insights (Sept. 1990): 6; and Carr and Ittner reference in Note 17.
^^
reference in Note 17.
l, Strauss and Corbin, and Miller and Crabtree references in Note 7.
reference in Note 1.
reference in Note 1,
reference in Note 1; and Miles and Huberman reference in Note 7.
reference in Note 1; Lee. and Miles and Huberman references in Note
7.
•'^Miles and Huberman reference in Note 7.
•'•'Yin reference in Note I.
-^^W. Lawrence Neuman, Social Research Methods (Needham Heights, Mass.:
Allyn and Bacon, 1991); David Silverman, Interpreting Qualitative Data (Thousand
Oaks, Calif.: Sage Publications, 1993); Cozby, and Marshall and Rossman references
in Note 7.
J. Gilchrist, "Key Informant Interviews," in Doing Qualitative
Research, Benjamin F. Crabtree and William L. Miller, eds. (Newbury Park, Calif.:
Sage Publications, 1992), pp. 70-89.
•'^Neuman reference in Note 34.
reference in Note 1; Mintzberg reference in Note 7; and Gilchrist reference
In Note 35.
•'^Yin reference in Note 1.
JOURNALOF BUSINESS LOGISTICS. Vol. 17, No. 2. 1996
137
^\.\s,a M. Ellram, Total Cost Modeling (Tempe, Ariz.: Center for Advanced
Purchasing Studies, 1994); Yin reference in Note 1; Gilchrist reference in Note
35; and Miller and Crabtree reference in Note 7.
'*^in reference in Note 1.
'^'Yin reference in Note 1,
'*^Steven J. Zyzanski, Ian R. McWhInney, Robert Blake Jr., Benjamin F. Crabtree
and William L. Miller, "Qualitative Research: Perspectives on the Future," in Doing
Qualitative Research, Benjamin Crabtree and William L. Miller, eds. (Newbury
Park, Calif.: Sage Publications, 1992), p. 231-248; Cozby, and Miles and Huberman
references in Note 7; and Silverman reference in Note 34.
'^•'Miles and Huberman reference in Note 7.
Strauss and Corbin reference in Note 7.
'*^Cozby reference in Note 7.
'*^Strauss and Corbin reference in Note 7.
^^Miles and Huberman reference in Note 7.
'*^Yin reference in Note 1.
Miles and Huberman reference in Note 7.
and Corbin reference in Note 7.
and Huberman reference in Note 7.
' Strauss and Corbin reference in Note 7.
^^Yin reference in Note 1; Kuzel, and Miles and Huberman references in Note
7.
^^
and Corbin reference in Note 7.
and Huberman reference in Note 7.
and Corbin reference in Note 7.
reference in Note I.
and Corbin reference in Note 7.
Yin reference in Note 6.
Fernandez reference in Note 25.
^'Strauss and Corbin reference Note 7.
138
ELLRAM
^^Yin reference in Note 1.
^Strauss and Corbin reference in Note 7.
Author's Note: The author would like to thank the Center for Advanced
Purchasing Studies for providing a grant to support this research, and John T. Mentzer
for his input into the conceptualization of this paper.
ABOUT THE AUTHOR
Lisa Ellram is assistant professor of purchasing and logistics management
at Arizona State Univereity. She received her B.S.B. and M.B.A. degrees from
the University of Minnesota and her Ph.D. from Ohio State University. She is
recognized as a Certified Purchasing Manager by the National Association of
Purchasing Management. Her research interests include international and domestic
supply chain management, buyer-seller relationships, purchasing strategy, and total
cost modeling.