Yi Wu

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Implications of Case Study Research in Information Systems in

Supply Chain Management

Yi Wu

Warwick Business School

University of Warwick

Coventry, CV4 7AL UK

Telephone: (+) 44 (0) 24 7657 5816

Email: [email protected]

Supervisor, Name:

Supervisor, Email:

16th

EDAMBA Summer Academy

Soreze, France

July 2007

Abstract

This research is concerned with Information System (IS) integration in the

context of agile capability of supply chain management (SCM). Case studyresearch has been carried out for empirical research. Interviews and survey were

employed for data collection to provide comprehensive data on the role and

impact of IS in relation to supply chain agility, and to reflect a range of

perceptions from ‘thick description’ of interviews and quantitative presentation.

In conclusion, several strengths and weaknesses are discussed for each method,

by highlighting the value of a mixed-methods approach in this study.

Key Words

Case study, interviews, survey, qualitative methods, quantitative methods

1 Introduction

This research is concerned with the role of information systems (IS) in achieving

agile capabilities in supply chain management (SCM), which includes customer

sensitivity enhancement, process integration, network integration and virtual

integration through the process of logistics, procurement and operations in

supply chains. More specifically, it explores the value creation process from IS

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integration in supply chain agility and how IS realizes values in several

operational dimensions in supply chain. A conceptual framework has been

developed in order to gain insights into the impact of IS on agility and to develop

propositions which highlight the role of IS as a platform to various integration

processes in supply chain agility.

Empirical research is carried out through a pilot case study and follow-up

multiple case studies1

along Chinese automotive supply chain. The initial case

study is for modifying the research propositions and testing the overall research

design, followed by case studies to provide an in-depth understanding of the

conditions under which IS creates value along supply chainsSemi-structured

interviews are deployed to IT professionals and senior managers from logistics,

procurement and operation departments to gain an in-depth understanding and

surveys will be handed out to test propositions.

The paper is set out to gain an in-depth understanding of the implications of

case study in this research. The paper is organized as following. Section 2

discusses the reasons to adopt case study. Section 3 is concerned with the pros

and cons of the research techniques applied in this research and section 4

evaluate case study, while section 5 explores the issues needed to be addressed.

2 Reason to adopt case study

I choose the case study design to explore the relations of IS integration andsupply chain agility as many studies fall short on unraveling potential

mechanism in which IS may affect supply chain agility

According to Ritchie (2003), the use of methods is heavily influenced by the

aims of the research and the specific questions that need to be answered. Case

study approach is appropriate because ‘it is a research strategy, focusing on

understanding the dynamics present within single settings’ (Eisenhardt 1989).

The research focuses on the contemporary phenomena, and in the context of IS

research, the focus has been moved from technical to managerial and

organizational questions, and as a consequence, the research will investigate how

context interacts IS applications. In order to understand the phenomenon, the

research focuses on organizational structures, the business processing taking

places etc (Benbasat et al., 1987).

1 In this research, a case study is ‘an empirical inquiry that investigates a contemporary

phenomenon within its real-life context, especially when the boundaries between phenomenon

and context are not clearly evident ’ (Yin 1994), usually combining data collection methods such

as archives, interviews, questionnaires and observation (Eisenhardt 1989).

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Case study research is one of the most common approaches applied in IS field

(Alavi et al., 1992), because it has multiple perspectives which are rooted in a

specific context and provides multiple data collection methods (Richie et al.,

2003). Therefore, case study research is not exclusively concerned with

qualitative methods as all evidence will go to the data collection (Gillham, 2000).

In addition, a case study approach is well-suited to IS study because the nature of

the discipline is the study of IS as the technology per se in the context of

organizations (Myers, 1997).

3 Data collection

3.1 Interview

Semi-structured interviews2

with open-ended questions will help collect the field

data concerning with the organizational patterns of IS and their relation to supply

chain agility. The interviews have been carried out with IT professionals, senior

managers from logistics, procurement and operation departments in companies.

Each interview lasted around 40 minutes under the interview guide related with

list of questions.

Semi-structured interview has already focused on a particular subject;

however, it is still free to build up the conversation within this subject area. Such

flexibility makes the interview a good technique for exploration (Chein &

Proshansky, 1959).In particular with the research objective to develop the way to maximize IS

applications in supply chains, interviews can provide an in-depth understanding,

insights on people’s experiences, and help to approach the research questions

from different dimensions (Mason, 2002). Meanwhile, interviews also allow

accessing a wider variety of people to achieve a greater breadth of coverage

(Ryman, 2001).

Another advantage is that with the interview guide, it can help me to carefully

decide how best to use the limited time available in an interview and also to help

to interview a number of different people more systematic and comprehensive by

delimiting the issues to explore in advance (Mishler, 1996).

On the other hand, there are limits of using interviews. First, it has the

common problem of bias in the interview processes that interviewers can only

2 A semi-structured interview is that the researcher has an interview guide, but interviewees

have ‘a great deal of leeway in how to reply’. Questions may not follow the sequence listed in

the guide. Questions that are not on the list can also be asked as they pick up on the answers

from interviewees (Ryman, 2001).

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hear what they want or interviewees give what interviewers want to hear (Yin,

1994).

Second, the meaning of words sometimes can become ambiguous as ‘the

spoken word has always a residue of ambiguity, no matter how carefully we

work the questions or how carefully we report r code the answers’ (Fontana &

Frey, 2000).

Third, there has possibility of reluctance of talking insides in an interview

context along as they may concern on the interviewees with regard to how much

the interviewer can be trusted (Ryman, 2001).

In order to improve data accuracy, interviews will be recorded under

interviewees’ permission so that I can be more attentive to the interviewees (Yin,

1994), and interview reports will be sent back (Myers & Newman, 2007).

3.2 Survey

In this research, I applied survey to evaluate propositions about the critical

factors of IS and the relations to supply chain, using a 5 point Likert-scale,

mainly answering the questions of the casual relationship, for instance, what the

values are and to what degree the values have been achieved. There are relevant

examples in the IS and SCM field supporting the methods (Goldman et al., 1995;

Mondragon et al., 2004).

Quantitative methods in social research are aiming to develop casualpropositions between concepts (Bryman, 1988). Through being able to

quantifying the data, it can help complement or extend the range of evidence (e.g.

from interview) on the topics under study.

The impersonal nature of q survey, e.g. standardized wording and sequence of

questions, ensures some uniformity from one measurement situation to another

(Chein & Proshansky, 1959), because a common pitfall in qualitative data

collection is an ‘bias’ in the selection of informants and in the evaluation of

statements. Survey can help to correct bias in the interpretation of events.

Replies to survey can also provide leads for later interviews and eliminate the

need to ask routine background questions (Sieber, 1973). Furthermore, survey

also contributes to qualitative data analysis. When qualitative method plays an

important role in the theoretical structure, survey data become essential for

buttressing the argument, and can help to verify the field interpretation (Seiber,

1973).

However, on the other hand, the weakness of the survey lies on its incapacity

to reveal covert and hidden activities (Bryman, 1995).

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4 Mixed methods

4.1 IS Research traditions

Many studies have been carried out to examine the effects of one or more

variables of applying IS. For example, they regard IS as an important factor or

view organizations as acting in rational consort to achieve outcomes through IS

application (Kaplan et al., 1988). Therefore, many researches are based on the

quantitative outcomes such as technical, effectiveness and performance

measurement. Such study treats organizational context, technology features, user

applications as static, and objective instead of dynamic and interacting. These

studies focused on the static constructs, but they neglect the aspects of social

interaction that may influence outcomes (Lyytinen, 1987).

Concepts or context may change over time according to how participants view

and experience (Kaplan et al., 1988). For example, studies are concerned with IS

with respect to organizational structures etc, and in these studies, IS is viewed as

‘impact’ rather than a social construct (Danziger, 1985).

However, with the recognition of qualitative research for conducting IS in the

social context, interpreting IS in terms of social action and meanings is

becoming popular, as evidence grows that IS development and use is a social, as

well as technical progress that includes constructs related to social,

organizational and conceptual aspects of the systems (Kling and Scacchi, 1982;

Markus, 1983), for example, the research on the IS with the organizationalchange (Markus &Robey, 1988).

In fact, each research method has its own appropriate uses, based on research

questions and analytical assumptions (Markus & Robey, 1988; Weick, 1984).

Although there is still disagreement concerning the use of approaches, it is

possible to integrate the methods as combining the methods introduces testability

and context into the research (Kaplan and Duchon, 1988).

4.2 Mixed methods in this research

Bulk of literatures has discussed the values of combining methods in social

research as it is becoming increasingly common in recent years (Bryman, 2006).

It helps us to ‘think outside the box’, to theorize beyond the micro-macro divide,

and to enhance and extend the logic of qualitative explanations (Mason, 2006).

Each of these two approaches provides a distinctive kind of evidence and when

used together they can offer a powerful resource to inform and illuminate

practice (Ritchie, 2003).

I choose to integrate these methods in order to provide a full picture of the

research. In fact, both methods are brought together to study the same

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phenomenon but divided according to research objectives on what is explored,

and according to which information needs collected, as this has been discussed

by Ritchie (2003). Specifically in this research, the investigation will be needed

(requiring for qualitative methods) for integration processes, accompanied by

some measurement of outcomes (requiring quantitative methods).

Quantitative data can indicate relationships which may not be noticeable to the

researchers. It also keeps the researchers from ‘vivid, but false impressions in

qualitative data’. On the other hand, qualitative data lies in the knowledge it

provides the dynamics of social processes, change and social context so that it

can answer ‘how’ and ‘why’ questions in these domain, and also the results can

be strengthened by quantitative support (Eisenhardt, 1989; Mason, 2006).

Therefore, these techniques can provide comprehensive data on the role and the

impact of IS in relation to supply chain agility, and reflect a range of perceptions

from ‘think description’ of interviews and quantitative presentation to gain a

fuller picture of the phenomenon under study (Byrman, 1995; Mason, 2002).

Moreover, using multiple methods increases the robustness of results because

findings can be strengthened through triangulation (Jick, 1979). That is the

validation through different sources of data converge (Benbasat et al., 1987;

Bonoma, 1985), or divergence when an explanation is developed to account for

(Trend, 1979). Therefore the results can be based on convergence of different

sources and methods.Mixed methods are followed the approaches of ‘the logic of triangulation

3’

(Ryman, 1995).Denzin (1978) outlines four types of triangulation, including

diverse sources of data, different investigators, perspectives to the same data and

different methods. In this research, I will collect data mainly adopting interviews

from different people in a company to obtain comprehensive information, and

richer descriptions of phenomenon result on the processing of implementing IS

integration among firms, the business objectives of applying IS and their

understanding of using IS across departments. Meanwhile surveys were

distributed to a random sample of employees quantifying the critical success

factors of IS integration and the impacts from IS.

Qualitative data from interviews play the main role in this research. It should

be underscored that the quantitative results were used largely to supplement the

qualitative data as ‘the survey became more meaningful when interpreted in light

of critical qualitative information…Triangulation can lead to a prominent role

for qualitative evidence’ (Jick, 1979).

3 Triangulation is defined as ‘the combination of methodologies in the study of the same

phenomenon’ (Denzin, 1978).

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4.4 Quality of the research

Case study research has been advanced for information system research in order

to understand the nature and complexity of the processes taking place (Benbasat

et al., 1987; Kaplan and Dunchon, 1988). Although many scholars argue that one

can not mix research methods across qualitative and quantitative paradigms due

to the different philosophic premises, purposed and epistemic roots (Leininger,

1991; Lincoln and Guba, 1985), one can mix methods in each paradigm

(Leininger, 1990) to achieve cross-validation, which is combining two or more

sources to study the same phenomenon to gain a complete understanding (Denzin,

1970), and to achieve complementary results by using the strengthens of one

methods to enhance the other (Morgan, 1978).

Validity4 of Qualitative Data Collection

In the qualitative research, ‘the issue of validity is…a question of whether the

researcher sees what he thinks he sees’ (Kirk and Miller, 1986). In current study,

I collected from various interviewees in one organization and also sent out the

survey. During the interview process, the interview guide was used and interview

was recoded under the permission or the note was taken when they did not allow

the tape recording. Following the interview was the interview report sent back to

interviewees. Theses procedures were intended to maximize the validity of

interview as a data collection by ensuring that interview was not misunderstoodor included my bias of interpretation as an interviewer. Silverman (2000)

proposed two common responses to improve the data validity are data

triangulation and respondent validation.

Generalization

Difficulty in generalizing from case studies has been considered a major

shortcoming of the methods, no matter involving single case or multiple cases

(Yin, 1999). Theoretical generalization is the rational for generalizing from

qualitative research (Mitchell, 1983). On the other hand, generalization in

quantitative research is based on choosing representative samples and using

probability. However, in this research, interviews still tends to prevail as a major

source of data collection. It is unusual to find examples of investigations in

which qualitative and quantitative research have a roughly equal role (Bryman,

1995).

Bryman (1995) outlined several ways in which the use of number can help

qualitative research to establish the generalizability, such as combining survey

4 Validity is defined as the truth interpreted as the extent to which an account accurately

represents the social phenomena to which it refers (Hammersley, 1990).

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with case study, or sampling within the case. For example, in Silverman’s

research (1984) of clinics, he used participant observation to obtain an in-depth

understanding of patient behavior, and applied the quantitative comparisons of

various indicators of interaction as evidence in the study.

In this research, I mainly applied qualitative data to explore the IS in the

context of organizations, employing the quantitative information to measure

performances as a means of establishing the generalization.

5 Conclusions

The study aims to use case study research to explore the IS integration in the

context of supply chain agility. In terms of contribution to the literature,

collecting qualitative data provides a rich description of IS integration processes

and its relation to agile capability, and it can be supported by quantitative survey.

Especially in IS field, it needs a variety of approaches to study as ‘no one

method can provide the richness that the information systems, as a discipline,

needs for further advances’ (Kaplan & Duchon, 1988). However, there are

several caveats with the application of mixed methods in the study of IS. For

example, Replication is difficult, especially for the qualitative methods (Seale,

1999). It has been largely absent from most organizational study, but it is usually

considered as an important step in scientific progress (Jick, 1979).

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