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Preface .......................................................................................................................... vi

Section I: Causal Mapping: An Overview of Approaches

Chapter I

Causal Mapping: An Historical Overview .....................................................................1

V.K. Narayanan, Drexel University, USA

Chapter II

Causal Mapping: A Discussion and Demonstration ................................................... 20

Deborah J. Armstrong, University of Arkansas, USA

Chapter III

What Have We Learned from Almost 30 Years of Research on Causal

Mapping? Methodological Lessons and Choices for the Information Systems and

Information Technology Communities ..................................................................... 46

Gerard P. Hodgkinson , The University of Leeds, UK

Gail P. Clarkson, The University of Leeds, UK

Section II: Advances in Causal Mapping Methods

Chapter IV

Revealing Social Structure from Texts: Meta-Matrix Text Analysis as a Novel

Method for Network Text Analysis ............................................................................. 81

Jana Diesner, Carnegie Mellon University, USA

Kathleen M. Carley, Carnegie Mellon University, USA

Chapter V

Belief Function Approach to Evidential Reasoning in Causal Maps ...................... 109

Rajendra P. Srivastava, University of Kansas, USA

Mari W. Buche, Michigan Technological University, USA

Tom L. Roberts, University of Kansas, USA

Chapter VI

An Empirical Comparison of Collective Causal Mapping Approaches ................... 142

Huy V. Vo, Ho Chi Minh City University of Technology, Vietnam

Marshall Scott Poole, Texas A&M University, USA

James F. Courtney, University of Central Florida, USA

Chapter VII

Expanding Horizons: Juxtaposing Causal Mapping and Survey Techniques .......... 174

Deborah J. Armstrong, University of Arkansas, USA

V.K. Narayanan, Drexel University, USA

Chapter VIII

Reflections on the Interview Process in Evocative Settings ..................................... 195

Kay M. Nelson, The Ohio State University, USA

Section III: Causal Mapping in IS/IT: Research and Applications

Chapter IX

Using Causal Mapping to Uncover Cognitive Diversity within a Top

Management Team .................................................................................................... 203

David P. Tegarden, Virginia Tech, USA

Linda F. Tegarden, Virginia Tech, USA

Steven D. Sheetz, Virginia Tech, USA

Chapter X

Causal Mapping for the Investigation of the Adoption of UML in Information

Technology Project Development .............................................................................. 233

Tor J. Larsen, Norwegian School of Management, Norway

Fred Niederman, Saint Louis University, USA

Chapter XI

Using Causal Mapping to Support Information Systems Development:

Some Considerations ................................................................................................ 263

Fran Ackermann, Strathclyde Business School, UK

Colin Eden, Strathclyde Business School, UK

Chapter XII

Strategic Implications of Causal Mapping in Strategy Analysis and

Formulation ............................................................................................................... 284

Douglas L. Micklich, Illinois State University, USA

Chapter XIII

Knowledge at Work in Software Development: A Cognitive Approach for Sharing

Knowledge and Creating Decision Support for Life-Cycle Selection ...................... 312

Luca Iandoli, University of Naples Federico II, Italy

Giuseppe Zollo, University of Naples Federico II, Italy

Section IV: Potential Directions

Chapter XIV

Object-Oriented Approaches to Causal Mapping: A Proposal .............................. 343

Robert F. Otondo, The University of Memphis, USA

Chapter XV

An Outline of Approaches to Analyzing the Behavior of

Causal Maps .............................................................................................................. 368

V.K. Narayanan, Drexel University, USA

Jiali Liao, Drexel University, USA

About the Authors ..................................................................................................... 378

Index ........................................................................................................................ 384

Causal maps represent cognition as a system of cause-effect relations for the purpose

of capturing the structure of human cognition from texts, either archival or interview

generated. Given the structure of causal maps, they can be represented pictorially, or

as matrices. Once these cognitive structures have been represented, they can be

examined for patterns, theory building or hypothesis testing. As you will see, the tool

is versatile and can be used for policy making, exploratory, theoretical, and large scale

empirical works.

Ever since Axelrod developed causal mapping as a tool for policy research its use has

been increasing in frequency for research in various disciplines. IS researchers are just

now discovering the power of causal mapping as a research tool, and its importance in

knowledge management. Given the newness of the tool to the area, most researchers

use other disciplines to learn about causal mapping, thus having to adapt the method

for use in IT contexts.

The mission of the book is to bring together in a single volume both the necessary

knowledge for using causal maps, recent advances yet to reach the professional IT

community, and IS research works in progress employing causal mapping as a tool.

Thus the primary mission of the book is to provide an authoritative source - a one stop

learning place, if you will - for researchers interested in using causal mapping as a

research or policy tool.

Contents of the Book

To accomplish this mission the chapters are clustered into four sections.

Section I lays out the context of the book, presenting the history and logic of causal

mapping, and the mechanics of using it as a research or policy tool. Chapter I by

Narayanan provides a historical perspective on the evolution of causal mapping into

the IS/IT field. It sketches the diversity of perspectives, research contexts and foci

within the causal mapping method. In Chapter II Armstrong explicates the choice

points a researcher will face when conducting a causal mapping study and demonstrates

the step-by-step process for conducting causal mapping research. Finally, in

Chapter III, Hodgkinson and Clarkson review the major developments in the causal

mapping method across a variety of domains so as to address the strengths and limitations

of various approaches for the IS/IT community.

Section II includes five chapters that highlight the current advances in research (being

made in related disciplines) using causal mapping to enrich the research of those currently

employing causal mapping in IT research and policy making. Thus Chapter IV by

Diesner and Carley details an approach to text based causal maps called the meta-matrix

model, which lends a second level of organization to the networks of concepts found in

a text. A tool for text analysis (AutoMap) is detailed in a demonstration of the approach.

Chapter V by Srivastava, Buche and Roberts demonstrates the use of the

evidential reasoning approach under the Dempster-Shafer theory of belief functions to

analyze revealed causal maps in an IT organization example. Chapter VI by Vo, Poole

and Courtney provides two studies that compare three approaches to building collective

causal maps: aggregate mapping, congregate mapping and workshop mapping.

The approaches are compared both conceptually and empirically to determine which

approach performs best. In Chapter VII, Armstrong and Narayanan provide an extension

of the causal mapping method in which casual maps derived from interviews are

juxtaposed against causal maps developed from survey responses. Similarities and

differences of the maps are discussed as well as the appropriateness of this validation

technique. In Chapter VIII Nelson provides some reflections on the interactively elicited

causal mapping process in a discovery (or exploratory) context. Issues in the

interview process, identification procedure and coding scheme development are addressed.

Section III provides examples of papers in IS/IT using causal mapping techniques. Two

chapters represent examples of causal mapping in IS/IT. Chapter IX by Tegarden,

Tegarden and Sheetz details a study which focuses on the identification of cognitive

diversity through causal mapping and cluster analysis. The study uncovered cognitive

factions (diversity) within a top management team and details the various perceptions

of the firm. Chapter X by Larsen and Niederman studies the use of UML and objectoriented

analysis and design in software development. The remaining three studies

illustrate the use of causal mapping inn applications. In Chapter XI, Ackermann and

Eden focus on the use of causal mapping to facilitate the development of a shared

meaning between business units and IS developers through a common platform which

enables negotiated outcomes. Chapter XII by Micklich uses concept mapping, cognitive

mapping and causal mapping to investigate factors in the demise of a telecommunications

leader through a case study analysis. Finally, Chapter XIII by Luca Iandoli

and Zollo presents a methodology based on causal mapping for the investigation and

management of knowledge created by software development teams engaged in application

development. A detailed application of the methodology to a case study in a

software development firm is presented to demonstrate the methodological aspects.

The final section presents proposals for future causal mapping research to excite those

whose research can be enriched by the use of causal mapping. Chapter XIV by Otondo

presents a proposal to extend causal mapping research by representing linguistic and

semantic nuances in associative, categorical and cognitive maps. Those maps are then

used to link related elements to causal maps to create an integrated logical view of

object-oriented design. In Chapter XV, Narayanan and Liao outline several methods for

approaching the behavior of causal maps.

The chapters in this book were invited or solicited in a call for papers dispersed

to the IS community via listserv and direct e-mail. Almost everyone

invited participated in the development of the book. Out of those responding

to the call, nearly half were picked up for further development. All chapters

were involved in multiple rounds of reviews. Several individuals helped with

the development of the book. We thank Mehdi Khosrow-Pour of Idea Group

for encouraging us in developing the book, and Jan Travers, Michele Rossi,

and Jennifer Sundstrom for keeping us on track. The authors would like to

thank Paige Rutner, Christy Weer and other Ph.D. students at the University of

Arkansas and Drexel University for their assistance and helpful comments.

The authors would also like to thank Ken Armstrong for his creative input.