mitigating supply chain disruptions- essays on lean management, interactive complexity, and tight coupling

MITIGATING SUPPLY CHAIN DISRUPTIONS:
ESSAYS ON LEAN MANAGEMENT, INTERACTIVE COMPLEXITY
AND TIGHT COUPLING


DISSERTATION


Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate School of
The Ohio State University

By

Kathryn Ann Marley, M.B.A

* * * * *

The Ohio State University

2006


Dissertation Committee:

Professor Peter T. Ward, D.B.A. Adviser Approved by

Professor James Hill, Ph.D.

Professor Paul Nutt, Ph.D.

Professor David A. Schilling, Ph.D. __________________________________

Professor Steven J. Spear, D.B.A. Adviser

Graduate Program in Business Administration
















Copyright by
Kathryn A. Marley
2006

ii


ABSTRACT



The prevalence and cost implications of supply chain disruptions is the motivation
for a considerable amount of academic and practitioner literature (e.g., Rice and Caniato,
2003; Hendricks and Singhal, 2003; Blackhurst et al., 2005; Hendricks and Singhal,
2005a, 2005b; Kleindorfer and Saad, 2005; Sheffi, 2005; Tang, 2006; Tomlin, 2006). In
this dissertation, I consider disruptions as accidents and use organizational accident
theory to address how supply chain disruptions can be prevented by understanding the

role of lean management, interactive complexity and tight coupling within a system
(Perrow, 1984, 1999a). I accomplish this through three related essays. I address the
theoretical basis for lean management conceptually in the first essay. In the second and
third essays, I address empirically the effects of interactive complexity and tight coupling
on the likelihood of supply chain disruptions, and the impact that different levels of these
conditions have on reducing supply chain disruptions.
Although lean management has attracted a great deal of attention within academic
and practitioner literature, there is little research that addresses why lean management
appears to work in practice. In the first essay, I address the theoretical basis for lean
management by drawing insights from research that considers how complex systems
achieve reliability. Specifically, I consider two organizational accident theories - Normal
Accident Theory (NAT) and High Reliability Theory (HRT). NAT suggests that, in the

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absence of countermeasures, a high degree of interactive complexity and tight coupling
lead to accidents (Perrow, 1984, 1999a), while HRT argues that organizations facing
these conditions may be vulnerable to accidents but can manage these conditions through
application of countermeasures (Roberts, 1990a). Firms practicing lean management
achieve improved operational performance by removing complexity from processes
(Womack et al., 1990; Womack and Jones, 1996). Therefore, we attempt to make a
theoretical contribution by connecting the observable attributes apparent in lean
management with the measurable performance being achieved to suggest why and under
what conditions these attributes contribute to high levels of performance.
In our second essay, we consider the impact of interactive complexity and tight
coupling on supply chain disruptions. Although some disruptions are the result of
abnormal events, such as hurricanes, fires, or intentional acts, the focus of this research is
on “normal” supply chain disruptions. We suggest that disruptions are likely to occur
under conditions of a high degree of interactive complexity and tight coupling (Perrow,

1984, 1999a). To accomplish this, we estimate the levels of interactive complexity and
tight coupling of various processes in a steel processing plant and relate these to the
likelihood of supply chain disruptions. The results indicate that there is a significant
process complexity effect, thus suggesting that process simplification can be an effective
countermeasure to preventing supply chain disruptions.
In our third essay, we aim to understand the structural changes that firms can
make to mitigate supply chain disruptions. According to NAT and HRT, the likelihood
of disruptions can be reduced by making structural changes to reduce interactive

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complexity, reduce tight coupling, or attack both simultaneously (Perrow, 1999b;
Roberts, 1990a). To understand which approach works best, we compare the proportion
of supply chain disruptions from groups of processes from a steel processing plant with
varying levels of interactive complexity and tight coupling. We find significantly fewer
disruptions under conditions of low process complexity and tight coupling and no fewer
disruptions when processes are simplified and buffered with additional inventory.
Because lean management involves simplifying processes with reduced slack, our results
support the benefits of adopting lean management practices to improve supply chain
performance.

v

Dedicated to Gregg and Colton, the loves of my life and my best friends.

You fill my life with more joy and happiness than I could ever hope for.

Thanks for being a part of the journey with me!

vi


ACKNOWLEDGMENTS



I would like to thank my advisor Peter Ward for his support,
advice, friendship, and mentoring throughout my Ph.D program.

Thanks also to my committee members James Hill, Paul Nutt,
David Schilling, and Steven Spear.
Your helpful comments and guidance are very much appreciated.

Thanks to my parents and family for their endless love and support.

Thanks to Gopesh and Sowmya Anand for being
such helpful, supportive, loving, and loyal friends.
Friends like you are irreplaceable!
The Marley’s will miss you!

Thanks to the Fisher College of Business, Center for Operational Excellence and
Lean Enterprise Institute for their financial support.

vii


VITA



July 23, 1974……… Born - Sewickley, Pennsylvania

1996…………………B.A. Christian Ministries/Social Service, Grove City College

2000………… M.B.A., Management, University of Akron

2003…………………M.A., Operations Management, The Ohio State University



PUBLICATIONS

Marley, K.A., Collier, D.A., Meyer-Goldstein, S., 2004. The Role of Clinical and Process
Quality In Achieving Patient Satisfaction in Hospitals, Decision Sciences 35 (3), 349-
369.




FIELDS OF STUDY

Major Field: Business Administration

Minor Field: Quantitative Psychology and Logistics












viii


TABLE OF CONTENTS



Page

Abstract………………………………………………………………………… ii

Dedication………………………………………………………………………… v

Acknowledgments………………………………………………………………… vi

Vita………………………………………………………………………………… vii

List of Tables……………………………………………………………………… xi

List of Figures……………………………………………………………………… xii

Chapters:

1. Introduction……………………………………………………………… 1

2. Normal Disruptions and Ordinary Processes……………………………… 7

2.1 Lean Management……………………………………………………. 11

2.1.1 The how of lean management……………………………… 13
2.1.2 The why of lean management …………………………… 15
2.1.3 Theoretical consistencies with lean management………… 21

2.2 Matrix of Choices……………………………………………………… 25

2.3 Propositions……………………………………………………………. 30

2.4 Illustration……………………………………………………………. 34

2.5 Conclusion……………………………………………………………. 36



ix

3. Interactive Complexity, Tight Coupling, and Disruption-free
Performance…………………………………………………………………46

3.1 Literature Review……………………………………………………… 48

3.1.1 Supply Chain Disruptions………………………………… 48
3.1.2 Organizational Accident Theories…………………………. 53
3.1.3 Hypotheses…………………………………………………. 57
.
3.2 Methods……………………………………………………………… 61

3.2.1 Sample………………………………………………………61
3.2.2 Dependent Variable - Supply Chain Disruptions…………. 62
3.2.3 Independent Variable - Interactive Complexity…………… 63
3.2.4 Independent Variable – Tight Coupling…………………… 66

3.3 Analysis and Results…………………………………………………… 67

3.4 Discussion……………………………………………………………… 69

3.5 Conclusion…………………………………………………………… 76

3.6 Limitations and Future Research………………………………………. 77

4. The Impact of Lean Management on Disruptions…………………… 84

4.1 Literature Review……………………………………………………… 87

4.1.1 Supply Chain Disruptions…………………………………. 87

4.1.2 Normal Accident Theory and High Reliability Theory…… 91
4.1.3 Hypotheses………………………………………………… 95

4.2 Methods……………………………………………………………… 101

4.2.1 Sample………………………………………………………101
4.2.2 Dependent Variable - Supply Chain Disruptions…………. 102
4.2.3 Independent Variable - Interactive Complexity…………… 102
4.2.4 Independent Variable –Tight Coupling……………………. 104


x


4.3 Analysis and Results……………………………………………………106

4.4 Discussion………………………………………………………………109

4.5 Conclusion………………………………………………………………115

4.6 Limitations and Future Research………………………………………. 116


List of References………………………………………………………………… 123

xi


LIST OF TABLES

Table Page

2.1 Rules of the Toyota Production System……………………………………. 42

2.2 Strategies of High Reliability Organizations………………………………. 43
.
2.3 Consistencies between NAT dimensions and lean management………… 44

2.4 Consistencies between HRT dimensions and lean management………… 45

3.1 Definition of steps in steel processing…………………………………… 80

3.2 Descriptive Statistics and Correlations……………………………………. 81

3.3 Logistic Regression Analysis……………………………………………… 82

3.4 Rules of the Toyota Production System…………………………………… 83

4.1 Definition of steps in steel processing…………………………………… 119

4.2 Descriptive statistics – Process Complexity and Tight Coupling…………. 120

4.3 Descriptive statistics – Product Complexity and Tight Coupling…………. 121

4.4 Difference Between Proportions…………………………………………… 122

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LIST OF FIGURES



Figure Page

2.1 The tools and practices of lean management………………………………. 38

2.2 The interaction of the tools and rules of lean management……………… 39

2.3 Normal Accident Theory framework………………………………………. 40

2.4 Normal Accident Theory framework – Mitigating Disruptions………… 41

3.1 Research Model……………………………………………………………. 78

3.2 Interaction between Tight Coupling (Inventory) and Probability of a
Disruption at different levels of complexity……………………………… 79

4.1 Research Model……………………………………………………………. 118

1
CHAPTER 1

INTRODUCTION



The significant cost and operational implications of supply chain disruptions are
the subject of a considerable amount of academic and practitioner research (e.g., Rice and
Caniato, 2003; Hendricks and Singhal, 2003, 2005a, 2005b; Blackhurst et al., 2005;
2005a, 2005b; Kleindorfer and Saad, 2005; Sheffi, 2005; Tang, 2006, Tomlin, 2006). For
our purposes, we define a supply chain disruption as a stoppage in production at a
customers’ plant caused by activities that occur at a supplier plant upstream. Supply chain
disruptions may be the result of activities such as poor scheduling and planning,

communication, machine or transportation breakdowns, quality or computer problems, or
employee errors (Blackhurst et al., 2005; Sheffi, 2005). Because supply chain
performance can be considered a good metric, we consider the structural changes that
firms can make to reduce the likelihood of supply chain disruptions.
In his article in the Academy of Management Review, Whetten (1989) discusses
the necessary elements of a theoretical contribution. Building off the work of Dubin
(1978) and others from theory development disciplines, he describes a complete theory as
containing four elements – (1) what, (2) how, (3) why, and (4) who, where, when. The
“what” involves identifying which factors should be included to provide an explanation

2
of the phenomena. Here, it is important to balance comprehensiveness with parsimony;
including all pertinent concepts, while eliminating those that add little understanding. The
“how” draws relationships by adding order and pattern to the factors. In addition,
causality may be introduced. According to Whetten, the “why” step is the “theoretical
glue that welds the model together.” It is here where the “underlying psychological,
economic, or social dynamics that justify the selection of the factors and the proposed
causal relationships” is determined. Lastly, the “who, what, when” step invoke the
necessary limitations of the proposed theory. This, most often, comes through testing of
the first three steps.
Using Whetten’s (1989) framework, this dissertation attempts to add a theoretical
basis to lean management by considering why adopting lean management can reduce the
likelihood of supply chain disruptions. The essence of lean management is the creation of
a culture that encourages learning and, thus continuous incremental process improvement
(Spear, 2002). The “what” and “how” of lean management are well-established in
literature. They include Total Quality Management, Just-in-Time Production, Total
Preventive Maintenance, and Employee Involvement (McKone et al., 1999; Cua et al.,
2001; McKone et al., 2001; Shah and Ward, 2003). In addition, Spear and Bowen (1999)
describe “how” the tools lead to operational advantage in their discussion of the “Rules of
the Toyota Production System.” Adding theory to lean management requires us to go

beyond “what” tools and practices comprise lean and “how” these tools lead to
operational advantage for companies who practice them. To make a theoretical
contribution we must address “why” it is that lean works by understanding the logic
behind the philosophy and testing our proposed theory (Whetten, 1989).

3
Within our study, we consider the impact of adopting lean management on the
likelihood of supply chain disruptions. Within the supply chain disruption literature,
many researchers suggest countermeasures to mitigate supply chain disruptions. These
countermeasures include strategies such as adding redundancy and flexibility (Rice and
Caniato, 2003; Sheffi, 2005), monitoring supplier relationships (Toby, 2005), and
increasing inventory levels (Chopra and Sodhi, 2004; Tomlin, 2006). However, largely
neglected in extant literature is a discussion of how simplifying processes through lean
management can reduce the likelihood of supply chain disruptions.
To understand the relationship between lean management and supply chain
disruptions, we draw insights from organizational theory that addresses how catastrophic
accidents can be avoided. This literature is useful to our study because both safety
accidents and supply chain disruptions involve a “disruption to the ongoing or future
output of a system” (Perrow, 1984, 1999a). Within the organizational accident literature,
we consider two theories, Normal Accident Theory (NAT) and High Reliability Theory
(HRT). The basic notion of NAT is that accidents are inevitable under conditions of tight
coupling and a high degree of interactive complexity (Perrow, 1984, 1999a). Tight
coupling refers to the level of slack or buffer within the system and interactive
complexity refers to the way that “parts within a system are connected and interact”
(Sagan, 1993). To reduce catastrophic potential, NAT researchers suggest that firms
either add slack to their system or reduce complexity (Perrow, 1999b). HRT researchers
address the various countermeasures that some organizations have adopted to remain
remarkably error-free despite operating under conditions of tight coupling and a high
degree of interactive complexity (Roberts 1990a, 1990b; Weick et al., 1999). Strategies

4
such as increasing training and redundancy and decentralizing decision-making are
suggested. Both theories provide a lens to explain the lack of disruptions achieved by
successful practitioners of lean management.
In Chapter 2, we conceptually develop the argument of why lean management
works in practice. Within this chapter, we draw comparisons between the characteristics
of lean management firms and research in NAT and HRT to suggest how the dimensions
of interactive complexity and tight coupling impact the success of firms practicing lean
management. Specifically, we argue that reducing complexity while maintaining slack
gives firms operational advantage over firms with more complex processes. Reducing
complexity enables firms to streamline their processes, eliminate waste and increase the
overall reliability of the system (Womack and Jones, 1996; Spear, 2004). In addition,
operating with small buffers of inventory allows firms to be responsive to changes within
their systems because process steps are not decoupled by slack resources (Levy, 1997).
We conclude this chapter with propositions suggesting that firms practicing lean
management will be characterized by low levels of interactive complexity and tight
coupling and that these dimensions will lead to a reduced likelihood of supply chain
disruptions. In addition, we suggest that some of the strategies suggested by HRO
researchers enhance the reliability of lean management firms, providing additional
protection against disruptions.
The last step in Whetten’s (1989) discussion on what constitutes a theoretical
contribution involves testing of the proposed theory. Therefore, the next two chapters of
the dissertation are essays empirically testing the relationship between interactive
complexity, tight coupling, and the likelihood of supply chain disruptions. In Chapter 3,

5
we present literature on supply chain disruption mitigation countermeasures and suggest
that the NAT and HRT dimensions of a high level of interactive complexity and tight
coupling lead to increased supply chain disruptions. Within our analysis, we consider
interactive complexity to be comprised of process and product complexity. In addition,

we characterize the level of tight coupling in the system as the amount of inventory
before, within, and after processes. Our research hypotheses for Chapter 3 are that a high
level of interactive complexity and low inventory individually lead to an increased
likelihood of supply chain disruptions, as well as the interaction between the conditions.
To test these hypotheses, we use logistic regression on archival data from 451 orders
from a steel processing plant. We measure the level of product complexity, process
complexity, and inventory for each order and determine whether or not these orders
caused disruptions at customer plants. The results from this analysis provide insights into
how reducing complexity can be considered an internal countermeasure to mitigate
supply chain disruptions.
In Chapter 4, we consider how altering the dimensions of interactive complexity
and tight coupling can be considered a mitigation strategy to reduce the likelihood of
supply chain disruptions. Within the organizational accident literature, researchers
suggest that to reduce the likelihood of disruptions, firms can reduce complexity, increase
slack, or perform both simultaneously (Perrow, 1984, 1999a; Roberts, 1990a). We
suggest that firms practicing lean management are successful because they have reduced
the complexity within their systems concomitant with a reduction in slack (Womack et
al., 1990; Womack and Jones, 1996). Therefore, in this study, we argue that there will be
a significantly lower proportion of disruptions for orders characterized by low process

6
complexity and low inventory than for orders characterized by (1) high process
complexity and low inventory, (2) high process complexity and high inventory, and (3)
low process complexity and high inventory. Using a dataset of orders from the steel
processing plant, we test our hypotheses using a standardized z test. The results from this
analysis will provide managers with insights on how lean management can be used as a
strategy to mitigate disruptions.
Within this dissertation, we attempt to make a theoretical contribution by
understanding the interplay of lean management principles, interactive complexity and
tight coupling and their effect on supply chain disruptions. Drawing insights from

organizational accident literature, we present a conceptual and empirical argument for
why lean management works in practice. We address empirically the relationship
between interactive complexity and inventory levels and supply chain disruptions, as well
as how altering the levels of interactive complexity and inventory can be considered a
countermeasure for reducing supply chain disruptions.









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CHAPTER 2

NORMAL DISRUPTIONS AND ORDINARY PROCESSES

Lean management has attracted a great deal of attention within academic and
practitioner literature because it suggests an approach that leads to both high performance
and continuous improvement (e.g., Womack et al., 1990; Womack and Jones, 1996;
Spear and Bowen, 1999; Shah and Ward, 2003; Hines et al., 2004; Liker, 2004; Bhasin
and Burcher, 2006; Liker and Morgan, 2006). The essence of lean management is the
creation of a culture that encourages learning and, thus continuous incremental process
improvement through simplifying the way that work is performed (Womack and Jones,
1996, Spear, 2002). This emphasis on continuous improvement is achieved in part by
applying a set of well delineated principles to identify and eliminate waste from all
aspects of the organization (Womack and Jones, 1996). Within literature there is no
shortage of examples of firms that have adopted lean management practices. Although

the roots of lean management can be found in the Toyota Production System (Sugimori,
1977; Monden, 1981, Spear and Bowen, 1999; Liker, 2004), firms in industries such as
healthcare (Bushell et al., 2002), steel (Proctor, 1997; Dhandapani et al., 2004;
shipbuilding (Storch and Lim, 1999), textile and clothing (Bruce et al., 2004) and
publishing (Huls, 2005) are finding ways to apply lean management principles and
achieve operational success.

8
Within these firms, a well-defined set of lean management tools such as pull
systems, quality management programs, preventative maintenance programs and
employee involvement programs are consistently applied (Shah and Ward, 2003).
However, a question that remains unresolved is why adopting these lean management
tools leads to improved performance. In other words, are there certain conditions that
exist within the firm that drive the successful application of lean practices? Determining
these conditions not only provides a theoretical basis for lean management, but also
enables managers to better understand the structural and infrastructural characteristics
that support a lean management initiative.
To address the theoretical basis for lean management, we argue that many of the
firms that adopt lean can be characterized as complex work systems. Complexity
manifests itself in a variety of ways within these organizations – appearing within
individual processes, products, and relationships with suppliers and customers. Firms
managing these complex work systems pursue lean management to achieve improved
reliability, responsiveness, and productivity (Levy, 1997; Pavnaskar et al., 2003; Spear,
2004). However as complexity increases, firms become more vulnerable to experiencing
disruptions (Roberts and Libuser, 1993). We argue that the theoretical basis for lean
management lies in understanding how to overcome the complexity inherent in these
systems to achieve disruption-free performance.

9
Within the organizational theory literature, there is a body of knowledge that

addresses how to manage complex systems when the consequences from accidents or
disruptions are very great. We refer to this literature as organizational accident theory and
consider contributions from two theories - Normal Accidents Theory (NAT) (e.g., Sagan,
1993; Perrow, 1984, 1999a) and High Reliability Theory (HRT) (e.g. Roberts, 1990a,
1990; Weick and Sutcliffe, 2001). Thus, to help explain how lean management appears
to lead to success in avoiding disruptions in more prosaic operational settings, we draw
insights from models developed to describe the dynamics of managing risk in situations
that are inherently perilous.
A common thread throughout organizational accident literature is the notion of
managing interactive complexity. Interactive complexity “refers to the presence of
unfamiliar or unplanned and unexpected events in a system that are either not visible or
not immediately comprehensible”(Marais et al., 2004) As firms and their supply chains
expand and the number of communication and technological links increase, they become
more interactively complex. Dealing effectively with interactive complexity is at the
heart of the literature on reliability in organizations facing perilous risk.







10
Charles Perrow has emphasized the vulnerability of complex systems to
unintended and unanticipated consequences. Perrow’s book, Normal Accidents, (1999),
describes how these undesirable outcomes are directly the result of systems having so
many elements, connected in so many ways, that no one is capable of understanding fully
the system’s structure or dynamics. To avoid the inevitability of a (normal) accident
under conditions of very tight coupling or little slack, firms should attempt to reduce the
number of elements and number of interconnections within the system to make itself

more tractable (Perrow, 1999b).
High reliability organization researchers have approached a question similar to
that of NAT but have reframed it slightly from “how do complex organizations fail?” to
“how do complex organizations succeed?” They characterize “high reliability
organizations (HROs)” as those that have very few accidents despite operating under
complex and demanding conditions (Roberts, 1990a, 1990b; Weick and Sutcliffe, 2001).
Proponents of high reliability theory (HRT) recognize that characteristics such as high
interactive complexity and tight coupling can be potentially damaging to an organization;
however, they believe that strategies such as redundancy, accountability, responsibility,
and a “culture of reliability” can mitigate the effects (Roberts, 1990a).
Addressed in NAT and HRT are two constructs that are fundamental to the
concept of lean management – interactive complexity and organizational slack. Because
both theories also emphasize several principles that are fundamental to the ideas of lean
management (standardization, reliability, learning, training), they provide a conceptual
basis for understanding why the tools and practices inherent to lean management are so

11
effective in achieving disruption-free performance in operations where the consequences
of failure take a financial rather than human toll. We discuss the important concepts in
NAT and HRT and how they can be applied to explain why and under what conditions
lean management serves to avoid disruptions that were previously considered “normal.”

2.1 Lean Management
Whetten (1989) discusses the necessary elements of a theoretical contribution.
Building on the work of Dubin (1978) and others from theory development disciplines,
he describes a complete theory as containing four elements – (1) what, (2) how, (3) why,
and (4) who, where, when. Using the lens provided by NAT and HRO, we address the
paucity of theoretical support for lean management.
The essence of lean management is the notion of simplifying processes. Womack
and Jones (1996) suggest that simplification can be accomplished by “identifying all

activities that are muda (waste) and eliminating them.” Wasteful activities are those that
do not add value from the customer perspective. By singling out the value added steps in
the process, the flow between activities becomes less jumbled and more linear and
problems and defects are easily identified and eliminated (Womack and Jones, 1996;
Rother and Shook, 2003). Lean management firms focus on continuous improvement
that extends within the plant and throughout the enterprise (Womack and Jones, 1994).
The notion of simplification extends to the programs that comprise lean
management. Previous research has addressed the specific tools and techniques that are
practiced in lean systems that, when adopted by firms, can contribute to high

12
performance. It is well established that there are four elements within lean management–
Just-in-Time (JIT), Total Quality Management (TQM), Total Productive Maintenance
(TPM), and Employee Involvement (EI) (McKone et al., 1999; Cua et al., 2001; McKone
et al., 2001; Shah and Ward, 2003). JIT accounts for the flow of production and includes
such elements as reduced setups and lot sizes, pull systems, and kanbans. (Davy et al.,
1992; Flynn et al., 1995; White, 1999; Cua et al., 2001; McKone et al., 2001; Shah and
Ward, 2003; Kannan and Tan, 2005). TQM describes an organization-wide focus on
quality, not only within the creation of the product or service, but also in the development
of procedures to address how employees can improve the quality of their work. Practices
such as Statistical Process Control, Benchmarking, Process Capability Analysis are
included here (Flynn et al., 1995; Hackman and Wageman, 1995; Powell, 1995; Ahire et
al., 1996; Dow, 1999; Cua et al., 2001; McKone et al., 2001; Shah and Ward, 2003).
TPM involves autonomous and planned maintenance activities that support a
company’s efforts in keeping equipment in proper shape throughout its entire life, by
involving all levels of employees in regular procedures (McKone et al., 1999). Activities
such as housekeeping (5S), cross-training maintenance, and schedule compliance are
included (McKone and Weiss, 1998; Cua et al., 2001; McKone et al, 2001; Shah and
Ward, 2003). EI accounts for the role of employees in achieving the goals and objectives
of the above programs. Developing cross-functional teams, empowering employees and

decentralizing decision-making are ways that firms accomplish the goals of lean
management (Pil and MacDuffie, 1995; MacDuffie, 1996; Cua et al., 2001; Shah and
Ward, 2003).